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THE TRIAL-READY COHORT FOR PRECLINICAL AND PRODROMAL ALZHEIMER’S DISEASE (TRC-PAD): EXPERIENCE FROM THE FIRST 3 YEARS

 

S. Walter1, O.G. Langford1, T.B. Clanton1, G.A. Jimenez-Maggiora1, R. Raman1, M.S. Rafii1, E.J. Shaffer1, R.A. Sperling2, J.L. Cummings3, P.S. Aisen1 and the TRC-PAD Investigators*

 

1. Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, USA; 2. Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 3. Department of Brain Health, School of Integrated Health Sciences, University of Las Vegas, Nevada; Cleveland Clinic Lou Ruvo Center for Brain Health, USA; * TRC-PAD investigators are listed at www.trcpad.org

Corresponding Author: S. Walter, Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, USA, waltersa@usc.edu

J Prev Alz Dis 2020;4(7):234-241
Published online August 13, 2020, http://dx.doi.org/10.14283/jpad.2020.47


Abstract

BACKGROUND: The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD) aims to accelerate enrollment for Alzheimer’s disease (AD) clinical trials by remotely identifying and tracking individuals who are at high risk for developing symptoms of AD, and referring these individuals to in-person cognitive and biomarker evaluation with the purpose of engaging them in clinical trials. A risk algorithm using statistical modeling to predict brain amyloidosis will be refined as TRC-PAD advances with a maturing data set.
Objectives: To provide a summary of the steps taken to build this Trial-Ready cohort (TRC) and share results of the first 3 years of enrollment into the program.
Design: Participants are remotely enrolled in the Alzheimer Prevention Trials (APT) Webstudy with quarterly assessments, and through an algorithm identified as potentially at high risk, referred to clinical sites for biomarker confirmation, and enrolled into the TRC.
Setting: Both an online study and in-clinic non-interventional cohort study.
Participants: APT Webstudy participants are aged 50 or older, with an interest in participation in AD therapeutic trials. TRC participants must have a study partner, stable medical condition, and elevated brain amyloid, as measured by amyloid positron emission tomography or cerebrospinal fluid analysis. Additional risk assessments include apolipoprotein E genotyping.
Measurements: In the APT Webstudy, participants complete the Cognitive Function Index and Cogstate Brief Battery. The TRC includes the Preclinical Alzheimer’s Cognitive Composite, comprised of the Free and Cued Selective Reminding Test, the Delayed Paragraph Recall score on the Logical Memory IIa test from the Wechsler Memory Scale, the Digit-Symbol Substitution test from the Wechsler Adult Intelligence Scale-Revised, and the Mini Mental State Examination total score (1).
Results: During the first 3 years of this program, the APT Webstudy has 30,650 consented participants, with 23 sites approved for in person screening, 112 participants have been referred for in-clinic screening visits with eighteen enrolled to the TRC. The majority of participants consented to APT Webstudy have a family history of AD (62%), identify as Caucasian (92.5%), have over twelve years of formal education (85%), and are women (73%). Follow up rates for the first quarterly assessment were 38.2% with 29.5% completing the follow up Cogstate Battery.
Conclusions: After successfully designing and implementing this program, the study team’s priority is to improve diversity of participants both in the APT Webstudy and TRC, to continue enrollment into the TRC to our target of 2,000, and to improve longitudinal retention, while beginning the process of referring TRC participants into clinical trials.

Key words: Alzheimer’s disease, prevention, webstudy, remote study.


 

Background

The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD) program aims to accelerate enrollment into clinical trials for AD by building a cohort of biomarker-confirmed eligible participants. The first stage of the program is remote recruitment of participants to the Alzheimer Prevention Trials (APT) Webstudy (2). Participants are followed with quarterly assessments, and through an algorithm identified as potentially at high risk, and referred to clinical sites. Participants are screened for Trial-ready cohort (TRC) eligibility, involving cognitive testing, genotyping and amyloid biomarker measures, and then if eligible, enrolled and followed longitudinally until an appropriate clinical trial becomes available. Separate papers summarize the program design and implementation considerations (3), the complex informatics infrastructure (4), the algorithm to predict brain amyloidosis and risk for AD (5), and recruitment strategies (2). Here we expand on the experience of the TRC-PAD program during its initial three years.

Study network and infrastructure

The TRC-PAD program is the result of extensive collaboration between multiple principal investigators (PIs), online National Registries, the Coordinating Center, and the network of clinical trial sites. Registries that referred participants to the APT Webstudy were the Alzheimer’s Prevention Registry (APR), The Alzheimer’s Association TrialMatch, Brain Health Registry (BHR), and Healthy Brains, as well as registries managed by clinical trial sites. The study was coordinated by the Alzheimer’s Therapeutic Research Institute (ATRI) at the University of Southern California (USC). Periodic updates were provided to the clinical trial sites involved in the program during the development phase. A small group of “vanguard sites” were selected first, with their study teams providing feedback on the referral process, before expanding to the total sites. Each clinical site participating in the TRC receives modest financial support for local recruitment and referral efforts, separate from their reimbursement for TRC participant visits. In 2019, the TRC-PAD program became affiliated with the Alzheimer’s Clinical Trials Consortium (ACTC) with scientific guidance provided by the ACTC Steering Committee.

Regulatory oversight

The APT Webstudy is overseen by the University of Southern California (USC) Institutional Review Board (IRB), which reviews and approves all participant-facing content, including the informed consent documents, web pages, emails, newsletters, and quarterly testing reminders. The IRB provided initial approval for the APT Webstudy in November 2017 and the Webstudy launched four weeks later (Figure 1). IRBs overseeing Registries also reviewed recruitment materials. The protocol describing in-person visits, screening, and enrollment in the TRC is overseen by Advarra IRB, the central IRB. In some cases, the local IRBs that oversee the clinical trial sites also required review of materials.

APT Webstudy Participant support

Support is provided in-house by the APT Webstudy team at the USC Alzheimer’s Therapeutic Research Institute (ATRI). Participants may telephone or email the study team with their questions. Using a ticketing and tagging system, each issue is tracked centrally, which allows the support team to identify patterns and trends. Questions are triaged to subject matter experts when needed; for example, to a clinician or technical team member. Issues are reviewed centrally at regular intervals and used to improve the website and study communications.

Retention tools

Retention of study participants and capturing longitudinal assessments, particularly cognitive testing, are critical to the program aims. The APT Webstudy team developed a participant engagement platform to optimize the Webstudy experience. Each participant is provided results of their clinical and cognitive testing over the course of the study. Reminder emails alert participants when the next quarterly assessment is due. In addition, a quarterly newsletter called “Alzheimer’s Research Today” is emailed to all participants, including updates from the field of AD research, describing upcoming studies, and providing information on new features of the Webstudy.

APT Webstudy experience

In order to register for the APT Webstudy, participants are asked to log in using either their existing social login credentials, or to create an account by providing a username, email address and password. Once logged on, participants are considered ‘registered.’ The Webstudy is designed as a ‘walk through’ experience, with each new section opening after completion of the former section.

Step 1

Personal profile. Participants provide basic information including age, race and ethnicity, education, zip code, whether they have been diagnosed with Alzheimer’s disease, and whether they are interested in participating in future AD clinical trials and are willing to share information with clinical sites near them.

Step 2

Consent. Each participant is asked to indicate whether they agree to participate or do not agree to participate. The consent form is displayed online and may be downloaded. Consent is required to move forward and may be revoked at any time.

Step 3

Lifestyle. Participants are asked brief questions about diet and lifestyle. Questions about prior genetic and amyloid testing were added in January 2019, 12 months after the APT Webstudy launched. Participants enrolled prior to this question being included are prompted to respond to these questions the next time they sign on.

Step 4

Remote Cognitive and Functional Assessments. The Cognitive Function Instrument (CFI) is a 15-item participant-reported questionnaire (6, 7). This assessment captures the participant’s perceived ability to perform high level functional tasks in daily life, as well as their sense of overall cognitive functional ability. The participant self-reported CFI has been validated in prior studies to provide early indication of future cognitive decline (7). The Cogstate Brief Battery (CBB), comprised of four simple playing card tasks measuring psychomotor speed and recent memory (8), is used to assess cognition and memory function. The One-Card Learning Test has shown particular sensitivity to amyloid-related decline in preclinical and prodromal AD (9).

Step 5: Review Scores

After completing the remote assessments, the participant can review their CFI scores in a ‘Dashboard’ view. There is a description below the score of the test, explaining what the scores might mean, (e.g. “An increasing score over time might mean cognitive decline”). CBB scores are processed within 2-5 days, and participants are notified by email when scores are available. The website description of the CBB emphasizes that the tool is used for research, and that a change in score between -10 to +10 is considered normal. After completion, the cognitive test questions are no longer available to the participant, and the next available testing date is displayed (3 months from previous test date).

Clinical Site Referrals

Data from the APT Webstudy are evaluated monthly using an adaptive algorithm. This algorithm uses statistical models to assess each participant’s risk of AD amyloidosis (5). In order to be referred, participants must have consented to the APT Webstudy, agreed to share information with researchers, and provided a valid zip code. Participants are ranked by their predicted risk, and those with the highest risk are referred to the nearest TRC-PAD site based on their zip code. Site referrals are provided via a secure web-based tool, the Site Referral System (SRS), with the flow of participants customized to meet the site’s capacity. Site staff reach out to participants using their preferred method of contact, conduct prescreening, and if the participants are interested and appears to be eligible, invites them for an in-person screening visit to confirm eligibility for the Trial-Ready Cohort (TRC).

Trial Ready Cohort (TRC)

The eligibility criteria for TRC-PAD broadly encompass both current and upcoming clinical trials in prodromal and preclinical AD, with the aim of enrolling 2,000 participants; approximately 1,000 preclinical and 1,000 prodromal. Screening is conducted in multiple phases, first confirming clinical and cognitive eligibility and performing apolipoprotein E (APOE) genetic testing. Using this additional information, the participant’s risk assessment is updated and reviewed centrally before screening proceeds to amyloid testing, either by positron emission tomography (PET) imaging or cerebrospinal fluid (CSF) collection by lumbar puncture. Following procedures that were designed and refined for the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) study (10, 11), participants are told whether they are eligible for the TRC. A 21 CFR Part 11 compliant electronic data capture system was developed by the TRC-PAD study team to manage participant data (4). Broad data-sharing in the TRC consent allow the data to be potentially used as run-in data for downstream clinical trials, minimizing participant burden. Once enrolled in the TRC, participants are followed with clinical and cognitive assessments every 6 months until a clinical trial becomes available at their site. The decision to screen for a clinical trial is entirely that of the participants, with appropriate guidance from their clinician. The protocol is designed to allow participants to re-enter the cohort after participation in another study or a break for any other reason.

 

Results

APT Webstudy Enrollment

The first major increase in APT Webstudy enrollment followed an article in a San Diego newspaper in February 2018, which resulted in over 2,000 consented participants. Gradually other recruitment initiatives were rolled out, resulting in 10,000 participants in January 2019, doubling to 20,000 participants in August 2019. As of the data cut for this manuscript (April 20, 2020) there are 30,650 participants consented to the APT Webstudy. More details on APT Webstudy recruitment methods and metrics are described in another paper in this series (2).

Table 1. APT and TRC Demographics (April 20, 2020)

 

APT Webstudy Demographics

Participants consenting to the APT Webstudy range in age from 17 to 94 with the mean age of 64.5, and 98.8% of participants are over the age of 50. A majority (73.0%) of Webstudy participants are female. 62.2% have a parent or sibling diagnosed with AD, and 4.6% report a diagnosis of AD. 85% have post-secondary education, with 14% reporting high school or equivalent education. Participants are 92.5% Caucasian, with 2.3% Hispanic/Latino, 1.5% African American, 1.4% Asian, and 0.2% American Indian and 0.1% Pacific Islander. 53.2% of participants are retired or not working, 30.6% are working full time, and 14.7% part-time. Within the US, geographic distribution of participants is broad, with participants in 59.1% of US counties (2). About half of APT Webstudy participants report no medical concerns, with the other half most commonly reporting high blood pressure (30%), diabetes (8%), or vascular disease (4%). In terms of lifestyle, 74% exercise 1 or more hours per week, and 81% do not drink alcohol regularly (defined as 2 drinks per day or more). Most participants prefer being contacted by email (78.7%) over a phone call (3.1%).

TRC Enrollment

The first referral from SRS to a TRC-PAD Site was in July 2019 with the first screening visit conducted one month later (Figure 1). As additional sites were approved to enroll, screening activity increased to 20 screens per month in late 2019 and into early 2020. As of April 20, 2020, 1,178 participants have been referred to SRS, and 171 (14%) (Figure 2) have been subsequently referred to be screened for TRC. 112 TRC screening visits have been conducted at 9 Sites, with 54 TRC participants completing the amyloid testing, resulting in 25 participants eligible for enrollment into the TRC. 18 participants have completed a baseline visit (Figure 2).

Figure 1. TRC-PAD Program Timeline

igure 2. TRC-PAD Program Funnel

 

TRC Demographics

Of the 112 participants with an in-person screening visit, participants are aged 60-79, (mean 71.1 SD 10.6), 49.5% are women, and 93% identify as Caucasian.

APT Webstudy Retention and Drop-outs

Participants were most likely to drop from the Webstudy at the point of consent, with 3,307 (9.7%) registering for the Webstudy but not completing the consent and 8,850 (28.9% of consented participants) not completing the initial CBB. Based on feedback from participants through the user support desk, the missed cognitive assessments are due to technical challenges and lack of compatibility of the CBB with smart phones. Retention is a challenge in the Webstudy with only 10,393 (38.2%) returning for their 2nd visit and 7,220 (28.8%) returning for visit 3. 538 participants have completed up to 8 follow up visits. The CBB retention has been lower, with 8,025 (29.5%) completing testing for the 2nd visit, and 5,777 (23%) for the 3rd visit. 461 participants have completed the CBB for up to the 8th follow up visit.

User Support

Since launching the APT Webstudy, over 1,900 inquiries have been received from users, with a majority (78%) received by email. The most frequent reason for support (38%) is regarding the Cogstate testing. 19% of support requests are related to logging into the Webstudy, 7% are questions related to the scores for CFI or Cogstate, 7% are for non Cogstate-related technical support, and the remainder are miscellaneous support needs. Most inquiries require more than one response and took more than 2 days to resolve. Phone inquiries require an average of 20 minutes of staff time to resolve.

Self-report of prior testing

13.03% of the APT Webstudy participants report undergoing prior APOE testing. Of these 3,989 participants with prior testing, 28% report not carrying the APOE-4 risk gene, 33% report one copy of the APOE-4 allele, and 9% reported having 2 copies. 5% reported that they carry the risk gene but do not know the details, and 23% didn’t know the results. In contrast, only 4.03% of participants had prior amyloid testing, with 2.86% having a prior PET Scan, and 1.17% a prior lumbar puncture.

APT clinical and cognitive assessment

Nearly every participant that signed consent completed the CFI (97%), with a majority scoring in normal ranges (Figure 3). 65% of Webstudy participants completed the initial Cogstate testing (Figure 4).

Figure 3. APT Webstudy Cognitive Function Instrument (CFI)

Figure 4. APT Webstudy Cogstate One card learning

 

Discussion

We have demonstrated that it is feasible to build a cohort of remotely-consented and enrolled participants with normal cognition, with broad geographic distribution using an unsupervised cognitive assessment battery to evaluate for increased risk for future cognitive decline. This first stage of the TRC-PAD program represents the best in what collaborative science can achieve. The partnership between the PI’s, an experienced Coordinating Center, the network of sites, academic partners, and the valuable experience and advice of investigators overseeing the APR, TrialMatch, HealthyBrains, and BHR have been critical to this success.
In general, the group of individuals enrolled in the APT Webstudy are similar to those enrolled in clinical trials, with most being highly educated and Caucasian, and a majority reporting a family history of AD. We were intentional in designing the APT assessments to be as brief as possible, and believe that low drop-out rates during initial visit is due to this. The most commonly reported problem leading to missing information on the CBB was incompatibility with smart phones; we expect that compatibility will be improved in the future.
Retention to the APT Webstudy is comparable to what has been reported by online Registry studies (12) and remains a significant challenge. Capturing longitudinal information is an important goal of TRC-PAD. More work is needed to understand why participants are not returning, in order to improve content, language, and presentation.
The APT Webstudy and TRC have both recruited a mostly white and highly educated group, which limits the representativeness of clinical trial participants using this program to the general population. We hope to improve accessibility of the APT Webstudy with the recently released Spanish translation and Spanish-language user support.
Providing consistent and knowledgeable user support for a remote Webstudy has been critical to success. We have found great value in using a centralized ticketing system, which consolidates multiple communication channels (e.g. email, telephone) and allows the study team to identify trends and prioritize development and refinement of procedures.
Ultimately, the success of TRC-PAD will be measured by efficient referral of representative participants from TRC-PAD into clinical trials. Can we predict brain amyloid elevation using Webstudy data augmented by in-person assessment, APOE genotyping and eventually plasma amyloid peptide testing (3) to reduce screening amyloid PET expenses? Can we reduce the long recruitment and screening timelines seen in studies like A4 and early symptomatic-stage AD trials? Can we minimize participant and site burden through efficient design and data-sharing between TRC-PAD and clinical trials? How do we enroll an inclusive group of individuals who are representative of the population at greatest risk for cognitive decline due to AD? TRC-PAD remains a work in progress. Continuing adjustments to its design are essential to optimizing its value.

 

Funding: The study was supported by a grant from NIA/NIH (R01AG053798). The sponsors had no role in the design and conduct of the study, in the collection, analysis, and interpretation of data, in the preparation of the manuscript, or in the review or approval of the manuscript.

Acknowledgments: We would like to acknowledge and thank our participants, the teams at each of the clinical sites, and the USC Alzheimer’s Therapeutic Research Institute (ATRI) Coordinating Center team members whose work made this study possible. In particular, Devon Gessert, Yuliana Cabrera, Emily Voeller, Stefani Bruschi, Jia-Shing So, Marian Wong, Rosio Gonzalez-Beristain, and Godfrey Coker. A full list of TRC-PAD investigators is at: www.trcpad.org.

Ethical standard: Institutional Review Boards (IRBs) approved these studies, and all participants gave informed consent before participating.

Conflict of interest: The authors report grants from National Institute on Aging, during the conduct of the study. None of the authors have additional financial interests, relationships or affiliations relevant to the subject of this manuscript.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

References

1. Mormino EC, Papp KV, Rentz DM, et al. Early and late change on the preclinical Alzheimer’s cognitive composite in clinically normal older individuals with elevated amyloid β. Alzheimers Dement 2017;13(9):1004-1012
2. Walter S, Clanton TB, Langford OG, Recruitment into the Alzheimer Prevention Trials (APT) Webstudy for a Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s Disease (TRC-PAD). J Prev Alz Dis 2020; DOI: 10.14283/jpad.2020.46
3. Aisen PS, Sperling R., Cummings J, et al. The Trial-Ready Cohort for Preclinical/Prodromal Alzheimer’s Disease (TRC-PAD) Project: An Overview. J Prev Alz Dis 2020; DOI: 10.14283/jpad.2020.45
4. Jimenez-Maggiora GA , Bruschi S., Raman R, et al. TRC-PAD: Accelerating Recruitment of AD Clinical Trials through Innovative Information Technology. J Prev Alz Dis 2020; DOI: 10.14283/jpad.2020.48
5. Langford O, Raman R, Sperling RA, et al. Predicting Amyloid Burden to Accelerate Recruitment of Secondary Prevention Clinical Trials. J Prev Alz Dis 2020; DOI: 10.14283/jpad.2020.44
6. Walsh SP, Raman R, Jones KB, Aisen PS. ADCS Prevention Instrument Project: The Mail-In Cognitive Function Screening Instrument (MCFSI). Alzheimer Dis Assoc Disord 2006;20(4 Suppl 3):S170-8
7. Amariglio RE, Donohue MC, Marshall GA, et al. Tracking Early Decline in Cognitive Function in Older Individuals at Risk for Alzheimer Disease Dementia. JAMA Neurol 2015;72(4):446-454
8. Crook TH, Kay GG, Larrabee GJ, et al. Computer-based cognitive testing. Neuropsychol assess of Neuropsychiatr. and Neuromedical Disord 2009:84-100
9. Darby DG, Brodtmann A, Pietrzak RH, et al. Episodic Memory Decline Predicts Cortical Amyloid Status in Community-Dwelling Older Adults. J Alzheimers Dis 2011;27(3):627-637
10. Sperling RA, Rentz, DM, Johnson KA, et al. The A4 Study: Stopping AD before Symptoms Begin? Sci Transl Med 2014 Mar 19; 6(228): 228fs13
11. Sperling, RA, Donohue, MC, Raman, R, Sun, et al. Association of Factors with Elevated Amyloid burden in Clinically Normal Older Individuals. JAMA Neurol 2020 Apr 6;e200387. Doi: 10.1001/jamaneurol.2020.0387
12. Weiner MW, Nosheny R, Camacho M, et al. The Brain Health Registry: An internet-based platform for recruitment, assessment, and longitudinal monitoring of participants for neuroscience studies. Alzheimers Dement 2018;14(8):1063-1076

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RECRUITMENT INTO THE ALZHEIMER PREVENTION TRIALS (APT) WEBSTUDY FOR A TRIAL-READY COHORT FOR PRECLINICAL AND PRODROMAL ALZHEIMER’S DISEASE (TRCPAD)

S. Walter1, T.B. Clanton1, O.G. Langford1, M.S. Rafii1, E.J. Shaffer1, J.D. Grill3, G.A. Jimenez-Maggiora1, R.A. Sperling2, J.L. Cummings4, P.S. Aisen1 and the TRC-PAD Investigators*

1. Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, USA; 2. Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 3. Institute for Memory Impairments and Neurological Disorders, University of California, Irvine;
4. Department of Brain Health, School of Integrated Health Sciences, University of Las Vegas, Nevada; Cleveland Clinic Lou Ruvo Center for Brain Health, USA;* TRC-PAD Investigators are listed at www.trcpad.org

Corresponding Author: S. Walter, Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, USA, waltersa@usc.edu

J Prev Alz Dis 2020;4(7):219-225
Published online August 11, 2020, http://dx.doi.org/10.14283/jpad.2020.46

 


Abstract

BACKGROUND: The Alzheimer Prevention Trials (APT) Webstudy is the first stage in establishing a Trial-ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD). This paper describes recruitment approaches for the APT Webstudy.
Objectives: To remotely enroll a cohort of individuals into a web-based longitudinal observational study. Participants are followed quarterly with brief cognitive and functional assessments, and referred to Sites for in-clinic testing and biomarker confirmation prior to enrolling in the Trial-ready Cohort (TRC).
Design: Participants are referred to the APT Webstudy from existing registries of individuals interested in brain health and Alzheimer’s disease research, as well as through central and site recruitment efforts. The study team utilizes Urchin Tracking Modules (UTM) codes to better understand the impact of electronic recruitment methods.
Setting: A remotely enrolled online study.
Participants: Volunteers who are at least 50 years old and interested in Alzheimer’s research.
Measurements: Demographics and recruitment source of participant where measured by UTM.
Results: 30,650 participants consented to the APT Webstudy as of April 2020, with 69.7% resulting from referrals from online registries. Emails sent by the registry to participants were the most effective means of recruitment. Participants are distributed across the US, and the demographics of the APT Webstudy reflect the referral registries, with 73.1% female, 85.0% highly educated, and 92.5% Caucasian.
Conclusions: We have demonstrated the feasibility of enrolling a remote web-based study utilizing existing registries as a primary referral source. The next priority of the study team is to engage in recruitment initiatives that will improve the diversity of the cohort, towards the goal of clinical trials that better represent the US population.

Key words: Trial-ready cohort, online registry, remote recruitment, web-based, preclinical, Alzheimer’s disease, prevention.


 

Background

Identifying eligible participants for early intervention Alzheimer’s disease (AD) clinical trials continues to be a significant challenge in the field (1, 2). The overarching aim of the Trial-Ready Cohort in Preclinical and Prodromal Alzheimer’s Disease (TRC-PAD) program is to accelerate enrollment for early stage AD clinical trials (3). This will be accomplished by identifying and screening participants to confirm eligibility for these trials, including amyloid biomarker confirmation, and then monitoring and maintaining engagement with these participants through longitudinal visits until an appropriate trial is available. The considerations behind the design of TRC-PAD are described by Aisen et al. (4). The first step in establishing the Trial-ready Cohort (TRC) was to recruit participants into the Alzheimer Prevention Trials (APT) Webstudy, an online assessment tool designed to serve as a feeder to the in-person TRC-PAD cohort. We projected the APT Webstudy would require between 25,000 and 50,000 participants, with at least 20% participants from under-represented communities, in order to identify enough eligible participants for a planned TRC of n=2,000. The APT Webstudy program requires secure and scalable informatics infrastructure (5), as well as an algorithm to identify participants and rank them by risk of brain amyloidosis and development of AD dementia (6). These elements of the program are described in separate papers in this series.
The APT Webstudy was launched as clinical trials have increasingly utilized web-based tools, including registries, to improve efficiency in screening (7-9). Although leveraging registries to recruit for clinical trials is not a new concept, the establishment of online registries has broadened access to participants who are interested and eligible for studies (10-13). Going further than remote recruitment, Orri et al (14) conducted the first entirely web-based clinical trial run under an Investigational New Drug (IND) application. Digital tools allow researchers to optimize the use of mobile technologies in clinical trials, respond to the preferences of participants (15), and measure and fine-tune communication methods (16). To our knowledge, TRC-PAD is the first program inviting participants from various existing registries to a join a longitudinal Webstudy with identification and referral of high-risk individuals to an in-person TRC. In this article, we describe the preliminary experience of efforts to recruit to APT Webstudy, including from national and local registries, as a unifying path to enrollment in TRC-PAD.

 

Methods

APT Webstudy Experience

Participants log in using either their existing social login credentials or by creating an account and providing a username, email address and password. Once logged on, participants are considered ‘registered.’ The Webstudy is designed as a ‘walk through’ experience, with each new section opening after completion of the former. The sections are: Step 1: Personal Profile; Step 2: Consent; Step 3 Lifestyle; Step 4: Remote cognitive and functional assessments; Step 5: Review scores. Sections are described in more detail in a separate paper in this series (17). The questionnaires and assessments were designed to be brief with a target duration of 15 minutes.

Recruitment

APT Webstudy participants are recruited from multiple sources. For the purposes of this paper, the term registry refers to a online registry, study, or service matching individuals interested in participating in studies or clinical trials to prevent or delay AD dementia. Early in its development, the TRC-PAD study team established partnerships with each of the largest “Feeder” registries, and in collaboration with the managing team or investigators, developed a referral strategy based on the registry’s unique population and existing communication pathways. Each strategy began small and was expanded when we were able to ensure the stability of the Webstudy infrastructure, as well as our capacity to provide user support. Outreach took the form of direct email campaigns highlighting the APT Webstudy on the registry website, e-newsletters, and social media posts. In addition to referrals from registries, both central and site-based strategies were employed.

UTM Codes

Urchin Tracking Modules (UTM) were generated to track participants that registered for the APT Webstudy in response to digital outreach, and were embedded in emails, webpages, and social media advertisements. For some registries, although various outreach activities were utilized, all responses linked back through the registry website, requiring use of a single UTM, and limiting our ability to understand the response rates to different digital communications. Recruitment strategies that did not utilize a UTM included printed materials (i.e., brochures, newsletters and magazines) and earned media (i.e., online and print newspaper articles).

The Alzheimer’s Prevention Registry (APR) (www.endalznow.org)

APR was launched in October 2012 by the Banner Alzheimer’s Institute with the aim of providing a shared resource to the AD scientific community to facilitate enrollment in studies to prevent AD. In 2015, APR began offering an optional APOE genotyping program (GeneMatch) to members ages 55-75 to help match individuals to research studies. As of August 2018, APR enrolled a total 320,000 participants with 75,351 agreeing to the GeneMatch program, and approximately 75,000 agreeing to be contacted by researchers (18). APR participants are primarily women (65.6%) and Caucasian (45.5%); 1.8% are Hispanic/Latino and less than 1% are from other underrepresented groups. It should be noted that these percentages are a reflection of only the 60.8% of APR participants who provided their Race or Ethnicity (Table 1) (19). 14% of APR participants are age 50-59, 35% age 60-69, and 23% age 70-79 (Table 1). The APT Webstudy recruitment strategy began with a pilot phase in April 2018, with batches of emails sent from APR to 7,293 individuals (Figure 1). This was followed by an article in the APR quarterly newsletter introducing the APT Webstudy and posts on APR’s social media accounts. In January 2019, emails were sent in batches to 75,000 registrants inviting them to join the APT Webstudy. In March and April 2020, follow up emails were sent to participants who had not opened the email or clicked the link for the APT Webstudy, with additional reminders scheduled for May 2020.

Alzheimer’s Association TrialMatch (trialmatch.alz.org)

Alzheimer’s Association TrialMatch (trialmatch.alz.org) is a free online matching service that utilizes user’s information to generate a custom report of clinical trials for which they may be a good fit. TrialMatch has a large pool of 322,997 users, with 134,148 providing contact and personal information. Individuals enrolled in TrialMatch indicate whether they are a healthy volunteer (52.8%), a caregiver looking for clinical trials for someone else such as a family member with AD (31.7%), or a person living with the disease looking for trials (13.3%). A small percent (2.2%) of users are entered into TrialMatch by a physician or researcher. Individuals under 50 comprise 35% of the Healthy Volunteers and 20% of all TrialMatch participants. 69% of TrialMatch are over the age of 50. Participants are 73.4% Caucasian, 4.5% Hispanic/Latino, and 65% are women. Women comprise 78% of the healthy controls and 54% of caregivers looking for trials for someone else. 22% of TrialMatch users either care for someone with a diagnosis of AD or have a diagnosis of AD. The first APT Webstudy recruitment campaign began in March 2019, with direct emails targeting 48,000 TrialMatch users living within 200 miles of potential TRC-PAD clinical sites. An additional 33,000 users were invited to join APT Webstudy beginning in December 2019. Emails were sent in batches of 5,000 twice a week, and is ongoing at the time of this manuscript.

The Brain Health Registry (BHR) (brainhealthregistry.org)

The Brain Health Registry (BHR) (brainhealthregistry.org) collects longitudinal health, cognitive, and lifestyle data through detailed self-report questionnaires and online cognitive tests (Cogstate, Lumosity, and MemTrax) (16). BHR was launched in 2014 and currently has baseline data on 56,982 participants. BHR participants are 80.9% Caucasian, 5.3% Hispanic/Latino, 73.9% women, with 73% of participants over the age of 50 (20) (Table 1). The BHR team sent emails to 18,240 participants inviting them to register for the APT Webstudy beginning in March 2019 (Figure 1). Emails were sent in batches of 500 every week. If participants do not respond, two follow-up emails are sent, with a second set of reminder emails 231 and 238 days from their initial email contact. The BHR team also featured the APT Webstudy in their e-newsletter.

Table 1. Feeder Registries and APT Demographics

The Cleveland Clinic Healthy Brains Registry (healthybrains.org)

 

The Cleveland Clinic Healthy Brains Registry (healthybrains.org) is a longitudinal, web-based symptomatic and lifestyle assessment (21), with over 13,000 registrants, and over half expressing interest in enrolling into clinical trials. HealthyBrains has registrants and newsletter subscribers from across the nation. The highest number of registrants in the US states of Ohio, Nevada, California and Florida. Registrants were invited to join the APT Webstudy through an article on the HealthyBrains website in May 2018, followed by features in two newsletters, sent by email (Figure 1).

Figure 1. Alzheimer Prevention Trials (APT) Webstudy: Feeder Registry Recruitment Campaign Timeline

 

UCI Consent-to-Contact (C2C) Registry (c2c.uci.edu)

UCI Consent-to-Contact (C2C) Registry (c2c.uci.edu) is a confidential online tool to help match local volunteers in Orange County, CA, with research studies at the University of California, Irvine (22). Registrants enroll by providing an email address or by phoning the research site, remotely completing a series of questions regarding medical history and research interests. Beginning in July 2019, 7,300 C2C participants were invited by email to join the APT Webstudy (Figure 1).

Other sources

Anticipating that the registry-based approach would have limitations, especially in identifying eligible participants from under-represented groups, the APT Webstudy team developed recruitment strategies utilizing the TRC-PAD site network as well as other central activities. Sites participating in the TRC-PAD cohort study were identified early in the development of the program, with some agreeing to work locally to recruit participants to the APT Webstudy. Each of the TRC sites were invited to utilize their own databases of individuals interested in clinical research and email information about the APT Webstudy. The TRC-PAD study team provided flyers, postcards, newsletter and email template language, social media content and leaflets describing the APT Webstudy. Language for these materials was approved by the Institutional Review Board (IRB) and UTM codes were generated where appropriate. Sites also held community outreach events, partnered with other local community organizations to share information about the study, advertised on social media, and posted information about the Webstudy on their own webpages. Central recruitment efforts included generating earned media including newspaper and online and print edition magazine articles, local TV interviews, and posting the study on websites for clinical trials and AD. The earned media stories included an article in the San Diego Union Tribune in January 2018, two letters to the editor in May 2019, in local papers that have circulations of 80,000 (Charleston, SC) and 150,000 (Lexington, KY) respectively. Grand Magazine published an online piece about the APT Webstudy on August 12, 2019, generating 54,000 impressions. The Saturday Evening Post, with a circulation of 302,000 and majority of readers over the age of 45, included APT in its January/February 2020 print edition. So far, the only paid advertising was in the form of Facebook advertisements. Facebook ads ran in eight markets for two weeks in November 2018 for a cost of $12,000, and six markets for 5 weeks in August-September 2019 for a cost of $3,000. The ads were targeted geographically and to the largest minority population in each location, based around the location of TRC sites.

 

Results

APT Webstudy Enrollment: At the time of preparing this mansuscript, there are 30,650 participants consented to the APT Webstudy. Recruitment strategies for the first year were a mix of central and local efforts (Figure 1). The first notable increase was in January 2018 following local newspaper coverage. In March 2018, email referrals were piloted for APR Registry. In April 2018, APR and HealthyBrains introduced the Webstudy in their newsletters. In the first year, 388 participants per month consented to the APT Webstudy on an average. The APR email referrals began in earnest in January 2019, leading to a dramatic increase in consented participants, with 5,196 consenting in January 2019 (Figure 1). This was followed by email referrals from TrialMatch and BHR. In the second year, participants consented to the APT Webstudy on an average of 1,514 per month.

Demographics

Participants in the APT Webstudy have a mean age of 64.56 with a majority of participants ages 50-59 (28.9%) and 60-69 (44.1%) (Table 1). Most participants identify as women (73.0%), white (92.5%) and more than high school level education (85.0%). 2.3% of APT Webstudy participants self describe as Hispanic/Latino. Although most participants are retired or not working (53.2%), a significant percentage are employed either full (30.6%) or part-time (14.7%) (Table 2). A majority of participants have a family history of AD (62.6%) and do not have a personal diagnosis of AD (94.6%). Further details on lifestyle and medical history are provided on Tables 2 and 3.

Table 2. APT Webstudy Health and Lifestyle

Table 3. APT Webstudy Recruitment by Referral Sourc

 

Enrollment by Referral sources

At this point in the recruitment to the APT Webstudy, registries were the primary source of participants, with referrals resulting in 69.69% of consented individuals, according to UTM codes. APR was by far the biggest contributer with 38.98% of all APT Webstudy consented participants, followed by 25.40% referred by TrialMatch. Those referred by APR were also slightly more likely to both register and consent to APT (Table 3). All together 15.9% of the APR participants that were contacted consented to APT, compared to 9.8% or less for other registries. Email (32.92%) and websites (40.78%) were the most common mode of referral, however website visits were largely driven by email campaigns. Central media efforts that could be tracked with UTM resulted in 234 participants. The central Facebook ads accounted for 7,800 and 3,000 clicks which translated to 0.15% of consenting participants.

Geographic Distribution

APT Webstudy participants reside in each of the 50 United States (US), the District of Columbia, and Puerto Rico. States with the highest number of consented participants include California (16.63%), Florida (5.65%), New York (4.67%), Texas (4.66%), and Virginia (4.38%). International location is not currently collected. Participants consented to the APT Webstudy reside in 1931 (or 60%) of US counties. The top ten counties with participants consented to APT are San Diego County, CA (n=1621); Orange County, CA (n=861) Maricopa County, AZ (n=764), Los Angeles County, CA (n=612), Cook County, IL (n=443) Charleston County, SC (n=384), Fayette County, KY (n=279), King County, WA (n=270) Pima County, AZ (n=239) and Middlesex County, MA (n=238) (Figure 2).

Figure 2. APT Webstudy Enrollment: Heatmap of US Counties

 

Discussion

We have demonstrated that online registries are not only feasible but they are an excellent method to identify and recruit participants for a Webstudy. Participants in a registry have already demonstrated an interest in research and willingness to provide information about themselves. In addition, registries have communication infrastructure and digital platforms designed to engage individuals through educational materials, newsletters and other outreach, which may lead to higher rates of referral. UTM codes were shown to be an effective method to track the referral source in this study. The strategy that yielded highest rates of responses was to first feature the APT Webstudy in the registry’s newsletter, followed by direct email communication to registrants. Although not tracked with separate UTM codes, the consistent increase of participants demonstrates that sending second and third emails to non-responders produces additional participants. Although central media efforts and social media advertising were piloted in this first stage of recruitment, this strategy has not been fully explored as a potential source for remotely enrolled participants.
The registries used in this study had a contact-to-consent rate ranging from 1.8%-15.9%, despite having very similar composition of registrants. This brings up several questions as to best practices. Was the higher rate of consent from APR compared to BHR due to the fact that APR directly targets individuals interested in clinical trials? Could the observed rate of consent to contacted participant be influenced by the level of engagement utilized by the respective registries?
It is not surprising that the demographics of participants in the APT Webstudy are similar in demographics to the registries that referred the majority of participants. However, understanding why such a large majority of participants are women is important. Further research may reveal both barriers to in-person research and preferences for online studies. The low rate of Hispanic/Latino involvement in APT Webstudy can likely be attributed to 2 factors, (1) the low rates of Hispanic/Latino participants in the referral registries and (2) the APT Webstudy and recruitment materials had not been translated into Spanish.
We acknowledge that the APT Webstudy has an inherent selection bias, in that participants must have access to the internet in order to participate. This disproportionately excludes many people from under-represented communities, where according to recent Pew reports, only 57% of Hispanic and African American adults own a laptop or a tablet (23), compared to 82% of Caucasians. Although those over 65 years of age are more likely to use a desktop or tablet to access the internet, lower income Americans, those with less than college education, and black and Hispanic populations, are all more likely to use a cell phone to access the internet (24). Although the APT Webstudy is mobile-friendly, the cognitive testing at present requires use of a tablet or computer. The study team is considering changes to cognitive testing that will allow for the use of smart phones and expand accessibility to all communities. Other researchers (25) have demonstrated that text messages can be an effective communication channel with research participants. Would people be more responsive to a text message inviting them to return for a study visit?
The Spanish language version of the APT Webstudy was launched early in 2020, with efforts underway to optimize the cultural sensitivity of the Webstudy and all participant-facing content. A key aim of the study is to engage in recruitment initiatives that will improve the diversity of the cohort, towards the goal of clinical trials that better represent the US population. For the African-American community in particular, recruitment campaigns will highlight disparities in Alzheimer’s disease risk and care, and the role research and clinical trials can play in effecting change.
This study has several limitations. The feeder registries differ in numerous ways, including sample sizes, aims or purpose, geographic distribution, length of time from when participants were first engaged with, and frequency of participant engagement. The current analyses did not account for these differences. Similarly, varying levels of data were available for participants in feeder registries, preventing combination of data streams for more sophisticated analyses of recruitment efficiency. Recruitment from feeder registries was peformed over multiple years, introducing potential confounding by time. Quantification of site level efforts toward recruitment was minimal, limiting our ability to understand the efficacy of site level efforts relative to using central efforts or these feeder registries.
In conclusion, this study demonstrates the feasibility of recruiting from feeder registries into a common platform for identifying potentially eligible participants for a Trial-ready cohort. A robust sample was assembled in a relatively short period of time that is anticipated to play a key role in the national AD clinical trial agenda.

 

Acknowledgements: From the Alzheimer’s Assocation, our thanks to Keith Fargo, Stephen Hall, and Martha Tierney. From APR: Jessica Langbaum, Cassandra Kettenhoven, and Nellie High. From Brain Health Registry: Rachel Nosheny, and Joseph Eichenbaum. From University California Irvine Registry we’d like to thank Meagan Witbracht. Coordinating Center staff providing support to APT Webstudy participants are Godfrey Coker and Rocio Gonzalez-Beristain. The informatics development team is Stefania Burschi, Jia-Shing So, and Marian Wong.

Funding: The study was supported by R01AG053798 from NIA/NIH. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

Ethical standard: Institutional Review Boards (IRBs) approved these studies, and all participants gave informed consent before participating.

Conflict of interest: The authors report grants from National Institute on Aging, during the conduct of the study. None of the authors have additional financial interests, relationships or affiliations relevant to the subject of this manuscript.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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TARGETING LIFESTYLE BEHAVIOR TO IMPROVE BRAIN HEALTH: USER-EXPERIENCES OF AN ONLINE PROGRAM FOR INDIVIDUALS WITH SUBJECTIVE COGNITIVE DECLINE

 

L.M.P. Wesselman1, A.K. Schild2, A.M. Hooghiemstra1,3, D. Meiberth2, A.J. Drijver4, M.v. Leeuwenstijn-Koopman1, N.D. Prins1, S. Brennan5, P. Scheltens1, F. Jessen2,6, W.M. van der Flier1,7, S.A.M. Sikkes1,8

 

1. Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; 2. Department of Psychiatry, University Hospital Cologne, Medical Faculty, Cologne, Germany; 3. Department of Medical Humanities, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands; 4. Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, The Netherlands; 5. The Adapt Centre, & The Institute of Neuroscience, Trinity College Dublin; 6. German Center for Neurodegenerative Disorders (DZNE), Bonn-Cologne, Germany; 7. Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands; 8. Clinical Developmental Psychology & Clinical Neuropsychology, Faculty of Behavioural and Movement Sciences (FGB), Vrije University Amsterdam, Amsterdam, the Netherlands.

Corresponding Author: Linda M.P. Wesselman, Alzheimer Center Amsterdam and Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, P.O. Box 7057, 1007 MB Amsterdam, the Netherlands, Telephone: +31-204440816; Fax: +31-204448529; E-mail: l.wesselman@amsterdamumc.nl

J Prev Alz Dis 2020;3(7):184-194
Published online March 2, 2020, http://dx.doi.org/10.14283/jpad.2020.9

 


Abstract

Background: Online programs targeting lifestyle have the potential to benefit brain health. We aimed to develop such a program for individuals with subjective cognitive decline (SCD). These individuals were reported to be at increased risk for dementia, and report both an intrinsic need for brain health information and motivation to participate in prevention strategies. Co-creation and user-evaluation benefits the adherence to and acceptance of online programs. Previously, we developed a prototype of the online program in co-creation with the users .
Objectives: We now aimed to evaluate the user-experiences of our online lifestyle program for brain health.
Design: 30-day user test; multi-method.
Setting: Participants were recruited in a memory clinic and (online) research registries in the Netherlands (Alzheimer Center Amsterdam) and Germany (Center for memory disorders, Cologne).
Participants: Individuals with SCD (N=137, 65±9y, 57% female).
Measurements: We assessed user-experiences quantitatively with rating daily advices and usefulness, satisfaction and ease of use questionnaires as well as qualitatively using telephone interviews.
Results: Quantitative data showed that daily advices were rated moderately useful (3.5 ±1.5, range 1-5 points). Participants (n=101, 78%) gave moderate ratings on the programs’ usability (3.7±1.3, max 7), ease of learning (3.6±1.9) and satisfaction (4.0±1.5), and marginal ratings on the overall usability (63.7±19.0, max 100). Qualitative data collected during telephone interviews showed that participants highly appreciated the content of the program. They elaborated that lower ratings of the program were mainly due to technical issues that hindered a smooth walk through. Participants reported that the program increased awareness of lifestyle factors related to brain health.
Conclusions: Overall user-experience of the online lifestyle program was moderate to positive. Qualitative data showed that content was appreciated and that flawless, easy access technique is essential. The heterogeneity in ratings of program content and in program use highlights the need for personalization. These findings support the use of online self-applied lifestyle programs when aiming to reach large groups of motivated at-risk individuals for brain health promotion.

Key words: Lifestyle, dementia, subjective cognitive decline, eHealth, prevention.

Abbreviations: SCD: subjective cognitive decline; MCI: mild cognitive impairment; SUS: System Usability Scale; USE: User Satisfaction and Ease of use.


 

Introduction

The World Health Organization (WHO) Global Action Plan on Dementia emphasized the need for campaigns to increase public awareness and understanding of dementia (1). Recent studies found that knowledge about prevention and treatment of dementia remains poor and that there is a need for adequate dementia prevention education (2, 3).
The body of evidence on the association between a healthy lifestyle and brain health keeps growing (4). Risk factors for dementia due to Alzheimer’s disease (AD), such as lifestyle factors, are suggested to be partly modifiable (5). A healthy lifestyle may therefore decrease the risk for AD dementia. Since the etiology of AD is complex and multifactorial, recommendations are made to target several risk factors simultaneously (6, 7). Indeed, a multifactorial intervention has been found to improve or maintain cognitive functioning in people at risk for dementia (8). However, this intervention was offered face-to-face, which is beneficial for program use because of personal contact, but is relatively expensive and limits possibilities to reach a larger group of individuals. Offering intervention programs online has an important advantage because it offers the opportunity to reach many users, in particular in remote areas (9).
Our international EuroSCD-project aimed to develop an online lifestyle program for brain health. Individuals with subjective cognitive decline (SCD) experience cognitive decline in absence of objective cognitive impairments. SCD has previously been reported to be a risk factor for dementia and AD (10, 11). Therefore, individuals with SCD might be an ideal target group for online interventions. This at-risk group might present at memory clinics, their GP or research registries, and was found to be motivated to participate in prevention strategies (12). Individuals at-risk might benefit most from prevention strategies aimed at optimizing brain health or preventing cognitive decline (13, 14).
Our recent review and meta-analysis on online lifestyle programs for brain health suggested that these programs could indeed benefit brain health (15). However, the programs that we reviewed were heterogeneous in content and set-up. Further, characteristics and the methods and results of evaluations of the programs were often not described consistently. More specifically, it was often unclear how user-participation was operationalized and thus how users were involved during the development of the programs (15). This is an important aspect during the development of online programs, because it is essential to involve future users during development. With the users’ input, a program will better fit the users’ needs, which benefits acceptance and adherence, and thereby the implementation of sustainable innovations (16). Previously, we investigated barriers and facilitators for the use of an online lifestyle program in individuals with SCD (12). We found that both program characteristics and personal factors need to be considered, with trustworthiness, user-friendliness, and personalization being important facilitators. We implemented these results during the development of an online lifestyle program for brain health. In co-creation with the users, we developed and adapted the program in multiple iterations. We now aimed to evaluate user-experiences of our online lifestyle program in Dutch and German individuals with SCD, using both quantitative and qualitative methods.

 

Methods

Project and study design

This study is part of the European ‘Subjective cognitive decline in preclinical Alzheimer’s Disease: European initiative on harmonization and on a lifestyle-based prevention strategy’ project (Euro-SCD; JPND_PS_FP-689-019), which aims to develop an online lifestyle program for individuals with SCD. The Euro-SCD project is a collaboration between the Alzheimer Center Amsterdam, the Netherlands (17), Hospital Clinic Barcelona, Spain, and the Center for memory disorders, University Hospital Cologne, Germany. The study was conducted in accordance with Good Clinical Practice (GCP) Guidelines, applicable national guidelines, and to the Declaration of Helsinki. The local ethical committees approved this study and all participants provided informed consent.
The current study was conducted in the Netherlands and Germany (Figure 1: study overview). First, we conducted a feasibility study in the Netherlands to evaluate practicalities and study procedures. This allowed us to improve the online program and optimize the planned study procedures. Subsequently, we performed a 30-day online user test in both the Netherlands and Germany to evaluate user-experiences.

Figure 1. Study overview

Figure 1. Study overview

NOTE: This Figure illustrates the study overview. During the feasibility study, using an iterative process, the program was adapted and study procedures were optimized. The 30-day online user test was quantitatively evaluated with questionnaires, rating of daily advices and data log, and qualitatively by follow-up telephone interviews in a subsample of participants. USE: User Satisfaction and Ease of use questionnaire; SUS: System Usability Scale. a: conducted in the Netherlands, b: recruited via Dutch Brain Health Registry, c: recruited via Cologne Alzheimer dementia prevention registry.

 

Participants

Individuals with SCD were recruited through either a memory clinic or research registry:
1) memory clinic: we included individuals that visited the Alzheimer Center Amsterdam because of cognitive complaints. They underwent clinical work-up including clinical evaluation, neuropsychological assessment, and MRI scan. Although not mandatory, an informant was present in most cases during consults and assessments. When all clinical investigations were normal, and no cognitive disorder could be objectified, patients were labelled as having SCD ((17) i.e. clinical criteria for MCI, dementia or psychiatric disorder not fulfilled, no neurological diseases known to cause memory complaints (e.g. Parkinson’s disease, epilepsy), HIV, abuse of alcohol or other substances). Individuals were invited for study participation based on the following criteria: I) diagnosis of SCD II) age 50 years or older, and III) owning a smartphone, tablet or computer.
2) research registries: we included individuals that signed up for research registries, a) the Dutch Brain Health Registry (online register; www.hersenonderzoek.nl) which facilitates participant recruitment for neuroscience studies and is open for individuals of any age; b) the Cologne Alzheimer dementia prevention registry [Kölner Alzheimer Präventionsregister (KAP)], which is open for individuals of any age interested in the field of dementia. Through newsletters individuals receive information on research and are asked to participate in scientific studies. Individuals were invited for study participation based on the following criteria: I) self-reported experience of memory loss as assessed by either the question “Do you have memory complaints?” (Dutch registry) or the SCD interview (18) (German registry), II) age 50 years or older, III) no diagnosis of Alzheimer’s disease, another type of dementia or mild cognitive impairment, as assessed through self-report, and VI) owning a smartphone, tablet or computer to access the online lifestyle program. No informant information was available for the participants from the research registries.

Online lifestyle program

Hello Brain is a European Project (FP7 grant no 304867) led by Trinity College Dublin. Hello Brain comprises a website and app which are available in English French and German. The website www.hellobrain.eu shares information and videos about the brain, brain health and brain research. The App aims to support users to live a brain healthy life by giving daily suggestions called ‘brain buffs’. There are five brain buff categories: physical activity, social activity, mental activity, lifestyle (nutrition, smoking, alcohol) and attitude (referring to stress management and positive thinking; 30 brain buffs per category). Participants are instructed to read the brain buff and are encouraged to engage in the described activity. If the user cannot or does not want to conduct a specific brain buff, a new brain buff can be requested.
For the current project, a collaboration was started between the EuroSCD team and Trinity College Dublin. We first investigated the preferences and wishes for an online lifestyle program in an international group of users (12). Then, in collaboration with users and a technical party, we adapted the program HelloBrain (Dutch: HalloHersenen, German: HalloGehirn; Appendix 1: details and screenshots). The scientific content was translated and the modules were adapted in order for the interactive module to become the main module. Additional brain buffs were created by a team of brain researchers and added to the program (15 per category) in order to allow tailoring based on a personal profile. The overall lay-out of HelloBrain was changed to a calmer look-and-feel by applying the grey background, that was included in some of the original HelloBrain screens, to all screens while keeping the colorful details.

Feasibility study

After the above mentioned adaptations, we performed a feasibility study to evaluate accessibility and the study procedures, to collect qualitative feedback and optimize study procedures for the online user test. We used 4 iterations of user input and adaptations to create a version of the program that was ready to evaluate user-experiences in a 30-day user test.

Focus groups

In 4 focus groups (memory clinic + Dutch Brain Health Registry, total N=17: 67±6y, 65% female) the language and structure of the program was evaluated. Specific topics were hierarchy of screens (wireframe), language, lay-out, and the wording of reminders and instructions. Feedback was translated into technical and content-related adaptations, and passed on to the developers. We used an iterative process, meaning that after each focus group the program was adapted. In the next focus group the adapted version of the program was evaluated.

Technical pilot

We conducted a technical pilot to evaluate accessibility of the program. Accessibility was defined as the ability to log in to the website or the app independently, with devices at home. Participants (memory clinic, N=5: 61±8y, 80% female) received access to the program through the website or the app for 2 weeks. All technical issues raised by the participants were collected and adaptations were made.

Pilot test phase

To evaluate feasibility of the planned study procedures, we conducted a pilot test phase in which we included 43 SCD subjects (Dutch Brain Health Registry, 65±8y, 66% female). Participants received account information by email and were instructed to use the program for 30 days. Users were able to email the researchers and if necessary, we initiated contact by telephone. At the end of the test-period, participants received digital questionnaires by email to evaluate the procedure of sending online questionnaires, having participants filling out the questionnaires and adequate data collection.

30-day user test: user-experiences

Participants

Finally, we conducted a 30-day user test to evaluate user-experiences. Individuals from the Dutch Brain Health Registry and the Cologne Alzheimer dementia prevention registry were approached. These individuals were not involved in previous phases of the program development.

Procedures

Participants received account information and could access the program for 30 days. Participants were instructed to use the program on a daily basis and complete one brain buff each day. Besides the daily brain buff, participants could access the information on brain health as they liked. After the 30-day user test the participants received self-report questionnaires to evaluate the program. In addition, participants were asked whether they were willing to share their experiences during a telephone interview. Study procedures slightly differed between centers, because of characteristics of the research registers (online in the Netherlands, on paper after an in-person information session in Germany) and requirements of the Cologne ethical committee to send information via post instead of email.

Measures

Data log

During the online user test, log data regarding the usage of the program were collected. Log data entailed number of log ins, log outs, brain buffs completed, brain buffs passed, and page visits during the test period.

Usefulness of daily advices

After indicating that a brain buff was completed, participants were asked to provide a rating of the usefulness of the brain buff. This rating was illustrated with 1 to 5 stars. Participants were invited to leave a comment.

Usability, ease of learning and satisfaction

We used the User Satisfaction and Ease of use (USE) (19) and the System Usability Scale (SUS) questionnaire (20) to assess perceived user-experiences of the online program. The USE questionnaire includes items on usefulness (e.g. is the program perceived as useful, does it have value to the user), ease of learning (e.g. is it easy to learn how the program works) and satisfaction (e.g. does it fulfill the wishes and expectations of the user), with scores ranging from 1 to 7. We used the domain scores for usefulness, ease of learning and satisfaction, by averaging the scores of items per domain. The SUS questionnaire includes 10 items on usability (scores ranging from 1-5; e.g. degree of convenience when using the program). The SUS questionnaire includes both positive and negative items. Total SUS score (range 0-100) was calculated by subtracting 1 from positive items and inversing negative items (5 – item score), summing these scores and multiplying with 2.5 (20). For both questionnaires higher scores indicate better ratings.

Qualitative exploration of user-experiences

We held semi-structured telephone interviews to gain more insight in the questionnaire results and to discuss additional topics. We chose a random sample (N=30) from participants that indicated to be willing to participate in the telephone interview. Aspects that were deemed most important to improve, good and useful aspects of the program and communication during the user test were discussed. In case the questionnaire results needed clarification, the interviewer posed specific questions.

Frequency of Internet use

In the Dutch subsample, a question regarding frequency of internet use was included in the usability questionnaire. In a German subsample frequency of internet use was discussed during the in-depth interview.

Data analysis

Analyses of quantitative data were conducted using SPSS version 22. Descriptive methods were used to describe demographics, average ratings of daily advices per category, use of the program (data log) and user-experience scores (questionnaires) in means and standard deviation, or percentages. Analysis of variance was used to compare questionnaire scores of Dutch and German participants, and to compare the ratings between brain buff categories. P-values of ≤0.05 were considered significant. Qualitative data was collected during the telephone interviews. Every interview was summarized in a short report. All comments were summarized independently by two researchers (LW, AKS). Data was then structured by these researchers upon consensus, in order to identify themes that were of importance to the participants when using the program of when participating in this study.

 

Results

Feasibility study

Focus groups

We let the participants discuss terminology within the program. At first, we kept some English terms in the program. The participants proposed to use Dutch language only. We discussed which terms should be incorporated to replace the English terms. ‘Brain buff’ became ‘Oppepper’ (Dutch for ‘Boost’), and although the category name ‘Attitude’ also translates to the Dutch ‘Attitude’, participants preferred a different wording (‘Houding’; Dutch synonym for ‘Attitude’). Participants agreed with the order and hierarchy of the screens (the wireframe). Upon their input the button for instructions was enlarged and placed more prominently, and we added ‘Uitleg’ (Dutch for ‘Explanation’) underneath this circled question mark symbol. Participants mentioned that back-and-forth buttons needed to be more prominent, which we adapted accordingly, and the hierarchy of the current location should be visible. Therefore, so called ‘Breadcrumbs’ were added to the page. Breadcrumbs are a simple display of the current location in the program, and easy way to click to a location with higher hierarchy (e.g. Start page / Brain Health / Neuroplasticity). Participants mentioned that they would prefer more instructions when entering the main screen. Together with the technical party and participants we came up with the solution to add a highlighting instruction, which highlights and explains all parts of the screen one by one.

Technical pilot

Of the 5 participants that evaluated the accessibility of the program, nearly all (4/5) reported a smooth download and log in without any assistance. One participant was not able to log in, as a result of a problem with the internet browser. Together with the technical party, the issue was resolved. After log in, 2 participants reported several technical bugs, such as wrong linking between pages or not enough variation in the daily advices, which was caused by an algorithm error. These issues were solved by the technical party.

Pilot test phase

Sending and receiving the questionnaires digitally went well. Participants did not report problems filling out the digital questionnaires. Almost all communication was done via email and online questionnaires. Some participants liked the efficient communication and felt that they were skilled enough to work online, while others would have preferred personal contact throughout the test-phase and provide feedback by telephone. Some participants mentioned that they would have liked an ‘emergency hotline’ in order to have personal contact by telephone in case they would have needed help when using in the program. Based on participants’ suggestions, we made the instructions for the online user test more detailed.

30-day user test: user-experiences

Participants

In total, 137 SCD subjects (55 Netherlands, 82 Germany) were included in the online user test. Participants were on average 65.1±8.6 years of age, 57% female and participants completed 11.3±1.9 years of education. German participants had on average more years of education (12.6±1.4) compared to Dutch participants (10.2±1.9, p<.01). The majority of the participants reported to use the internet on a daily basis (>90% of a subsample; Dutch N=55, German N=15).

Data log

In total, 120 (88%) participants used the online lifestyle program during the 30-day test period, whereas 17 (12%) participants did not log in. On average, participants reported to have completed 31±31 daily advices and requested a different brain buff 23±40times during these 30 days. Participants switched between pages on average 117 times (from brain buff screen to informative module and back, or within the informative module).

Usefulness of brain buffs

In total, participants rated 3266 brain buffs with a mean score of 3.5 (±1.5, max 5). The mean ratings differed between categories (F(4,3261)=5,725, p=.000). In general, buffs in the Attitude (3.6±1.4) and Physical activity (3.6±1.4) categories were higher appreciated than Lifestyle advices (3.3±1.6, resp. p<.001 and p=.001). Brain buffs of all categories received scores ranging from 1 to 5 stars and rankings were accompanied by both positive and negative comments. While some participants really liked a brain buff (“It would be very easy and fun to do this every day”) others disliked the same brain buffs (“I have never liked this and I will not do this today”). This diversity in appreciation of the categories, is presented in Figure 2.

Figure 2. Variety in reported usefulness of brain buffs

Figure 2. Variety in reported usefulness of brain buffs

NOTE: This figure illustrates the percentages of brain buffs that received 1 to 5 stars ratings per category, and presents a negative (1 star, left) and a positive (5 stars, right) quotes for each category for illustrative purposes

 

Usability, ease of learning and satisfaction

The questionnaire was completed by 101 participants (response rate 74%; 37 Netherlands, 64 Germany). Participants gave on average moderate scores on items of the USE questionnaire (max 7): usefulness 3.7±1.3, ease of learning 3.6±1.9 and satisfaction 4.0±1.5 points. Dutch participants rated the program higher on these 3 domains compared to German participants (Dutch: 4.1±1.3, 4.8±1.5, 4.4±1.4 vs. German: 3.4±1.3, 2.4±1.5, 3.7±1.6; p<.05). The average score for usability on the SUS questionnaire was 63.7±19 out of 100, which translates to ‘OK to good’ (21) and did not differ between Dutch and German participants. Figure 3 presents the heterogeneity of user-experience scores within the total group.

Figure 3. Heterogeneity in user-experiences

Figure 3. Heterogeneity in user-experiences

 

Qualitative exploration of user-experiences

Table 1 gives a summary of the qualitative feedback illustrated by quotes. Participants mentioned that they would prefer a personalized program, meaning that it would fit their specific preferences. For example, with content based on their current lifestyle and preferred lifestyle category. Some of the participants used the program mainly for information, while others mainly liked the interactive part. When asked what was most important to improve, participants mostly mentioned to optimize technical aspects of the program to ensure a smooth walk-through.
Most participants mentioned to highly appreciate the content of the program. They liked to have a platform available to read about the brain and brain health, and to have access to a trustworthy source of information. When specifically asked what they liked most about the program, participants reported that the program induced awareness of lifestyle factors that are related to brain health. While most participants knew that physical exercise is related to brain health, they were often not aware of the relation between nutrition or social activities and brain health. Some participants mentioned that the program was positive and induced motivation to live healthier. Others were stimulated to look at their current lifestyle, felt confirmation that they have a healthy lifestyle or were motivated to continue with current lifestyle changes.

Table 1. Summary of in-depth exploration of user-experiences, collected during telephone interviews

Table 1. Summary of in-depth exploration of user-experiences, collected during telephone interviews

NOTE: This Table presents qualitative feedback, which was provided by 30 participants during the telephone interviews.

 

Discussion

We developed an online lifestyle program for brain health and found that its’ overall user-experience was moderate to positive. Qualitatively, participants reported to appreciate the content of the program and having a trustworthy source of information on lifestyle and brain health. Quantitative scores on usefulness and ease of learning showed room for improvement. We observed high heterogeneity in the preference of specific lifestyle topics, which emphasizes the need for personalization.
Content on the brain and brain health of the online program, as offered in the brain buffs and the information pages, was highly appreciated by the participants. Both the brain buffs and the information pages were reported to be interesting and useful. Many participants reported to have learned new things. Often they were not aware that all the lifestyle factors that were included in the program were associated to brain health. Previous studies into the attitudes towards prevention of AD and related dementias highlighted the need to improve the beliefs and attitudes towards dementia prevention (1, 3, 22). Our study showed that a tool with information on lifestyle and brain health can contribute to the awareness on modifiable risk factors of dementia.
Involving the users throughout the process of development of an online program is expected to benefit usability and thereby adherence to the program. Our recent review, however, showed that for online lifestyle programs aimed at brain health it was often unclear whether and how users were involved during development and evaluation of the program (15). For example, a study on adherence to lifestyle interventions for dementia prevention found that adherence was lowest for the unsupervised computer-based cognitive training compared to other supervised trainings (23). However, user-involvement during development and evaluation was not described and therefore it remains unclear whether this could have benefitted adherence rates. In this study we aimed to evaluate and optimize user-experiences. When a program will be implemented internationally, it is important to explore cultural differences. Our multinational participatory research design increases the quality of output and sustainability, but also ensures culturally appropriate research, which is of importance when developing an international application (24). As a next step, additional options to increase the impact of the program should be explored. It might be worthwhile to evaluate integration of persuasive technologies that aim to influence behavior and attitudes. If such technologies are used the right way, it is more likely that users reach health-related goals (25).
The heterogeneity in the ratings of brain buffs, the frequent requests for different brain buffs and the qualitative feedback emphasize the need for personalization. Personalization has also been identified as one of the principles to increase appreciation and overall adherence to an online intervention (26, 27). In the current version of the program, part of the content was personalized, since users could request a different brain buff and could access information as they wished. Participants mentioned that they would prefer to receive brain buffs based on their current lifestyle behavior. Further evaluation and integration of personalization options, such as adapting lifestyle advices based on current lifestyle habits, could improve user-experience and thereby adherence to the program.
Lessons learned from the qualitative input of the users, mainly entail the preference for tailoring based on current lifestyle behavior. In addition, participants mentioned different possible effects of the program. Therefore, it might be interesting to rethink the most appropriate outcome measures of future lifestyle-based interventions in SCD. While changes in lifestyle or brain health might seem obvious, effects on psychological well-being or fear for dementia could also be worth consideration.
The quantitative ratings evaluating user-experience were moderate, which was lower than we expected. We identified room for improvement, particularly in ease of learning. Meaning that additional adaptations are necessary to improve instructions and clarity within the program. Differences in ratings could have several reasons, such as education, cultural differences, differences in reporting and differences in digital skills – which we did not assess systematically. Regarding the 30-day user test, German participants reported difficulties when learning to use the program. Some of the technical difficulties occurred only in the German back-end. Although we fixed these technical issues and thoroughly tested the program, we could not rule out remaining minor issues, possibly contributing to the differences in these scores. In our previous study (12), we found that German individuals with SCD used the Internet less often compared to the Dutch participants. However, information on the current Dutch sample and a subset of the German sample showed that over 90% of the participants uses the internet on a daily basis and therefore frequency of internet use is unlikely to influence perceived difficulties. Further, we did not match participants from the feasibility study and 30-day user test. Therefore, we cannot rule out the influence of demographical differences on perceived usability and satisfaction during development and the actual test phase.
In summary, qualitative feedback on the programs’ content was positive, while quantitative feedback on program characteristics showed room for improvement. This discrepancy between the positive qualitative feedback and the moderate quantitative ratings emphasizes the importance of combining methods when evaluation usability of eHealth applications, which was also emphasized in a recent scoping review on methods of usability testing in the development of eHealth applications (28).
This study had some limitations. First, the development and feasibility study took place in the Netherlands, and not in Germany. However, we believe it is promising that participants with different nationalities appreciated the same program, strengthening feasibility to offer one program in multiple countries. Second, a selection bias might have occurred, a study on an online program could have attracted individuals with better digital skills. However, the digital literacy of the participants varied from limited to very skilled, which was also reflected in the variety of feedback regarding ‘ease-of-learning’. Since an online program will only be used by those able and willing to access a program online, the current participants seem representative for the actual target group. Third, we did not have detailed information on drop-outs and therefore cannot describe their characteristics. We did however encourage all individuals to complete the questionnaires and we interviewed individuals independent of their attitude towards the program. Fourth, the participants were recruited based on different SCD criteria between the memory clinic and the research registries. However, we deem the population representative for the heterogeneous populations that can be recruited via memory clinics and brain health registries, and results are generalizable as such. Finally, based on the data log we cannot make a distinction between merely clicking through the program and attentively reading pages. Therefore, we could not take frequency or duration of active participation into account. In the future, this information could be considered when evaluating user-experiences and lifestyle effects of the program.
The strengths of the study include the study design. This was a multicenter study conducted in Germany and the Netherlands. This international character contributes to the generalizability of the findings to other European populations. Results also suggest that although some differences were found, one online tool for multiple European countries would be feasible. Second, we involved the target population throughout the process of development and evaluation. Co-creation is expected to increase the extent to which the tool fits the users’ preferences and digital skills and thereby acceptation and impact of the innovation in further stages (29, 30). Therefore, the users’ input was crucial and resulted in an online lifestyle program fitting the needs and preferences of individuals with SCD. Third, we combined methods to assess user-experiences of the online lifestyle program. The quantitative and qualitative methods were found to complement each other. Finally, we focused on individuals with SCD, who do not show cognitive deficits but at group level are at increased risk for cognitive decline. Therefore, this group is of clinical relevance in the context of dementia prevention. Individuals with SCD also report a need for brain health information, which has not yet been fulfilled since trustworthy sources are still lacking. This group is willing to participate in prevention strategies, which was also observed during recruitment and led to a higher inclusion number than planned.
In conclusion, in this study we developed and evaluated an online lifestyle program for brain health in individuals with SCD. We found that the overall user-experience of our program was moderate to positive. Participants appreciated content on lifestyle and brain health. The variety in preferences for different categories highlighted the need for personalization. It was feasible to offer this online lifestyle program in an at-risk population with SCD. Online self-applied lifestyle programs seem useful when aiming to reach large groups of motivated at-risk individuals for brain health promotion.

 

Conflicts of interest: The authors state no conflicts of interest. Ms. Wesselman reports grants from JPND/ZonMw, grants from Stichting Equilibrio, during the conduct of the study; Dr. Schild reports grants from Bundesministerium für Bildung und Forschung, during the conduct of the study; Dr. Hooghiemstra has nothing to disclose; Mr. Meiberth reports grants from Bundesministerium für Bildung und Forschung, during the conduct of the study; Ms. Drijver has nothing to disclose; Ms. v Leeuwenstijn-Koopman has nothing to disclose; Dr. Prins has nothing to disclose; Dr. Brennan has nothing to disclose; Dr. Scheltens has nothing to disclose; Dr. Jessen reports grants from Bundesministerium für Bildung und Forschung, during the conduct of the study; Dr. van der Flier reports grants from JPND/ZonMw, during the conduct of the study; Dr. Sikkes reports grants from JPND/ZonMw, grants from Stichting Equilibrio, during the conduct of the study.

Funding: The project is supported through the following funding organizations under the aegis of JPND (www.jpnd.eu; JPND_PS_FP-689-019): Germany, Bundesministerium für Bildung und Forschung (BMBF grant number: 01ED1508), the Netherlands, ZonMw grant no. 733051043. It was additionally supported by a research grant from Stichting Equilibrio. W.M. van der Flier is recipient of a grant by Gieskes-Strijbis fonds. S. Sikkes is recipient of a ZonMw Off Road grant (grant no. 451001010).

Acknowledgements: We thank all participants for their contribution to this research project. We thank Roxelane BV. and specifically Rudolf Wolterbeek, Brian Fa Si Oen and Max Hasenaar for their contribution to this project representing the technical party within the collaboration. We thank Mark Dubbelman for data visualization. We thank the founders of HelloBrain.eu (Trinity College Dublin, supported by European Union’s Seventh Framework Program for research, grant no. 304867) for the fruitful collaboration. The website www.hellobrain.eu shares easy-to-understand information and animations about the brain, brain health and brain research. The freely available interactive app, Hello Brain Health, aims to support users to live a brain healthy life by giving daily suggestions called ‘brain buffs’. The app is available on the project website, the App Store and Google Play. The Alzheimer Center Amsterdam is supported by Alzheimer Nederland and Stichting VUmc fonds. Research of the Alzheimer Center Amsterdam is part of the neurodegeneration research program of Neuroscience Amsterdam. Wiesje van der Flier holds the Pasman chair. Hersenonderzoek.nl is funded by ZonMw-Memorabel (project no 73305095003), a project in the context of the Dutch Deltaplan Dementie, the Alzheimer’s Society in the Netherlands and the Brain Foundation Netherlands.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

SUPPLEMENTARY MATERIAL

 

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THE EUROPEAN PREVENTION OF ALZHEIMER’S DEMENTIA (EPAD) LONGITUDINAL COHORT STUDY: BASELINE DATA RELEASE V500.0

 
C.W. Ritchie1, G. Muniz-Terrera1, M. Kivipelto2, A. Solomon2, B. Tom3, J.L. Molinuevo4 On Behalf of the EPAD Consortium
 

1. University of Edinburgh, United Kingdom; 2. Karolinska Institute, Sweden; 3. University of Cambridge, United Kingdom; 4. Barcelona Beta Research Centre, Spain

Corresponding Author: Craig William Ritchie, University of Edinburgh, United Kingdom, craig.ritchie@ed.ac.uk

J Prev Alz Dis 2020;(7) in press
Published online November 26, 2019, http://dx.doi.org/10.14283/jpad.2019.46

 


Abstract

Background: The European Prevention of Alzheimer’s Dementia (EPAD) Programme is a pan-European project whose objective is to deliver a platform, adaptive, Phase 2 proof of concept (PoC) trial for the secondary prevention of Alzheimer’s dementia. A component of this platform is the Longitudinal Cohort Study (LCS) which acts as a readiness cohort for the PoC Trial as well as generating data for disease modelling work in the preclinical and prodromal phases of Alzheimer’s dementia.
Objectives: The first data wave has been collected, quality checked, released and now available for analysis to answer numerous research questions. Here we describe the results from key variables in the EPAD LCS with the objective of using these results to compliment analyses of these data in the future.
Design: EPAD LCS is a cohort study whose primary objective is as a readiness cohort for the EPAD PoC Trial. As such recruitment is not capped at any particular number but will continue to facilitate delivery of the EPAD PoC Trial. Research Participants are seen annually (with an additional 6 month visit in the first year).
Setting: The EPAD Trial Delivery Network comprises currently 21 centres across Europe.
Participants: Research participants are included if they are over 50 years old and do not have a diagnosis of dementia.
Measurements: All research participants undergo multiple assessments to fully characterise the biology of Alzheimer’s disease and relate this to risk factors (both fixed and modifiable) and biomarker expression of disease through brain imaging, fluid samples (CSF, blood, urine and saliva), cognitive performance, functional abilities and neuropsychiatric symptomatology.
Results: V500.0 represents the first 500 research participants baselined into EPAD LCS. The mean age was 66.4 (SD=6.7) and 47.8% were male. The data was split for presentation into 4 groups: [1] CDR=0 and Amyloid + (preclinical AD), [2] CDR=0 and Amyloid –, [3] CDR=0.5 and Amyloid + (prodromal AD) and [4] CDR=0.5 and Amyloid -.
Conclusions: The EPAD LCS is achieving its primary objective of trial readiness and the structured approach to data release as manifest by this first data release of V500.0 will assist researchers to describe and compare their findings as well as in systematic reviews and meta-analyses. It is anticipated given current recruitment rates that V1500.0 data release will take place in Autumn 2019. V500.1 (when the 1 year follow up is completed on the V500.0 (sub)cohort will be in Autumn 2019 also.

Key words: EPAD, Cohort, Alzheimer’s disease, Prevention, Disease modelling.


 

Background

The European Prevention of Alzheimer’s Dementia (EPAD) project was initiated in January 2015 and is funded by the Innovative Medicines Initiative. The overall project background and objectives are described elsewhere (1). In summary EPAD has a singular objective and that is to develop an entire infrastructure for the delivery of the EPAD Proof of Concept Trial. The EPAD PoC Trial is a platform trial, which employs a single master protocol with multiple appendices (representing each intervention) that uses Bayesian Adaptive Designs to develop interventions for the secondary prevention of Alzheimer’s dementia through Phase 2. The EPAD Infrastructure has many components including a virtual register of people in partnering parent cohorts across Europe, the Trial Delivery Centre (TDC) network, the PoC trial platform of TDCs, vendors and Clinical Research Organisations and the Longitudinal Cohort Study (LCS). The primary objective of the EPAD LCS is as a readiness cohort for the PoC to minimise screen failure by way of detailed characterisation of research participants within it and to provide run-in data to be used to compare with post-randomisation data from the PoC itself. In accumulating vast amounts of data from a very large and highly characterised cohort, the EPAD LCS will be able to deliver data (eventually on an open data access platform) to the entire research community to assist with disease modelling and knowledge generation regarding the interplay between risk factors, brain disease, expression of brain disease (through biomarkers, cognition, function and neuropsychiatric symptoms) and how these change over time. Aware of the potential power of these data in the understanding of preclinical and prodromal Alzheimer’s disease, the management of data releases to the research community had to be measured, transparent and organised. Moreover, all data and sample collection and sample analysis has been conducted to the highest GLP and GCP standards.
The V500.0 data release represents the first formal data release from the EPAD project for use by multiple researchers. This paper describes this data in detail to assist current and future researchers with their analysis and also to facilitate between project comparisons of data in systematic reviews and meta-analysis.

 

Methods

The EPAD LCS Protocol and Methodology is provided in detail elsewhere (2). The EPAD LCS has as its primary objective to be a readiness cohort for the EPAD PoC Trial. Therefore, recruitment into LCS is not capped and will continue ad infinitum to provide the necessary number of suitable research participants for the EPAD PoC Trial. The secondary objective of the EPAD LCS is to use the data generated for disease modelling. After consent, research participants complete a comprehensive series of assessments.
Research Participants are eligible for inclusion if they are over the age of 50 and do not have a diagnosis of dementia. They must also be deemed suitable in principal for later inclusion in a clinical trial and therefore should not have any medical or psychiatric disorders which would normally exclude people from such trials.
Research Participants are seen every year where the entire protocol of assessments is completed. There is also a 6-month visit where only cognition is assessed. The domains of assessment are [1] cognition, [2] neuroimaging, [3] fluid biomarkers, [4] genetics, [5] lifestyle, [6] clinical and psychiatric assessment, [7] neuropsychiatric symptoms, [8] function and [9] basic demography. The decisions on which outcome measures to use were subject to intense deliberation and review of the extant scientific literature by four EPAD Scientific Advisory Groups on Cognition and Clinical Outcomes, Biomarkers, Neuroimaging and Genetics.
Data releases from the EPAD LCS will be highly systematised. In our chosen nomenclature (V500.0): V=version, 500 is the number of sequentially recruited research participants and ‘.0’ refers to the data including only the baseline (visit 0) data. This subcohort will be followed over time so that the next release from this cohort V500.1 will take place in approximately 12 months. This will include all the baseline, 6 month and 12 month data from these 500 research participants. The ‘.1’ refers to the data including all data up until the 1 year visit, V500.2 will be when all data up until the 2 year visit is released.

Cognition and Clinical Outcomes

The Cognition and Clinical Scientific Advisory Group advised the LCS protocol authors on the construction of the EPAD Cognitive Examination (ECE) (3, 4) as well as on functional outcomes and the capturing of key neuropsychiatric features namely sleep, anxiety and depression. The cognitive outcomes captured are: RBANS (5, 6) (Primary Outcome Measure for EPAD PoC Trial), CDR (7), MMSE (8), NIH Toolbox tests (Dot Counting, Flanker) (9, 10), UCSF Brain Health Assessment (Favorites) (11), Supermarket Trolley Test (12) and Four Mountains Test (13). Function is assessed using the Amsterdam Instrumental Activity of Daily Living Assessment (14, 15). Sleep is assessed using the Pittsburgh Sleep Questionnaire (16); Anxiety is measured using the State/Trait Anxiety Inventory (17) and Depression using the Geriatric Depression Scale (18, 19).
All cognitive and clinical data is captured on tablets (either on the Medavante Virgil Platform or the UCSF Tabcat System). These data are then uploaded to the EPAD LCS Master Database held by the EPAD LCS Clinical Research Organisation IQVIA for conciliation with other data sources e.g. imaging and eCRF data before being quality controlled and then pushed to the Analytical Database hosted by the EPAD Partner Aridhia.

Neuroimaging Outcomes

The Neuroimaging Scientific Advisory Group advised the LCS protocol authors on structural and functional MRI based evaluations optimised for understanding brain changes in preclinical and prodromal Alzheimer’s disease (20). The structural sequence captured in the protocol were Cortical thickness, deep grey matter volumes, fractional anisotropy of temporal lobe, diffusion kurtosis (multi b-valueDTI) and network alterations. The functional MRI outcomes were global & parietal CBF and changes within the default-mode network & relation with hippocampal activity(rsfMRI), Bolus arrival time (multi-delay arterial spin labelling) and network analysis (rsfMRI) though not all of these data have been analysed as yet in V500.0 and therefore not presented in this paper.
All brain-imaging facilities are accredited by the EPAD LCS Imaging CRO IXICO. Imaging files from the site are transferred to IXICO for central reading and safety evaluation. Key outcomes are then transferred to the Master Database for conciliation with other data feeds before these data are transferred to Aridhia and the EPAD Analytical Database. MRI scanners are a minimum of 1.5T.

Biomarker Outcomes

The Biomarker Scientific Advisory Group after review of the existing evidence around neuropathological changes in preclinical and prodromal AD had to decide which biomarkers were either fully validated as markers of disease or remained at the discovery phase of development. The former were to be incorporated in the protocol whilst the potential to explore the others would be reserved to a future date from EPAD LCS samples collected, shipped and stored under optimal conditions. The Biomarker SAG therefore also oversaw the creation of the laboratory manual (available on line at www.ep-ad.org).
The only biomarkers in the protocol are CSF ABeta, Tau and Phosphorylated Tau. All samples are shipped from sites and stored centrally at the EPAD BioBank at the University of Edinburgh before CSF samples taken in Sarstedt tubes are shipped to the University of Gothenburg, Sweden for analysis using the Roche Diagnostics Elecsys Platform. Results are then forwarded to the IQVIA Master Database and then transferred to the Aridhia Analytical Database. Using this system a threshold of 1,000pg/ml of ABeta42 was agreed upon to define amyloid positivity.
Saliva (drooling sample and salivette), urine and plasma are also stored in the EPAD BioBank for future use. To date none of these samples have been analysed.

Genetics Outcomes

The Genetics Scientific Advisory Group had a similar remit to that of the Biomarker SAG in so much as they agreed on recommendations for outcomes to be done in all samples and within the protocol and advise on optimal storage for future use. They recommended that all samples should be tested for ApoE status of the research participants. Sampling preparation and storage details can be found in the EPAD lab manual (available on line at www.ep-ad.org)
Taqman Genotyping was carried out in a single laboratory on QuantStudio12K Flex to establish ApoE variants. Genomic DNA was isolated from whole blood and genotyping was performed in 384 well-plates, using the TaqMan polymerase chain reaction-based method. The final volume PCR reaction was 5 μl using 20 ng of genomic DNA, 2.5 μl of Taqman Master Mix and 0.125μl of 40x Assay By design Genotyping Assay Mix, or 0.25µl of 20x Assay On Demand Genotyping Assay. The cycling parameters were 95° for 10 minutes, followed by forty cycles of denaturation at 92° for 15 seconds and annealing/extension at 60° for 1 minute. PCR plates were then read on ThermoFisher QuantStudio 12K Flex Real Time PCR System instrument with QuantStudio 12K Flex Software or Taqman Genotyper Software v1.3.

Demographic, lifestyle, clinical and other outcomes

The EPAD LCS Protocol authors decided upon all outcomes following advice from the four listed Scientific Advisory Groups. Other outcomes were decided solely by the protocol authors. Lifestyle factors captured were self reported physical activity, diet, smoking/alcohol/drug behaviour. Demography included gender, age, years of education and race (where allowable by regional authorities to be captured). Clinical history and physical examination was captured in standardised source documents to cover all medical and psychiatric domains including medication use. Specific assessment of head injury was undertaken using the Brain Injuries Screening Questionnaire.

Results

All results are presented similarly as the total sample and by amyloid and CDR status. Some data on variables presented are missing and then within that grouping amyloid status may be missing too due to analysis problems.
Lifestyle variables and medical history of research participants are not presented here but available on line on the EPAD website.

Table 1. Demographics and ApoE Status

Table 1. Demographics and ApoE Status

Table 2. Cognition

Table 2. Cognition

Table 3. Neuroimaging

Table 3. Neuroimaging

Table 4. CSF Biomarkers

Table 4. CSF Biomarkers

Table 5. Other Key Outcomes

Table 5. Other Key Outcomes


 

Discussion

The objective of this paper was to convey the structure of the EPAD LCS using the first data release from the project. With a large cohort that has open ended and perpetual recruitment, it was considered crucial that the academic and broader research community could have clarity on which data sets are being used from EPAD that form the basis of secondary data analysis. It is not in the scope of this paper to draw any conclusions from the data as no research question is being proposed here or hypothesis being tested. However, in terms of readiness for the EPAD PoC trial, just under 35% of the cohort are amyloid positive with the majority of these being CDR=0 which probably reflects the initial source of recruitment to EPAD LCS from population based parent cohorts (21). To date 26.6% of the sample have preclinical Alzheimer’s disease and 8.3% prodromal Alzheimer’s disease. However with an increasing drive in recent months to significantly increase the proportion of people in the cohort with CDR=0.5 (in V500.0 = 14.8%) to nearer 30%, we expect confidently that by 2020 and commencement of the PoC trial, the LCS will have the necessary level of readiness. V500.0 also has a broad range of research participants in terms of many key outcomes that will assist in disease modelling work and other hypothesis testing.
The quality of the data, sample preparation, storage and analysis was of paramount concern to the EPAD Consortium and much effort has gone into this with lab and imaging manuals available on the EPAD website to give researchers both assurance and clarity on the processes undertaken in EPAD to deliver high quality data.
The value of the EPAD LCS will clearly increase as the sample size increases and greater length of follow up is achieved in each sub-cohort. Description of each data release from EPAD is planned and will follow this initial formatting.

 

Conclusions

The EPAD Programme is a very large and ambitious programme that is ultimately set to deliver a platform, multi-arm PoC trial to test interventions targeting the secondary prevention of Alzheimer’s dementia. Whilst the project has numerous key components, the EPAD LCS is central to all the efforts. Data from this cohort will be of great value to the research community so managed, orderly, structured and well described data releases are critical as a reflection of the importance of this database and the time and effort all our research participants have committed and made to help understand Alzheimer’s disease before dementia develops and in doing so move a step closer to its prevention.

 

Conflict of interest: No conflict of interest.

Funding: The European Prevention of Alzheimer’s Dementia project has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EPAD grant agreement number 115736.

Ethical Standards: The EPAD LCS protocol and materials are submitted to the Independent Ethics Committee or other relevant ethical review board for written approval as required by local laws and regulations. A copy of approval is required by the University of Edinburgh as Sponsor before the study commences at each site. The study is designed and conducted in accordance with the guidelines for Good Clinical Practice (GCP), and with the ethical principles as proclaimed in the Declaration of Helsinki. All participants are required to provide written informed consent prior to participation in any research activities laid out in the EPAD LCS protocol.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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MULTIDOMAIN INTERVENTIONS TO PREVENT COGNITIVE IMPAIRMENT, ALZHEIMER’S DISEASE, AND DEMENTIA: FROM FINGER TO WORLD-WIDE FINGERS

 

A. Rosenberg1, F. Mangialasche2,3, T. Ngandu4, A. Solomon1,2, M. Kivipelto2,5,6,7,8

 

1.  Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland; 2. Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; 3. Aging Research Center, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; 4. Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland; 5. Theme Aging, Karolinska University Hospital, Stockholm, Sweden; 6. Stockholms Sjukhem, Research & Development Unit, Stockholm, Sweden; 7. The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom;
8. Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland

Corresponding Author: Miia Kivipelto,  Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Universitetssjukhuset, Karolinska Vägen 37 A, QA32, 171 64 Solna, Sweden, Phone: +46 (0)73 99 40 922, miia.kivipelto@ki.se

J Prev Alz Dis 2019;
Published online October 10, 2019, http://dx.doi.org/10.14283/jpad.2019.41

 


Abstract

Alzheimer’s disease (AD) and dementia are a global public health priority, and prevention has been highlighted as a pivotal component in managing the dementia epidemic. Modifiable risk factors of dementia and AD include lifestyle-related factors, vascular and metabolic disorders, and psychosocial factors. Randomized controlled clinical trials (RCTs) are needed to clarify whether modifying such factors can prevent or postpone cognitive impairment and dementia in older adults. Given the complex, multifactorial, and heterogeneous nature of late-onset AD and dementia, interventions targeting several risk factors and mechanisms simultaneously may be required for optimal preventive effects. The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) is the first large, long-term RCT to demonstrate that a multidomain lifestyle-based intervention ameliorating vascular and lifestyle-related risk factors can preserve cognitive functioning and reduce the risk of cognitive decline among older adults at increased risk of dementia. To investigate the multidomain intervention in other populations and diverse cultural and geographical settings, the World-Wide FINGERS (WW-FINGERS) network was recently launched (https://alz.org/wwfingers). Within this network, new FINGER-type trials with shared core methodology, but local culture and context-specific adaptations, will be conducted in several countries. The WW-FINGERS initiative facilitates international collaborations, provides a platform for testing multidomain strategies to prevent cognitive impairment and dementia, and aims at generating high-quality scientific evidence to support public health and clinical decision-making. Furthermore, the WW-FINGERS network can support the implementation of preventive strategies and translation of research findings into practice.

Key words: Alzheimer’s disease, cognitive impairment, dementia, multidomain, prevention, randomized controlled trial.


 

Dementia is the main cause of disability among older adults, affecting around 50 million people worldwide (1). Driven by population aging, this number is expected to increase rapidly to over 150 million by 2050, creating a major public health and social challenge (2). Alzheimer’s disease (AD) underlies the majority of dementia cases, often in association with vascular neuropathology. Disease-modifying therapies are not yet available for AD, and despite the recent positive signals in some of the ongoing randomized controlled trials (RCTs) testing anti-amyloid compounds, drug trials have mostly reported disappointing results (3,4). Given the evidence emerging from longitudinal observational studies, indicating that late-life cognitive impairment, AD, and dementia are heterogeneous and multifactorial conditions driven by a combination of genetic, vascular, metabolic, and lifestyle-related factors, the potential of dementia prevention through risk factor modification and management has gained increasing attention.
Findings from observational studies need to be substantiated by RCTs, which are considered the gold standard to verify the effect of an intervention. Results of the earlier, smaller, shorter-term prevention RCTs focusing on individual lifestyle components and risk factors have been mostly modest, and evidence from large, long-term trials is only beginning to emerge (5). Importantly, in light of the current knowledge about the complex and multifactorial etiology of late-onset AD and dementia, targeting several risk factors and mechanisms simultaneously, as well as tailoring interventions to individual risk profiles, may be necessary to obtain optimal preventive effects. So far, three large European multidomain lifestyle-based prevention trials have been completed: the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (6), the French Multidomain Alzheimer Preventive Trial (MAPT) (7), and the Dutch Prevention of Dementia by Intensive Vascular Care (PreDIVA) (8). The FINGER trial reported significant beneficial intervention effects on the primary outcome, namely change in global cognitive performance, among older ‘at risk’ adults from the general population (6). Notably, exploratory subgroup analyses of MAPT and PreDIVA also suggested cognitive benefits in subpopulations of participants with increased risk of dementia (7-9). Taken together, these studies indicate that administering multidomain lifestyle-based interventions to older at-risk adults may be feasible and effective. However, to fully understand the potential and impact of multidomain preventive interventions, their efficacy and feasibility needs to be explored in diverse populations and contexts worldwide. The FINGER model is now tested and adapted in several new preventive trials globally, and the World-Wide-FINGERS (WW-FINGERS) network (https://alz.org/wwfingers) was launched to support these joint initiatives aiming to reduce the burden of cognitive impairment and dementia. This article will provide an up-to-date overview of the multidomain intervention concept, lessons learned from the recent multidomain RCTs, and future directions in the field.

 

Modifiable risk and protective factors of cognitive impairment, Alzheimer’s disease, and dementia: a window of opportunity for prevention

Increasing evidence from long-term prospective cohort studies linking several modifiable risk and protective factors with late-onset dementia and AD has accumulated during the past decades (10, 11). These include vascular and metabolic risk factors and disorders, lifestyle-related, and psychosocial factors. It is also common that neurodegenerative and vascular pathology co-occur, particularly in older adults with dementia, and mixed dementia has been reported to be the most common type of dementia among individuals older than 80 years (12, 13). With regard to several vascular risk factors, the association with dementia risk is modified by age, and different risk factors may be relevant at different time points in life (14). For example, hypertension, obesity, and hypercholesterolemia in mid-life are risk factors for late-onset dementia and AD (15), but the opposite association has been reported later in life and in studies with shorter follow-up times, possibly reflecting reverse-causality (i.e., those factors decrease in the early, asymptomatic stages of dementia most likely as a consequence of the disease) (16, 17). In addition to vascular and metabolic factors (high blood pressure and cholesterol, obesity, diabetes, impaired glucose metabolism), smoking (18), excessive use of alcohol (19), depression (20), as well as other psychosocial factors, such as work-related stress, feelings of hopelessness or loneliness, and infrequent social contacts (21-23), are associated with an increased dementia risk. Protective factors for cognitive impairment, dementia and AD include regular physical activity (24), having a higher formal education (25) and an intellectually demanding and stimulating work (occupational complexity) (26), as well as engaging in cognitively and mentally stimulating leisure activities (27). Social engagement and having a rich social network have also been associated with a reduced risk of dementia and AD (28, 29).
Among pharmacological treatments, both observational studies and RCTs have indicated that antihypertensive drugs may be associated with a reduced risk of AD and dementia (30). The recent large, long-term Systolic Blood Pressure Intervention Trial (SPRINT) Memory and Cognition IN Decreased Hypertension (MIND) RCT reported that intensive blood pressure control (goal <120 mmHg) can be more effective in reducing the risk of cognitive impairment than standard blood pressure control (goal <140 mmHg), although the question of the optimal therapeutic target for systolic blood pressure among oldest old individuals (85+ years) still remains (31). Findings regarding other medications, such as statins, hormone replacement therapy, and non-steroidal anti-inflammatory drugs, are conflicting, as the beneficial effects suggested by observational studies have not been confirmed in RCTs (10).
In relation to diet, some individual nutrients, including omega-3 polyunsaturated fatty acids, vitamins B6 and B12, folate, vitamin D, and vitamins A, C, E (antioxidants), have been associated with a reduced risk of dementia in observational studies (32), although no conclusive evidence has so far emerged from trials testing nutraceutical supplements. Furthermore, regular intake of fish, fruits, vegetables, and nuts have been linked with a reduced risk of cognitive impairment and dementia. Among dietary patterns, cognitive benefits have been reported for different diets which are based on frequent consumption of fruits and vegetables, unsaturated fats, whole grain products, and fish: the Mediterranean Diet, the DASH (Dietary Approaches to Stop Hypertension), the hybrid MIND (Mediterranean-DASH Intervention for Neurodegenerative Delay) diet, and the healthy Nordic diet (33-37). As opposed to single nutrients, the role of healthy and balanced dietary patterns may be more relevant, because nutrients have cumulative and synergistic effects.
Overall, it has been estimated that approximately 35% of dementia cases worldwide could be attributable to nine modifiable risk factors: low educational attainment in early life, midlife hypertension and obesity, diabetes mellitus, smoking, physical inactivity, depression, social isolation and hearing loss over the entire adult life course (38). This indicates clearly a prevention potential across the lifespan. In line with these findings, secular trend studies have indicated that the age-specific incidence and prevalence of dementia may have declined in some Western countries (39), potentially as a result of improved treatment of cardiovascular disease and vascular risk factors, reduction in smoking, increased educational attainment, and an overall improvement in lifestyle. However, the prevalence of dementia has been shown to increase faster than expected in countries like China and Japan (40,41), and with increasing prevalence of some risk factors, such as obesity and type 2 diabetes (42), there is a great need for global efforts to manage risk factors and reduce the burden of dementia.
A key issue to consider in preventive interventions is the fact that multiple risk and protective factors for dementia and AD usually co-occur and interact across the lifespan to determine the individual’s overall risk of dementia. For instance, in the context of interactions between genetic and environmental factors, it has been reported that the harmful effects of unhealthy lifestyle (i.e., unhealthy diet, alcohol misuse, smoking, physical inactivity) may be more pronounced among carriers of apolipoprotein E (APOE) ε4 allele, which is the most well-known genetic risk factor of late-onset AD (43). Furthermore, vascular factors can have additive effects (10). Overall, co-occurrence of risk factors, as well as their time- and age-dependent effects, underline the complexity of dementia prevention and imply that a ”one-size-fits-all” preventive approach might not be effective. Instead, a tailored, life-course approach targeting multiple risk factors is likely needed for effective prevention of cognitive impairment and dementia. This means that middle-aged and older adults, as well as individuals with heterogeneous risk profiles, may benefit from somewhat different multidomain preventive strategies in order to change their risk profiles.

 

From observational studies to clinical trials: large multidomain lifestyle-based interventions

Three pioneering, large, long-term multidomain lifestyle prevention trials have been recently conducted in Europe: the Finnish FINGER trial; the French MAPT trial, and the Dutch PreDIVA trial.
The two-year FINGER trial (NCT01041989) is the first large, long-term, multicenter RCT showing  a significant effect of the multidomain lifestyle intervention against cognitive decline among older adults who had increased risk of dementia (6, 44). The FINGER trial enrolled 1260 older adults aged 60-77 years, recruited from previous population-based surveys. Inclusion criteria were as follows: increased risk of dementia based on the CAIDE (Cardiovascular Risk Factors, Aging and Dementia) Dementia Risk Score (≥6 points) (45); and cognitive performance at the mean level or slightly lower than expected for age. Participants were randomized into the multidomain intervention or control group. The multidomain intervention was delivered by trained professionals through both individual sessions and group activities, and it consisted of dietary counseling, exercise, cognitive training, social activities, and monitoring and management of vascular and metabolic risk factors. The control group was offered regular health advice.
The primary outcome of the trial was change in cognitive performance measured by a neuropsychological test battery (NTB) composite score, and secondary cognitive outcomes included domain-specific NTB scores. After two years, the intervention showed significant beneficial effects on the NTB composite score (25% more improvement compared to control), as well as on executive functioning (83% more improvement), processing speed (150% more improvement), and complex memory tasks (40% more improvement). Furthermore, the intervention group had a lower risk of cognitive decline. Follow-ups at 5 and 7 years have been recently completed to determine long-term effects (data analysis is ongoing). The multidomain intervention was safe and well accepted, with high adherence and a low drop-out rate (12%), supporting the feasibility of lifestyle interventions in older at-risk adults. Importantly, the intervention benefits were not limited to cognition: additional favorable effects included body mass index (BMI) reduction (6), improved adherence to dietary guidelines and recommendations (46), and increase in physical activity (6) and health-related quality of life (47). The intervention also improved physical performance and supported daily functioning (48) and lowered the risk of multimorbidity as well as risk of developing new chronic diseases (49). Notably, pre-specified subgroup analyses indicated that the intervention was beneficial regardless of age, sex, education, vascular risk profile and baseline cognitive performance, indicating that the beneficial effects were not limited to a subset of participants, but findings may be generalized to a large population of older adults at increased risk of dementia (50). APOE ε4 carriers got clear benefit from the intervention (51).
The three-year MAPT trial (NCT00672685) is a large, long-term RCT combining lifestyle-based intervention with a nutraceutical compound (7). MAPT enrolled 1680 community dwellers aged 70 years or older who had either subjective memory complaints, limitation in one instrumental activity of daily living, or slow gait speed. In the four parallel arms of the RCT, two intervention groups received a multidomain lifestyle intervention consisting of cognitive training and counseling on nutrition and physical activity, either alone or in combination with omega-3 fatty acid supplementation. One intervention group received only the omega-3 fatty acid supplementation, and one arm was assigned to placebo. The primary outcome was change in a cognitive composite score, and secondary outcomes included the individual components of the composite score, other cognitive test scores (e.g. Mini-Mental State Examination MMSE), and the Short Physical Performance Battery and Alzheimer’s Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) Prevention Instrument scores. Although the trial failed to meet its primary outcome, beneficial intervention effects were observed when both groups receiving the multidomain lifestyle intervention were combined. Also, the combined multidomain lifestyle plus omega-3 fatty acid intervention had beneficial effects on some secondary outcomes (ten MMSE orientation items). Moreover, exploratory analyses indicated beneficial effects in specific subgroups of at-risk participants: those with brain amyloid pathology or a CAIDE risk score of ≥6 points (7, 9), which was the same cut-off used in FINGER to select participants.
The PreDIVA (ISRCTN29711771) is a six-year study targeting 3526 older adults aged 70-78 years, recruited via general practices (8). Compared to the FINGER and MAPT participants, the PreDIVA population was rather unselected. The intervention group received a nurse-led multidomain intervention consisting of advice concerning healthy lifestyle and intensive vascular care and risk factor management, including initiation or optimization of antithrombotics and pharmacological treatments for hypertension, dyslipidemia, or diabetes, when necessary. The control group was offered regular care. The main results of the trial did not show any difference in dementia incidence, which was the primary outcome, between the intervention and control groups. However, in the exploratory analyses, a reduction in the incidence of dementia was observed among individuals with untreated hypertension who adhered to the treatment during the trial.
Several important lessons can be learned from these large multidomain prevention trials. First, selecting the right target population at the right time is crucial. Targeting at-risk individuals (as opposed to an unselected population) is likely the most feasible strategy. Second, the FINGER trial demonstrated the importance of starting early enough: the prevention potential of a multidomain lifestyle intervention, especially if not combined with pharmacological treatments, may be highest among relatively healthy and younger old adults. Finally, the content of the intervention is crucial. The intervention may need to be intensive enough and preferably include also active counseling and coaching delivered in different ways (not only advice). Based on the content and duration of the intervention sessions and study visits, the FINGER intervention was the most intensive, and the participants attended both group and individual sessions. Despite the relatively intensive nature of the intervention, adherence was high, as approximately 72% of the participants reported at least some engagement in all intervention components. Thus, the FINGER multidomain intervention seemed feasible, pragmatic, and not too strenuous. Designing and adapting the content of the intervention for various target populations is essential to optimize the effect. Finally, the choice of an appropriate outcome measure to assess intervention effects is also important. Incidence of dementia is a robust outcome, and trials with such outcome would require a large sample size and long-term follow-up, especially when targeting cognitively healthy older adults. For this population, there is currently no gold standard measure to detect cognitive changes predictive of future dementia. However, composite cognitive scores capturing several cognitive domains may be useful (52), not only to detect early changes typical for AD, but also for vascular cognitive impairment, since both disorders often co-occur in advanced age.

 

Other innovative multidomain preventive strategies

Building upon the experiences of the preventive RCTs conducted so far, the next generation of multidomain prevention trials has started to incorporate and utilize novel technologies and tools, such as eHealth and mHealth, to optimize the delivery of multidomain interventions. One example of an Internet-based eHealth study is the Healthy Aging Through Internet Counselling in the Elderly (HATICE, ISRCTN48151589), which is a European 18-month RCT testing the efficacy of an Internet platform in improving self-management of cardiovascular risk factors for prevention of cardiovascular disease and cognitive decline (53). The trial enrolled 2724 non-demented, computer literate community-dwellers aged 65+ from Finland, France, and the Netherlands. Participants were required to have at least two cardiovascular risk factors and/or history of cardiovascular disease or diabetes. Participants were randomized 1:1 to intervention and control groups. The intervention group had access to an interactive Internet platform, designed to encourage lifestyle changes with the remote support of a lifestyle coach, according to national and European guidelines for cardiovascular risk factor management (54). The control platform included only basic health information and no interactive features or coach support. The trial has been completed, and data analysis is ongoing. If the delivery of preventive interventions through Internet or e.g. via mobile applications proved to be feasible and effective and induced sustained behavioral changes, it could support self-management and be a cost-effective way to reach and involve a large population across the world.
While the FINGER, MAPT, and PreDIVA trials targeted older adults from the general population, some new multidomain prevention studies focus on at-risk populations in clinical settings. One particularly relevant target population for multidomain prevention are individuals with prodromal AD. For this more advanced and symptomatic state of AD dementia risk, lifestyle and vascular changes alone may not be sufficient. Rather, a combination of lifestyle and pharmacological approaches may be necessary to prevent or delay the onset of dementia. There are currently no proven therapeutic options available for such individuals, but in the multinational European LipiDiDiet trial (NTR1705) (55), the effects of the medical food product Fortasyn Connect (Souvenaid) were investigated in 311 memory clinic patients with prodromal AD, as defined by the International Working Group (IWG)-1 research criteria (56). Fortasyn Connect is a mixture of multiple nutrients, such as vitamins, polyunsaturated fatty acids, and phospholipids, which improves the formation and function of synapses (57). The primary outcome of the LipiDiDiet trial was change in cognitive performance measured with an NTB composite score. Secondary outcomes included change in e.g. memory scores, Clinical Dementia Rating-Sum of Boxes (CDR-SB), and brain volume. The two-year core trial was completed in 2015. Despite no significant effect on the primary outcome, group differences in favor of the treatment group were observed for cognitive and functional outcomes (45% less worsening in the CDR-SB in the intervention group), and hippocampal atrophy (26% less deterioration in the intervention group) (55). Notably, the observed decline in the NTB in the control group was smaller than expected. Analyses of the intervention effects at 36 months will be completed soon.

Going global: from FINGER to World-Wide FINGERS

Following the encouraging results of the FINGER trial, the World-Wide FINGERS (WW-FINGERS, https://alz.org/wwfingers) network was launched in July 2017 in connection to the Alzheimer’s Association International Conference in London (founder and scientific lead: Professor Miia Kivipelto; hosted by Alzheimer Association). By collectively convening international research teams under the WW-FINGERS leadership of Prof. Miia Kivipelto and Dr. Maria Carrillo, WW-FINGERS will facilitate data sharing and joint analysis across studies, establish opportunities for joint initiatives across country borders, and strengthen the potential evidence-base for multidomain lifestyle interventions.
This initiative supports and coordinates other trials worldwide in testing the feasibility and efficacy of FINGER-type preventive interventions in different at-risk populations, across diverse geographical and cultural settings. All WW-FINGERS trials share the same key concept of a pragmatic multidomain approach, i.e. targeting several modifiable risk factors simultaneously. WW-FINGERS will facilitate data sharing and joint analysis across studies, and to ensure comparability of the results and to facilitate pooling of accumulating data, the trials aim to use common core outcome measures. At the same time, local and cultural adaptations will be applied in relation to the content and delivery method of the intervention. For example, dietary counseling will follow national recommendations while taking into account country- or region-specific habits, and pharmacological vascular risk factor management, when applicable, will be based on national care guidelines. This is essential to improve engagement and adherence, and subsequently, to facilitate the effective and sustainable implementation of preventive strategies. Several countries worldwide have joined the WW-FINGERS network and are currently at different stages of planning and conducting their FINGER-type prevention trials (Figure 1). Recruitment is already ongoing in several trials.

Figure 1. World map with countries which are involved in the WW-FINGERS network. Blue indicates involvement in ongoing WW-FINGERS studies. Studies are currently planned in countries marked with purple

Figure 1. World map with countries which are involved in the WW-FINGERS network. Blue indicates involvement in ongoing WW-FINGERS studies. Studies are currently planned in countries marked with purple

 

WW-FINGERS trials

The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER), supported by the Alzheimer’s Association, aims to test the FINGER intervention in a more diverse US population. It is a two-year trial targeting 2000 older adults aged 60-79 years with normal cognition but increased risk for future cognitive decline. The trial will compare two lifestyle-based interventions (structured vs self-guided lifestyle intervention), which vary in their intensity and structure. Another ongoing trial testing the FINGER-based model is the randomized controlled Multimodal INtervention to delay Dementia and disability in rural China (MIND-CHINA), aiming at recruiting up to 3500 older adults aged 60-79 years who are living in rural areas of the Shandong province. The MIND-CHINA trial uses cluster randomization by village and includes two intervention arms and a control arm. Due to high prevalence of untreated vascular risk factors in this population, the trial will focus on the management and treatment of these factors. Participants in the vascular intervention group will be provided with pharmacological control and management of three major vascular risk factors (hypertension, dyslipidemia, diabetes); the multidomain intervention group will have both the management of the vascular risk factors and a multidomain lifestyle intervention. In the lifestyle intervention, special emphasis will be placed on reducing salt intake, which is a key dietary challenge in China. In Singapore, the six-month feasibility study SINGapore GERiatric intervention study to reduce physical frailty and cognitive decline (SINGER) targeting 70 participants with mild/moderate frailty and/or cognitive impairment is ongoing. The two-year study AUstralian-Multidomain Approach to Reduce Dementia Risk by PrOtecting Brain Health with Lifestyle intervention (AU-ARROW) is currently planned in Australia. Another Australian multidomain prevention trial, the ongoing three-year Maintain Your Brain (MYB) trial, is associated with WW-FINGERS (study design and outcomes not fully harmonized with other WW-FINGERS studies). The MYB RCT randomized 6236 non-demented community-dwellers aged 55-77 years. Assessments and interventions are conducted online, and the multidomain eHealth intervention consists of exercise, cognitive training, dietary advice, guidance to stop smoking and reduce alcohol consumption, blood pressure and cholesterol management, and cognitive behavior therapy to manage depressive symptoms and to facilitate social interaction.
Another initiative within the WW-FINGERS network is the multinational European collaboration project MIND-AD – Multimodal preventive trials for Alzheimer’s Disease: towards multinational strategies, which is based on the promising results of the FINGER and LipiDiDiet trials. In the ongoing six-month Multimodal Preventive Trial for Alzheimer’s Disease (MIND-ADmini)(NCT03249688) pilot trial (extended six-month follow-up in some countries), a multidomain lifestyle intervention derived from the FINGER trial is tested both alone and in combination with Souvenaid among individuals with prodromal AD and vascular or lifestyle-related risk factors. The control group receives usual care and regular health advice. Trial participants were recruited from Finland, France, Germany, and Sweden, and the main objective is to assess the feasibility of the multidomain intervention in this population. MIND-AD can serve as a model and platform for future trials combining non-pharmacological and pharmacological approaches to prevent or delay the onset of dementia. A master protocol for combination therapy is currently under development.
In addition to the abovementioned trials, WW-FINGERS interventions are also planned in several other countries including Japan, Canada, UK, the Netherlands, Spain, Italy, India, South Korea, Malaysia, and several Latin American countries (LATAM FINGER project) (Figure 1).

 

Conclusions

Prevention has been recognized as pivotal in halting the expected worldwide increase of AD and dementia cases. Successful preventive approaches should be feasible, accessible, cost-effective, and sustainable for populations in different geographical, economic, and cultural settings. Several modifiable risk factors, which can be managed to promote brain health and reduce the risk of late-life AD and dementia, have been identified. Yet, the majority of the observational studies on risk and protective factors have been conducted in high-income countries, with few findings available from low- and middle-income countries, which are facing the highest rise in dementia prevalence and incidence. In fact, by 2050, 68 % of all people with dementia worldwide are expected to live in low- and middle-income countries (1). The World Health Organization has invited experts worldwide to produce a global action plan and guidelines for cognitive decline and dementia risk reduction (58), and studies documenting prevalence and time-trends of risk factors in low- and middle-income countries can help develop preventive models for these areas.
The multidomain preventive approach has already proven its efficacy in other age-related chronic conditions (diabetes mellitus, cardiovascular disease (59,60)), and can facilitate also the reduction of dementia risk by addressing the multifactorial, complex, and heterogeneous nature of late-life cognitive impairment, AD, and dementia. Importantly, it offers prevention potential on a large scale, with possibilities for worldwide implementation. Country-specific adaptations will be crucial to ensure effective implementation of multidomain preventive interventions in different cultural, geographical, and economical settings, as well as public health care systems. Introduction of innovative eHealth and mHealth tools can facilitate implementation and monitoring of the interventions, while reducing costs and reaching larger regions and populations. The proportion of older adults using Internet is increasing, supporting the use of eHealth-based approaches, but feasibility is a key issue and is actively investigated. For instance, in the HATICE RCT older adults were involved in the development of the Internet platform that was used to deliver the multidomain intervention, in order to optimize its acceptability and use (61). Similar efforts may be needed also in future trials investigating eHealth or mHealth tools.
The complex nature of late-life cognitive impairment, AD, and dementia translates into a need to identify different risk profiles in order to develop tailored preventive strategies, within the framework of preventive precision medicine. WW-FINGERS is a landmark initiative, which will facilitate identification of efficacious preventive approaches for specific risk profiles and cost-effective implementation of such approaches in different settings. The WW-FINGERS model can be further developed to integrate pharmacological treatments, as the AD drug development field advances and succeeds in identifying effective disease-modifying compounds. Multidomain schemes combining pharmacological and non-pharmacological interventions can be developed and tested to define secondary and tertiary preventive strategies across the full spectrum of AD.
The WW-FINGERS network facilitates international collaboration in dementia prevention and provides an opportunity to harmonize prevention studies, as well as share experiences and data to obtain maximum scientific impact. Furthermore, the network aims at generating high-quality scientific evidence to support public health and clinical decision-making. This global joint effort can also have a key role in promoting rapid and effective dissemination and implementation of research findings.

 

Funding: This work was supported by the Academy of Finland grants (278457, 287490, 305810, 317465, 319318); Joint Program of Neurodegenerative Disorders – prevention (MIND-AD) grant through the following funding organisations under the aegis of JPND – www.jpnd.eu: Finland, Suomen Akatemia (Academy of Finland, 291803); Sweden, Vetenskapsrådet (VR) (Swedish Research Council, 529-2014-7503); Swedish Research Council grant 2017-06105; Juho Vainio Foundation, Finnish Medical Foundation; Finnish Social Insurance Institution; Ministry of Education and Culture Research Grant; Finnish Cultural Foundation North Savo regional fund, Finnish Brain Foundation; Knut and Alice Wallenberg Foundation Sweden; Center for Innovative Medicine (CIMED) at Karolinska Institutet Sweden; Stiftelsen Stockholms sjukhem Sweden; Konung Gustaf V:s och Drottning Victorias Frimurarstiftelse Sweden; af Jochnick Foundation Sweden; the European Research Council Starting Grant (ERC-804371), Alzheimer Fonden Sweden. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Conflict of interest: The authors have no conflicts of interest to declare.

Ethical standards: All studies presented in this article are conducted according to the principles of the Declaration of Helsinki and following the guidelines for Good Clinical Practice. Studies are approved by local ethics committees and all participants provided written informed consent.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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FACTORS ASSOCIATED WITH ALZHEIMER’S DISEASE: AN OVERVIEW OF REVIEWS

 

M. Rochoy1,2, V. Rivas1, E. Chazard1,3, E. Decarpentry1, G. Saudemont1, P.-A. Hazard1, F. Puisieux1, S. Gautier1,2, R. Bordet1,2

 

1. Univ. Lille, F-59000 Lille, France; 2. INSERM, U1171-Degenerative and Vascular Cognitive Disorders, F-59000 Lille, France; 3. EA2694, Public Health Department, Univ Lille, CHU Lille, F-59000 Lille, France

Corresponding Author: Michaël Rochoy, 20 rue André Pantigny, 62230 Outreau, France. +33667576735, michael.rochoy@gmail.com

J Prev Alz Dis 2019;2(6):121-134
Published online February 11, 2019, http://dx.doi.org/10.14283/jpad.2019.7

 


Abstract

Alzheimer’s disease (AD) is a frequent pathology, with a poor prognosis, for which no curative treatment is available in 2018. AD prevention is an important issue, and is an important research topic.
In this manuscript, we have synthesized the literature reviews and meta-analyses relating to modifiable risk factors associated with AD. Smoking, diabetes, high blood pressure, obesity, hypercholesterolemia, physical inactivity, depression, head trauma, heart failure, bleeding and ischemic strokes, sleep apnea syndrome appeared to be associated with an increased risk of AD. In addition to these well-known associations, we highlight here the existence of associated factors less described: hyperhomocysteinemia, hearing loss, essential tremor, occupational exposure to magnetic fields.
On the contrary, some oral antidiabetic drugs, education and intellectual activity, a Mediterranean-type diet or using Healthy Diet Indicator, consumption of unsaturated fatty acids seemed to have a protective effect.
Better knowledge of risk factors for AD allows for better identification of patients at risk. This may contribute to the emergence of prevention policies to delay or prevent the onset of AD.

Key words: Alzheimer’s disease, prevention, risk factors, early intervention.

List of abbreviations: AD: Alzheimer’s disease; OR: Odds-Ratio; RR: Relative Ratio


 

Background

The prevalence of dementia is estimated to be over 45 million people and could reach 115 million by 2050 (1). Alzheimer’s disease (AD) accounts for 60-70% of dementias (2). The prevalence of dementia is increasing as the population ages (3). Nevertheless, several studies showed a decrease in the prevalence rate of dementia or severe cognitive impairment after the age of 65 over the last 10 to 30 years in the United States (4–7) and Europe (8–13). The decrease in the prevalence rate could be explained by prevention and better management of risk factors (14).
The main risk factor for AD is age. Another known risk factor is heredity; thus, many genetic determinants have been studied, notably ApoE4, ApoE3 or presenilin S1 and S2 (15, 16).
In 2018, AD remains incurable and prevention is essential: it is based on the management of modifiable risk factors.
Many studies focused on AD “risk factors”. In response to the large number of articles, systematic literature reviews focused on classes of risk factors (genetic, environmental, infectious, etc.). For clinicians, it seems important to synthesize these numerous studies and reviews, and provide an overview of literature reviews.
Our aim was to summarize the literature reviews conducted on modifiable risk factors for AD.

 

Methods

This overview of literature reviews was conducted using the PubMed search engine (MEDLINE database), with the equation: “Alzheimer disease”[MeSH] AND “risk factor” [All Fields] AND (Meta-Analysis[ptyp] OR Review[ptyp]). The research was carried out in February 2017 and checked in November 2017.
The inclusion criteria were literature review or meta-analysis of epidemiological articles.
There was no time limit on the reviews and meta-analyses included.
The exclusion criteria were:
–     Descriptive literature reviews
–     Literature reviews that do not detail the populations studied
–    Pathophysiological literature reviews
–     Animal model studies
–     Articles not accessible in full
–     Articles in a language other than English or French

An additional search was performed on the UpToDate® site. The literature reviews cited, not found via the PubMed query, have been added.
A second additional search was carried out on the French Health Scientific Literature search engine (LiSSa) to look for other risk factors that were not noticed during the initial searches, via literature reviews published in journals not indexed on MEDLINE.
When the same association was covered by several reviews, we excluded the oldest ones.
As the purpose of this work is to provide an up-to-date synthesis of the literature reviews, most of the main and/or relevant results of the studies have been extracted.

 

Results

We identified 668 literature reviews and included 86 from PubMed. We included 5 articles with additional research (UpToDate® and LiSSa). Reviews and meta-analysis included are summarized in Table 1.

Table 1. Summary of reviews and meta-analysis

Table 1. Summary of reviews and meta-analysis

There are many modifiable risk factors for AD, summarized in Table 2. Levels of evidence are resumed in Table 3.

Table 2. Modifiable factors associated with AD

Table 2. Modifiable factors associated with AD

 

Table 3. Summary of evidences concerning associated factors for Alzheimer’s dementia

Table 3. Summary of evidences concerning associated factors for Alzheimer’s dementia

 

Cardiovascular

Several literature reviews established a link between hypertension at different life stages and an increased risk of AD (17–21).
A systematic review summarized the findings from population-based observational studies and randomized clinical trials addressing the relations of blood pressure to cognitive function and dementia (20). Concerning “late-life” hypertension, seven longitudinal studies reported an association with AD, three longitudinal studies and two cross-sectional studies found no association, five cross-sectional studies reported an inverse association (potentially protective) (20). Concerning “mid-life” hypertension, an association with AD has been reported in four of five longitudinal studies (20).
Barnes and Yaffe associated «mid-life» hypertension and AD with OR = 1.61 (CI95 [1.16 – 2.24]). «Late-life» hypertension was not associated with an increased risk of AD in 8 of the 13 studies included (22). In another literature review, patients with the highest coefficient of variation in blood pressure were more likely to have an increased risk of cognitive impairment or dementia (17).
In 2006, another review highlighted a link between low diastolic BP (between 65 and 80 mmHg) and increased risk of AD (18).
Most published studies demonstrate associations between atrial fibrillation and impaired cognition, but no atrial fibrillation treatment has yet been associated with a reduced incidence of cognitive decline or dementia (23).
Heart failure was associated with 60% increased dementia risk (RR = 1.60 ; CI95 [1.19-2.13]) (24). Heart failure is associated with increased radiologic brain damage, particularly in the limbic system (which includes the hippocampus), similar to objective damage in AD patients (25).
A meta-analysis o associated hyperhomocysteinemia (> 15 µmol/L) and AD: OR = 3.37 (CI95% [1.90 – 5.95]) (26). This association is suggested in other reviews MA (27, 28). The link between vitamin deficiency (B9 or B12) and hyperhomocysteinemia is known and this could constitute a confounding bias.
Kivipelto et al. associated risk of AD and «mid-life» hypercholesterolemia (not in «late life») (29). In another review, 5 prospective studies were studied: 3 showed a significant association between AD and hypercholesterolemia; on the other hand, 1 study showed no significant association, while the last showed, conversely, a protective effect with a RR estimated at 0.4 (CI95 [0.2 – 0.8]) (18).
Hemorrhagic and ischemic stroke was also considered as risk factors for dementia: an increase in the risk of dementia by 10% after a first episode, and up to more than 20% after several episodes (30). Subclinical brain microbleeds (4 or more) were associated with an increase in cognitive impairment (HR = 2.10 ; CI95 [1.21 – 3.64]) (31).
One review analyzed different types of antihypertensive agents and their possible association with AD: there was no difference between control group, diuretic group or angiotensin 2 antagonist. In contrast, the authors report a decrease in RR dementia in patients using a calcium channel blocker (RR = 0.55; CI95 [0.24 – 0.73]) (32). For ACE inhibitors, the authors reported, at the conclusion of their review, a significant difference between the treatment and control groups in the incidence of cognitive impairment, but no significant difference in the occurrence of dementia (32).
In the review by Miida et al., the included cross-sectional studies showed a significant decrease in the risk of AD in patients using statins; but 3 out of 4 prospective studies did not show a significant decrease in the risk of AD, as did the 8 randomized controlled trials (RCTs) (33).

Habitus, social contact and educational level

Physical activity was associated with a decreased risk of cognitive impairment in 21 of 24 cohorts included (87.5%) and 100% of cross-sectional studies; a meta-analysis of 8 studies reported RR at 0.58 (CI95 [0.49 – 0.70]) for high vs low physical activity (34). In 2011, Barnes and Yaffe concluded that there is an association between physical inactivity and increased risk of dementia in the various reviews and meta-analyses included in their study (19). Wheeler et al. suggest that reducing and replacing sedentary behavior with intermittent light-intensity physical activity may protect against cognitive decline by reducing glycemic variability (35).
Active smoking (versus never smoking) was associated with an increased risk of dementia: RR = 1.79 (CI95 [1.43 – 2.23]) (22). In 2014, Beydoun et al. published a literature review with somewhat more nuanced results on this relationship between smoking and cognitive impairment: 16 of the 29 cohort epidemiological studies included (55.2%) found an association between smoking and increased risk of cognitive impairment, as 2 of the 7 cross-sectional studies included. In a meta-analysis of 9 of 29 studies, the authors calculated a RR of AD for current and former smokers compared to never smokers at 1.37 (CI95 [1.23 – 1.52]) (28).
Concerning alcohol, Beydoun et al. noted an association between alcohol and increased cognitive impairment in 44% of cohorts included and 75% of cross-sectional studies (28).
In 2009, Anstey et al. published a meta-analysis of 15 cohorts whose results suggest that alcohol consumption is associated with a decreased risk of AD: RR = 0.66 (CI95 [0.47 – 0.94]) (36). Confounding factors were possible, particularly due to alcohol-related comorbidities.
There was a moderate association between caffeine consumption and decreased risk of cognitive problems: in one review, 4 of the 7 cross-sectional studies and 3 of the 11 cohorts included found this association. Five other cohorts among the 11 identified this link in a partial way in the subgroup analyses (for example, only among women) (28).
Frequent social contact and cognitive stimulation would be protective factors (37).
A lower educational level was associated with an increased risk of AD, with an RR estimated at 1.80 (CI95 [1.43 – 2.27]) (38) or 1.99 (CI95 [1.30 – 3.04]) in Beydoun’s meta-analysis (knowing that low educational level here means less than 8 years of education) (28).

Pneumology

A meta-analysis of 6 cohort studies (19,940 patients) associated sleep apnea syndrome and dementia (RR = 1.69; CI95 [1.34 – 2.13]). The association is also found in subgroup analyses, with or without polysomnography, adjusted or not on ApoE4 (39).

Infectiology

One of 3 case-control studies and 2 epidemiological studies showed a possible link between Chlamydia pneumoniae infection and AD possibly through chronic neuronal inflammation (40).
The prevalence of Helicobacter pylori was increased in patients with AD in case-control studies; in cohorts patients with H. pylori often have poorer cognitive performance (confounding bias). However, the authors conclude their narrative review with a lack of longitudinal studies to support the association between infection and AD, to explain more precisely the mechanism by which H. pylori would actually intervene in pathogenesis, and to determine the utility of eradication of the bacterium in patients with AD or cognitive disorders (41).
A review of 12 case-control studies did not associated Herpes Simplex Virus 1 infection and AD (40). In the same review, it is suggested that HHV6 is not an independent risk factor for AD. Nevertheless, its presence could increase the neuronal damage caused by HSV1 in patients with ApoE4.

Endocrinology and metabolism

The risk of dementia (especially AD) increased in cases of «mid-life» underweight (BMI < 18.5) or «mid-life» obesity (between 45 and 64 years of age according to the authors); this association is not present after 64 years of age, in late life (42). «Mid-life» obesity was associated with an increased risk of dementia : RR = 1.59 (CI95 [1.02 – 2.48]) (22).
Diabetes is also a risk factor for AD in most studies, with an estimated RR of 1.53 (CI95 [1.42 – 1.63]), or slightly higher in so-called «eastern» populations, with an RR of 1.62 (CI95 [1.49 – 1.75]) (43). Mid-life and late-life diabetes were associated with AD (42); interaction is possible with cerebrovascular risk (18).
The impact of metformin use on the occurrence of cognitive impairment is unclear: protective role in a cohort, risk factor in a case-control study. In one studiy, metformin + hypoglycemic sulfonamide combination therapy is associated with a decrease in AD compared to untreated diabetic patients (HR = 0.65; CI95 [0.56 – 0.74]) (44).
Hypotestosteronemia in elderly men would be associated with an increase in AD (RR = 1.48; CI95 [1.12 – 1.96]). However, the authors do not detail their definition of «elderly male» and report that the studies included in their meta-analysis have different definitions for hypotestosteronemia (45)

Psychiatry, neurology and anesthesia

A meta-analysis associated history of depression and increased risk of AD: RR = 1.90 (CI95 [1.55 – 2.33]) in cohort studies (46). Late-life depression is associated with increased risk of AD (37).
In 2015, Harrington et al. studied the relationship between depression and Aβ plaques in a healthy, older adult population. The majority of included studies found a significant increase in Aβ levels in depressed patients. However, the authors mentioned many biases in the 19 cross-sectional studies included (47).
Long-term benzodiazepine users had an increased risk of dementia compared with never users: RR = 1.49 (CI95 [1.30 – 1.72]). The risk of dementia increased by 22% for every additional 20 defined daily dose per year (RR = 1.22 ; CI95 [1.18 – 1.25]) (48).
Peripheral and central hearing impairment were associated with a risk of AD (49). The RR was estimated at 2.82 (CI95 [1.47 – 5.42]) between hearing impairment and risk of cognitive impairment (50).
Head injury with loss of consciousness could also be a risk factor for AD, according to several studies, with an estimated RR of 1.82 (CI95 [1.26 – 2.67]) (51). In a subgroup analysis, OR is significant only for men (OR = 2.29 ; CI95 [1.47 – 2.06]), not for women (52).
A review of 6 epidemiological studies reports that an essential tremor would be associated with an increased risk of AD (53).
A meta-analysis of 15 case-control studies did not associated general anesthesia and AD (OR = 1.05; CI95 [0.93 – 1.19]) (54).

Environmental

Several literature reviews have highlighted a possible link between AD and exposure to extremely low frequency electromagnetic fields, particularly in a professional context (electrician, electronics technician, welder…) (55–57). The latest meta-analysis (20 studies) highlighted the numerous biases (particularly publication bias) and heterogeneity of the populations being compared, without a dose-response relationship. They suggested a higher risk for train drivers (RR = 2.94; CI95 [1.15 – 7.51]) than for welders (RR = 1.54; CI95 [1.00 – 2.38]) or electricians (RR = 1.18; CI95 [1.01 – 1.37]) (58).
A positive association was observed between pesticide exposure and AD (OR = 1.34; CI95 [1.08 – 1.67]) (59).

Diet, nutrients

Regular use of anti-acids (with aluminium) has no relationship with increased risk of AD: a meta-analysis estimated OR for case-control studies at 1.0 (CI95 [0.8 – 1.2]) and for prospective studies at 0.8 (CI95 [0.4 – 1.8]) (60). A review highlighted a possible relationship between aluminium in drinking water and AD, but noted inconsistencies (61).
A review showed no association or inconsistent associations between vitamin B12 intake and cognitive function (62).
A literature review of 57 studies concluded that there is no evidence to support a possible recommendation for the preventive use of zinc for AD (63).
A decrease in manganese plasma levels may also be associated with an increased risk of AD (64).
In one review, magnesium was not associated with AD, but a lowered level of magnesium within the cerebrospinal fluid increased the risk of AD (65).
A combined meta-analysis of 3 meta-analyses estimates an HR of 0.92 (CI95 [0.88 – 0.97]) in favour of an inverse (protective) relationship between mediterranean diet and risk of AD (66). In 2017, Yusufov et al. published a systematic review of the literature in which 10 of the 12 studies included found an association between Mediterranean diet and reduction in the risk of AD (67).
Van de Rest et al. studied the impact of the Healthy Diet Indicator diet, based on World Health Organization recommendations: 6 of the 6 cross-sectional studies and 6 of the 8 longitudinal studies included found an association between diet adequate to HDI recommendations and decreased risk of cognitive impairment (66).
The intake of unsaturated fatty acids (notably via fish consumption) is associated with a reduction in the risk of AD and dementia (68). This association is mainly found in cross-sectional studies (5/5), less in cohorts (7/18); a meta-analysis of 5 studies estimated RR at 0.67 (CI95 [0.47 – 0.95]) (28). A role of the intestinal flora has been mentioned in the pathogenesis of Alzheimer’s disease (69).
In the review by Yusufov et al. 7 of the 9 studies included found that dietary intake of vitamin E was associated with a decreased risk of AD (67). Beydoun et al. report a similar association, but in 9 of 21 cohort studies and 2 of 6 cross-sectional studies included in their review (34).
An overview of systematic review suggested that Ginkgo biloba extract has potentially beneficial effects for people with dementia when it is administered at doses greater than 200mg/day for at least 5 months (70).
Yusufov et al. note that 4 of the 5 included studies found an association between folate (vitamin B9) intake and decreased risk of AD (67).
Plasma vitamin D concentration greater than 560 ng/mL is associated with minimal gain at the MMSE level estimated at 1.16 points (CI95 [0.46 – 1.85]) in a meta-analysis (71). Several confounding biases are possible, including better sun exposure of non-dementia patients.
An other meta-analysis showed significantly lower plasma levels of folate, vitamin A, vitamin B12, vitamin C, and vitamin E (P < .001), non-significantly lower levels of zinc (P = .050) and vitamin D (P = .075) in AD patients, and non-significant differences for plasma levels of copper and iron; this lower plasma nutrient levels could indicate that patients with AD have impaired systemic availability of several nutrients (72).

 

Discussion

Principal results

Cardiovascular risk factors are an important part of the reviews selected in this research work. Thus, most of the journals included report an association between the different cardiovascular risk factors and the occurrence of AD.
Medically, several reviews suggest that a history of depressive syndrome is associated with an increased risk of AD. Hearing, central or peripheral impairment also seems to increase the risk of AD. However, the studies do not allow us to conclude whether the risk is corrected with the use of hearing aids.
On the environmental level, intellectual inactivity and low educational level (less than 8 years of study) seem to be the most associated factors in this research with an increased risk of AD.
Unlike intellectual inactivity and low educational level, the authors of the reviews hypothesize that a higher level of education would be associated with a lower risk of AD.
On the drug side, it would appear that the use of calcium channel blockers is associated with a decrease in dementia (but not in AD in particular). For IECs, the results point to a decrease in cognitive disorders, but not in the occurrence of dementia.
In terms of diet, the Mediterranean diet is the most studied, and seems to be associated with a decrease in the risk of AD. The results of the various reviews also seem to point towards a protective role for a diet rich in unsaturated fatty acids ω.
Dietwise, no relationship has been found between plasma or cerebrospinal zinc levels and the incidence of dementia or AD. Similarly, there is no reported link between zinc supplementation and the prevention of AD.
The same applies to vitamin B or vitamin E supplementation. Plasma magnesium levels also do not appear to be associated with a risk of AD.
The absorption of aluminum, through drinking water or medication, does not appear to be associated with the development of AD or dementia.
Medically, the use of ARB2 or diuretics does not appear to affect the onset of dementia. More anecdotally, general anesthesia did not show an association with the occurrence of AD either.
From an environmental perspective, it appears that HSV1 and HHV6 infections are not associated with the occurrence of AD.
Alcohol consumption presents contradictory results. Some studies tend to show a protective effect of alcohol on the occurrence of dementia and AD, while others suggest the opposite relationship.

Strengths and limitations

Alzheimer’s disease is a frequent pathology, with a poor prognosis, without curative treatment available in 2018. Knowing how to prevent it better is an important issue, and a lot of research is being carried out in this direction. The large number of literature reviews and meta-analyses carried out on the subject can make a global approach difficult. Our synthesis is intended to be an overview of the various literature reviews in 2018, in order to take stock of what seems likely, what seems doubtful and what is not yet well studied. This is a substantial work based on 90 literature reviews and meta-analyses. Our results are consistent with the previous syntheses carried out on the same subject.
It is likely that the initial research equation may have caused a selection bias in the results presented by the PubMed database.
A publication bias is to be mentioned; in order to limit it, we completed our research with a search in the encyclopedia «UpToDate» and in French-speaking journals not indexed via LiSSa.
An «interpretation» bias is possible in the inclusion of the different reviews.
This study assumes that all included reviews and meta-analyses are of equal quality and value, which is not the case. The various reviews may be sources of bias, which may have influenced the results presented. Many confounding biases can exist in studies and be amplified by literature reviews.
Moreover, the subject matter is vast and complicated, it is not easy to approach it in its entirety, through very heterogeneous publications, which highlight different pathophysiological hypotheses in order to explain in a rational and scientific way the possible suspected association.

Perspectives

We have only studied literature reviews; risk or protective factors may exist, have been studied in retrospective or prospective studies that have not yet been reviewed.
As studies and reviews progress, some clearly identified risk factors can be modified, particularly in the cardiovascular and environmental fields. It may be interesting to study the impact of prevention on targeted modifiable risk factors in order to assess the impact on the incidence of AD and dementia.
On the other hand, some of the factors studied appear to be «doubtful», and it seems appropriate to carry out additional studies. For example, it may be relevant to study the impact of H. pylori eradication on the occurrence of AD, in order to determine whether systematic treatment can be an axis of AD prevention.

 

Conclusions

Specifying the risk factors for AD is a major issue to better prevent or delay its appearance. Current studies identify many modifiable risk factors. The impact of these modifiable factors appears to be greater and more reliable than genetic factors. Risk factors can induce AD, anticipate it or aggravate it; protective factors can have a specific effect or an effect limiting the impact of a pathology (antidepressant, anti-hypertensive…). To our knowledge, the cumulative effect of the various risk factors has not been studied.
Identifying patients at risk is important in order to prevent or delay the onset of AD, and also to limit high-risk behaviors (driving, treatment management, gas handling), anticipate dependency, limit financial risks (legal protection) or integrate a research protocol.
Synthesizing the literature reviews also highlights doubtful risk factors and unstudied risk factors. In addition, some risk factors have emerged in recent articles, but have not yet been studied in literature reviews. Studying these factors also makes it possible to make physiopathological assumptions that will lead to a better understanding of the mechanisms involved in the development of AD.

 

Ethics approval and consent to participate: Not applicable.

Consent for publication: Not applicable.

Availability of data and material: Not applicable / all articles used in this overview are cited in the text.

Competing interests: The authors declare that they have no competing interests.

Funding: Not applicable.

Authors’ contributions: MR, VR reviewed the literature and were involved in manuscript preparation and revision. EC, ED, GS, PAH, FP, SG, RB were involved in manuscrit revision. All authors read and approved the final manuscript.

Acknowledgements: The authors acknowledge fellow colleagues for the discussions. We apologize to authors whose studies were not cited due to space constraints.

 

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DIET AS A RISK FACTOR FOR COGNITIVE DECLINE IN AFRICAN AMERICANS AND CAUCASIANS WITH A PARENTAL HISTORY OF ALZHEIMER’S DISEASE: A CROSS- SECTIONAL PILOT STUDY DIETARY PATTERNS

 

A.C. Nutaitis1, S.D. Tharwani1, M.C. Serra2, F.C. Goldstein1, L. Zhao3, S.S. Sher4, D.D. Verble1, W. Wharton1

 

1. Emory University, Department of Neurology; 2. Atlanta VA Medical Center & Emory University Department of Medicine; 3. Emory University, Department of Biostatistics and Bioinformatics; 4. Emory University, Department of Internal Medicine

Corresponding Author: Whitney Wharton, PhD, Assistant Professor, Neurology, Emory University, w.wharton@emory.edu

J Prev Alz Dis 2018
Published online November 30, 2018, http://dx.doi.org/10.14283/jpad.2018.44

 


Abstract

Background: African Americans (AA) are more likely to develop Alzheimer’s disease (AD) than Caucasians (CC). Dietary modification may have the potential to reduce the risk of developing AD.
Objective: The objective of this study is to investigate the relationship between Southern and Prudent diet patterns and cognitive performance in individuals at risk for developing AD.
Design: Cross-sectional observational study.
Participants: Sixty-six cognitively normal AA and CC individuals aged 46-77 years with a parental history of AD were enrolled.
Measurements: Participants completed a Food Frequency questionnaire, cognitive function testing, which consisted of 8 neuropsychological tests, and cardiovascular risk factor assessments, including evaluation of microvascular and macrovascular function and ambulatory blood pressure monitoring.
Results:  Results revealed a relationship between the Southern diet and worse cognitive performance among AAs. AAs who consumed pies, mashed potatoes, tea, and sugar drinks showed worse cognitive performance (p<0.05) compared with CCs. In addition, gravy (p=0.06) and cooking oil/fat (p=0.06) showed negative trends with cognitive performance in AAs. In both CC and AA adults, greater adherence to a Prudent dietary pattern was associated with better cognitive outcomes. Cardiovascular results show that participants are overall healthy. AAs and CCs did not differ on any vascular measure including BP, arterial stiffness and endothelial function.
Conclusion: Research shows that dietary factors can associate with cognitive outcomes. This preliminary cross-sectional study suggests that foods characteristic of the Southern and Prudent diets may have differential effects on cognitive function in middle-aged individuals at high risk for AD. Results suggest that diet could be a non-pharmaceutical tool to reduce cognitive decline in racially diverse populations. It is possible that the increased prevalence of AD in AA could be partially reduced via diet modification.

Key words: Alzheimer’s disease, Diet, African-American, Prevention, Nutrition, Race, Cognition, Vascular.

Abbreviations:  AA: African Americans; AD: Alzheimer’s disease; CCs: Caucasians.


 

Introduction

Over five million people in the U.S. are living with Alzheimer’s disease (AD), and in the next thirty years, the prevalence will increase to over sixteen million (1). Individuals at high risk of AD include African Americans (AAs), who have a 64% higher chance of developing AD than Caucasians (CCs) (2), and individuals with a parental history of AD, who are ten times more likely to become afflicted themselves (3). In the absence of a disease-modifying treatment, it is critical that we identify modifiable risk factors to promote cognitive health and reduce AD risk. Current preventative efforts focusing on lifestyle interventions including diet, exercise, and cognitive training (4, 5). Importantly, midlife (40-65 years of age) is when the neuropathological AD related changes begin and when the impact of vascular risk factors begin to have lasting effects. Thus, middle age is the optimal time to implement an AD focused lifestyle intervention.
Research suggests that adherence to a healthy diet confers cognitive benefits in older populations (6-8). Such diets include the Prudent, Dietary Approaches to Stop Hypertension (DASH) and Mediterranean diets, characterized by fruit, vegetables, legumes, fish and olive oil. While these studies are encouraging, few studies have examined the potential influence of diet on cognition in middle-aged, ethnically diverse populations, who are at high risk for AD.
In addition to genetic contributions, the increased prevalence of AD in AAs may be a result of modifiable risk factors including dietary intake (9-12). In a study examining the association between the Mediterranean diet and cognitive decline, AA participants who had higher adherence with the Mediterranean diet had slower cognitive decline compared to participants with less Mediterranean diet adherence (13). Furthermore, current literature suggests that geographic and racial differences in cardiovascular disease risk are associated with the Southern dietary pattern (characterized by fried foods, fats, eggs, organ and processed meats and sugar-sweetened beverages) and thus it is possible that this Southern dietary pattern may contribute to cognitive decline (14). These findings stress the need for prospective studies addressing the relationships between diet and cognitive function in racially diverse populations in the U.S (15).
The goal of this study was to assess the relationship between dietary patterns, vascular function, and cognitive decline, in a middle aged, diverse cohort at high risk for AD due to a parental history of AD. We hypothesize that a higher intake of a  Southern dietary pattern and lower intake of a  Prudent (healthy) in dietary pattern increases the risk for vascular dysfunction and cognitive impairment, especially among AA, compared to CC, adults.

 

Subjects and Methods

Study Sample

Sixty-six subjects enrolled in an ongoing NIH/NIA funded study (ASCEND PI: Wharton) and with a parental history of AD took part in this cross-sectional pilot observational cohort study. Parental history was confirmed via autopsy or probable AD as defined by NINDS-ADRDA criteria and the Dementia Questionnaire (16). Subjects received vascular and cognitive assessments under the IRB approved protocol.

Demographic Information

Age, gender, level of education, income, exercise, smoking status, and depression was acquired via a self-reported survey. Exercise was reported as mean days per week of cardiovascular exercise (17).
Dietary Pattern Assessment: Diet was assessed via the Jackson Heart Study’s shortened version of the Lower Mississippi Delta Nutrition Intervention Research Initiative Food Frequency Questionnaire (FFQ) (18). The questionnaire consists of 160 items and takes 20 minutes to complete. Participants self-reported quantity and frequency of food and drink consumption on an online survey at home via a secure, individual web link. Subjects were given a $15.00 gift card for completing the survey.
Food items from the FFQ were classified into the Southern or Prudent diets in accordance Reasons for Geographic and Racial Differences in Stroke (REGARDS) study guidelines (14). Food items including fried foods, fats, eggs, organ and processed meats and sugar-sweetened beverages were classified as characteristic of the Southern diet (14). Healthy foods including fruits, vegetables, whole grains, and fish were classified as Prudent diet related items (19).

Cardiovascular Risk Factor Assessment

Vascular measures were selected based on prior research with vascular function in individuals at risk for AD (20, 21). Participants underwent a one-hour fasting assessment including microvascular vasodilatory function, using digital pulse amplitude tonometry (EndoPAT) and macrovascular vascular function (assessed by flow mediated vasodilation (FMD)). In addition, a blood pressure (BP) assessment was obtained via 24-hour ambulatory BP monitoring (Spacelabs Healthcare©). We examined 24-hour average systolic and diastolic blood pressure and nocturnal dipping patterns, all of which have been linked to cognition and AD (22).

Neuropsychological testing

Cognitive function was evaluated by a one-hour battery of eight neuropsychological tests in domains reportedly affected in early AD and susceptible to the effects of hypertension (23). The tests included: Montreal Cognitive Assessment (MOCA), Benson visuospatial memory task, Buschke Delay Memory Test, Trails A and B, Digit Span Backwards, Mental Rotation Test (MRT), and Multilingual Naming Test (MINT). These tests targeted specific AD related cognitive domains including: working memory, executive function (Trail-Making Test B) (24, 25), language (MINT) (26), verbal memory (Buschke) (27), visuospatial ability (MRT) (28) and global cognition (MOCA) (29).

Data Analysis

Researchers utilized IBM SPSS Statistics Version 22 to test for group differences between AAs and CCs in demographics, vascular risk factors, and cognitive performance. We conducted independent two-sample t-test for continuous variables and chi-square test for characteristic variables, controlling for age, gender and education. As there is not sufficient power to detect an interaction of diet and race, we examined the association between diet and cognition in each racial group separately. Correlations between cognitive performance and foods were assessed using Pearson’s r partial correlations controlling for education and age on the cognitive tests in which we found racial differences at p=0.10. Because eight cognitive tests were included in the analyses, the threshold of significance level using a false discovery rate approximation was adjusted such that a threshold p-value of 0.03 was used.

 

Results

Table 1 shows the demographic characteristics for 21 AAs and 45 CCs. Participants were middle aged (M=58.6 years), mostly female (67.6%), and highly educated (83.8% graduate or postgraduate education). While AAs and CCs did not differ on demographics including age, education, exercise, smoking status, or self-reported depression, significant racial differences were present for gender and income, such that a larger percent of AA females than CC females participated in the study, and AAs reported significantly less income compared to CCs. Participants were generally very healthy and AAs and CCs did not differ on any vascular measure including BP, arterial stiffness and endothelial function.

Table 1. Demographic Characteristics and Cardiovascular Data for African Americans and Caucasians. (AA= African American, CC=Caucasian)

Table 1. Demographic Characteristics and Cardiovascular Data for African Americans and Caucasians. (AA= African American, CC=Caucasian)

*P < 0.05; ** P < 0.01; RHI=reactive hyperemia index; AIx= augmentation index; FMD= flow mediated vasodilation

 

Table 2 shows cognitive test results by race. Results show that CCs significantly outperformed AAs on global cognition (MOCA), naming (MINT), and executive function (Trails B) tests (all p values <0.05). In addition, results revealed a trend for CCs to outperform AAs in verbal memory (Buschke Delay) (p= 0.073).
Table 3 shows Pearson’s r partial correlations between foods and cognitive performance, by race. Five of six southern foods show moderate to strong correlations with cognitive tests in AAs. In AAs, pies, mashed potatoes, and sugar drinks were correlated with cognitive performance (all p values <0.01) and trends were found with tea (p=0.04), gravy (p=0.06) and cooking oil/fat (p=0.06), such that AAs performed worse on cognitive tests with consumption of these foods. Results show that AAs were more negatively impacted than CCs by foods characteristic of the Southern diet. Conversely, CCs who consumed mashed potatoes (p=0.01) and sugar drinks (p<0.10) performed better on cognitive assessments. Foods characteristic of the Prudent diet, such as whole grain breads (p=0.04), baked fish (p=0.03), and grape juice (p<0.01), were positively associated with cognitive performance in CCs. In addition, 100% orange juice (OJ) showed a trend (p<0.10) of better performance on cognitive assessment in CC. The most pronounced relationship was seen with 100% grape juice, such that AAs consuming 100% grape juice performed significantly better on the MINT (p<0.01). Results suggest a stronger relationship between the Prudent diet and cognitive performance in CCs vs. AAs.

 

Table 2. Means and standard deviations on cognitive tests in African Americans and Caucasians. (AA= African American, CC=Caucasian)

Table 2. Means and standard deviations on cognitive tests in African Americans and Caucasians. (AA= African American, CC=Caucasian

†P<0.1; *P < 0.05

Table 3. Pearson’s r correlations between cognition and foods by race for individuals who completed Food Frequency Questionnaire. (AA= African American, CC=Caucasian; 1-6=Southern Diet, 7-10=Prudent Diet)

Table 3. Pearson’s r correlations between cognition and foods by race for individuals who completed Food Frequency Questionnaire. (AA= African American, CC=Caucasian; 1-6=Southern Diet, 7-10=Prudent Diet)

†P<0.10; *P<0.05; **P<0.01

 

Discussion

To our knowledge, this is the first study to report a relationship between diet and cognitive performance in healthy, racially diverse middle-aged adults with a parental history of AD. CCs outperformed AAs on cognitive tests of global cognition, language, and executive function. Racial differences on cognitive tests could not be explained by age, education, vascular risk factors, exercise, smoking, or depression. However, our results suggest that these differences may be partially attributed to dietary patterns specific to the Southern and Prudent diets.
A positive relationship between cognition and the Prudent (healthy) diet and a negative relationship between cognition and the Southern (less healthy) diet was observed. Similarly, Shakersain et al. recently identified a relationship between lower adherence to a Prudent diet and greater rates of cognitive decline [6]. Further, Seetharaman et al. reported that elevated diabetes risk, which is higher in AAs than CCs, is related to poorer performance on perceptual speed, verbal ability, spatial ability, and overall cognition (30).  Foods in our study characteristic of the Southern diet, such as pies, tea, and sugar drinks, were negatively associated with cognitive performance and thus it is possible that this may be a result of the higher glycemic index of these foods. Our results also align with studies showing that a diet high in gravy or butter is associated with poor cognition in older adults (31). Further, we show that racial differences in diet such that AAs reported stronger alliance with the Southern diet than CCs. This finding is not unique to our study, as previous studies show that AAs are less likely to adhere to the DASH diet compared with CCs (32). Our study highlights the need for culturally sensitive dietary interventions to combat cognitive decline in high-risk populations.
Only one Prudent item (100% grape juice) was correlated to cognitive performance in AAs, in contrast to five Prudent items (whole grain breads, mashed potatoes, baked fish, 100% grape juice and 100% OJ). The Prudent diet is nutrient dense, containing numerous nutrients with anti-inflammatory and antioxidant properties, including fiber, poly-unsaturated fatty acids, vitamins, minerals, carotenoids, and polyphenols, among others (6). Therefore, it is possible that the negative effects of elevated inflammation and oxidative stress, which is more prevalent among AAs, on cognitive health may be dampened by the effects of the Prudent diet (34, 35). The association between beverages and cognitive performance should also be noted. Individuals may be more consistent with their beverage choices, (i.e. coffee or OJ), than food choices, and thus beverages may associate more strongly with cognitive function due to a higher intake.
The need for advancements in preventative and treatment strategies in high-risk groups, including AAs is great (36). Results showed racial differences in the relationship between diet and cognitive performance. It is possible that dietary intake may be contributing to early cognitive decline in AAs, or preservation of cognitive functioning in CCs. This finding is important, as the current literature suggests that even though late-life positive dietary patterns may result in notable health improvements (19, 37), mid-life is the optimal time to incorporate these changes, before the irreversible AD cascade begins (38). Thus diet modification may hold promise as a modifiable risk factor for AD.
Strengths of this study include a comprehensive battery of neuropsychology testing and vascular measures, and a middle aged, racially diverse cohort at high risk for AD. Also the FFQ is both racially and geographically sensitive (18). Limitations of this pilot project include the small sample size and the overall health of the cohort. It is possible that diet may have a more pronounced impact in individuals with preexisting health complications. Next the FFQ does not include information regarding longitudinal food choices, and these data should be collected in future studies (39).
In summary, our results stress the need for further research investigating the potential of dietary intake as a non-pharmaceutical intervention in individuals at risk for AD. Because AAs have an increased incidence and prevalence of AD (2, 40), investigation of modifiable risk factors that target this high-risk group is essential. Specifically, nutritional education and dietary interventions designed to shift individuals, particularly AAs, from Southern diets to healthier, Prudent – like diets, may be a cost efficient way to preserve cognitive function in otherwise healthy individuals.

 

Funding: This project was funded by the National Institute of Health (NIH) and in part by the Scholarly Independent Research at Emory (SIRE) Research grant for undergraduate students. The NIH and SIRE had no role in study design, collection, analysis or interpretation of data; in the writing of the report; or in the decision to submit the article for publication.

Acknowledgments: All persons who have made substantial contributions to this manuscript are listed as authors. Their contributions are listed below: Alexandra C. Nutaitis, BS: Designed research, Conducted research, Analyzed data, Wrote paper, Had primary responsibility for final content . Sonum D. Tharwani: Conducted research, Wrote paper. Monica C. Serra, PhD: Provided essential reagents or materials, Analyzed data, Wrote paper. Felicia C. Goldstein, PhD: Designed research, Wrote paper. Liping Zhao, MSPH: Provided essential reagents or materials, Analyzed data, Wrote paper
Salman S. Sher, MD: Conducted research, Provided essential reagents or materials, Analyzed data, Wrote paper
Danielle D. Verble, MA: Conducted research, Wrote paper
Whitney Wharton, PhD: Designed research, Conducted research, Analyzed data, Wrote paper Had primary responsibility for final content

Sources of Support: NIH-NIA under grants: NIH-NIA 5 P50 AG025688, K01AG042498, and U01 AG016976. Independent funding for the present pilot study was obtained through Emory University’s Scholarly Inquiry Research Grant for undergraduate students (PI: Nutaitis).

Conflict of interest: No author has a conflict of interest to report.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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AURAPTENE IN THE PEELS OF CITRUS KAWACHIENSIS (KAWACHIBANKAN) CONTRIBUTES TO THE PRESERVATION OF COGNITIVE FUNCTION: A RANDOMIZED, PLACEBO-CONTROLLED, DOUBLE-BLIND STUDY IN HEALTHY VOLUNTEERS

 

M. Igase1, Y. Okada1, M. Ochi1, K. Igase2, H. Ochi1, S. Okuyama3, Y. Furukawa3, Y. Ohyagi1

 

1. Department of Geriatric Medicine and Neurology, Ehime University Graduate School of Medicine, Ehime, Japan; 2. Department of Advanced Neurosurgery, Ehime University Graduate School of Medicine, Ehime, Japan; 3. Department of Pharmaceutical Pharmacology, College of Pharmaceutical Sciences, Matsuyama University, Ehime, Japan

Corresponding Author: Michiya Igase, MD, PhD, Department of Geriatric Medicine and Neurology, Ehime University Graduate School of Medicine, 454 Shitsukawa, Toon City, Ehime 791-0295, Japan, Phone: +81-89-960-5851, Fax: +81-89-960-5852, E-mail: migase@m.ehime-u.ac.jp

J Prev Alz Dis 2018 inpress
Published online December 19, 2017, http://dx.doi.org/10.14283/jpad.2017.47

 


Abstract

OBJECTIVES: Dementia, which is characterized by a progressive decline in cognitive function, is a major concern in aging societies. Although a number of treatments have been approved, an effective therapy to prevent the disorder is lacking. A supplement that improves cognitive function would benefit patients. The aim of this study was to assess whether auraptene, a citrus coumarin, has a protective effect on cognitive decline.
DESIGN: A randomized, placebo-controlled, double-blind study
SETTING: Outpatient medical check-up program for cognitive disorders
PARTICIPANTS: 84 adult volunteers (they are cognitively normal) met inclusion and exclusion criteria to participate.
INTERVENTION: 42 participants received auraptene enriched (containing 6.0 mg/day of auraptene) test juice, and another participants received placebo juice.
MEASUREMENTS: 1) Mild Cognitive Impairment (MCI) Screen using the 10-word immediate recall test. 2) The Mini-Mental State Examination (MMSE). Cognitive assessment ware carried out baseline and at 24 weeks.
RESULTS: Auraptene enriched test juice did not improve cognitive function after 24 weeks compared with baseline data. However, there was a significant difference in the percentage change in cognitive function between the test and placebo orange juice groups (6.3 ± 18.9 vs. −2.4 ± 14.8, P < 0.05). Multiple regression analysis demonstrated a significant independent relationship between the percentage change in the 10-word immediate recall test score and test juice consumption including baseline 10-word immediate recall test score in all subjects.
CONCLUSION: This is the first study to assess the effectiveness of auraptene in the prevention of cognitive decline. Our results suggest that auraptene is a safe supplement for the prevention of cognitive decline.

Key words: Auraptene, Kawachibankan, randomized trial, multiple regression analysis, 10-word immediate recall test, cognitive decline, prevention


 

Introduction

Many advances have been made in the understanding of age-related changes in cognition, especially in dementia. Dementia is characterized by a progressive decline in cognitive function and is a major concern in aging societies (1). Research has focused on cognitive and neurobiological changes that occur during aging, and there is increasing interest in developing and understanding methods to prevent, slow, or reverse the cognitive decline that occurs in normal healthy older adults. Although a number of treatments have been approved, an effective therapy to prevent the disorder is lacking (2); therefore, a supplement that improves cognitive function would greatly benefit patients.
Recently, natural products are increasingly being used for the management and treatment of central nervous system disorders (3). The key desirable characteristics of natural products are their safety, efficacy and cultural acceptability. Coumarins, phenolic compounds that are found in various plants, bacteria and fungi, are an example of such natural products. Auraptene (AUR) is a natural bioactive monoterpene coumarin ether that was first identified in citrus fruits (4), and has anti-inflammatory and anti-carcinogenic activity (5). Citrus kawachiensis (Kawachibankan) is a citrus product specific to Ehime Prefecture, Japan. We previously showed that the peels of Kawachibankan contain abundant AUR at higher concentrations than that found in other citrus peels (6, 7). Although Kawachibankan peels containe a high amounts of naringin and a middle amounts of narirutin besides AUR, our previous study suggested that the major functional compound within the Kawachibankan peels for causing the anti-inflammation effect in the model mice was AUR. The reasons for this conclusion are as follows: <1> an anti-inflammatory effect on the brain was also observed by the administration of AUR given alone; <2> the administration of authentic naringin alone had not so much effect; <3>narirutin, being an isomer of naringin, would also likely have no anti-inflammatory property. (8). Another report has demonstrated the neuroprotective and memory-enhancing effects of AUR (9) in a rat model of cerebral ischemia.
Here, we assessed whether AUR in Kawachibankan peels has a protective effect on cognitive decline in healthy human subjects.

 

Methods

The subjects were participants in a medical check-up program at the Ehime University Hospital Anti-aging Centre (AAC) specifically designed to evaluate atherosclerosis and cognitive decline (10).
Enrolment was conducted over a 5-month period starting in March 2016. To rule out the impact of disease or medications, we excluded participants with a history of symptomatic cardiovascular events, including coronary heart disease and ischemic stroke, and those receiving medications for diabetes, dyslipidemia, hypertension or dementia.
A total of 84 subjects (age, mean±standard deviation [SD]: 71±9 years) who fulfilled the study criteria were enrolled. Subjects were randomized into two groups by a computerized random number generator. One group received 125 mL of test juice containing 6.0 mg of AUR per day and the other received the same volume of placebo juice containing 0.1 mg of AUR per day, for a duration of 24 weeks.
The study was conducted after approval by the institutional review board for clinical trial services at Ehime University Graduate School of Medicine (Ehime, Japan) and was performed by the study investigators. Written informed consent was obtained from all participants before examination. The study was conducted in accordance with the ethical principles described in the current version of the Declaration of Helsinki.

Laboratory tests

Hematological examinations were conducted at baseline and after 24 weeks. Blood samples were collected between 9:00 and 10:00 am from the cubital vein following an overnight fast. The following routine biochemical parameters were determined in fresh samples: alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (γ-GTP), high-density lipoprotein (HDL), serum triglycerides (TG), and serum creatinine (sCr). LDL levels were calculated using the Friedewald formula (11). Estimated glomerular filtration rate (eGFR; mL/min/1.73 m2) was calculated using the Cockcroft–Gault formula (12).

Cognitive assessment

To assess cognitive function, we conducted a «Mild Cognitive Impairment (MCI) Screen» (13) using the 10-word immediate recall test. The test was performed 3 times, and the sum of the scores was calculated for each subject. The MCI Screen was derived from the protocol of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) 10-word recall test (14), which is a 10-minute, computationally scored, staff-administered, neuropsychological test to screen for MCI. The validity and specificity of this test for differentiating normal aging from MCI have been described elsewhere (13). Cross validation has been confirmed using the Clinical Dementia Rating score as a reference. The overall accuracy in discriminating both amnestic and mixed cognitive domain types of MCI from normal aging is 97% (15). The Mini-Mental State Examination (MMSE), a global cognitive function test (16), was used to rule out apparent dementia in this study. Cognitive assessment were carried out baseline and at 24 weeks.

Statistical analysis

All continuous variables are expressed as mean ± SD, unless otherwise indicated. Comparisons between the two groups were assessed using the Student’s t test. The Wilcoxon signed-rank test was used to analyze differences in 10-word immediate recall test scores for each group at 24 weeks after the initial administration of the drinks compared with baseline. Correlations between variables were evaluated using Pearson’s correlation coefficient. We conducted simple regression and multiple regression analyses of variables that independently predict the percentage change in the 10-word immediate recall test scores in the whole study population, including those who consumed the test juice. In all comparisons, P < 0.05 was considered statistically significant. Analyses were performed using the SPSS software package for Windows version 17 (SPSS, Chicago, IL, USA). All participants were advised to follow their routine diets during the study.

 

Results

Eighty-four subjects were randomly assigned to receive either test juice (42 subjects) or placebo juice (42 subjects). Of the 84 subjects, 2 participants did not complete the study because they moved to a new residence during the study period. As a result, a total of 82 subjects were included in the final analysis. Their mean age was 71 years, and 27 (33%) were men (Table 1). Although there were no patients with dementia diagnosed by MMSE, 3 participants had been diagnosed with MCI by MCI screen (Table 1). There was no significant difference in education level between the two groups.

Table 1. Characteristics of participants

Table 1. Characteristics of participants

Values are expressed as mean ± standard deviation. BMI, body mass index; MCI, mild cognitive impairment; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyltransferase; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, serum triglyceride; sCr, serum creatinine; eGFR, creatinine-based estimated glomerular filtration rate.

 

Change in the 10-word immediate recall test scores

Changes in the 10-word immediate recall test scores are shown in Table 2. Participants in the test juice group had higher scores at week 24 compared to week 0, but this difference was not statistically significant. In contrast, the percentage change in the 10-word immediate recall test score was significantly higher in the test juice group compared to the placebo group (P < 0.05). There was a positive correlation between the percentage change in the 10-word immediate recall test score and baseline 10-word immediate recall test score in the whole population and in the test juice group (Table 3). Multiple regression analysis demonstrated a significant independent relationship between the percentage change in the 10-word immediate recall test score and test juice consumption including baseline 10-word immediate recall test score in all subjects (Table 3).

Table 2. Change in the 10-word immediate recall test score performed 3 times

Table 2. Change in the 10-word immediate recall test score performed 3 times

Values are expressed as mean ± standard deviation; MMSE, Mini-Mental State Examination; *Intergroup comparison (P < 0.05, vs. placebo).

 

Table 3. Simple regression and multiple regression analyses of variables that independently predict changes in the 10-word immediate recall test scores (/30)

Table 3. Simple regression and multiple regression analyses of variables that independently predict changes in the 10-word immediate recall test scores (/30)

*Adjusted for age and sex.

 

Biochemical evaluations

The results of the baseline and 24-week laboratory examinations are shown in Table 4. None of the biochemical parameters showed any significant variation during the study period. These findings demonstrate the safety of the test juice in humans.

 

Table 4. Blood test results of participants

Table 4. Blood test results of participants

Values are expressed as mean ± standard deviation; sCr, serum creatinine; BUN, blood urea nitrogen; eGFR, creatinine-based estimated glomerular filtration rate; LDL, low-density lipoprotein; HDL, high-density lipoprotein; TG, serum triglyceride; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyltransferase; hsCRP, high-sensitivity C-reactive protein.

 

Discussion

In this clinical study, we provided the first evidence that AUR-containing juice has a protective effect on cognitive decline in healthy human subjects. Our previous study showed that dried peel powder of Kawachibankan peels containe a high amount of naringin, middle amounts of narirutin besides AUR. Although the major compound in the dried peels of Kawachibankan peels was naringin, the results obtained in our study suggested that the major functional compound within the dried peels of Kawachibankan peels for causing the anti-inflammation effect in the model mice was AUR. The reasons for this conclusion are as follows: (1) an anti-inflammatory effect on the brain was also observed by the administration of authentic AUR given alone; (2) the administration of authentic naringin alone had not so much effect; (3) narirutin, being an isomer of naringin, would also likely have no anti-inflammatory property. For selection of the treatment arm dosage, we converted based on results of animal model (conversion index was 100.) (8).Clinical trials on cognitive decline
The lack of a current cure for dementia has led to an increasing interest in establishing strategies for the prevention of cognitive decline, which is a surrogate marker for dementia. Previous reports have shown that supplementation with omega-3 polyunsaturated fatty acids, which have anti-inflammatory effects, might protect against cognitive decline and Alzheimer’s disease (17-19). However, these findings were from cohort studies. Results from randomized controlled trials of up to 2 years’ duration are conflicting (20).
Although the etiology of dementia is assumed to be multi-factorial, many intervention studies target single factors that influence cognitive function. The results of several trials of multi-domain interventions (e.g., exercise, mental training and diet) have been positive (21). The results of our small clinical study suggest that AUR in the peels of citrus Kawachibankan protects against cognitive decline in healthy human subjects. However, we did not take lifestyle factors into account. AUR combined with lifestyle interventions might have a greater effect in preventing cognitive decline. A large cohort study is needed to investigate this further.
What is the mechanism by which AUR affects cognitive function?
AUR, a citrus coumarin, improved spatial learning and ameliorated cognitive impairment in a rat model of vascular dementia (9). The preventive mechanism of AUR is hypothesized to be related to its anti-inflammatory effects. We previously demonstrated that AUR exerts anti-inflammatory effects in the ischemic brain (22). Treatment of mice with AUR for eight days immediately after ischemia-inducing surgery suppressed neuronal cell death in the hippocampus, presumably through its anti-inflammatory effects in the brain. We showed that AUR passes through the blood–brain barrier and directly exerts anti-inflammatory effects in the brain (23). AUR suppressed microglial activation, COX-2 expression in astrocytes, and COX-2 mRNA expression in the hippocampus, and was still detectable in the brain 60 min after intraperitoneal administration. These results indicate that AUR directly exerts anti-inflammatory actions on the brain, which may underlie its beneficial effects on cognitive function.

 

Conclusion

The peels of Kawachibankan (citrus kawachiensis), a citrus product from Ehime Prefecture, Japan, contain abundant levels of AUR. The results of our study suggest that AUR may be beneficial as a neuroprotective agent for the treatment of neurological disorders in a clinical setting.

 

Conflict of interest: All participating authors declare no conflict of interest.

Ethical standards: The study was conducted after approval by the institutional review board for clinical trial services at Ehime University Graduate School of Medicine (Ehime, Japan) and was performed by the study investigators. Written informed consent was obtained from all participants before examination. The study was conducted in accordance with the ethical principles described in the current version of the Declaration of Helsinki.

 

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23.     Okuyama S, Morita M, Kaji M, Amakura Y, Yoshimura M, Shimamoto K, Ookido Y, Nakajima M, Furukawa Y.  Auraptene Acts as an Anti-Inflammatory Agent in the Mouse Brain. Molecules 2015;20: 20230-9.

CARE MANAGEMENT TO PROMOTE TREATMENT ADHERENCE IN PATIENTS WITH COGNITIVE IMPAIRMENT AND VASCULAR RISK FACTORS: A DEMONSTRATION PROJECT

 

L.M. Bonner1,2, A. Hanson3, G. Robinson4, E. Lowy1, S. Craft5

 

1. VA Puget Sound Healthcare System, Seattle, WA, USA;
2. University of Washington School of Medicine, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA; 3. University of Washington School of Medicine, Geriatric Medicine, Seattle, WA, USA; 4. Seattle University College of Nursing, Seattle, WA, USA; 5. Wake Forest University, Winston-Salem, North Carolina, USA

Corresponding Author: Laura Bonner, PhD, GRECC-S-182, VA Puget Sound Healthcare System, 1660 S. Columbian Way, Seattle, WA 98108, 206-550-1681, lmebonner@live.com

J Prev Alz Dis 2018;5(1):36-41
Published online July 11, 2017, http://dx.doi.org/10.14283/jpad.2017.28

 


Abstract

Dementia prevention is highly important. Improved control of vascular risk factors has the potential to decrease dementia risk, but may be difficult. Therefore, we developed and piloted a care management protocol for Veterans at risk for dementia. We enrolled 32 Veterans with diabetes and hypertension, at least one of which was poorly controlled, and cognitive impairment. Participants were randomly assigned to a 6-month care management intervention or to usual care. At enrollment, 6-months and 12-months, we assessed cognitive performance, mood, and diabetes and hypertension control. At follow-up, diastolic blood pressure was lower in intervention participants at 6 months (p=.041) and 12 months (p=.022); hemoglobin A1c, global mental status and mood did not differ between groups. Recall of a distractor list (p=.006) and logical memory long-delay recall (p=.036) were better at 6 months in the intervention group (p=.006). Care management may contribute to improved control of dementia risk factors.

Key words: Dementia, prevention, chronic disease, care management, treatment adherence, type 2 diabetes, hypertension.


 

 

Introduction

N eurodegenerative disorders, including Alzheimer’s disease and vascular dementia, cause significant disability among older adults, with negative effects on quality of life for patients and families, and financial costs to society. Unfortunately, limited treatment options exist once dementia has been diagnosed. Prevention of these disorders is therefore highly important. Recent research supports the role of vascular risk factors, including hypertension and diabetes, as potentially modifiable contributors to neurodegenerative disease (1).
Adherence to treatment regimens among patients with multiple chronic conditions is often suboptimal, and adherence may be even more difficult for patients with cognitive deficits (2). Therefore, patients with comorbid diabetes and hypertension who have cognitive deficits are at high risk of worsened control of their vascular risk factors and thus, worsened cognitive status. Such patients, while at high risk of dementia, may benefit significantly from improved control of chronic conditions.
Care management has been used to improve adherence among patients with various chronic conditions (hypertension, diabetes, depression, etc. (3)). Little is known, however, about how to adapt care management protocols to patients with cognitive deficits, despite the high prevalence of cognitive disorders in an aging patient population. Further, although care management is intended to prevent complications of chronic illness, its potential to prevent cognitive decline through improved control of risk factors has not been studied. Our goal in this demonstration project was to provide care management, specifically tailored to Veterans with existing cognitive impairment to improve disease control and prevent or slow further cognitive decline.

 

Methods

Recruitment

Veterans were eligible for recruitment if they were older than 54 years and had both diabetes and hypertension, with poor control of at least one disorder. Poor control was defined as systolic blood pressure > 140 mm Hg or hemoglobin A1c > 7.0 %. Eligibility for the study also required a cognitive deficit as determined by study neuropsychological assessment procedures or pre-existing memory disorder diagnosis (including Mild Cognitive Impairment (MCI), Alzheimer’s disease, vascular dementia, or Cognitive Disorder Not Otherwise Specified). Note that study enrollment was completed prior to revisions to the Diagnostic and Statistical Manual, 5th edition (4). Therefore, the terms “dementia” and “Mild Cognitive Impairment” are used throughout this report. Participants with dementia were eligible if their deficits were mild enough to allow comprehension of concerns raised by the care manager and ability to make and act on decisions about health-related behaviors such as exercise and medications. Participants with dementia were also required to have a caregiver who enrolled in the study. The optimal age of intervention for dementia prevention is still under investigation, but neurodegenerative changes are thought to begin in the brain a decade prior to cognitive symptoms (5). Individuals aged 54 years and older may already be experiencing the neurodegenerative changes in the brain that precede a diagnosis of dementia, but the neurodegenerative process may be still be amenable to intervention.

In-person assessment

Multiple recruitment strategies were employed in order to recruit from the broadest possible population of VA patients. Recruitment strategies included: in-clinic recruitment, mailed letters followed up by in-person or telephone screening, and referrals from VA clinicians.

In-person and mail recruitment

VA patient names were obtained from VA databases and screened for medical eligibility. Eligible Veterans were then recruited in-person from VA primary care clinics, or were recruited by mail. In the mail recruitment process, a letter describing the study was mailed to eligible patients and followed up with a phone call.
For both the mail and in-clinic recruitment processes, a two-step screening process was used to determine cognitive eligibility. Patients first completed a brief cognitive screening. Those whose screening results suggested cognitive impairment were then invited to participate in the study. These participants completed a one-hour cognitive screening including assessment of mental status, attention, verbal memory, visual memory, verbal fluency, functional abilities and mood.

Telephone-only assessment

Travel to the VA for screening and cognitive assessment was a barrier to participation for some Veterans. Therefore, we offered a telephone screening and assessment process for interested Veterans.

Referrals

Potential participants could also be referred by VA clinicians. Veterans referred from Memory Disorders Clinic had already completed a clinical memory assessment; memory test data from the clinical assessment were used in lieu of research screening to determine eligibility.

Instruments

In-person screening

The initial screening included brief instruments (Mini-Cog (6)) or Montreal Cognitive Assessment (MoCA; (7)). A score of 4 or 5 on the Mini-Cog was considered cognitively intact and therefore ineligible. A score of 3 was considered marginal; clinical judgment was required to determine eligibility. A score of After the initial screening, participants provided informed consent and completed a one-hour memory assessment. The memory assessment included the Modified Mini Mental Status Examination (3-MSE), Wechsler Memory Scale, 3rd Edition, Logical Memory subtest (8); the California Verbal Learning Test, 2nd Edition (9); category and phonemic fluency, and the Geriatric Depression Scale (10).

Telephone assessment

The telephone assessment used the Rivermead story (immediate recall) subtest (11), category fluency, Telephone Interview for Cognitive Status (12) and Center for Epidemiologic Studies Depression scale (13).

Randomization

Participants were assigned to intervention or usual-care group using a pseudo-randomization procedure (selecting among 3 sealed envelopes, 1 of which contained a usual-care assignment and 2 of which contained an intervention assignment).

Care management

Veterans randomized into the intervention group worked with the RN care manager to develop individualized plans to address barriers to treatment adherence. The intervention primarily used telephone contact in order to minimize travel for participants, although some participants chose to have in-person visits with the care manager. The intervention was adapted to each patient’s needs, but included education about disease management, discussion of barriers to adherence, and encouragement of patient engagement with other services such as social work, nutrition, and pharmacy. Spouses and other caregivers were encouraged to participate in conversations if permitted by the participant. The intervention continued for a 6-month period.

Data collection

Cognitive data

The one-hour memory assessment was repeated at 6 and at 12-months for participants who had completed this assessment at enrollment. Participants who had completed a telephone assessment at enrollment repeated the telephone assessment at 6 and 12 months.

Health status

Laboratory values and other health-related variables were abstracted from each Veteran’s electronic health record at baseline, 6-months and 12-months. Variables included: demographic information, systolic and diastolic blood pressure, weight, hemoglobin A1c, and lipids, diagnoses of sleep apnea, cognitive disorders, mental health conditions, hyperlipidemia and medications.

Data analysis

Analyses of the dependent measures were conducted using mixed effects linear regression, with treatment and follow-up interval as fixed effects, and participant as a random effect. Restricted maximum likelihood and the Kenward-Roger approximation for degrees of freedom were used to address the small sample size. Disparate sets of respondents among the dependent measures precluded multivariate analyses. Analyses were not adjusted for multiple comparisons. We believe that this approach is appropriate given the exploratory nature of this study.
Statistical analyses were conducted using Statistical Package for the Social Sciences (14) and Stata (15). All study procedures were approved by the VA Puget Sound Institutional Review Board.

 

Results

Screening/Enrollment

Overall, 136 veterans were assessed for eligibility for this study. Of those assessed, 87 were recruited as described in the methods and 49 were referred by Memory Disorders Clinic providers after being diagnosed with cognitive impairment. Of these 136 individuals, 58 did not meet inclusion criteria, 6 refused to participate, and 39 were excluded for other reasons. 33 veterans were randomized. One participant in the usual-care group was excluded after randomization due to determination of no cognitive impairment, leaving a combined total of 32 Veterans across all referral sources. Of enrolled participants, 5 were diagnosed with mild dementia, the remainder with mild cognitive deficits.

Demographics

The majority of participants were male. One-fourth were African-American. The mean GDS score was 16.9 + 6.68 for usual care and 13.2 + 8.64 for intervention participants; these scores are consistent with the presence of depression. Descriptive statistics are presented in Table 1. The intervention group had a higher score on logical memory, otherwise baseline demographics did not differ between groups.

Table 1. Baseline Demographics

Table 1. Baseline Demographics

1: MMSE: Mini Mental State Examination; 2: GDS: Geriatric Depression Scale; 3: CVLT: California Verbal Learning Test, 2nd Edition

 

In unadjusted analyses, diastolic blood pressure was lower in intervention than usual-care participants at 6 months (z=-2.17, p=.030) and at 12 months (z=-2.44, p=.015). Systolic blood pressure was lower in intervention participants at 12 months (z=-2.02, p=.043) but not at 6 months (z=-1.15, p=.252). Hemoglobin A1c (6-month: z=-.18, p=.856; 12-month: z=-.16, p=.876) did not differ between groups. Global cognitive status did not differ between groups. Immediate and delayed recall for a list of unrelated words did not differ between groups, except that recall of a distractor list was better at 6 months in the intervention group (z=3.14; p=.002). Logical memory long-delay recall was better at 6-months in intervention than usual-care participants (z=2.35, p=.019). Depression scores did not differ between groups. Results are presented in Table 2.

Table 2. This table shows the raw scores for each of the measures at 6 and 12 months by group

Table 2. This table shows the raw scores for each of the measures at 6 and 12 months by group

p values < 0.05 are starred; 1: MMSE: Mini Mental State Examination; 2: GDS: Geriatric Depression Scale; 3: CVLT: California Verbal Learning Test, 2nd Edition

 

Conclusions/Discussion

This study demonstrates the potential of care management approaches to engage patients with cognitive limitations, with the ultimate goal of dementia prevention. Care management was individually adapted to the specific needs of each participant (nutrition education, engagement of family caregivers, and so forth). Although global cognitive status did not differ between intervention and usual-care groups, recall of short stories and recall of a word list presented once were superior in the intervention group at 6-months. Diastolic blood pressure control was superior in the intervention group at 6-months and both systolic and diastolic blood pressure control were superior at 12-months. These results suggest that care management designed for Veterans with cognitive impairments and risk factors for dementia can positively affect both cognitive and vascular health related variables. Although blood pressure improvements were sustained at 12 months, cognitive improvements were not; these results suggest that follow-up care may be important to sustain cognitive benefits.
The presence of elevated GDS scores among our participants suggests that depression is a common co-morbid condition among veterans with cognitive impairment, diabetes and hypertension, and may be an important target for future intervention.
The high enrollment of African American Veterans is interesting, especially given historical challenges to research recruitment in this population. Further research is needed to understand how best to serve the needs of African American older adults with cognitive deficits and vascular risk factors.
To our knowledge, this is the first protocol developed to prevent dementia in patients with vascular risk factors who are beginning to experience mild cognitive symptoms. Given the prevalence and impact of dementia, further exploration of this promising avenue of prevention is warranted.

Limitations

This study was a pilot study with a small sample size. More research is needed to determine the optimal care management protocol for Veterans, and older adults in general, who have multiple vascular risk factors for dementia. This study was conducted among Veterans receiving care in VA; more research is needed to determine how to serve the needs of patients with cognitive impairments in other settings.
We did not conduct a formal measure of engagement in the intervention. Anecdotally, we found that engagement varied, with some participants seeking little contact with the care manager and others frequently calling the care manager and acting on recommendations. However, this pattern of variable engagement is likely to reflect actual implementation of care management in the clinical setting.
We did not examine changes in medications or other treatments during study participation. It is possible that medication changes were initiated by physicians due to clinical changes independent of study participation. Medication changes could also have been affected by study participation (for example, a patient might have been encouraged by the care manager to discuss side effects with his or her physician). This topic is complex and requires further study.
Due to the limited scope of this project, we abstracted laboratory data from the VA electronic medical record rather than obtaining direct measurements. Therefore laboratory values are not available for each participant at each time point.
Despite these limitations, this study demonstrates the potential benefits of care management for older adults with cognitive deficits and vascular risk factors, and suggests a useful avenue for further dementia prevention research. Specifically, this study demonstrates that improvement in important disease markers (systolic and diastolic blood pressure, logical memory and list-learning) may be achieved in the absence of improved global mental status, and suggests the importance of mood as a target of intervention for older adults with chronic illness and cognitive impairment.
Funding: This work was supported by the U.S. Department of Veterans Affairs, VISN 20, through a Memorandum of Understanding with the VISN 20 Geriatric Research, Education and Clinical Center (GRECC). The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

 

Acknowledgments: We are grateful for the participation of the VA Puget Sound Primary Care clinics and thank the clinic staff who supported participant recruitment. We appreciate the helpful contributions of Jutta Joseph, PharmD; William Banks, MD; Emily Trittschuh, PhD; Brenna Cholerton, PhD; and G. Stennis Watson, PhD. We are grateful to Soo Borson, MD, for allowing us to use the Mini-Cog as a screening instrument. Finally, we acknowledge the research participants without whom this work would not have been possible.

Prior Presentation: A preliminary version of this study was presented at the Alzheimer’s Association International Conference in Boston, 2013.

Conflict of Interest: There are no conflicts of interest for any of the authors.

Ethical standards: Participants provided written informed consent to participate in this study. This consent procedure and all study procedures were approved by the VA Puget Sound IRB.

 

References

1. Langa K, Larson EB, Crimmins EM et al. A comparison of the prevalence of dementia in the United States in 2000 and 2012. JAMA Internal Medicine. Published online November 21, 2016. doi:10.1001/jamainternmed.2016.6807
2. Harkness K, Heckman GA, Akhtar-Danesh N, Demers C, Gunn E, McKelvie RS. Cognitive function and self-care management in older patients with heart failure. Eur J Cardiovasc Nurs. 2014, Jun;13(3):277-84. doi: 10.1177/1474515113492603. Epub 2013 Jun 3.
3. Shaw RJ, McDuffie JR, Hendrix CC, Edie A, Lindsey-Davis L, Williams JW. 2013 Aug. Effects of Nurse-Managed Protocols in the Outpatient Management of Adults with Chronic Conditions [Internet]. Washington (DC): Department of Veterans Affairs; VA Evidence-based Synthesis Program Reports.
4. American Psychiatric Association 2013. Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). Washington, DC: Author.
5. Raskin J, Cummings J, Hardy J, Schuh K, Dean RA. Neurobiology of Alzheimer’s Disease: Integrated molecular, physiological, anatomical, biomarker, and cognitive dimensions. Curr Alzheimer Res. 2015;12(8):712-22.
6. Borson S. The mini-cog: a cognitive “vital signs” measure for dementia screening in multi-lingual elderly. Int J Geriatr Psychiatry; 2000;15(11):1021.
7. Nasreddine Z. 2003) The Montreal Cognitive Assessment. http://www.mocatest.org/ Accessed 9/16/14.
8. Wechsler, D. (1997) Wechsler Memory Scale, 3rd Edition. San Antonio, TX: PsychCorp.
9. Delis DC, Kramer JH, Kaplan E, Ober BA. 2000. California Verbal Learning Test, 2nd Edition. San Antonio, TX: Pearson, 2000.
10. Yesavage JA. 1988. Geriatric Depression Scale. Psychopharmacol Bull. 24(4):709-11.
11. Wilson BA, Greenfield E, Clare L, et al. Rivermead Behavioral Memory Test. Pearson, 2008.
12. Brandt J & Folstein M. Telephone Interview for Cognitive Status. Lutz, FL: Psychological Assessment Resources, 1988.
13. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychol Meas. 1977;3:385–401. doi: 10.1177/014662167700100306.
14. IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.
15. StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP

GLOBAL ALZHEIMER’S PLATFORM TRIAL READY COHORTS FOR THE PREVENTION OF ALZHEIMER’S DEMENTIA

 

R. Sperling1, J. Cummings2, M. Donohue3, P. Aisen3

 

1. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 2. Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; 3. Alzheimer’s Therapeutic Research Institute (ATRI), Keck School of Medicine, University of Southern California, San Diego, CA, USA

Corresponding Author: Reisa Sperling, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA, reisa@rics.bwh.harvard.edu
 
J Prev Alz Dis 2016;3(4):185-187
Published online August 16, 2016, http://dx.doi.org/10.14283/jpad.2016.108

 


 

Introduction

The recent launch of several Alzheimer’s disease (AD) clinical trials targeting the preclinical stage of the disease has highlighted the need for a paradigm shift in prevention trial recruitment. While there are multiple promising mechanisms to test, each new clinical trial can take up to 1-2 years to set up and likely 2-3 years to complete enrollment. Consequently, we are running out of time to outpace the public health epidemic precipitated by the aging of the world’s population. .
The concept of preclinical AD is based on the now widely-accepted observation that amyloid accumulates in the brain for many years prior to the development of symptoms (1, 2).  In 2011, an international working group convened by the National Institute on Aging and the Alzheimer’s Association proposed a conceptual framework and operational research criteria for defining preclinical AD based on presence of amyloidosis, with or without neurodegeneration and subtle cognitive decline (3). In this framework, amyloidosis could be assessed using positron emission tomography (PET) imaging or cerebrospinal fluid (CSF) analysis (low CSF Aβ1-42).  A similar framework, but with a somewhat different lexicon was proposed by the International Working Group for New Research Criteria for the Diagnosis of AD, which has a similar concept of “preclinical AD,” but defines presymptomatic as individuals with autosomal dominant genetic risk, and refers to biomarker-positive individuals as “at-risk” (4).  
Since these criteria were first introduced, the concept of preclinical AD has evolved as increasing evidence has supported the hypothetical temporal evolution of AD biomarkers and clinical symptoms (5). Studies in populations with autosomal dominant forms of AD (ADAD), in particular, have suggested that disease markers can be detected in a predictable order prior to the expected onset of symptoms: changes in the CSF levels of amyloid 25 years before expected onset; amyloid deposition assessed using PET imaging 15 years before expected onset, and impaired episodic memory 10 years before expected onset (6).

 

The challenge of identifying and recruiting participants for secondary prevention trials

This evolving understanding of the earliest stages in the AD continuum have spawned secondary prevention trials in both genetic-at-risk and amyloid-at-risk cohorts, defined by an absence of clinically detectable impairment but the presence of either 1) a deterministic genetic mutation that confers near certainty of developing AD, or 2) biomarker evidence that amyloid has begun to accumulate in the brain. Identifying individuals who fit into these two categories has thus become a major challenge for those planning such trials.    
The Global Alzheimer’s Platform (GAP) was established in 2013 as a collaboration of the Global CEO initiative on Alzheimer’s disease (CEOi) and the New York Academy of Sciences (NYAS). In parallel with initiatives in Europe, Canada, and Japan, GAP aims to coalesce the special expertise and infrastructure needed to accelerate clinical trials across all stages of AD, including preclinical stages. GAP comprises several components, including GAP-NET to support site infrastructure with pre-certifications, master contracts, and a centralized IRB (7); and GAP Trial Ready Cohorts for Preclinical and Prodromal Alzheimer’s Dementia (GAP TRC-PAD).
The goal of GAP TRC-PAD is to build an efficient and sustainable recruitment system for upcoming secondary prevention trials (Figure 1). Drawing from existing registries and studies, including the Brain Health Registry (BHR), Alzheimer’s Prevention Registry (APR), the Cleveland Clinic’s Healthybrains.org (8), and the Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study, non-demented individuals over the age of 60 who are interested in participating in clinical trials will be invited to join the GAP Registry. Those who sign an electronic informed consent, will be asked to submit data on demographics, family, medical, and lifestyle history, and cognitive function.   

 

Figure 1. Structure of GAP TRC-PAD

 

GAP TRC-PAD set as its initial goal to identify a large number of potential participants, rapidly screen these individuals using an adaptive risk algorithm, and ultimately identify 1000 preclinical and 1000 prodromal participants as a “Trial Ready Cohort” for the first GAP clinical trials.  In addition, GAP seeks to develop and validate web-based cognitive and functional assessments for use in future trials.

 

Predicting amyloid status

Amyloid status can be determined by CSF studies or PET imaging, and in cognitively healthy controls, low baseline CSF Aβ1-42 was shown to be associated with future Aβ positivity (9). However, screening large numbers of people with these tests would be prohibitively expensive and not feasible from a pragmatic point of view. Thus, investigators have identified other inexpensive and non-invasive measures that are predictive of amyloid status. For example, in a population-based study of cognitive normal elderly, age and APOE genotype were shown to be predictive of amyloid accumulation (10); and in a study of clinically normal older individuals, subjective cognitive concerns (SCC) were shown to be predictive of Aβ positivity (11). APOEε4 genotype has also been linked to high amyloid burden in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Among cognitively healthy individuals, APOEε4 carriers were more than twice as likely to have positive amyloid PET scans compared to non-carriers (12). More recently, results from the AIBL study showed that high amyloid burden was associated with older age, subjective memory complaints, and APOEε4 genotype (13).  Another novel “measure” that may be predictive of amyloid positivity is lack of practice effects on cognitive testing. In a preliminary study, higher uptake of 18F-flutemetamol on PET imaging was five times higher in individuals with low practice effects on a delayed recall memory task compared to those with high practice effects (14).   
Data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) also showed that among cognitively normal older adults with significant memory concern, elevated amyloid deposition and abnormal CSF biomarker were strongly associated with APOEε4 carrier status (15). Aβ-positive participants in ADNI and AIBL also show more decline in cognition compared to Aβ-negative participants as measured by the ADCS Preclinical Alzheimer’s Cognitive Composite (ADCS-PACC), especially among APOEε4 carriers (16).  
Working with ADNI data, investigators at the University of Southern California’s Alzheimer’s Therapeutic Research Institute (ATRI) developed an adaptive algorithm to predict amyloid status based on APOE carriage status, baseline scores on the ADCS-PACC, age, and family history.  Preliminary results suggest that this algorithm, applied to populations of cognitively normal (pre-clinical) and non-demented but cognitively impaired (prodromal) potential clinical trial participants, will enable identification of those likely to be amyloid positive. Amyloid testing on only these pre-selected groups should then reduce the number of screen fails, expedite the enrollment process, and reduce the overall costs of a study. A larger study is planned in 2016 to confirm these findings.   
As more is learned about algorithmic function, it will be possible to adjust algorithms to yield specific populations of interest.  For example, APOE 4 carriage may be highly influential in current amyloid lowering strategies but some drugs may have genotype-specific effects or side effects and recruitment of both e4 carriers and non-carriers may be important.  Algorithm adjustment will be necessary to achieve this.  Other biomarkers might also play a greater role in algorithms that currently conceptualized, including Tau PET imaging which may be more useful in staging individuals along the preclinical/prodromal progression.  
Some interventions might be most effective prior to substantial tangle accumulation or cerebral atrophy, suggestive of neuronal loss, has begun whereas other interventions might have a greater effect after the onset of atrophy when inflammation and tau-related cell death may have a greater role.  Integrating Tau PET and magnetic resonance imaging (MRI) into the algorithm might assist in identifying varying pathologies in early populations that can be paired with different mechanisms of action of test therapies.
 A greater range of data — from sleep measured to “low friction” assessments such as amount of cell phone use, to higher friction measures such as success in on-line games — might be integrated into future algorithms to identify patients in early phases of disease or to more fully characterize the range of abnormalities exhibited by minimally cognitively affected individuals.  

 

Conclusions

Registries that capture large numbers of cognitively normal potential clinical trial participants will be essential to enable testing of interventions designed for secondary prevention. Equally important will be a means for quickly and accurately identifying individuals within the registry who meet the requirements of a particular study. The GAP Registry and GAP TRC-PAD are designed specifically to meet these needs, and in combination with the infrastructure developed by GAP-NET, should provide the integrated platform necessary for efficient clinical trials not only in the pre-dementia space, but across all disease stages.
The Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) Study is the first prevention trial targeting individuals at risk for AD based on evidence of brain amyloid accumulation (17). Using the adaptive algorithm developed as described in this paper, we anticipate being able to select from an initial registry of approximately 50,000 individuals, bringing in a subset for further screening with PET or other measures, ultimately yielding a trial ready cohort of 1000 preclinical and 1000 prodromal patients, thus reducing the time required to fully enroll participants for the first GAP trials. While the A4 Study is designed with the goal of showing efficacy of an anti-amyloid agent to prevent the cognitive decline due to AD, equally important will be the additional information we will acquire to inform future prevention trials regarding expediting enrollment and developing more sensitive endpoints, creating population-appropriate outcome measures, and novel biomarkers, including theragnostic markers to track therapeutic responses.  

 

Disclosures: Reisa Sperling has served as a consultant for Abbvie, Biogen, Bracket, Genentech, Lundbeck, Roche, and Sanofi. She has served as a co-investigator for Avid, Eli Lilly, and Janssen Alzheimer Immunotherapy clinical trials. She has spoken at symposia sponsored by Eli Lilly, Biogen, and Janssen. R. Sperling receives research support from Janssen Pharmaceuticals, and Eli Lilly and Co.. She also receives research support from the following grants: P01 AG036694, U01 AG032438, U01 AG024904, R01 AG037497, R01 AG034556, K24 AG035007, P50 AG005134, U19 AG010483, R01 AG027435, Fidelity Biosciences, Harvard NeuroDiscovery Center, and the Alzheimer’s Association. Paul Aisen has served as a consultant to the following companies:  NeuroPhage, Elan, Eisai, Bristol-Myers Squibb, Eli Lilly, Merck, Roche, Amgen, Genentech, Abbott, Pfizer, Novartis, AstraZeneca, Janssen, Medivation, Ichor, Lundbeck, Biogen, iPerian, Probiodrug, Anavex, Abbvie, Janssen, Cohbar.  Dr. Aisen receives research support from Eli Lilly, the Alzheimer’s Association and the NIH [NIA U01-AG10483 (PI), NIA U01-AG024904 (Coordinating Center Director), NIA R01-AG030048 (PI), and R01-AG16381 (Co-I)]. Jeffrey Cummings has received in kind research support from Avid Radiopharmaceuticals and Teva Pharmaceuticals. He has provided consultation to AbbVie, Acadia, ADAMAS, Alzheon, Anavex, AstraZeneca, Avanir, Biogen-Idec, Biotie, Boehinger-Ingelheim, Chase, Eisai, Forum, Genentech, Intracellular Therapies, Lilly, Lundbeck, Merck, Neurotrope, Novartis, Nutricia, Otsuka, Pfizer, Prana, QR Pharma, Resverlogix, Roche, Suven, Takeda, and Toyoma companies. He has provided consultation to GE Healthcare and MedAvante and owns stock in ADAMAS, Prana, Sonexa, MedAvante, Neurotrax, and Neurokos. Dr. Cummings owns the copyright of the Neuropsychiatric Inventory.

Acknowledgments: The authors wish to acknowledge the invaluable contributions of colleagues at the Harvard Aging Brain Study at Massachusetts General Hospital, the Center for Alzheimer Research and Treatment at the Brigham and Women’s Hospital, the Cleveland Clinic Low Ruvo Center for Brain Health, and the Alzheimer Therapeutic Research Institute at University of Southern California Keck School of Medicine. The authors also wish to thank Lisa Bain for assistance with the manuscript preparation.

Conflict of interest: None.

 

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2.    Morris JC, Price JL. Pathologic correlates of nondemented aging, mild cognitive impairment, and early-stage Alzheimer’s disease. Journal of molecular neuroscience : MN. 2001;17(2):101-18.
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