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THE JAPAN-MULTIMODAL INTERVENTION TRIAL FOR PREVENTION OF DEMENTIA (J-MINT): THE STUDY PROTOCOL FOR AN 18-MONTH, MULTICENTER, RANDOMIZED, CONTROLLED TRIAL

 

T. Sugimoto1,2, T. Sakurai1,3, H. Akatsu4, T. Doi5, Y. Fujiwara6, A. Hirakawa7, F. Kinoshita8, M. Kuzuya9, S. Lee5, K. Matsuo10, M. Michikawa11, S. Ogawa6, R. Otsuka12, K. Sato13, H. Shimada14, H. Suzuki15, H. Suzuki6, H. Takechi16, S. Takeda17, H. Umegaki9, S. Wakayama18, H. Arai19, On behalf of the J-MINT investigators

 

1. Center for Comprehensive Care and Research on Memory Disorders, National Center for Geriatrics and Gerontology, Obu, Japan; 2. Medical Genome Center, National Center for Geriatrics and Gerontology, Obu, Japan; 3. Department of Cognition and Behavior Science, Nagoya University Graduate School of Medicine, Nagoya, Japan; 4. Department of Community-based Medical Education, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan; 5. Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Obu, Japan; 6. Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan; 7. Department of Clinical Biostatistics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan; 8. Department of Advanced Medicine, Nagoya University Hospital, Nagoya, Japan; 9. Department of Community Healthcare and Geriatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan; 10. Department of Dentistry and Oral-Maxillofacial Surgery, School of Medicine, Fujita Health University, Toyoake, Japan; 11. Department of Biochemistry, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan; 12. Section of the National Institute for Longevity Sciences‒Longitudinal Study of Aging, National Center for Geriatrics and Gerontology, Obu, Japan; 13. Department of Rehabilitation Medicine, National Center for Geriatrics and Gerontology, Obu, Japan; 14. Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Obu, Japan; 15. Sompo Care Inc., Tokyo, Japan; 16. Department of Geriatrics and Cognitive Disorders, School of Medicine, Fujita Health University, Toyoake, Japan; 17. Department of Clinical Psychology, Tottori University Graduate School of Medical Sciences, Yonago, Japan; 18. Sompo Holdings, Inc., Tokyo, Japan; 19. National Center for Geriatrics and Gerontology, Obu, Japan.

Corresponding Author: Takashi Sakurai, 7-430 Morioka, Obu, Aichi, 474-8511, Japan, Tel: +81-562-46-2311, E-mail: tsakurai@ncgg.go.jp

J Prev Alz Dis 2021;
Published online June 9, 2021, http://dx.doi.org/10.14283/jpad.2021.29

 


Abstract

Background/Objectives: The Japan-multimodal intervention trial for prevention of dementia (J-MINT) is intended to verify the effectiveness of multi-domain interventions and to clarify the mechanism of cognitive improvement and deterioration by carrying out assessment of dementia-related biomarkers, omics analysis and brain imaging analysis among older adults at high risk of dementia. Moreover, the J-MINT trial collaborates with partnering private enterprises in the implementation of relevant interventional measures. This manuscript describes the study protocol.
Design/Setting: Eighteen-month, multi-centered, randomized controlled trial.
Participants: We plan to recruit 500 older adults aged 65-85 years with mild cognitive impairment. Subjects will be centrally randomized into intervention and control groups at a 1:1 allocation ratio using the dynamic allocation method with all subjects stratified by age, sex, and cognition.
Intervention: The multi-domain intervention program includes: (1) management of vascular risk factors; (2) group-based physical exercise and self-monitoring of physical activity; (3) nutritional counseling; and (4) cognitive training. Health-related information will be provided to the control group every two months.
Measurements: The primary and secondary outcomes will be assessed at baseline, 6-, 12-, and 18-month follow-up. The primary outcome is the change from baseline to 18 months in a global composite score combining several neuropsychological domains. Secondary outcomes include: cognitive change in each neuropsychological test, incident dementia, changes in blood and dementia-related biomarkers, changes in geriatric assessment including activities of daily living, frailty status and neuroimaging, and number of medications taken.
Conclusions: This trial that enlist the support of private enterprises will lead to the creation of new services for dementia prevention as well as to verify the effectiveness of multi-domain interventions for dementia prevention.

Key words: Cognitive decline, multidomain intervention, physical exercise, nutrition, cognitive training.


 

Introduction

The number of people living with dementia is estimated at 46.8 million in 2015 worldwide, and is expected to increase to 131.5 million by 2050 (1). In recent years, several studies have reported a decreasing incidence of dementia in Western countries (2-4), which, however, is not the case in Japan (5). Given the high drug development failure rate in Alzheimer’s disease (AD) (6), especially for disease-modifying therapies, developing successful non-pharmacological strategies to prevent dementia is an urgent priority.
To date, several large multi-domain prevention trials have shown that interventions targeting multiple modifiable risk factors for dementia simultaneously in older adults, especially in those at increased risk of dementia, could slow cognitive decline and reduce incident dementia (7-9). The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) is the first large randomized controlled trial (RCT) which demonstrated that a multi-domain lifestyle intervention (dietary counseling, physical exercise, cognitive training, and vascular and metabolic risk monitoring) could ameliorate cognitive decline in older adults at increased risk of developing dementia, though the effect size (difference between control and intervention groups) was very small (Cohen’s d = 0.13) (7). Sub-group analyses of the other two RCTs, the Prevention of Dementia by Intensive Vascular Care (PreDIVA) (8) and the Multidomain Alzheimer Preventive Trial (MAPT) (9) also showed the effectiveness of multi-domain intervention in older adults at increased risk of dementia, although the primary outcomes were not statistically significant. These studies provide important methodological lessons: selection of at-risk individuals; appropriate timing and intensity of the interventions implemented; and selection of appropriate sensitive tools to detect changes in cognition (10, 11). However, further studies are still needed to verify the superior effectiveness of multi-domain interventions in different settings and populations (10, 11). In addition, the mechanism of effectiveness of such interventions should be further explored. In this context, the World-Wide FINGERS (WW-FINGERS) Network was launched at the 2017 Alzheimer’s Association International Conference (AAIC) in London (12). This network aims to test, adapt, and optimize the FINGER multi-domain lifestyle model for use in various populations and settings. Furthermore, data sharing is an important mission of this network, with about 30 countries around the world participating in the network (12).
In Japan, the Japan-Multimodal Intervention Trial for Prevention of Dementia (J-MINT) was started in 2019 and included in the WW-FINGERS Network (12). The aim of the J-MINT trial is to verify whether multi-domain intervention, which consists of management of vascular risk factors, group-based physical exercise and self-monitoring of physical activity, nutritional counseling, and cognitive training, could prevent the progression of cognitive decline among older adults with mild cognitive impairment. Specifically, assessment of blood-based biomarkers, omics analysis and neuroimaging make up the core of the J-MINT trial toward elucidation of the mechanism of cognitive improvement and deterioration. Additionally, the J-MINT trial collaborates with partnering private enterprises in the implementation of relevant interventional measures. This manuscript describes the study protocol for the J-MINT trial developed in accordance with the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 statement (see Appendix 1).

 

Methods

Study design

The J-MINT trial is designed as an 18-month, open-labeled, randomized, controlled, multicenter trial of multidomain interventions designed to target modifiable risk factors for dementia among older adults with mild cognitive impairment. Being organized by a central coordinating center at the National Center for Geriatrics and Gerontology (NCGG), this study involves the following 4 other centers located in Japan: Nagoya University; Nagoya City University, Fujita Health University, and Tokyo Metropolitan Institute of Gerontology. A total of 500 subjects being recruited at these centers will be randomized into intervention or control groups during the course of the trial. Multi-domain interventions provided by partnering private enterprises will cover the following 4 domains: management of vascular risk factors (diabetes, hypertension, and dyslipidemia), group-based physical exercise and increasing physical activity, nutritional counselling, and cognitive training using Brain HQ (Posit Science Corporation). The control group will be given instructions on the management of vascular risk factors and health-related information in writing. The primary and secondary outcomes will be assessed in both groups at baseline, 6, 12, and 18 months. The study flow diagram is shown in Figure 1.

Figure 1. Study flow of the Japan-multidomain intervention trial for prevention of dementia (J-MINT)

 

Ethic committee review and approval

All study procedures have been reviewed and approved by the Institutional Review Boards (IRBs) at each study site and the trial has been registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) as number UMIN000038671. The purpose, nature, and potential risks of participation in the trial will be fully explained to the participants, and all participants will provide written informed consent before participating in the trial.

Eligibility criteria (Inclusion/exclusion criteria)

Table 1 shows the inclusion and exclusion criteria of the J-MINT trial. In order to focus on those at increased risk of dementia, the target population for the trial was defined as older adults with mild cognitive impairment. All prospective participants will be evaluated for the presence of mild cognitive impairment by using the National Center for Geriatrics and Gerontology Functional Assessment Tool (NCGG-FAT) which has been established as a screening tool for older adults at high risk of incident dementia (13, 14). Participants are to be deemed eligible for entry in the J-MINT trial (1) if they are 65-85 years old at the time of enrollment; (2) if they have age- and education-adjusted cognitive decline with a standard deviation (SD) of 1.0 or more from the reference threshold for one or more of the four cognitive domains of memory, attention, executive function, and processing speed, as measured with the NCGG-FAT; and (3) if they are able to provide written informed consent for themselves (Table 1).
Participants are to be excluded: (1) if they need to restrict any physical exercise and/or diet due to functional decline, including severe bone or joint disease, renal failure, and unstable ischemic heart disease and cardiopulmonary disorders; (2) if they were diagnosed with dementia; (3) if they have a Mini-Mental State Examination (MMSE) score of less than 24 (15); (4) if they have a care certificate for long-term care facilities; (5) if they are unable to speak Japanese; (6) if they are unable to undergo cognitive tests; (7) if they are deemed ineligible for enrollment by the responsible investigator or co-investigator at each study site (Table 1).

Table 1. Inclusion and exclusion criteria for J-MINT study.

Note. Abbreviations: J-MINT, Japan-multimodal intervention trial for prevention of dementia; MMSE, Mini-mental state examination; NCGG-FAT, National Center for Geriatrics and Gerontology-Functional Assessment Tool; SD, standard deviation.

 

Enrollment and assessment procedures

Recruitment

The NCGG and 4 other centers are to recruit participants from their hospital and/or community-based cohorts. In some cohorts, the cognitive test results to be obtained at the time of participation are to be used to select participants who are likely to meet the selection criteria, and an invitation is to be directly sent by mail to those who have met the criteria. In addition, prospective participants, i.e., patients as well as community residents, are to be informed of the call for recruitment in this study through posters, newspaper advertisements, and public relations papers. Research staff is to fully explain the purpose, nature, and potential risks of participation in this trial for prospective participants before trial participation. Then, participants who provided written informed consent are to be assessed for their cognitive function (the NCGG-FAT (13, 14), and the MMSE (15)). Participants are to be evaluated for final eligibility by the research staff and clinicians according to the trial’s inclusion and exclusion criteria. Participant recruitment was started in November, 2019 and completed in December, 2020.

Assessment

Figure 2 shows the timeline in the J-MINT trial for assessments scheduled according to the SPIRIT guidelines. All participants are to complete neuropsychological tests at baseline, as well as at 6-, 12-, and 18-month follow-up and to undergo comprehensive geriatric assessments (CGA) at baseline, as well as 6- and 18-month follow-up. Additionally, the participants are to undergo blood tests, dementia-related biomarker tests, and brain magnetic resonance imaging (MRI) or computed tomography (CT) evaluations at baseline and at 18-month follow-up. The participants are to be evaluated for adherence to and satisfaction with the intervention protocol, and all adverse events experienced by the participants are to be recorded during the trial.

Figure 2. Timeline for scheduled assessments of the J-MINT trial

*: Non-mandatory; †: Dementia-related biomarker testing and whole genome sequencing are to be conducted only for subjects recruited at the National Center for Geriatrics and Gerontology. Abbreviations: CT, computed tomography; J-MINT, Japan-multidomain intervention trial for prevention of dementia; MRI, magnetic resonance imaging; NfL, neurofilament light chain; SPECT, single photon emission computed tomography.

 

Primary outcome measure: cognitive change at 18-month follow-up (composite score)

The primary outcome measure is the change from baseline at 18 months in a global composite score using several neuropsychological tests, which include tests of global cognitive function (MMSE (15)); memory (Logical memory Ⅰ and Ⅱ subset of the Wechsler Memory Scale-Revised (WMS-R) (16) and the Free and Cued Selective Reminding Test (FCSRT) (17)); attention (Digit Span of the Wechsler Adult Intelligence Scale (WAIS)-III (18)); executive function/processing speed (Trail Making Test (TMT) (19), Digit Symbol Substitution Test (DSST) subset of the WAIS-III (18), Letter word fluency test (19)).
Neuropsychological tests are to be performed at each site by trained and board-certificated psychologists, occupational therapists, and/or speech therapists, who were trained in the implementation and scoring of neuropsychological tests through participation in a training session held at the NCGG. Moreover, the Logical memory Ⅰ and Ⅱ subset of the WMS-R is to be scored by two psychologists from the NCGG to minimize variability in scoring. Then, the composite score is to be generated by averaging the Z scores of each neuropsychological test standardized by the baseline mean and standard deviation (SD) for each test from the full-analysis set population. A Z score of –1, for example, represents a score 1 SD below the baseline mean. A 1-point decrease on the composite score indicates an average decline of 1 SD across the neuropsychological tests.

Secondary outcome measures

Secondary outcome measures of cognitive changes are: change from the baseline to 6 and 12 months in global composite score; change from baseline in score of each neuropsychological test at 6-/12-/18-month follow-up; and incident dementia. At follow-up conducted every 6 months, participants are to be advised to receive primary health care or present to a memory clinic for further evaluation (e.g., neuropsychological tests, blood tests, brain MRI, CT, or single photon emission computed tomography (SPECT)) (1) if they have complaints about cognitive decline; (2) if they have a MMSE score of less than 24 or (3) if they have a decline in MMSE score of 3 points or more from the baseline. They are to be confirmed to have incident dementia, by consensus of two or more physicians, according to the criteria of the National Institute on Aging-Alzheimer’s Association (NIA/AA) workgroups (20), with the diagnosis of incident dementia confirmed, as required, in consultation with the Endpoint (incident dementia) Committee of the J-MINT trial (see Appendix 2).
Other secondary outcome measures are changes in each component of CGA including activities of daily living (ADL) and frailty status, blood markers, dementia-related blood biomarkers, neuroimaging assessed using MRI or CT, and number of medications taken.

a) Comprehensive geriatric assessment

CGA includes the following self-administered questionnaires and physical and cognitive performance:
– ADL: Participants are to be assessed for basic and instrumental ADL. Basic ADL is to be assessed using the Barthel index (21), which assesses basic self-care abilities, such as feeding, transferring from a bed to a chair, bathing, bowel control, and bladder control, with the score ranging from 0 (complete dependence) to 100 (complete independence). Instrumental ADL is to be assessed using the Lawton index (22), which includes 8 items, such as using the telephone, shopping, and handling medications, with the score ranging from 0 (low function) to 8 (high function).
– Frailty status: Participants are to be assessed for physical frailty status based on the frailty phenotype proposed by Fried et al. in the Cardiovascular Health Study (23). The components of the frailty phenotype include shrinking, weakness, slowness, self-reported exhaustion, and low physical activity. Participants are to be assessed for social frailty status based on the following 5 items: living alone, going out less frequently than last year, not visiting friends often, not feeling like helping friends or family, and not talking with anybody every day (24). Participants are also to be assessed for oral frailty status by using the Oral Frailty Index-8 (25), which includes 8 items: subjective difficulties in eating hard food, choking on tea or soup, using denture, caring for dry mouth, going out, chewing hard food such as pickled radish or shredded and dried squid, brushing teeth at least twice a day, and regularly visiting a dental clinic.
– Dietary diversity: The 11-item Food Diversity Score Kyoto (26) has been modified to assess each participant’s dietary diversity by asking about frequency in consumption of 14 foods for the past week (i.e., cereals, fish and shellfish, meat, eggs, milk, dairy products, beans, seaweed, potatoes, fruit, nuts, and oils and fat).
– Nutritional status: Participants are to be assessed for nutritional status using the Mini-Nutritional Assessment Short-Form (MNA-SF) (27) composed of 6 questions, whose score ranges from 0 to 14, with a higher score indicating better nutritional status.
– Appetite: Participants are to be assessed for their appetite using the Council on Nutritional Appetite Questionnaire (28). The total score ranges from 8 to 40, with a higher score indicating a better appetite.
– Depressive symptoms: Participants are to be assessed for depressive symptoms using self-rated 15-item Geriatric Depression Scale (29). This scale ranges from 0 to 15, with a higher score indicating a higher level of depressive symptoms.
– History of falls and fall risk: Participants are to be evaluated for history of falls within the past 12 months and fall risk, with the latter assessed using the Fall Risk Index (30) composed of 21 questions to detect the risk of falls, including the following 3 subcategories: physical function (8 items), geriatric syndrome (8 items) and environmental hazards (5 items). Each item receives a score of 1 (risk present) or 0 (risk absent), with a higher sum for each category indicating a higher risk of falls.
– Social network: Participants are to be assessed for social network using the Lubben Social Network Scale 6 (31), which is composed of 6 questions. The score ranges from 0 to 30, with a higher score indicating better social network.
– Health-related quality of life: Participants are to be assessed for health-related quality of life using a health index of the EQ-5D (32) consisting of 5 dimensions (mobility, self-care, pain/discomfort, usual activities, and anxiety/depression). The scores for these five dimensions are combined to obtain up to 3,125 possible health states, from which a single index (utility) score is computed.
– Sleep quality: Participants are to be assessed for their sleep quality using the Pittsburgh Sleep Quality Index (PSQI) (33), which is intended to assess subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. This index score ranges from 0 to 21 and higher score indicates poor sleep quality.
– Social participation: Participants are to be assessed for social participation using the questionnaire about social engagement in eight types of groups (34): (1) neighborhood associations/senior citizen clubs/fire-fighting teams (Local Community); (2) hobby groups (Hobby); (3) sports groups or clubs (Sports); (4) political organizations or groups (Politics); (5) industrial or trade associations (Industry); (6) religious organizations or groups (Religion); (7) volunteer groups (Volunteer); and (8) Others.
– Handicap from hearing loss: Participants are to be assessed for handicap from hearing loss using Hearing Handicap Inventory for the Elderly (HHIE) (35), which consists of 25 questions, with 13 questions of these evaluating emotional aspects of hearing-related QOL, and the remaining 12 evaluating social haring-related QOL among older adults. The total score ranges from 0 to 100, and a higher total score indicates a more severe subjective hearing-related handicap.
– Anthropometric measurements: Participants are to undergo anthropometric measurements including height, body weight, and calf circumference, with body mass index calculated as body weight in kilograms divided by height in square meters (kg/m2). In addition, optionally, participants are to be evaluated for presence or absence of sarcopenia (36) with appendicular muscle mass (AMM) measured by bioelectrical impedance analysis (BIA), and skeletal muscle mass index calculated as AMM divided by height in square meters (kg/m2).
– Physical performance: Participants are to be evaluated for usual gait speed over a distance of 2.4 m at the middle of the walkway that has both acceleration and deceleration zones each 1 m long, with the gait speed measured twice and the mean value calculated (37). Hand grip strength of both right and left hand are to be measured in the participants using a standard digital hand grip dynamometer (Takei Scientific Instruments Co., Ltd, Japan) in standing position with the shoulder adducted and neutrally rotated and the elbow fully extended (38). Participants are to be assessed for lower extremity muscular strength by the Five-Times-Sit-to-Stand test (39), which measures the time (seconds) required to perform five successive chair stands as quickly as possible from the initial seated position with their arms crossed on their chest and sitting with their back against a chair.
– Visual function and vision-related QOL (optional): Participants are to be assessed for visual acuity (naked- and best corrected-visual acuity), visual refraction, and intra-ocular pressure. Slit lump examination and fundus examination are to be performed. The retinal and peripapillary nerve fiber layer thickness is to be measured by the optical coherence tomography (Model RS-3000, Nidek, Japan) without pupil dilatation. Additionally, the 25-Item National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25) (40) is to be used to assess their vision-specific health related QOL.
– Cognitive function (optional): Participants are to be assessed for cognitive function by CogEvo (Total Brain Care, Kobe, Japan) (41) and Japanese version of the Montreal Cognitive Assessment (MoCA-J) (42). CogEvo is a computer-aided cognitive function test battery, which allows for evaluation fo cognitive function including orientation, attention, memory, executive function and spatial cognition. MoCA-J is a brief cognitive screening tool for detecting older adults with mild cognitive impairment by assessing nine domains of cognition including attention, concentration, executive functions, memory, language, visuoconstructional skills, conceptual thinking, calculation, and orientation.

b) Blood and urinary tests

Blood markers assessed in all participants at baseline and 18-month follow-up are to include glucose, insulin, hemoglobin A1c, glycoalbumin, total protein, albumin (Alb), aspartate aminotransferase, alanine aminotransferase, γ-glutamyl transpeptidase, total cholesterol, high density lipoprotein-cholesterol, triglyceride, creatinine (Cr), estimated glomerular filtration rate, blood urea nitrogen, sodium, potassium, chloride, calcium, phosphorus, free triiodothyronine, free thyroxine, thyroid stimulating hormone, rapid plasma reagin, treponema pallidum hemagglutination, vitamin B1, vitamin B12, folate, and C-reactive protein. In addition, all participants will be assessed at baseline for their apolipoprotein E (APOE) phenotype.
Optionally, the following are to be measured: brain natriuretic peptide, interleukin-6, 25-hydroxyvitamin D, ghrelin, glucagon-like peptide-1, blood ketone bodies, carnitine, total bile acid, osmotic pressure, catecholamines, fatty acids, leptin, creatine, creatine kinase, nicotinamide phosphoribosyltransferase, and microRNAs. Urine glucose, urine protein, occult blood, urine Alb/Cr (u-Alb/Cr), and 8-Hydroxy-deoxyguanosine are also to be assessed optionally.

c) Blood-based dementia-related biomarkers

Participants recruited from the NCGG are to be assessed for dementia-related biomarkers. To assess amyloid-β (Aβ) deposition in the brain, which is the earliest pathological signature of AD, ratios of plasma Aβ-related peptides, APP669-711/Aβ1-42 and Aβ1-40/Aβ1-42, and their composites are to be measured using the immunoprecipitation-mass spectrometry assay (43). In addition, plasma concentrations of tau phosphorylated at threonine 181 (p-tau181) and neurofilament light chain (NfL) are to be assessed using the single-molecule array (SimoaTM) platform (44, 45).

d) Whole genome sequencing

Whole genome sequencing is to be applied to blood samples from participants recruited from the NCGG, which is being used to conduct a comprehensive search for mutations within genes known to be associated with dementia and to identify novel pathogenic genes.

e) Brain MRI and CT

At baseline and 18-month follow-up, brain MRI or CT will be performed by the scanner available at each site to detect any local lesion, such as cerebral infarction, that could greatly affect cognitive function. At the NCGG, three-dimensional (3D) T1-weighted images, T2-weighted images, T2*-weighted images, 3D fluid attenuation inversion recovery (FLAIR) images, diffusion-weighted images, and diffusion kurtosis images are to be acquired on a Siemens Magnetom Skyra 3T MRI scanner (Siemens Medical Solutions, Erlangen Germany). To elucidate the mechanisms of cognitive improvement and deterioration during the intervention period, brain structural alterations, such as atrophy, cerebral small vessel disease and micro structural change in white matter and gray matter, are to be analyzed.

Adverse events and serious adverse events

To evaluate the safety of the intervention, all adverse events (AEs) and serious AEs are to be monitored during the course of the trial. Information to be collected about AEs is to include their date of onset, severity, associated treatment, consequences, and causation. Serious AEs are to be reported to the principal investigator, the IRB, and the co-investigators immediately.

Interventions procedures

Intervention arm

The intervention group is to receive multi-domain intervention programs including: (1) management of vascular risk factors; (2) group-based physical exercises and self-monitoring of physical activity; (3) nutritional counseling; and (4) cognitive training using Brain HQ. Figure 3 shows the J-MINT trial network, where the NCGG and the 4 other centers are to manage vascular risk factors and supervise the implementation of the multi-domain intervention, while working with Sompo Holdings, Inc. and Sompo Care Inc., care management companies in Japan. Group-based physical exercise programs, nutritional counseling, and cognitive training are to be provided by Konami Sports Co., Ltd., Sompo Health Support Inc., and Posit Science Corporation, respectively.

Figure 3. Network of the Japan-multidomain intervention trial for prevention of dementia

 

Management of vascular risk factors

Diabetes mellitus, hypertension, and dyslipidemia in the participants are to be treated according to relevant clinical practice guidelines in Japan, with diabetes managed based on the treatment guideline for elderly patients with diabetes mellitus 2017 by the Japan Diabetes Society (JDS)/Japan Geriatric Society (JGS) Joint Committee (46), Hypertension managed based on the Japanese Society of Hypertension Guidelines for the Management of Hypertension (JSH 2019) (47), and dyslipidemia managed based on the Japan Atherosclerosis Society (JAS) Guidelines for Prevention of Atherosclerotic Cardiovascular Diseases 2017 (48). Results of blood tests and brain MRI or CT will be mailed to all participants in both the intervention and control arms, together with letters recommending that they contact primary health care as required.

Group-based physical exercise and self- monitoring of physical activity

Participants are to engage in the group-based physical exercise session lasting 90 minutes at each site once a week for a total 78 sessions. Trained instructors are to provide group-based physical exercise sessions, each of which includes muscle stretching, muscle strength training, aerobic exercise, dual-task training combining exercise and cognitive tasks, namely “cognicise” (“cogni” for cognition + “cise” for exercise), and a group meeting to promote behavioral change, consistently with a previous trial (49). Intervention with combined cognitive and physical exercise was shown to improve cognitive and physical performance in older adults with mild cognitive impairment (49).
Two types of exercise session are to be provided: (1) one involving muscle strength training, which consists of 10 minutes of muscle stretching, 15-20 minutes of muscle strength training, 5 minutes of rest, 20-30 minutes of aerobic exercise, 5 minutes of rest, 20-30 minutes of dual-task training; (2) the other involving group meeting, which consist of 10 minutes of stretching, 20-30 minutes of aerobic exercise, 5 minutes of rest, 20-30 minutes of dual-task training, 5 minutes of rest, and 15-20 minutes of group meeting. The sessions involving muscle strength training and group meeting are to be provided at a ratio of 1:1 and 3:1 per month from baseline to 6 months and from 6 months to 18 months, respectively. Aerobic exercise is to be set at moderate intensity and to be progressively intensified from 40% to 80% of maximum heart rate (HR) over the study period. The maximum HR is to be estimated by age-predicted maximal HR formula (207 – 0.7 × age). HR during aerobic exercise is to be monitored by using the wrist-worn device (Fitbit® Inspire HR activity monitor). Instructors are also to monitor their HR and exercise intensity using an iPad Air tablet computer synchronizing with participant’s Fitbit® Inspire HR activity monitor. These devices are to be distributed to all participants in the intervention arm.
In group meetings, health-related information including that on prevention of dementia, frailty, knee and low back pain, malnutrition, sleep disorder, and falls and fall-related fracture, and the beneficial effect of social participation and physical activity is to be provided to promote healthy behaviors. Moreover, participants are also to be assessed for their subjective physical activity, perceived benefit and barrier to exercise, and satisfaction with the intervention programs by using the Global Physical Activity Questionnaire (50), the Exercise Benefits/Barriers Scale (51), and the Client Satisfaction Questionnaire (52), respectively, at the start of the intervention, as well as at 6-, 12-, and 18-month follow-up.
Participants are to receive several exercise videos/messages every week via an iPad Air tablet computer to promote home-based muscle strengthening exercises, aerobic exercise, and dual-task training three or more times a week. Moreover, participants are also to be advised to monitor their daily steps, HR, and sleep using an iPad Air tablet computer synchronizing with their Fitbit® Inspire HR activity monitor.

Nutritional counseling

Nutritional counseling is to be offered individually by qualified health consultants (registered dieticians, nurses, or public health nurses). Participants are to receive face-to-face counseling (60 minutes per session) once and telephone counseling 4 times during a 6-month period, with face-to-face counseling 3 times and twelve times telephone counseling are scheduled to occur 3 and 12 times, respectively, during the course of the18-month intervention period. In face-to-face counseling, health consultants are to assess each participant’s current situation and problems, propose coping methods, and set individual goals together with the participant. In telephone counseling, health consultants are to assess changes in lifestyle and track goal achievement. Participants are to be requested to monitor their body weight and to track goal achievement everyday using a study-provided booklet.
For the first 6 months, nutritional counseling is to focus on improvement of lifestyle (sleep and waking times) and dietary behavior (dietary timing, frequency, and regularity) based on the body’s circadian rhythm (chrono-nutrition). From the next 7 to 18 months, nutritional counseling is to include guidance on dietary intake required to improve cognitive and physical condition, including frailty and sarcopenia and on chewing and swallowing function and oral care (assessment of oral frailty (25), brushing teeth, and regular visits to a dental clinic). Appropriate dietary intakes are to be determined based on the Dietary Reference Intakes for Japanese (2020) (53), which provide the reference intakes of proteins, fats, carbohydrates, vitamins, and minerals and guidance on energy-providing nutrient balance for older adults 65-74 years old and 75 years or older, respectively. Moreover, participants are to be instructed to take a well-balanced diet and increase dietary diversity, which is reported to be associated with better physical and cognitive performance in Japanese older community-dwelling adults (54, 55). Participants are also to be requested to monitor their dietary diversity every day using a study-provided booklet. Additionally, based on the evidence from previous cohort studies and clinical trial (56-60), intake of fish and seafood containing eicosapentaenoic and docosahexaenoic acids, milk and dairy products, fruits, vegetables, and green tea is to be also recommended.

Cognitive training

Participants are to be instructed to engage in cognitive training individually using an iPad Air tablet computer wherein the Brain HQ (Japanese version) has been installed. The Brain HQ (Japanese version) is customized for the J-MINT trial and consists of 13 visual exercises focusing on specific cognitive abilities, such as attention, processing speed, memory, mental flexibility, and visuospatial ability. Exercise difficulty is adjusted based on cognitive abilities of each individual to ensure and sustain engagement of attention and motivation. Brain HQ exercise is reported to be beneficial for several cognitive domains including processing speed and memory in an RCT conducted specifically in older adults (61).
During the 4-6, 10-12, and 16-18 months (intensive training periods) in the 18-month intervention period, participants are to be instructed to engage in intensive training lasting at least 30 minutes per day for 4 or more days per week. Participants are to be monitored for adherence during each intensive training period as well as in the entire 18-month intervention period. Lower adherence may also be expected in cognitive training due to its use of tablet computers involving operational difficulties. Therefore, continuous support is to be provided not only in terms of instructions on the tablet computer operations at the start of the program, but in the form of a free consultation desk to be put in place during the intervention period.

Delivery of intervention during the coronavirus disease-19 (COVID-19) pandemic

The declaration by the Japanese government of a state of emergency due to the COVID-19 pandemic is expected to result in travel restrictions, social distancing, and avoidance of “3Cs” (closed spaces, crowded places, and close-contact settings, particularly their combination) and is likely to lead to part of the J-MINT intervention being restricted, especially group-based physical exercise and face-to-face nutritional counseling. In such situation, the J-MINT trial is to provide on-line intervention programs for physical exercise and nutritional counseling.

Price sensitivity measurement

At the completion of the intervention programs, a price sensitivity measurement approach is to be drawn on to discuss the appropriate price of each intervention program in view of its future implementation in the real-world setting.

Control arm

The control group is to receive health-related information in writing every 2 months on how to prevent/manage dementia, frailty, low back pain, malnutrition, health-related disease, sleep disorder and falls and fall-related fracture, as well as on the beneficial effect of social participation and physical activity and how to manage vascular risk factors according to current clinical practice guidelines.

Statistical considerations

Sample size

Since, to date, no multi-domain intervention trials have detected changes in our global composite score consisting of several neuropsychological tests, sample size calculation was based on the previous randomized controlled trial that evaluated the effect of an exercise program combined with physical and cognitive tasks in 308 older adults with mild cognitive impairment shown to have an age-adjusted cognitive decline (an SD of 1.5 or more from the reference threshold in any of the cognitive domains determined by using the NCGG-FAT (49)). In this trial, the intervention group showed a significantly greater score change on the MMSE than the control group (Intervention group vs. control group, 0.0 ± 2.48 vs. -0.8 ± 2.48 after the 40-week trial. Based on this trial, we hypothesized that the present study is also likely to detect a difference of change in cognitive function between the intervention and control groups. With a two-sided significance level of 5% and a statistical power of 80%, the total sample size required by the t-test was calculated as 302. In addition, the dropout rate at final follow-up is estimated to be 40% at each trial site. Thus, it was assumed that the trial required to enroll a total of 500 patients.

Randomization and blinding

In this trial, participants are to be centrally randomized at a 1:1 allocation ratio into intervention and control groups using the dynamic allocation method through stratification by the following variables:
1) Age at enrollment (65-74 years vs. 75-85 years).
2) Sex (female vs. male).
3) MMSE (24-27 vs. 28-30)
4) Presence of memory impairment as determined by the NCGG-FAT (amnestic vs. non-amnestic)

Participants are to be randomized electronically via a web-based system constructed by a trial statistician (F. K.) and a co-investigator (A. H.). Study participants and research staff including investigators and clinicians at each site are to be blinded to the next assignment in the sequence using electronic assignment and a dynamic allocation algorithm.

Data collection forms and data monitoring

All variables are to be measured by trained research staff at each site, and most of the measured outcome data are to be collected in the form of hard copy forms. Then, these data are to be collected through entry of these data by assessors using an electronic data capture (EDC) system. All hard copy forms are to be retained as back-ups as required at each site.
On-site monitoring is to be conducted at each site to ensure that the patient rights are protected, the reported data are accurate, and the conduct of the trial is compliant with the current approved protocol. The monitor is to ensure that (1) written informed consent is obtained from all participants before their participation in the trial; (2) primary outcome data reported in the EDC are complete and accurate; and (3) all AEs and serious AEs are reported appropriately.

Data analyses

In this trial, we defined the following four analysis sets: (1) the intention-to-treat (ITT) analysis set, which includes all subjects randomized regardless of whether or not they received the intervention programs/health-related information; (2) the full analysis set (FAS), which includes subjects who received the intervention program/health-related information at least once and had at least one post-baseline assessment of neuropsychological tests; (3) the per protocol set (PPS), which includes subjects who received the intervention program/health-related information for 18-month or more; (4) the safety analysis set (SAF), which includes subjects who received the intervention program/health-related information at least once. The primary efficacy analysis is to be performed using the FAS, and the secondary efficacy analysis is to be performed using the ITT and the PPS.
Data are to be presented as means, medians, standard deviations, ranges and interquartile ranges for continuous and ordinal variables, and counts and percentages for categorical variables. Differences in baseline clinical characteristics between the intervention and control groups are to be examined for significance by using the t-test or the Mann-Whitney U test for continuous variables and by the chi-squared test or the Fisher’s exact test for categorical variables, as appropriate.
To evaluate differences from baseline in cognitive changes at 18-month follow-up between the intervention and control groups, the mixed-effects model for repeated measures (MMRM) with an unstructured covariance structure is to be used with groups, time of visit, group by time interaction, age at randomization, sex, presence of memory impairment at randomization (amnestic or non-amnestic), and baseline composite cognitive score as covariates. For the secondary continuous variables, the same analyses are to be performed using MMRM. For the secondary categorical variables, logistic regression analyses or chi-squared tests will be used as appropriate. Frequencies of serious AEs are to be summarized for the intervention and control groups.
All statistical analyses are to be performed using SAS (SAS Institute, Inc., Cary, NC, USA). P-values of < 0.05 are to be considered statistically significant.

 

Discussion

The J-MINT trial will be the first not only to demonstrate the effectiveness of multi-domain interventions but to clarify the mechanism of cognitive improvement and deterioration through assessment of dementia-related biomarkers, omics analysis and brain image analysis. Moreover, along with the creation of evidence for prevention of dementia, collaborative research with partnering companies is expected to allow creation of new services and manuals for proposed ideal services. The J-MINT trial raises some concern that high-intensity intervention programs may result in an insufficient level of adherence, which lead to minimal beneficial effect. To address this issue, group-based physical exercise and nutritional counseling have been designed, in light of encouraging results from the FINGER and MAPT trials, to include face-to-face contacts, which may increase adherence (62). Moreover, there is still lack of consensus about the level of sustained adherence deemed acceptable or sufficient for prevention of cognitive decline. Given that all participants are to be monitored for adherence to its intervention programs during the intervention period, the J-MINT may provide insight into the level of sustained adherence deemed acceptable or sufficient for each intervention program among older adults at higher risk of dementia.
Finally, the J-MINT Prime trial incorporating two RCTs, Japan-multimodal Intervention Trial for Prevention of Dementia in Kanagawa (UMIN000041887) and Japan-multimodal Intervention Trial for Prevention of Dementia PRIME Tamba Study (UMIN000041938), was initiated in Japan to clarify the effectiveness of multi-domain intervention in different settings and populations in Japan. Both the J-MINT trial and the J-MINT Prime trial are intended to evaluate cognitive and other outcomes measures, with their combined data-analyses being planned. These results are expected to contribute to the development of a mechanism through which a sustainable dementia prevention service may be made widely available to those in need.

 

Funding: This work was financially supported by Japan Agency for Medical Research and Development (AMED) under Grant Number JP20de0107002. 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 thank all the patients for their participation in the study and all members of the J-MINT study group (see Appendix 2) and on-site study staff for their efforts in the conduct of assessments and interventions.

Conflicts of interest: The authors have no conflict of interest to declare.

Trial registration: UMIN000038671; Registered on the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) 24 November 2019. (https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000044075).

 

SUPPLEMENTARY MATERIAL1

SUPPLEMENTARY MATERIAL2

 

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CORTICAL Β-AMYLOID IN OLDER ADULTS IS ASSOCIATED WITH MULTIDOMAIN INTERVENTIONS WITH AND WITHOUT OMEGA 3 POLYUNSATURATED FATTY ACID SUPPLEMENTATION

 

C. Hooper1, N. Coley2,3, P. De Souto Barreto1,2, P. Payoux4,5, A.S. Salabert4,5, S. Andrieu2,3, M. Weiner6, B. Vellas1,2 for the MAPT/DSA study group

1. Gérontopôle, Department of Geriatrics, CHU Toulouse, Purpan University Hospital, Toulouse, France; 2. UMR1027, Université de Toulouse, UPS, INSERM, Toulouse, France; 3. Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France; 4. UMR 1214, Toulouse Neuroimaging Center, University of Toulouse III, Toulouse, France; 5. Department of Nuclear Medicine, University Hospital of Toulouse (CHU-Toulouse), Toulouse, France; 6. University of California San Francisco, School of Medicine, 4150 Clement Street, San Francisco, California. USA.

Corresponding Author: Claudie Hooper, Gérontopôle, Department of Geriatrics, CHU Toulouse, Purpan University Hospital, Toulouse, France , Tel  : +33 (5) 61 77 64 25, Fax : +33 (5) 61 77 64 75 claudie28@yahoo.com

J Prev Alz Dis 2020;
Published online February 5, 2020, http://dx.doi.org/10.14283/jpad.2020.4


Abstract

Multidomain lifestyle interventions (including combinations of physical exercise, cognitive training and nutritional guidance) are attracting increasing research attention for reducing the risk of Alzheimer’s disease (AD). Here we examined for the first time the cross-sectional relationship between cortical β-amyloid (Aβ) and multidomain lifestyle interventions (nutritional and exercise counselling and cognitive training), omega 3 polyunsaturated fatty acid (n-3 PUFA) supplementation or their combination in 269 participants of the Multidomain Alzheimer Preventive Trial (MAPT). In adjusted multiple linear regression models, compared to the control group (receiving placebo alone), cortical Aβ, measured once during follow-up (mean 512.7 ± 249.6 days post-baseline), was significantly lower in the groups receiving multidomain lifestyle intervention + placebo (mean difference, -0.088, 95 % CI, -0.148,-0.029, p = 0.004) or multidomain lifestyle intervention + n-3 PUFA (-0.100, 95 % CI, -0.160,-0.041, p = 0.001), but there was no difference in the n-3 PUFA supplementation alone group (-0.011, 95 % CI, -0.072,0.051, p = 0.729).  Secondary analysis provided mixed results. Our findings suggest that multidomain interventions both with and without n-3 PUFA supplementation might be associated with lower cerebral Aβ. Future trials should investigate if such multidomain lifestyle interventions are causally associated with a reduction or the prevention of the accumulation of cerebral Aβ.

Key words: Multidomain lifestyle intervention, β-amyloid, physical activity, cognitive activity, nutrition, Alzheimer’s disease.


 

Introduction

Evidence suggests that the individual components of multidomain lifestyle interventions, including cognitive activity (1, 2), physical activity (3, 4) and nutrition (5, 6) are associated with reduced cerebral β-amyloid (Aβ). Physical activity has been cross-sectionally associated with reduced central Aβ in cognitively normal older adults (4) as well as in autosomal dominant  (early onset familial) cases of Alzheimer’s disease (AD) (3, 7). A less active lifestyle has been associated with more cerebral Aβ in apolipoprotein E (ApoE) ε4 carriers (8) and the association of physical activity with reduced cerebral Aβ appears to be more prominent in ApoE ε4 carriers (4, 9). Furthermore, long-term treadmill exercise reduces Aβ in murine models of AD possibly through reduced amyloidogenic-cleavage (10, 11) and/or increased Aβ degradation (10).
Lifetime cognitive activity has been cross-sectionally associated with reduced cerebral Aβ in human subjects (1) and in another cross-sectional study it was shown that Aβ was diminished in ApoE ε4 carriers that reported higher cognitive activity over the course of life (2). Moreover, lifetime intellectual enrichment (high education, high midlife cognitive activity) has been associated with lower cortical Aβ deposition longitudinally in ApoE ε4 carriers (12). However, there is in vitro and animal data to indicate that neural activity increases the secretion of Aβ (13, 14), which might lead to enhanced deposition if clearance mechanisms failed. Nevertheless, consistent with our hypothesis, transgenic Aβ-expressing mice exposed to enriched environments deposit less Aβ than control animals (15).
In terms of nutrition and Aβ, increased cerebral Aβ has been associated with a high glycaemic diet (16) and a lack of adherence to a Mediterranean style diet (17) and vitamin B12 as well as vitamin D (5) have been inversely associated with cerebral Aβ. Cell culture and animal models suggest that docosahexaenoic acid (DHA), the predominant omega (n-3) polyunsaturated fatty acid (PUFA) in the brain, might reduce Aβ production (18-20) and serum DHA has been inversely associated with brain Aβ cross-sectionally in older adults (21). To the contrary, however, we have previously reported that erythrocyte membrane DHA, eicosapentaenoic acid (EPA) as well as total n-3 PUFA were not cross-sectionally associated with cortical Aβ in participants of the placebo group of Multidomain Alzheimer Preventive Trial (MAPT) (22).
Using similar multidomain lifestyle interventions to those used in MAPT (nutritional and exercise counselling and cognitive training), other trials have explored the effects of multidomain interventions targeting a healthier lifestyle on cognitive function in older adults (23-26). However, to the best of our knowledge no information is available on the relationship between multidomain lifestyle interventions and cerebral Aβ burden. Hence we explored the cross-sectional relationship between cortical Aβ and multidomain lifestyle interventions, n-3 PUFA supplementation or their combination in 269 participants of the MAPT trial who underwent voluntary [18F] florbetapir positron emission tomography (PET). We hypothesised that multidomain lifestyle intervention might be associated with reduced cerebral Aβ and that this association might be potentiated by n-3 PUFA supplementation.

 

Methods

The Multidomain Alzheimer Preventive Trial (MAPT) and ethical approval

Data were obtained from a [18F] florbetapir PET study carried out as an ancillary project to MAPT (registration: NCT00672685), a large multicentre, phase III, randomized, placebo-controlled trial (RCT) which has already been described in detail (26). MAPT subjects (n=1680) were randomized to one of the four following arms: n-3 PUFA supplementation alone, multidomain lifestyle intervention (involving nutritional and exercise counselling and cognitive training) + placebo, multidomain lifestyle intervention + n-3 PUFA supplementation, or placebo alone (control group). Both MAPT and the PET sub-study were approved by the ethics committee in Toulouse (CPP SOOM II) and written consent was obtained from all participants.

Participants

At inclusion, subjects were community-dwelling men and women without dementia, aged ≥ 70 years, and who met at least one of the following criteria: spontaneous memory complaints, limitation in executing ≥ 1 Instrumental Activity of Daily Living, or slow gait speed (< 0.8 meters/sec). Participants of the study described here were 269 individuals who had data on cortical Aβ (excluding two participants who developed dementia as assessed at the clinical evaluation closest to PET-scan (Clinical Dementia Rating (CDR) ≥ 1)). MAPT participants who were not assessed for cerebral Aβ (n = 1408) were similar to the participants in the PET sub-study (n = 269) (Table S1).

The Multidomain Alzheimer Preventive Trial interventions

The MAPT multidomain lifestyle intervention was comprised of cognitive training, nutritional counselling and physical activity counselling (26). Group-based 2-hour sessions were performed twice a week during the first four weeks of the trial, once a week for the following four weeks and then once a month for the remainder of the trial’s 3-year follow-up period. The sessions comprised: one hour of cognitive training (memory and reasoning), 15 minutes of nutritional advice (based on guidelines established by the Programme National Nutrition Santé, the French National Nutrition Health Programme (27)) and 45 minutes of physical activity counselling. An exercise program was designed for each individual and participants were advised to increase the physical activity to the equivalent of at least 30 minutes walking per day 5 days a week. Two 2-hour reinforcement sessions were performed at 12 and 24 months to boost the effects of the interventions. Preventive consultations were also performed (at baseline, 12 and 24 months) with a physician to optimize the management of cardiovascular risk factors and detect functional impairments. All participants were also asked to consume two soft capsules daily as a single dose, containing either a placebo, or a total of 800 mg of DHA and 225 mg of EPA per day. The trial was double-blind for all subjects for n-3 PUFA supplementation or placebo allocation.  No lifestyle interventions were provided to participants in the placebo alone or n-3 PUFA alone groups.

[18F] Florbetapir Positron Emission Tomography (PET)

PET-scans as a measure of cortical Aβ were performed using [18F] florbetapir as previously described (28, 29). PET data acquisitions commenced 50 minutes after injection of a mean of 4 MBq/kg weight of [18F]-Florbetapir. Radiochemical purity of [18F]-Florbetapir was superior to 99.5 %. Regional standard uptake value ratios (SUVRs) were generated from semi-automated quantitative analysis with the whole cerebellum used as the reference region. Cortical-to-cerebellar SUVRs (cortical-SUVRs) were obtained using the mean signal of the following predefined cortical regions: frontal, temporal, parietal, precuneus, anterior cingulate, and posterior cingulate as previously described (30). A Quality Control procedure was carried out using a semi-quantification-based method. PET-scans were performed throughout the 3 year period of MAPT: the mean time of PET-scan acquisition (standard deviation, SD) was 512.7 ± 249.6 days after study baseline. There was no significant difference (p = 0.223 according to a one way analysis of variance: ANOVA) between the time interval between baseline and PET-scan in subjects allocated to the 4 MAPT groups (placebo: 464.9 ± 2.62.0 days, n-3 PUFA group: 501.8 ± 232.4 days, multidomain + placebo: 544.4 ± 237.3 days, multidomain + n-3 PUFA: 536.8 ± 259.8 days). Very few subjects were scanned before 6 months: 22 out of 269 (8.2 %).

Covariates

We selected the following covariates on the basis of data availability and the literature on AD (31-33): age at PET-scan assessment, gender, educational level, cognitive status assessed at the clinical visit closest to PET-scan [Clinical dementia rating (CDR): scores 0 or 0.5], time interval between baseline and PET-scan (in days), physical activity assessed at the clinical visit closest to PET-scan [measured in metabolic equivalent tasks – minutes per week (MET-min/week)] and ApoE ε4 genotype (carriers of at least one ε4 allele versus non-carriers).

Statistical Analysis

Descriptive statistics are presented as mean ± (SD) or absolute values/percentages. Clinical and demographic characteristics were compared between the participants in each group using chi squared tests for categorical variables and one-way ANOVA for continuous variables. This was a post-hoc analysis since the association between cortical Aβ burden and the MAPT interventions was not an a priori hypothesis of the MAPT study. We used multiple linear regression models to compare cortical Aβ levels (measured once per subject, at any time during follow-up, as described above) across the four MAPT randomization groups (placebo alone, n-3 PUFA supplementation alone, multidomain lifestyle intervention + placebo, and multidomain lifestyle intervention + n-3 PUFA supplementation) adjusting for all covariates. Next we dichotomized the dependent variable, cortical Aβ, with a positivity threshold of mean cortical SUVR ≥ 1.17 (28, 34) then performed logistic regression adjusting for all covariates. We ran three sensitivity analyses in order to substantiate our main analysis. Firstly, we ran a multiple linear regression adjusting for all covariates including only those participants who had their PET-scan ≥ 12 months post-baseline and hence had received MAPT interventions for ≥ 12 months. Secondly, we ran a multiple linear regression adjusting for all covariates including only those participants who had their PET-scan < 12 months post-baseline. Thirdly, we ran a multiple linear regression adjusting for all covariates after combining the MAPT data into 2 groups according to allocation to multidomain lifestyle intervention (placebo plus n-3 PUFA supplementation versus multidomain lifestyle intervention + placebo plus multidomain lifestyle intervention + n-3 PUFA supplementation). To explore the role of adherence to intervention, we ran multiple linear regression restricted to subjects in the multidomain groups adjusted for age, sex and ApoE ε4 carrier status to assess the association between cortical Aβ and adherence to the multidomain lifestyle intervention or adherence to the multidomain lifestyle intervention + n-3 PUFA supplementation. Adherence was defined as ≥ 75 % attendance to the sessions over the 3-year period of MAPT including participation in the two boost sessions at the 12 and 24 month follow-ups (reference: non-adherent < 75 % attendance) (5). Lastly, to explore the role of time on the association of MAPT intervention with cortical Aβ we ran a multiple linear regression analysis (adjusted for all covariates) with the introduction of an interaction term between MAPT group allocation and time between PET-scan and baseline (in days).  Due to the exploratory nature of the study there was no correction for multiple comparisons: P < 0.05 was considered statistically significant.  Statistical analyses were performed using Stata version 14 (Stata Corp., College Station, TX, USA).

 

Results

Sample characteristics

Demographic and clinical characteristics of the participants included in this study are shown in Table 1. There were no significant between-group differences in age, gender, cognitive status, time interval between baseline and PET-scan, physical activity and number of ApoE ε4 carriers. However, educational level differed significantly between groups as did cortical SUVR as a measure of Aβ burden. There was less cortical SUVR present in participants receiving multidomain intervention + placebo or multidomain + n-3 PUFA. The mean age of the participants was approximately 76 years, and around 60 % of the population were female. Participants exhibited a high level of education and almost half of the participants had a CDR score of 0.5 and approximately one third of the subjects carried at least one ApoE ε4 allele.

Table 1. Participant characteristics

Table 1. Participant characteristics

Age, CDR score, and MET-min/week reported at the clinical visit closest to the PET scan are presented. Data is expressed as mean ± standard deviation or as absolute values/percentages. Clinical and demographic characteristics were compared between the participants in each group using chi squared tests for categorical variables and one way analysis of variance (ANOVA) for continuous variables. Abbreviations: ApoE, apolipoprotein E; CDR, clinical dementia rating; MET-min/week, metabolic equivalent tasks – minutes per week; n-3, omega 3 polyunsaturated fatty acid supplementation; MI, multidomain intervention; SUVR, standard uptake ratio values.

 

Main analysis

In the adjusted multiple linear regression model, cortical Aβ was significantly lower in the multidomain lifestyle intervention + placebo group (mean difference, -0.088, 95 % CI, -0.148,-0.029, p = 0.004) and the multidomain lifestyle intervention + n-3 PUFA group (mean difference, -0.100, 95 % CI, -0.160,-0.041, p = 0.001), compared to the placebo alone group (table 2), but there was no difference between the placebo alone and n-3 PUFA supplementation alone groups (mean difference, -0.011, 95 % CI, -0.072,0.051, p = 0.729).  ApoE ε4 carrier status was also significantly associated with cortical Aβ in the model (mean difference, 0.118, 95 % CI, 0.071,0.166, p < 0.001) with ApoE ε4 carriers having greater SUVR compared to non-carriers, as expected. None of the other demographic and clinical co-variates were significantly associated with cortical Aβ.

Table 2. Multiple linear regressions examining the cross-sectional associations between cortical β-amyloid load and the MAPT interventions

Table 2. Multiple linear regressions examining the cross-sectional associations between cortical β-amyloid load and the MAPT interventions

The adjusted model contained fewer subjects due to missing data on covariates (age at PET-scan assessment, ApoE ε4 genotype, gender, educational level, time interval between baseline and PET-scan, and Clinical dementia rating (CDR) and physical activity assessed at the clinical visit closest to PET-scan). B-coefficients represent the mean difference in SUVR between the placebo and intervention. Mean SUVR (95 % CI) for the placebo group in the unadjusted model and as predicted from the adjusted model are 1.23 (1.19,1.27) and 1.33 (0.94,1.72) respectively. Abbreviations: B-coeff, B-coefficient; CI, confidence intervals; n-3 PUFA, omega 3 polyunsaturated fatty acid; p, probability; SUVR, standard uptake ratio values.

 

In the adjusted logistic regression analysis, compared to the placebo alone group, the odds of cortical amyloid positivity (defined as SUVR ≥ 1.17) were significantly lower in the multidomain lifestyle intervention + n-3 PUFA group (odds ratio (OR), 0.31, 95 % CI, 0.133,0.699, p = 0.005), but not in the multidomain lifestyle intervention + placebo group, although they were numerically lower (OR 0.61, 95 % CI, 0.272,1.345, p = 0.218) (Table 3).

Table 3. Logistic regression examining the cross-sectional associations between cortical β-amyloid and MAPT interventions

Table 3. Logistic regression examining the cross-sectional associations between cortical β-amyloid and MAPT interventions

β-amyloid positivity was defined with a threshold of mean cortical SUVR ≥ 1.17. Abbreviations: CI, confidence intervals; n-3 PUFA, omega 3 polyunsaturated fatty acid; p, probability.

 

Sensitivity analysis

In multiple linear regression amongst participants who had their PET scans ≥ 12 months post-baseline, and therefore had received intervention for ≥ 12 months, results were similar to the main analysis (Table 4). Amongst participants who had their PET scans < 12 months post-baseline cortical Aβ was still significantly lower in the multidomain lifestyle intervention + n-3 group compared to the placebo alone group (B-coefficient, -0.126, 95 % CI, -0.252,-0.001, p = 0.048), but the difference between the multidomain lifestyle intervention + placebo group and the placebo alone group was not significant (B-coefficient, -0.099, 95 % CI, -0.227,0.029, p = 0.127) (Table 5). Dividing the participants into two groups according to whether the subjects received multidomain lifestyle intervention or not gave similar results to the main analysis (B-coefficient, -0.089, 95 % CI, -0.132, -0.046, p <0.001: reference = placebo alone and n-3 PUFA supplementation alone groups combined).

Table 4. Sensitivity analysis in subjects having their PET-scan ≥ 12 months

Table 4. Sensitivity analysis in subjects having their PET-scan ≥ 12 months

The adjusted model contained fewer subjects due to missing data on confounders. B-coefficients represent the mean difference in SUVR between the placebo and intervention. Mean SUVR (95 % CI) for the placebo group in the unadjusted model and as predicted from the adjusted model are 1.22 (1.17,1.27) and 1.28 (0.83,1.73) respectively. Abbreviations: B-coeff, B-coefficient; CI, confidence intervals; n-3 PUFA, omega 3 polyunsaturated fatty acid; p, probability; SUVR, standard uptake ratio values.

Table 5. Sensitivity analysis in subjects having their PET-scan < 12 months

Table 5. Sensitivity analysis in subjects having their PET-scan < 12 months

The adjusted model contained fewer subjects due to missing data on confounders. B-coefficients represent the mean difference in SUVR between the placebo and intervention. Mean SUVR (95 % CI) for the placebo group in the unadjusted model and as predicted from the adjusted model are 1.24 (1.18,1.30) and 1.55 (0.63,2.48) respectively. Abbreviations: B-coeff, B-coefficient; CI, confidence intervals; n-3 PUFA, omega 3 polyunsaturated fatty acid; p, probability; SUVR, standard uptake ratio values.

 

Exploratory analysis

Cortical Aβ was not associated with multidomain intervention adherence in the multidomain lifestyle intervention + placebo group (mean difference between adherent and non-adherent subjects , -0.019, 95 % CI, -0.106,0.068, p = 0.668) nor in the multidomain lifestyle intervention + n-3 PUFA group (mean difference, 0.038, 95 % CI, -0.025, 0.102, p = 0.228). Furthermore, the interaction between MAPT group allocation and time between PET scan and baseline was not significantly associated with cortical Aβ in the model (p < 0.05).

 

Discussion

We have observed that assignment to multidomain lifestyle intervention with and without n-3 PUFA supplementation were similarly associated with less cortical Aβ load in older adults at risk of dementia. In contrast, n-3 PUFA supplementation alone was not associated with cortical Aβ. It should be noted, however that a significant association between the multidomain lifestyle intervention + n-3 PUFA group and cortical Aβ was also observed in a sensitivity analysis restricted to those subjects who received a PET-scan < 12 months post-baseline (although the majority of these subjects would still have received the intervention for at least 6 months prior to having their PET scan). Moreover, because it would be expected that the longer participants were exposed to the multidomain lifestyle intervention, the lower the cortical Aβ burden would be, we performed an exploratory analysis for an interaction between MAPT group allocation and time between PET scan and baseline. We found no significant interaction with time. What is more, exploratory analysis showed that cortical Aβ was not significantly associated with adherence to the multidomain lifestyle interventions. Collectively, these findings cast some doubt on our main analysis hence further validation studies are required.
In the primary analysis of MAPT, no significant effects of any of the interventions (multidomain lifestyle intervention + placebo; n-3 PUFA supplementation; multidomain lifestyle intervention + n-3 PUFA supplementation) were found on a composite cognitive score, compared to placebo alone, after adjustment for multiple testing (26). However, significantly less cognitive decline during follow-up was noted in the combined intervention group and in the multidomain intervention plus placebo group than in the placebo group in the subgroup of Aβ positive participants (26, 35). These findings suggest that multidomain intervention might work through the reduction of cerebral Aβ therefore providing indirect evidence to support to the main findings of the analysis presented here. Furthermore, there is a growing body of evidence to suggest that physical activity (4, 7, 8), cognitive activity (1, 2) and nutrition (5, 6) are independently associated with cerebral Aβ levels and thus collectively these elements might offer a synergistic effect on reducing cerebral Aβ.
In the short-term, analysis of existing longitudinal observational studies with data on cerebral Aβ in which two or more components of the MAPT multidomain lifestyle intervention could be operationalized might shed more light on our preliminary findings. Whilst, in the longer-term, our study specifically begs the question ‘Does multidomain lifestyle intervention reduce cortical Aβ?’. Further research in the form of a large RCT, in which cerebral Aβ is measured before and after the intervention, is required to respond to this question. Establishing the correct level of multidomain lifestyle intervention also remains to be determined. In terms of physical activity and cognitive training is sustained activity or activity of increasing difficulty required?  Which nutrients are more important for healthy aging, fats, specific vitamins or the correct dietary balance? Another important question to answer is: What is the best time window to administer a multi-domain intervention?  Cerebral Aβ accrual is believed to occur over a protracted period accounting for the long pro-dromal phase of AD (36); therefore, it is possible that mid-life interventions might be required to prevent future pathological changes. The duration of a lifestyle intervention is another important determinant of efficacy that requires investigation.
In conclusion we present here some evidence that  multidomain lifestyle intervention both with and without n-3 PUFA supplementation were similarly associated with less cortical Aβ in older adults at risk of dementia. Further validation studies are required to either support or refute our preliminary findings and to assess whether any relationships between multidomain interventions and cortical Aβ are causal.

 

Conflicts of Interest: The authors declare that they have no conflict of interest.

Sources of funding: “The MAPT study was supported by grants from the Gérontopôle of Toulouse, the French Ministry of Health (PHRC 2008, 2009), Pierre Fabre Research Institute (manufacturer of the omega-3 supplement), Exhonit Therapeutics SA, Avid Radiopharmaceuticals Inc and in part by a grant from the French National Agency for Research called “Investissements d’Avenir” n°ANR-11-LABX-0018-01. The promotion of this study was supported by the University Hospital Center of Toulouse. The data sharing activity was supported by the Association Monegasque pour la Recherche sur la maladie d’Alzheimer (AMPA) and the UMR 1027 Unit INSERM-University of Toulouse III”.

Sponsor’s role: None.

MAPT/DSA Group refers to MAPT Study Group: Principal investigator: Bruno Vellas (Toulouse); Coordination: Sophie Guyonnet ; Project leader: Isabelle Carrié; CRA: Lauréane Brigitte ; Investigators: Catherine Faisant, Françoise Lala, Julien Delrieu, Hélène Villars ; Psychologists: Emeline Combrouze, Carole Badufle, Audrey Zueras ; Methodology, statistical analysis and data management: Sandrine Andrieu, Christelle Cantet, Christophe Morin; Multidomain group: Gabor Abellan Van Kan, Charlotte Dupuy, Yves Rolland (physical and nutritional components), Céline Caillaud, Pierre-Jean Ousset (cognitive component), Françoise Lala (preventive consultation) (Toulouse). The cognitive component was designed in collaboration with Sherry Willis from the University of Seattle, and Sylvie Belleville, Brigitte Gilbert and Francine Fontaine from the University of Montreal.Co-Investigators in associated centres: Jean-François Dartigues, Isabelle Marcet, Fleur Delva, Alexandra Foubert, Sandrine Cerda (Bordeaux); Marie-Noëlle-Cuffi, Corinne Costes (Castres); Olivier Rouaud, Patrick Manckoundia, Valérie Quipourt, Sophie Marilier, Evelyne Franon (Dijon); Lawrence Bories, Marie-Laure Pader, Marie-France Basset, Bruno Lapoujade, Valérie Faure, Michael Li Yung Tong, Christine Malick-Loiseau, Evelyne Cazaban-Campistron (Foix); Françoise Desclaux, Colette Blatge (Lavaur); Thierry Dantoine, Cécile Laubarie-Mouret, Isabelle Saulnier, Jean-Pierre Clément, Marie-Agnès Picat, Laurence Bernard-Bourzeix, Stéphanie Willebois, Iléana Désormais, Noëlle Cardinaud (Limoges); Marc Bonnefoy, Pierre Livet, Pascale Rebaudet, Claire Gédéon, Catherine Burdet, Flavien Terracol (Lyon), Alain Pesce, Stéphanie Roth, Sylvie Chaillou, Sandrine Louchart (Monaco); Kristelle Sudres, Nicolas Lebrun, Nadège Barro-Belaygues (Montauban); Jacques Touchon, Karim Bennys, Audrey Gabelle, Aurélia Romano, Lynda Touati, Cécilia Marelli, Cécile Pays (Montpellier); Philippe Robert, Franck Le Duff, Claire Gervais, Sébastien Gonfrier (Nice); Yannick Gasnier and Serge Bordes, Danièle Begorre, Christian Carpuat, Khaled Khales, Jean-François Lefebvre, Samira Misbah El Idrissi, Pierre Skolil, Jean-Pierre Salles (Tarbes). MRI group: Carole Dufouil (Bordeaux), Stéphane Lehéricy, Marie Chupin, Jean-François Mangin, Ali Bouhayia (Paris); Michèle Allard (Bordeaux); Frédéric Ricolfi (Dijon); Dominique Dubois (Foix); Marie Paule Bonceour Martel (Limoges); François Cotton (Lyon); Alain Bonafé (Montpellier); Stéphane Chanalet (Nice); Françoise Hugon (Tarbes); Fabrice Bonneville, Christophe Cognard, François Chollet (Toulouse). PET scans group: Pierre Payoux, Thierry Voisin, Julien Delrieu, Sophie Peiffer, Anne Hitzel, (Toulouse); Michèle Allard (Bordeaux); Michel Zanca (Montpellier); Jacques Monteil (Limoges); Jacques Darcourt (Nice). Medico-economics group: Laurent Molinier, Hélène Derumeaux, Nadège Costa (Toulouse). Biological sample collection: Bertrand Perret, Claire Vinel, Sylvie Caspar-Bauguil (Toulouse). Safety management : Pascale Olivier-Abbal. DSA Group: Sandrine Andrieu, Christelle Cantet, Nicola Coley.

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SUPPLEMENTARY MATERIAL

 

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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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EFFECTS OF A SIX-MONTH MULTI-INGREDIENT NUTRITION SUPPLEMENT INTERVENTION OF OMEGA-3 POLYUNSATURATED FATTY ACIDS, VITAMIN D, RESVERATROL, AND WHEY PROTEIN ON COGNITIVE FUNCTION IN OLDER ADULTS: A RANDOMISED, DOUBLE-BLIND, CONTROLLED TRIAL

 

C. Moran1, A. Scotto di Palumbo2, J. Bramham1, A. Moran1, B. Rooney1, G. De Vito2, B. Egan2

 

1. School of Psychology, University College Dublin, Dublin, Ireland; 2. School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.

Corresponding Author: Catherine Moran, School of Psychology, Trinity College Institute for Neuroscience, Trinity College Dublin, College Green, Dublin 2, Ireland, E-mail: catherine.moran@ucdconnect.ie

J Prev Alz Dis 2017 inpress
Published online February 20, 2018, http://dx.doi.org/10.14283/jpad.2018.11

 


Abstract

Objectives: To investigate the impact of a six-month multi-ingredient nutrition supplement intervention (Smartfish®), containing omega-3 polyunsaturated fatty acids (PUFAs), vitamin D, resveratrol, and whey protein, on cognitive function in Irish older adults.
Design: Double-blind, randomised controlled trial (ClinicalTrials.gov: NCT02001831). A quantitative, mixed-model design was employed in which the dependent variable (cognitive function) was analysed with a between-subjects factor of group (placebo, intervention) and within-subjects factor of testing occasion (baseline, three-months, six-months).
Setting: Community-based intervention including assessments conducted at University College Dublin, Ireland.
Participants: Thirty-seven community-dwelling older adults (68-83 years; mean (x̄)= 75.14 years; standard deviation (SD)= 3.64; 18 males) with normal cognitive function (>24 on the Mini Mental State Examination) were assigned to the placebo (n= 17) or intervention (n= 20) via a block randomisation procedure.
Intervention: Daily consumption for six-months of a 200mL liquid juice intervention comprising 3000mg omega-3 PUFAs [1500mg docosahexaenoic acid (DHA) and 1500mg eicosapentaenoic acid (EPA)], 10μg vitamin D3, 150mg resveratrol and 8g whey protein isolate. The placebo contained 200mL juice only.
Measurements: A standardised cognitive assessment battery was conducted at baseline and follow-ups. Individual test scores were z-transformed to generate composite scores grouped into cognitive domains: executive function, memory, attention and sensorimotor speed. Motor imagery accuracy and subjective awareness of cognitive failures variables were computed from raw scores.
Results: A hierarchical statistical approach was used to analyse the data; first, by examining overall cognitive function, then by domain, and then by individual test scores. Using mixed between-within subjects, analyses of variance (ANOVAs), no significant differences in overall cognitive function or composite cognitive domains were observed between groups over time. The only significant interaction was for Stroop Color-Word Time (p< 0.05). The intervention group demonstrated reduced task completion time at three- and six-month follow-ups, indicating enhanced performance. Conclusion: The present nutrition intervention encompassed a multi-ingredient approach targeted towards improving cognitive function, but overall had only a limited beneficial impact in the older adult sample investigated. Future investigations should seek to establish any potential clinical applications of such targeted interventions with longer durations of supplementation, or in populations with defined cognitive deficits.

Key words: Cognitive failures, executive function, aging, nutrition, supplementation.

Abbreviations and Symbols: ANOVA: Analysis of Variance; AVLT: Auditory Verbal Learning Test; BMI: Body Mass Index; CFQ: Cognitive Failures Questionnaire; COWA: Controlled Oral Word Association; C-W: Color-Word; DHA: Docosahexaenoic acid; EPA: Eicosapentaenoic acid; INT: Intervention Group; MI: Motor Imagery; MMSE: Mini Mental State Examination; PI: Principal Investigator; PLAC: Placebo Group; PUFA: Polyunsaturated fatty acid; RCT: Randomised controlled trial; SD: Standard deviation; TMT: Trail Making Test; TUG: Timed Up and Go; UCD: University College Dublin; WAIS-III: Wechsler Adult Intelligence Scale III; x̄: Mean.


 

 

Introduction

Cognitive function tends to decline with advancing age. Older adults may experience compromises in memory, attention and executive functioning that significantly impair their capacity to cope with daily social and occupational demands (1). In the quest to understand possible mechanisms, recent research has explored the role of modifiable risk factors, such as physical activity (2) and diet (3), in curbing age-related cognitive decline. Of the dietary factors investigated to date, omega-3 polyunsaturated fatty acids (PUFAs) has the highest evidence-based potential for clinical use (4). The precise nature of this impact, however, remains unclear. To illustrate, in some studies, high omega-3 PUFA consumption is associated with improved cognitive functioning or reduced risk of dementia; whereas in others, no such effect is evident (5-9). A Cochrane review (3) reported on three randomised controlled trials (RCTs) (10-12) in this field and found no benefit of omega-3 PUFA supplementation on cognitive function in healthy elderly. However, more recent RCTs have demonstrated enhanced executive functioning (13) and object location memory task performance (although no effect on the Auditory Verbal Learning Test; AVLT) (14) after omega-3 PUFA supplementation in healthy older adults. Vitamin D insufficiency has been suggested as a potential modifiable risk for age-associated cognitive decline (15, 16). In this regard, two prospective population-based cohort studies (17, 18) examined this association, using the Mini Mental State Examination (MMSE) (19) and at least one version of the Trail Making Test (TMT) (20) in older adults at baseline and follow-up. Again, inconsistency of findings is apparent; whereas poorer cognitive function exists in participants who are vitamin D deficient (17), negligible evidence of a link between vitamin D and executive function or incident cognitive decline has also been observed (18). In addition, a 12-year population-based longitudinal study of 1058 adults (aged >50 years at baseline) found an association between vitamin D deficiency and poorer performance on a range of baseline cognitive assessments, but no association between vitamin D status and task performance or cognitive decline at follow-ups (21). As such, RCTs are warranted to causally determine the benefits, if any, of vitamin D supplementation in the treatment or prevention of cognitive decline.
Emerging research suggests that resveratrol, a polyphenol plant compound, may modulate mechanisms of neuronal aging (22-24). However, the complexity of the biological substrates of polyphenols in cells and animals represents a major challenge in extending this research to humans (25). In this regard, human studies evaluating the role of resveratrol on cognitive function are scant. The beneficial role of whey protein supplementation has also been examined; mostly regarding physiological health outcomes, including enhanced muscle mass (26), increased artery elasticity and decreased risk of heart disease and stroke (27). Despite the significant positive associations between these outcomes and brain function, interventional evidence is lacking on the specific role of dairy constituents in neurocognitive health over the lifespan (28).
In summary, evidence concerning the benefits of nutrition supplementation on cognitive processes in older adults remains inconclusive. Moreover, previous research has focused almost exclusively on the impact of individual ingredients on cognitive function. Against this background, the present study addresses this gap in the literature by experimentally evaluating a six-month multi-ingredient supplement intervention containing omega-3 PUFAs, vitamin D, resveratrol and whey protein on cognitive function in Irish older adults. It was hypothesised that the experimental intervention would improve overall cognitive functioning, executive function, memory, attention, sensorimotor speed, motor imagery (MI) accuracy and subjective awareness of cognitive failures, compared to the placebo condition.

 

Methods

Design

A double-blind RCT was employed to investigate the efficacy of a six-month, multi-ingredient nutrition supplement intervention for improving cognitive functioning in older adults; specifically, effects on executive function, memory, attention, sensorimotor speed, MI accuracy, and subjective awareness of cognitive failures were assessed. For this quantitative, mixed-model design, the dependent variable (“cognitive function”) was analysed with respect to a between-subjects factor of “group allocation” (placebo or intervention group) and a within-subjects factor of “testing occasion” (baseline, three-months, and six-months).

Ethical approval

All study procedures were enacted in accordance with the ethical codes of conduct of the Psychological Society of Ireland and the guidelines of the Declaration of Helsinki (2008, 2013). The research protocol was reviewed under the broader Smartfish® project and granted ethical approval from the University College Dublin (UCD) Human Research Ethics-Sciences Board (reference: LS-13-28-Egan). Participants provided written informed consent prior to study enrolment. No animals were included in this research.

Sample size calculation and study power

To calculate an estimate for sample size, an alpha value of 0.05 and beta value of 0.2 was set to ensure Power would be 0.8. Given our two allocation groups and three testing occasions, this determined that a sample size of 28 participants would be required to detect a medium effect size (f= 0.25) (GPower v3.1). To account for potential drop-out rate, we aimed to recruit more participants prior to randomisation. A post-hoc calculation of our actual power based on 37 trial-completers was conducted and demonstrated a 0.914 power to detect medium effects, in line with our intended goal.

Participants

Participants were recruited via a combination of methods including an advertisement placed in a national newspaper (Irish Times), invitations issued on the UCD alumni website, and recruitment flyers distributed to local elderly organisations and retirement homes. Individuals who expressed interest in the study were invited to UCD and provided with an information leaflet, which addressed issues of confidentiality, anonymity and data protection. At this point, a consent form was signed in the presence of the researcher. Eligibility for participation was then established from a pre-screening examination with a medical doctor. Participants aged 65 years or over, defined as ‘healthy’ (disease free) (29), who were independent, mobile and capable of completing the trial, and who scored above 24 on the MMSE [19] were considered eligible. Potential participants who concurrently fulfilled these inclusion prerequisites, and did not report current or recent (8-week) use of fish oil, or vitamin D or whey protein supplements, were subsequently selected for the trial.
Only participants who completed assessments at all three time-points were included in the statistical analysis (per protocol analysis). The total sample (N= 37) comprised 18 males and 19 females with an overall mean age of 75.14 years (SD= 3.64; range 68- 83 years). Of the 37 ‘trial completers’, 17 had been randomised into the placebo group (PLAC) and 20 had been randomised into the intervention group (INT) (see Figure 1 for a consort diagram detailing study participation). The principal investigator (PI), blind to the assessments, conducted this random allocation procedure by means of a block randomisation. Envelopes were selected from an opaque container, which contained an equal distribution of placebo and supplement. Once an envelope had been drawn it was not returned prior to the subsequent randomisation.

Intervention

In the active arm, the intervention liquid nutrient support (quantity 200mL per day; energy 200kcal per day) comprised 3000mg of long-chain omega-3 PUFAs [as 1500mg docosahexaenoic acid (DHA) and1500mg eicosapentaenoic acid (EPA)], 10μg of vitamin D3, 150mg of resveratrol, and 8g of whey protein isolate. The placebo nutrient support contained 200mL of juice only (energy 100kcal per day). Smartfish®, a Norwegian biotech company, provided both the supplement and placebo as ready-to-drink, palatable, pomegranate and apple flavoured juice formulations, presented in identically sealed TetraPak cartons. The formulations were indistinguishable in appearance and taste, and participants were required to consume their allotted formulation daily for a period of six-months. Research staff and participants were completely blind to group allocation until completion of the data collection. Participants received the juice cartons immediately following their baseline assessment, and these were replenished following their intermediate assessment. Compliance to the supplementation protocol was recorded using a daily tick-box diary completed by each participant.

Cognitive assessments

Between October 2013 and January 2015 data were collected in the Human Performance laboratory at the UCD Institute for Sport and Health. An extensive cognitive assessment battery comprising seven measures was conducted at three time points [baseline, intermediate (three-months) and follow-up (six-months)]. The battery was an English replication of that used in a previous investigation of omega-3 PUFA supplementation and cognitive function (13) with the addition of the Timed Up and Go (TUG) test (30) and the Cognitive Failures Questionnaire (CFQ) (31). The Trail Making Test (TMT) [20] was administered in two parts: Part A assessed sensorimotor speed and visual tracking and part B measured cognitive flexibility. The Auditory Verbal Learning Test (AVLT) (32) examined learning (immediate recall), retention (30-minute delayed recall) and retrieval (30-minute delayed recognition) of newly acquired verbal information. Alternate versions of the AVLT were used at follow-ups to prevent practice effects. The Stroop test (33) was administered as a measure of selective attention, processing speed, and susceptibility to cognitive interference. The version used consisted of two components, namely Color and Color-Word (C-W) tasks (34). The Controlled Oral Word Association test (COWA) (35) measured executive functioning and was administered in two parts to explore phonemic and categorical verbal fluency. The Digit Span test, taken from the Wechsler Adult Intelligence Scale III (WAIS-III) (36), comprised two different tests; the digits forward task, which measured attentional capacity and digits backward, which assessed working memory performance.
The TUG (30) is a chronometric task designed to measure MI accuracy. MI is the mental simulation of an action in the absence of execution (37). The standard version of the task (TUG Real) (38) measures, in seconds, the time taken for participants to stand from a standard chair, walk a distance of three metres, turn around, return to the chair and sit down again. In the MI task version (TUG Imagined), participants perform this task in their imagination and then, signal ‘stop’ to terminate the task. This measure was added to the battery as recent research has focused on the interface between mental and physical functioning, namely MI, as a potential biomarker of cognitive decline (39). Finally, the CFQ (31) is a 25-item self-report inventory that measures cognitive lapses in everyday life. It assesses frequencies of self-reported anomalies in perception, memory and motor function over the previous month. This aspect of cognitive function is often neglected in the literature, which focuses almost exclusively on subtle changes in performance as assessed by objective, lab-based measures. Few studies investigate the relative impact on real day-to-day functioning; and as impaired meta-awareness of cognitive failures has been demonstrated in early neurological conditions (40), this measure was included in the present study to fully establish the clinical utility of the intervention.
Data collection for each of the three testing occasions lasted approximately 45-minutes and was conducted by trained psychology Research Assistants under the supervision of a Clinical Neuropsychologist using scripted instructions and following standardised procedures. Each participant was issued a unique subject number at study entry. To ensure anonymity, only this subject number was used on the data recording forms; no other identifying information was linked to the assessments. Testing was conducted in the same quiet room at approximately the same time in the morning. Consumption of coffee and tea was not permitted before or during testing; participants were provided with a standard breakfast prior to commencement.

Statistical Analysis

IBM SPSS Statistics 20 (41) was used to analyse the data. Preliminary analyses were conducted to compare the placebo and intervention groups on demographics and baseline cognitive function variables (see Tables 1 and 2). Independent samples t-tests were used to compare the groups on continuous variables such as age, height, body mass, body mass index (BMI), number of years of full-time education and baseline cognitive test variables; while chi square tests compared the groups for gender and categorisation of highest qualification.

Table 1. Descriptive and Test Statistics Comparing Baseline Group Characteristics

Table 1. Descriptive and Test Statistics Comparing Baseline Group Characteristics

Note. Abbreviations: INT: Intervention group; PLAC: Placebo group. Gender data expressed as: n male (n female). Age, Height, Body Mass, BMI and Education data expressed as mean (SD). Qualification data expressed as frequency counts.

Table 2. Independent Samples t-Tests Comparing Baseline Cognitive Function Across Groups

Table 2. Independent Samples t-Tests Comparing Baseline Cognitive Function Across Groups

Note. Abbreviations: AVLT: Auditory Verbal Learning Test; CFQ: Cognitive Failures Questionnaire; INT: Intervention group; PLAC: Placebo group; SD: standard deviation; Stroop C-W: Stroop Color-Word Time; TMT: Trail Making Test; TUG: Timed Up and Go.

 

 

Following the protocol of previous research (12, 13), individual cognitive test scores were z-transformed and averaged to generate composite scores for each time point that were grouped for analysis in the following cognitive domains:
Executive function: [Z Phonemic Total + Z Category Total – Z TMT (part B-part A)/part A – Z Stroop (part C-W – part C)]/4
Memory: (ZAVLT Total + Z15 AVLT Delay + Z15 AVLT Recognition + ZDigit Span Backward)/4
Attention: ZDigit Span Forward
Sensorimotor speed: (-ZTMT A Time – ZStroop part C – ZStroop part C-W)/3
To establish a measure of MI accuracy that allowed for comparisons between groups, participants’ durations when performing the TUG Real and TUG Imagined were entered in the following formula, yielding an objective index, namely ‘TUG Delta’ (30):
TUG Delta: [(TUGr – TUGi)/(TUGr + TUGi)/2]*100

Finally, the subjective awareness of cognitive failures variable comprised raw CFQ total scores.
Subsequently, a three-tier hierarchical approach was adopted to test the research hypotheses for a Group X Time interaction as evidence of change due to the intervention (see Table 3). Firstly, a mixed between-within subjects ANOVA investigated whether there was an effect of intervention on overall cognition at six-months using composite variables. The alpha coefficient used as the significance criterion was 0.05. Secondly, each composite variable (executive function, memory, attention, sensorimotor speed, MI accuracy, subjective awareness of cognitive failures) was explored separately using a number of individual mixed between-within subjects ANOVAs. Thirdly, each individual test variable was investigated for an effect of intervention compared to placebo using mixed between-within subjects ANOVAs.
Sensitivity analyses using intention-to-treat methods for dealing with dropout-missing data (last observation carried forward, imputing means of the group, imputing means of the other group) were also conducted, and the inferential analyses repeated. However, as there were no major differences in findings between methods, only the results of the per-protocol analysis of 37 ‘trial completers’ are reported here.

 

Results

Cognitive function data for 37 participants, excluding the 14 dropout participants (27.45%), were available after six-months of the intervention. Seven participants withdrew from the trial before their intermediate assessment (1 male, 6 females; mean age 77.00 ± 5.60 years), and a further 7 withdrew before their final assessment (1 male, 6 females; mean age 73.86 ± 4.45 years). See Figure 1 for more detail on participant recruitment and retention. Chi-square and independent t-test analyses demonstrated that ‘excluded’ participants were not significantly different from ‘included’ participants regarding demographic characteristics or baseline cognitive function.

Figure 1. Consort diagram detailing study participation

Figure 1. Consort diagram detailing study participation

 

Data from the 37 trial completers were inspected for outliers using boxplots and any data points that extended above or below two standard deviations from the mean were excluded from further analysis. In total, 1.98% of data points were excluded as outliers and a further 0.66% of data points were counted as missing.
Continuous variables approximated normal distributions; thus, parametric statistics were utilised. At baseline, groups (PLAC, INT) were matched on demographic characteristics and cognitive function (Tables 1 and 2). Compliance to the supplementation protocol, using the self-report daily tick-box diary, was 95±5% for PLAC and 96±4% for INT.
Using mixed between-within subjects ANOVAs, no statistically significant differences in overall cognitive function or cognitive function domain scores (executive function, memory, attention, sensorimotor speed, MI accuracy and subjective awareness of cognitive failures) were observed for either group over six-months (Table 3). There was no evidence to suggest that the groups differed; that is, there was no difference in the efficacy of the intervention compared with the placebo on these cognitive variables. The effect of time, regardless of group, was significant for overall cognitive function, executive function and memory. Inspection of the z-scored means demonstrated that participants improved on these variables over the multiple testing occasions.

 

Table 3. Mixed Between-Within Subjects ANOVAs for Composite and Individual Test Variables

Table 3. Mixed Between-Within Subjects ANOVAs for Composite and Individual Test Variables

Note. 0, 3 and 6 denote month of testing. Abbreviations: AVLT: Auditory Verbal Learning Test; INT: Intervention group; MI: Motor Imagery; PLAC: Placebo group; SD: standard deviation; Stroop C-W: Stroop Color-Word Time; TMT: Trail Making Test; TUG: Timed Up and Go; *Significance at the .05 level; **Significance at the .01 level; ***Significance at the .001 level; a. Calculated from the formula: [Z Phonemic Total + Z Category Total – Z TMT (part B-part A)/part A – Z Stroop (part C-W – part C)]/4. The resulting data for ‘executive function’ are based on z-scores; b. Calculated from the formula: (ZAVLT Total + Z15 AVLT Delay + Z15 AVLT Recognition + ZDigit Span Backward)/4. The resulting data for ‘memory’ are based on z-scores; c. Calculated from the formula: Zdigit span-forward. The resulting data for ‘attention’ are based on z-scores; d. Calculated from the formula: (-ZTMT A Time – ZStroop part C – ZStroop part C-W)/3. The resulting data for ‘sensorimotor speed’ are based on z-scores; e. Calculated from the formula: [(“TUG” – “TUGi”)/(“TUG” + “TUGi”/2] x 100; f. Calculated from CFQ total scores; g. Significant effect of time for the intervention group, variance ratio F (2, 58) = 8.48; probability (p) <.05;  No significant effect of time for the control group, F (2, 58) = 1.21; p >.05;  No significant group effect at baseline, F (1, 58) = 0.12; p >.05;  Significant group effect at 3-months, F (1, 58) = 14.57; p <.01;  Significant group effect at 6-months, F (1, 58) = 6.53; p <.05.

 

 

This analytic procedure was repeated for all the individual cognitive test variables (Table 3). The only significant interaction between group and time was for ‘Stroop Color-Word Time’. However, it should be noted that a Bonferroni adjustment would remove this effect. Tests of simple effects were conducted to explore the nature of this interaction (see ‘Notes’, Table 3 for exact statistics). Results revealed a significant effect of time (reduction in scores) for the intervention group; no such significant effect was observed in the control group. The tests revealed that groups did not significantly differ at baseline, but by 3-months, the intervention group demonstrated significantly lower time scores than the control group. These effects were also evident at 6-months. This suggests that Stroop Color-Word performance improved over time for the intervention group compared to the placebo group.
No other significant interactions or group effects occurred. However, significant effects for time were observed for TMT A Time, Stroop Color Time and AVLT Delay variables. Using tests of within-subjects contrasts these effects were observed to be linear. Irrespective of group, participants showed a pattern of dis-improvement on the Stroop Color Time and AVLT Delay variables, and a pattern of performance improvement on the TMT A Time, task over the three testing occasions.

 

Discussion

The present study investigated the effects of a six-month multi-ingredient nutrition supplement intervention on cognitive function in community-dwelling Irish older adults. Although some previous research has demonstrated beneficial effects of individual ingredients on cognitive function in interventions with nutrition supplementation, the present study employed a novel multi-ingredient approach with nutrients combined to target cognitive function in older adults. Importantly, the assessment of cognitive function was comprehensive, with only two previous studies in which a comparable range of cognitive outcomes was examined (12, 13). Overall, no statistically significant differences in cognitive functioning or in composite cognitive outcomes were observed between groups over time. Therefore, the hypotheses stating that overall cognitive function, executive function, memory, attention, sensorimotor speed, MI accuracy and subjective awareness of cognitive failures would improve in the intervention group compared to placebo group at six-months were not supported. However, with one exception, Stroop Color-Word performance did improve for participants receiving the intervention compared to the placebo at three- and six-month follow ups. However, it should be noted that a Bonferroni adjustment would remove this effect. Thus, the multi-ingredient nutrition intervention had only limited beneficial impact on cognitive functioning after six-months of supplementation in an Irish, community-dwelling older adult population.
When looking to studies exploring single-ingredient interventions, findings are mixed. Several studies have supported the clinical utility of omega-3 PUFAs for cognitive enhancement and reduced dementia risk (5, 7); while, other similarly designed studies have contradicted such purported benefits (8). These seemingly incompatible reported findings served as a point of departure for a more systematic investigation. To this end, a Cochrane review (3) assimilated data from three interventional studies investigating the impact of omega-3 PUFA (EPA-DHA) supplementation on cognitive function in healthy older adults. The results refuted the purported benefits of omega-3 PUFAs on cognitive function following supplementation of 700mg/day EPA-DHA over 24-months (10), 400mg/day EPA-DHA over 40-months (11), and 1800mg/day or 400mg/day EPA-DHA six-months (12). In contrast, Witte and colleagues (13) assessed the impact of 26-week supplementation of 2200mg/day EPA-DHA on cognitive function in healthy older adults and observed measureable enhanced executive functions in the treatment group. Moreover, a double-blind placebo-controlled proof-of-concept trial found a differential beneficial effect of 2200mg/day omega-3 PUFA supplementation over 26 weeks on recall in an object-location-memory task but not for AVLT performance (14). However, the present study used a similar research design, omega-3 PUFA intervention dose and duration, and comparable cognitive assessment battery, but did not yield concordant results. The present study provided limited evidence for the positive and prophylactic impact of the multi-ingredient intervention (including omega 3 PUFA, vitamin D, resveratrol and whey protein), for maintaining neuronal health in later life.
The effects of vitamin D are also unclear from the previous literature, while some recent research has claimed a beneficial role of vitamin D in neuronal function (17); in contrast, other research reports no association between vitamin D status and cognitive function (18) or decline in cognitive performance over time (21). Here, mixed findings may be attributed to the fact that these studies did not use an interventional design and featured limited cognitive assessment batteries that may have lacked sensitivity for detecting subtle changes in cognitive function in healthy participants. The present study employed a prospective, longitudinal design with double-blind and placebo-controlled contrasts but reports negligible cognitive enhancement by the supplementation investigated.
Studies examining the impact of resveratrol on cognitive function remain in their infancy. Emerging animal and in vitro research suggests that dietary resveratrol may protect against cognitive decline in later life (22, 24). However, human clinical trials in this field are scarce. Moreover, evidence is lacking on the role of dairy constituents, such as whey protein, in cognition (28). Thus, the findings of the present study make an important contribution in this regard too; our results show that the combined omega 3 PUFA, vitamin D, resveratrol and whey protein supplementation did not yield benefits to cognitive function in this older adult sample.
A key challenge in the present study concerned retaining older adult participants in the longitudinal trial; seven participants dropped out before their intermediate assessment and a further seven, before their final assessment. Thus, it is possible that with a larger sample size, the associated increase in statistical power may have detected smaller effects. In addition, stringent recruitment procedures (namely, the pre-screening assessment of cognitive function via MMSE) may have favoured the selection of participants who were healthier than average i.e. the absence of a cognitive deficit. For instance, a recent investigation employing a broadly similar multi-ingredient nutrition supplement (omega-3 PUFAs, vitamin D, resveratrol and whey protein) reported improvements in cognitive function in older adults, albeit with a longer supplementation period and with participants with cognitive impairment ranging from mild to severe (43). Indeed, the majority of the present sample were university alumni. The recourse of educated participants is that the sample may have been unrepresentative of the wider older adult population. This may limit the generalizability of findings and raises issues from the standpoint of determining the efficacy of the intervention.
The study implemented a prospective, longitudinal design with double-blind and placebo-controlled contrasts to establish a causal effect of the intervention. In addition, standardised protocol was followed by trained and supervised researchers for data collection to reduce the potential impact of extraneous factors on cognitive performance. Participants were provided with a standard breakfast, and tested at the same time of day in the same room on both testing occasions. This allowed for the use of an extensive cognitive assessment battery comprising widely-used standardised measures with acceptable reliability and validity for use with the population under investigation. Finally, following previous research protocol, cognitive function was analysed by grouping crude individual test scores into a priori defined composite cognitive domains (12, 13, 30). The assimilation of cognitive measures in this way decreased variation associated with the individual tests, improved robustness of the outcomes and allowed for cross-comparison of findings with previous studies.
Although the present study reported no evidence elucidating the benefits of a combined omega-3 PUFA, vitamin D, resveratrol and whey protein intervention in this older adult sample, the results add to the large body of research in the field of nutrition, health and aging and extend the evidence base to an Irish context. From the perspective of identifying a suitable nutrition intervention to target age-related cognitive decline, current evidences are disappointing. Future researchers can build upon the current findings by conducting longer-term studies with larger more representative samples and incorporating diet and lifestyle measures, to more fully establish the prophylactic impact of the nutritional intervention on cognition.
In conclusion, the present study aimed to examine the impact of a targeted multi-ingredient nutrition supplement intervention, containing omega-3 PUFA, vitamin D, resveratrol and whey protein, on cognitive function. Overall, our findings suggest that the six-months of intervention had, with the exception of improved Stroop Color-Word performance, no beneficial impact on cognitive function in Irish community-dwelling older adults.

 

Acknowledgments: The authors’ responsibilities were as follows- JB, AM, BE, and GDV: designed the research; BE: acted as PI for the trial; CM and ASP: conducted data collection; JB & BR: planned and supervised the analysis; and CM and JB: wrote the manuscript, analysed the data and had primary responsibility for final content. All authors read and approved the final publication. A special word of thanks must be given to the psychology research assistants who assisted with data collection and recruitment; namely, Hannah Stynes, Susan Gibbons, Jane Maguire, Katie Grogan, Naoise MacGiollabhui, and Siobhan Blackwell. We would like to especially thank all the participants who generously contributed their time and efforts into realising this research.

Conflict of Interest: The research described herein was part-funded by Norwegian biotech company Smartfish®. Smartfish® provided the ready-to-drink juice formulations for the nutrition supplement intervention and placebo, but played no role in data collection, data analysis, or in the writing of this manuscript. None of the authors had any conflicts of interest with regard to the research described in this article.

Disclosure statementI: Catherine Moran had no conflicts of interest with regard to this research. Alessandro Scotto di Palumbo had no conflicts of interest with regard to this research. Jessica Bramham had no conflicts of interest with regard to this research. Aidan Moran had no conflicts of interest with regard to this research. Brendan Rooney had no conflicts of interest with regard to this research. Giuseppe De Vito had no conflicts of interest with regard to this research. Brendan Egan had no conflicts of interest with regard to this research.

Ethical standards:All study procedures were enacted in accordance with the ethical codes of conduct of the Psychological Society of Ireland and the guidelines of the Declaration of Helsinki (2008, 2013). The research protocol was granted ethical approval from the UCD Human Research Ethics-Sciences Board (reference: LS-13-28-Egan). Participants provided written informed consent prior to study enrolment. No animals were included in this research.

 

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ANTIOXIDANTS IN THE DIET AND COGNITIVE FUNCTION: WHICH ROLE FOR THE MEDITERRANEAN LIFE-STYLE?

C. Vassalle1, L. Sabatino2, A. Pingitore2, K. Chatzianagnostou1, F. Mastorci2, R. Ceravolo3

1. Fondazione CNR-Regione Toscana G Monasterio, Pisa, Italy; 2. Institute of Clinical Physiology-CNR, Pisa, Italy; 3. Neurology Institute-Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Corresponding Author: Dr. Cristina Vassalle, Fondazione G.Monasterio CNR-Regione Toscana, Pisa, Italy Phone: +39-050-3152199; Fax:+39-050-3153525. e-mail: cristina.vassalle@ftgm.it

J Prev Alz Dis 2017;4(1):58-64
Published online August 16, 2016, http://dx.doi.org/10.14283/jpad.2016.109


Abstract

 This review aims to focus on main antioxidants- abundantly contained in the diet- as well as of the whole Mediterranean diet and life-style and their relationship with cognitive function, especially critical in two phases of life, in children until adolescence and oldness. The role of emerging biochemical and molecular biomarkers as opportunity to estimate more accurately nutritional assumption and requirement, in terms of cognitive preservation and disease risk, will be also discussed.  The cluster of factors within the Mediterranean pattern -which include not only nutritional, but also physical, social, and stimulating aspects- is still largely understudied as a whole, but it is proposed as attractive research area and tool for public health planning of prevention and intervention.

Key words: Nutrition, cognitive decline, aging, Mediterranean diet, Mediterranean life-style, antioxidants, biomarkers.


Introduction

The progressive aging of western population is closely related to increased costs imposed by social-sanitary needs in over 65 subjects. Cognitive decline consists in a deterioration of cognitive function, characterized by increasing difficulties with cognitive processing speed, process information, language, think abstractly and problem solving, including aspects related to memory, executive functioning and reasoning (1). This condition may progress to dementia when the symptoms are severe enough to impact significantly with daily life (2). In this context, cognitive decline often related to progressive loss of personal independence and disability, will represent one of the main problem to face in the future society. Conversely, the knowledge of underlying mechanisms of brain morphology and function will constitute a critical step in developing preventive and therapeutic strategies that meet the demands of an aging society.
Normally, cognitive abilities increase up until adolescence or early adulthood and then they progressively decline. However, the age at which the decline begins and the speed of ability diminishes are highly variable among subjects (Figure 1) (3). Life-style habit, including nutrition and diet, can contribute to individual differences, and early life-phase living conditions may affect late-life health outcomes.

Figure 1. Functional capacity trend along life span and interval of intervention to maintain the best possible levels of brain functionality and prevent cognitive impairment and disability

Therefore, this review will focus on available evidences of single antioxidants or Mediterranean diet (MeD) and their effects on cognitive function in two critical phases of life: 1) from childhood to adolescence and 2) oldness. Moreover, since a low endogenous antioxidant status and inflammation may represent key factors for cognitive decline, the possible use of biomarkers related to these processes as tool to assess the relationship between diet and cognitive decline will be also evaluated. Finally, the cluster of factors within the Mediterranean style-life, still largely understudied as a whole including not only dietary, but also physical, social, and stimulating  factors, is proposed as attractive research area and tool for public health planning of prevention and intervention.

Nutrition in early life and later cognitive function

The effects of nutrition on cognitive function is crucial since pre-birth life and factors like the diet,  intake of folates or maternal vitamin B12 status during pregnancy or lactating have significant impact on successive measures of language, memory, and perception. However, there is a lack of pregnancy and birth cohorts to study ageing from the life-course perspective and to monitor how subjects age according to different biological as well as lifestyle variables (Table 1). In fact, different endpoints have been evaluated mostly in childhood, due to the  many difficulties arising to plan prospective studies with 10 years or more of follow-up (4-7). Moreover, often studies do not include subjects with frankly reduced nutrient status, and in most cases, the retrospective nature of data collection for food insufficiency in childhood may raise concern of recall bias.  In any case, some interesting observations may be extrapolated by available findings, suggesting that malnutrition during the first years of life drives risk for significant functional morbidity in adulthood. In fact, poor living conditions in early life may cause higher risk for chronic conditions such as depression, hypertension, Type 2 diabetes (T2D), and obesity, which in turn may drive to worse neuronal outcomes later during the adulthood. In this context, recent findings from a 40-year longitudinal study suggest that moderate to  severe malnutrition during infancy is associated with impaired IQ and academic skills in adulthood (8). Accordingly, very recent data revealed that food insufficiency in childhood would independently increase the risk of developing dementia in old age by 81%, after adjusting for sociodemographic factors (9). Conversely, results from the  1932 Scottish Mental Survey evidenced that lower B12 at age 79 is associated with cognitive decline between age 11 and 79, while serum folates at age 79 correlates with those at age 11 (10). On 2435 participants in the community-based Coronary Artery Risk Development in Young Adults (CARDIA) study of black and white men and women (18-30 years at the time of enrollment, 1985-86), the diet score was associated with cognitive function of the following 5 years and even 25 years, evidencing the importance of early adoption and maintenance of quality diet to preserve intellectual capacity along all life span (11).

Table 1. Nutrition and age-related cognitive impairment: actual limits and needs

Whether the results of these trials are not simple to perform and interpret in terms of underlying molecular mechanisms, some interesting insights may derive by experimental studies. Interestingly, very recent data suggest that improved cognition in adult rats -subjected to low calorie diet feeding during youth- may result from the increase of brain-derived neurotrophic factor (BDNF) involved in hippocampal neurogenesis (12). In particular, neuronal nuclear antigen-neuron marker expressing cells, which are involved in memory and are located in hippocampus dentate gyrus, resulted increased (12). Moreover, hippocampus and prefrontal cortex BDNF levels were increased, while serum glucose concentration and values of malondialdehyde (marker of lipid peroxidation) appear reduced in serum and hippocampus (12). Thus, BDNF could represent a critical underlying factor in the relationship between nutrition and cognition.

Antioxidants, diet and cognitive decline in elderly

Data from WHO predicted that the occurrence of cognitive impairment and dementia will interest 29 million people worldwide in 2020 (13). This alarming information is anyway alleviated by the prediction that even a small delay of the onset of Alzheimer disease (AD) may markedly reduce the disease prevalence and, consequently, even modest interventions postponing disease onset could translate in a major public health impact (14). In light of this consideration, many studies on the effects of single key nutrients -folate, vitamin B12, and vitamin E- in the elderly have been recently reviewed (15). Authors concluded that supplementation may protect against cognitive decline but only in elderly subjects with low status of these vitamins (for folate is <12 nmol/L or vitamin E intake <6.1 mg/day) (15). No clear definitive data emerge for vitamin B12 (15). Some other studies revealed an interaction between plasma concentrations of folate and vitamin B12 in relation to cognitive performance. In a large population of 2203 Norwegian elderly aged 72-74 years, where cognitive performance was assessed by six cognitive tests, vitamin B12 in the lowest quartile (< 274 pmol/L), combined with plasma folate in the highest quartile (>18.5 nmol/L) were associated with a reduced risk of cognitive impairment (16). Other results from the Framinghan cohort suggested that low vitamin B12 levels (<258 pmol/L) may predict cognitive decline, being a higher cognitive decline rate observed in subjects with low vitamin B12 and high plasma folate (>21.75 nmol/L) or supplemental folates (17).  In other studies, high folate or folic acid supplements resulted detrimental to cognition in older people with low vitamin B12 levels (18). Conversely, a recent study on the effects of 2-year folic acid and vitamin B12 supplementation on cognitive performance in elderly people with elevated homocysteine levels (2,919 elderly participants, ≥65 years) showed no change in cognitive performance (19). Nonetheless, in the Chicago Health and Aging Project (516 participants) higher levels of vitamin B12 were associated with slower rates of cognitive decline, although homocysteine concentration had no relationship to cognitive decline (20).
Recently, there has been increasing interest in the potential of flavanols, contained in fruit and vegetables, to improve cognitive functions in elderly. A high-flavanol intake was found to enhance dentate gyrus activity (hippocampal region considered involved in age-related memory decline), as measured by Functional Magnetic Resonance Imaging and cognitive tests (21). Moreover, these molecules are able to improve regional cerebral perfusion in elderly, which can be one of the possible acute mechanism by which flavanols exert their benefits on cognitive performance (22). Moreover, other data suggested that also the habitual consumption of green tea may be effective in reduce the risk of cognitive decline in elderly population (23, 24). Interestingly, thiamine (or vitamin B1 from cereals, meat, vegetables) deficiency is common in frail elderly (especially hospitalized and institutionalized subjects) and has been related to AD and other neurodegenerative conditions. (25-28). However, the role of thiamine on cognitive function in elderly subjects was recently reviewed, and authors concluded that at now there are no definitive data to clearly recognize the role of thiamine in neurological impairment and disease (28).
Although even the results on a single nutrient may be complex to understand, because often contradictory or associated to variables effect according to nutrient concentration, as in the case of vitamins and homocysteine, studies on the effects of a single food may be further limited because do not focus on the interactive effects with other components in a whole diet. In fact, intake is clearly based on a complex interaction of both macro- (proteins, fats, carbohydrates) and micro-nutrients (vitamins, minerals), and evaluation of the effects of a single nutrient or food could be not satisfactory enough. Actually, an interesting approach to examine the link between nutrition and cognitive function is the evaluation of whole dietary patterns, thus considering potential synergies among nutrients, as found in a balanced diet. In this context, both the Dietary Approaches to Stop Hypertension (DASH) and MeD dietary patterns were associated with consistently higher levels of cognitive function in elderly men and women over an 11-year period in a prospective design (29). These results were confirmed in the 826 Memory and Aging Project (826 participants, aged 81.5 ± 7.1 years) where both the DASH and MeD patterns resulted associated with slower rates of cognitive decline (30). The molecular mechanisms by which DASH and MeD may be related to beneficial effects on cognitive performance have not yet been fully cleared. However, the commonly diffused use of whole grains, nuts and legumes may be responsible for the similar protective effects of both DASH and MeD dietary patterns. This observation may be an important starting point for public-health nutrition recommendations worldwide, according to the wide diffusion of these food types in the diet of majority world populations.

MeD and cognitive decline in elderly

MeD is the food pattern typical of population living in Italy and other Mediterranean countries, characterized by a high fish, vegetable and  fruit consumption,  use of extravirgin  olive oil, low intake of dairy derivatives, sugar infrequent consume, moderate red wine use, red meat consumption (only 1-2 times/week). Noteworthy, a high adherence to MeD is associated with longevity and provides significant protection against morbidity and mortality related to chronic diseases including cancer, metabolic syndrome, depression, cardiovascular and neurodegenerative diseases (31).
There are also findings that a better adherence to MeD may reduce the risk of cognitive decline and some forms of dementia (32). In particular, a meta-analysis assessed the association between the MeD and Mild Cognitive Impairment (MCI) or AD from five prospective cohort studies with at least one year of follow up. Higher MeD adherence confers a reduced risk (33% lower) of developing both MCI and AD, and a reduced risk of progressing from MCI to AD (33). Another meta-analysis evaluated the association between MeD and a number of brain-related conditions, stroke, depression, and cognitive impairment (8 studies covered cognitive impairment), suggesting that high MeD adherence was strongly associated with reduced risk for cognitive impairment (MCI, dementia and AD) (34). These data were confirmed by other results from recent systematic revision and meta-analysis, evidencing that MeD adherence reduced the risk of developing MCI and AD, and the progression from MCI to AD (35-37). The interaction mechanism between MeD adherence and cognition could be almost in part linked to the oleocanthal, an extra-virgin olive-oil bioactive component, recently supposed to be involved in the modulation of tau protein, one of the main causes of Alzheimer neurodegeneration (38). Accordingly, greater adherence to MeD was associated with better scores in several cognitive function tests in elderly subjects (>60 years) living in a Polish rural community (39), thus suggesting some benefits even in non-Mediterranean populations when the main MeD principles were adopted. Conversely, adverse effects of ‘Western’ dietary patterns against the consumption of high vegetable and plant-based diet was evidenced in elderly (>60 years) included in the Australian Diabetes, Obesity and Lifestyle Study (40).

Oxidative stress and inflammatory biochemical markers in the relationship between MeD and cognitive decline

Biochemical markers represent indices of a biological state or condition, measurable in biological samples, especially into the blood. As antioxidants are major determinants of protective MeD effects, the measurements of inflammatory and oxidative stress biomarkers may contribute to fill the gap between nutrition and MeD on one side and age-related cognitive impairment and AD on the other. In particular, MeD adoption increases levels of carotenoids, vitamin A and vitamin E, and reduced oxidative stress and inflammation biomarker levels (e.g. uric acid, SH groups, SOD and GPx activities, FRAP and TRAP, TNF-α, and IL-10 cytokines, and malondialdehyde in the erythrocytes as marker of lipid peroxidation) (41). Recent data also suggested that MeD adherence favorably modifies levels of oxidative stress biomarkers (CoQ and β-carotene, isoprostanes and oxidized low-density lipoproteins) in elderly subjects (42). Some of these oxidative stress and inflammatory biomarkers have been proposed to evidence early risk AD profiles, even in the pre-symptomatic stage, and as additive tools for AD diagnosis, and prognosis (43-46). However, at now, there is scarcity of data on the possibility to modulate levels of inflammatory and oxidative stress biomarkers by nutrients and dietary patterns in patients with MCI or AD. In particular, there are not significant evidences for a role of C reactive protein, a common index of inflammation, in the association between MeD and lower risk of AD (118 incident AD cases during a 4-year follow-up in 1219 non-demented subjects aged  over 65 yrs) (47).
Beneficial effects of MeD have supposed to be related to prevention of shortening of telomeres, nucleoprotein structures that protect the ends of chromosomes, whose integrity is closely related to antioxidant availability (48-50). In this context, results from the PREDIMED-NAVARRA (PREvención con DIeta MEDiterránea-NAVARRA) study evidenced that diet significantly modulates telomere length, as an inverse relationship was observed between obesity parameters (body weight, body mass index, waist circumference and waist to height ratio) and telomere length (48). Telomeres may also retain potential value as risk biomarkers for MCI and AD, as shorter telomere length has been associated with several age-related chronic degenerative diseases (51, 52). Nonetheless, to the best of our knowledge there are no studies which evaluate telomere modulation by MeD in patients with cognitive decline.
The “case” of resveratrol is interesting, because this polyphenol (contained in grapes, some nuts and dried fruits, and red wine) exerts beneficial effects in in vitro models of neudegenerative diseases, including AD, Parkinson and Huntington’s disease, epilepsy, amyotrophic lateral sclerosis, although results on animal and patients are still lacking (53). In particular, its neuroprotective actions appear almost in part related to the  activation of  the sirtuins’ family member SIRT1 (35, 54-56). Increased SIRT1 expression has been related to antioxidant upregulation, and downregulation of pro-apoptotic factors through the involvement of Forkhead box O transcription factors (Fox01-06) and oxidative stress reduction (35). Moreover, SIRT1 negatively regulates p66Shc, that increases intracellular ROS levels through an oxidoreductase activity, and NF-κB, whose DNA-binding capacity is decreased by deacetylation of its RelA/p subunit by SIRT1 (35). Thus, SIRT1, with these multiple effects, has been related to different critical pathways, regarding metabolic control, DNA repair, apoptosis, cell survival, development, inflammation, and mitochondrial function (35). Other components of the MeD can also induce SIRT1, such as the polyphenol quercetin contained in red wine and red onions (57), and polyphenols in extra virgin olive oil (58). Thus, all these nutrients and the MeD as a whole deserve to be evaluated in future studies as safe, no-pharmacological SIRT1 activating tools, able to elicit endogenous neural protection, and preventing MCI and AD.
Interestingly, the emerging interaction between genes and dietary intake may account for the complex interplay between individual shape and external environment, and supports the concept of variable individual response to nutrition and heterogeneity in cognitive ageing. Accordingly, the benefits on lipid profile of fish oil fatty acids eicosapentaenoic and docosahexaenoic acids consumption appeared dependent on Apolipoprotein E genotypes in the 2340 subjects enrolled in the Multi-Ethnic Study of Atherosclerosis (mean age 61±10 yrs) (59).  Moreover, cognitive decline in T2D appears associated with an altered metabolomic profile involving sphingolipids, bile acids, and uric acid metabolism (60). Very interesting experimental data showed how maternal folate depletion and high-fat feeding from weaning may affect DNA methylation and DNA repair in brain of adult mouse, causing a high sensibility to oxidative damage (61). Nutritional interventions in the adulthood could positively counteract epigenetic changes, including DNA methylation and microRNA, associated with ageing (62). However, recent data, obtained on 9-week-old C57BL/6J mice exposed to a high-fat diet for 15 weeks, showed the development of diet-induced obesity and insulin resistance with the onset of irreversible epigenetic modifications in the brain, which persisted also if normal metabolic homeostasis is restored (63). In this context, results from the NU-AGE multidisciplinary consortium of 30 partners from 17 European Union countries are expected. This study aims to evaluate whether a one-year Mediterranean whole diet can affect  physical and cognitive status in the elderly (65-79 years of age), utilizing biomarkers obtained by a series of analyses, including omics (transcriptomics, epigenetics, metabolomics and metagenomics) (64).

Mediterranean life-style and cognitive decline in elderly

The MeD was recognized by UNESCO in 2010 as a cultural heritage of Humanity (65). Although nutritional elements represent the core of the Mediterranean lifestyle, several other aspects must be considered, such as para-dietetic (gastronomy, preparation, setting) and meta-dietetic (cultural) features of MeD, which impact on health and well-being (66). In particular, the Mediterranean Diet Foundation has evidenced additive aspects other than food, such as conviviality, socialization, biodiversity and seasonality, and moderate physical activity as essential complement to the MeD dietary pattern (66). Specifically, frugality and moderation in food consumption characterized this life-style. There is biodiversity and use of seasonal, traditional food, short production and distribution line. In the traditional MeD life-style, family has lunch together at home, food was consumed slowly, with a glass of red wine, conviviality and conversation ensured, together with periods of calm and mid-day rest. Outdoor living included walking, gardening and raising their own vegetables. Moreover, they cook their own food for their own pleasure and others’ satisfaction. The conviviality aspect of eating is important, as it contributes to increase communication and socialization, whereas dedicate time to food preparation and intensify multisensory stimulation through tactile, gustative, and visual stimuli are also involved.  This cluster of factors related in the MeD life-style has not yet been evaluated in association to cognitive function and various diseases. However, it is known that these parameters are individually important to cognitive function and may interact synergistically. Socialization and physical activity resulted associated to a better cognitive performance (67).Very recent studies address mealtimes, seen as an opportunity for social interaction, which may improve health and behavior in elderly people (68-70). Food and physical activity are two parameters closely interrelated, which represent complementary aspects of the energy balance that have regulated brain development and function during human evolution. The combination of an healthy dietary approach together with appropriate physical activities during life-time can contribute to maintain or decrease cognitive impairment (71). Accordingly, dietary factors, such as a diet poor in saturated fat, and exercise have been evidenced as important determinants of cognitive performance in experimental and human studies, modulating neuronal and behavioral plasticity through the increase of BDNF levels (72, 73).

Conclusion

Although there are still main pitfalls (Table 1), available data suggested that amount, content of food, meal frequency and context might represent a non-pharmacological, low-cost, and low-tech interventional option, effective as environmental inducer of brain plasticity for the prevention and improvement of cognitive function across all life span.
The possible use of oxidative and inflammatory biomarkers to assess the relationship between diet and cognitive impairment and neurological disease is also promising, although a substantial amount of work remains in terms of replicating the few findings already available. The rapid development of metabolomics and other “omics” techniques may increase the chance of finding relevant parameters for a more reliable and accurate assessment of association of food intake with functional status and disease risk profile markers. In the future, the identification and use of nutritional biomarkers could allow to estimate more accurately nutritional assumption and requirement, taking into account bioavailability and individual differences, and opening innovative approaches for personalized nutritional plan of cognitive decline prevention.
More important, scientific and clinical medical advances had created a profound evolution in the concept of health, that according to WHO is defined as “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity”. In this context, the concept of synergy between factors within the Mediterranean pattern -which include not only nutritional, but also physical, social, and stimulating aspects- offers the opportunity to evaluate the impact of a comprehensive lifestyle cluster. Such holistic approach may help to develop more efficacious interventional strategies  promoting wellbeing across the life span and preventing disabilities and cognitive impairment  beyond the biological, psychological and social barriers that aging implies.

Conflict of interest: None

 

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DIETARY FACTORS AND COGNITIVE DECLINE

 

P.J. Smith, J.A. Blumenthal

Department of Psychiatry and Behavioral Sciences at Duke University Medical Center, Durham, USA.

Corresponding Author: P.J. Smith, Department of Psychiatry and Behavioral Sciences, Box 3119, DUMC South, Trent Drive, Durham, NC, 27710, USA, patrick.j.smith@duke.edu

J Prev Alz Dis 2016;3(1):53-64
Published online June 1, 2015, http://dx.doi.org/10.14283/jpad.2015.71


Abstract

Cognitive decline is an increasingly important public health problem, with more than 100 million adults worldwide projected to develop dementia by 2050. Accordingly, there has been an increased interest in preventive strategies that diminish this risk. It has been recognized that lifestyle factors including dietary patterns, may be important in the prevention of cognitive decline and dementia in later life. Several dietary components have been examined, including antioxidants, fatty acids, and B vitamins. In addition, whole dietary eating plans, including the Mediterranean diet (MeDi), and the Dietary Approaches to Stop Hypertension (DASH) diet, with and without weight loss, have become areas of increasing interest. Although prospective epidemiological studies have observed that antioxidants, fatty acids, and B vitamins are associated with better cognitive functioning, randomized clinical trials have generally failed to confirm the value of any specific dietary component in improving neurocognition.  Several randomized trials have examined the impact of changing ‘whole’ diets on cognitive outcomes.  The MeDi and DASH diets offer promising preliminary results, but data are limited and more research in this area is needed.

Key words: Dietary patterns, nutrition, cognitive function, dementia.


Background

Epidemiology of Cognitive Impairment

Cognitive impairment is an increasingly pressing public health problem worldwide (1). The World Health Organization has estimated that 35.6 million individuals worldwide had dementia in 2011 and that the prevalence of dementia will double every 20 years, corresponding to an alarming 65.7 million individuals living with dementia in 2030 and 115.4 million adults worldwide by 2050 (2, 3).  In addition, the public health cost of dementia is staggering, with an estimated $604 billion dollars spent on dementia care in 2010 (4). In addition to prevalence and significant public health impact of dementia, an additional 5.4 million individuals have cognitive impairment that does not reach the threshold for dementia (e.g., cognitive impairment, no dementia [CIND] and mild cognitive impairment [MCI]) (5). Taken together, cognitive impairment is becoming increasingly common as the population in the United States ages and represents a significant public health problem.           

Lifestyle modification as a means of protecting against cognitive decline has only recently been embraced as a possible, alternative strategy to reduce the incidence of cognitive decline (6). Due to increasing epidemiological(7-10) and experimental evidence linking lifestyle factors to preservation of cognitive function, recent conference and consensus reports have emphasized the importance of dietary factors (reduced intake of saturated and trans fats, increased vegetable and fruit consumption, and dietary intake of vitamins E and B12)(11) and regular exercise (40 minutes of brisk walking 3 times per week), as public health recommendations to reduce the risk of Alzheimer’s Disease (AD) (6, 11). Lifestyle interventions have tended to focus on the impact of aerobic exercise, although recent studies have also suggested that dietary patterns may play an important role (12).

Methodological Considerations

As noted below, methodological differences appear to have an important role in understanding the impact of dietary intake on cognitive function. The most important methodological difference is observational vs. interventional methodologies: although observational studies have tended to support a relationship between greater intake of various nutritional components, interventional studies have generally reported equivocal findings. It is also worth noting that assessments of dietary intake and cognitive function have also varied significantly across studies, which may impact the overall pattern of findings.

Definitions of Cognitive Decline, Cognitive Impairment, and Dementia

Studies included in the present review have used varying definitions of dementia, cognitive impairment, and cognitive decline. Cognitive decline represents a ‘significant’ change in cognitive performance from a premorbid, baseline level (13-16). Cognitive impairment typically refers to one of a number of different clinical conditions specified by consensus statements and is  typically diagnosed based on clinical criteria (cognitive performance, clinician interview, and/or neuroimaging), including mild cognitive impairment (MCI: cognitive deficits that do not reach dementia severity and preserved activities of daily living) (17), vascular dementia (VaD)(18), and AD (19). In addition to the above, categorical definitions of cognitive function, many studies have used a continuous measure of cognitive performance within various cognitive domains, including memory, attention, processing speed, visuospatial performance, and executive functioning, although memory and executive function are more often used as the primary cognitive outcome measures (20).

Methods for Assessing Dietary Habits 

Several different assessment methods have been used to quantify patterns of dietary habits. These methods have primarily been self-report measures, such as food frequency questionnaires and diaries, although serum biomarkers have also been used in a handful of studies (21, 22). Food frequency questionnaires (FFQs) are one of the most commonly used methods to assess the relationship between dietary patterns and medical outcomes (23). Multiple FFQs are available, including the Willett FFQ developed at Harvard (24) and the Block FFQ(25). FFQs are typically structured such that the participants ‘typical’ dietary patterns are measured over the course of a period of several months to a year. The primary advantage of FFQs over dietary diaries is that they provide a measure of dietary intake over a longer period of time, although these instruments also rely heavily on patient recall and may therefore be subject to recall biases (26), which is particularly important in the study of cognitive function (27). Diet diaries are used to provide a more comprehensive, if more time-limited, assessment of dietary intake and are considered by some to be the ‘gold standard’ of assessment of dietary patterns (28, 29), despite known limitations (30-34). Participants are typically required to record everything they eat over a period of several days, typically including both weekdays and weekend days; sometimes the ‘most representative’ days are selected for analysis. The primary advantages of diet diaries are that they provide a comprehensive assessment of dietary intake and, when completed properly, are less vulnerable to recall biases (35, 36). The primary limitation of these techniques is that they only provide an assessment of dietary intake over a period of a few days and the diet may be affected by the increased awareness of food consumption and may therefore not be representative of regular dietary habits (34).

Although less commonly used, biomarkers provide a somewhat more objective measure of actual serum nutrient composition, providing a quantification of the amount of B vitamins, antioxidants, and fatty acids, among others from plasma samples. However, biochemical markers are also biased by individual differences in metabolism and absorption levels, and can also be affected by illnesses, medications, and genetic factors. Nevertheless, several studies have used these measures to examine the relationship between objective markers of nutrient intake and cognitive outcomes (37, 38). The primary advantage of biomarkers is their objective assessment of nutrient composition presumed to have been consumed, although these results may only reflect dietary intake at a particular time point and may be cumbersome, expensive, or infeasible in some epidemiological studies.

Dietary Components and Neurocognition

B Vitamins and Folate

Observational Studies

The relationship between folic acid (B9), pyridoxine (B6), and cobalamin (B12) has been the subject of extensive study, with multiple epidemiological studies demonstrating that individuals with higher blood levels of these nutrients demonstrating a lower likelihood of cognitive decline (39-47). B vitamins and folate are thought to exert a beneficial effect on cognition through metabolism of homocysteine (48), a protein that has been associated with greater cardiovascular risk and cognitive impairment. The relationship between poor nutritional status and cognitive decline was first described by Goodwin and colleagues (49), who noted that individuals with low levels of vitamins C and B12 scored more poorly on the Wechsler Memory Test. Following this initial publication, multiple epidemiological studies have reported a relationship between higher levels of B vitamins and folate and lower rates of incident dementia. Among older adults participating in the Kungsholmen longitudinal study in Sweden who were not being treated with B vitamin supplementation (50), those with low levels of both B12 and folate were more than twice as likely to develop dementia over a three-year follow-up and this relationship was even stronger in sub-analyses among individuals with higher baseline cognitive function.  Similar results were reported in a sample of older adults living in Manhattan (51): individuals in the highest quartile of folate intake were 50% less likely to develop AD over a six year follow-up and these results remained significant after controlling for total energy intake, cardiac disease, and APOE genotype. Not all epidemiological studies have reported similar findings, however: Morris and colleagues failed to find an association between B-6, B-12, and incident Alzheimer’s disease in more than 1,000 older adults participating in the Chicago Health and Aging Project (CHAP) (52).

Interventional Studies

Despite the encouraging findings of prospective studies, randomized trials have generally failed to replicate these positive findings. Multiple randomized trials have been conducted and several associated meta-analyses have also examined these findings (40-42). A recent meta-analytic review found no improvement following treatment with folic acid, with or without B vitamins, on cognitive function within four different domains of performance (memory, language, speed, and executive function)(53). In a systematic review of randomized controlled trials (RCT), Balk and colleagues (54) noted that existing trials have generally been small and have included heterogeneous outcome measures with few clinically validated outcomes. After identifying 14 trials, three trials of vitamin B6 and six trials of B12 were found to be acceptable for analysis.  None of the available interventions reported cognitive benefits associated with supplementation across a variety of doses, modes of administration, and populations.  Three trials examined the effects of folic acid, only one of which reported a benefit in cognitive function among individuals with cognitive impairment and low baseline serum folate levels.  Interestingly, all six trials that utilized various combinations of B vitamins concluded that the interventions had no impact on cognitive function and, among these, half reported that the placebo arm outperformed treatment participants on several cognitive tests.

Three Cochrane collaboration reports lend further credence to these findings.  In a systematic literature review, Malouf and Grimley (42) examined the effects of folate supplementation with and without B12 in the maintenance of cognitive function, as well as the prevention and treatment of dementia.  Eight RCTs met inclusion criteria: four among healthy, older adults and four among participants with mild to moderate cognitive impairment or dementia with or without diagnosed folate deficiency.  Two of these studies utilized a combination of folic acid and vitamin B12 and the majority of existing studies were successful in boosting B12 levels and, accordingly, reducing homocysteine concentrations.  Among healthy, older adults, there was no consistent evidence that folic acid supplementation with or without vitamin B12 improved cognitive function. A separate Cochrane database review conducted by Malouf and Sastre (41) reported similar findings in an examination of the effects of B12 on cognition, specifically.  Three trials were included, all of which examined this association among individuals with cognitive impairment and low levels of serum B12.  None of existing trials reported beneficial effects of B12 supplementation on cognitive function across patient groups and modes of administration.  Malouf and Grimley (40) have also examined the effects of B6 on cognitive function among both healthy, older adults as well as individuals with cognitive impairment and dementia.  In their Cochrane review, the authors reported that few RCTs had examined the effects of B6 among older adults and that none had examined these effects among individuals with cognitive impairment.  Among the two trials included in their review, neither demonstrated an effect of B6 supplementation on cognitive function.  More recently, Kang and colleagues (55) examined the effects of B6, B12, and folic acid among 2,009 women aged 65 years and older with cerebrovascular disease (CVD) or > 3 cardiovascular risk factors participating in the Women’s Antioxidant Cardiovascular Study.  Results showed that the trial was largely ineffective in delaying cognitive decline, but that a subgroup of women with low B vitamin levels at baseline demonstrated modest cognitive benefits.  Taken together, the vast majority of existing trials have failed to find a benefit of B6, B12, or folate supplementation on cognitive function.

Several individual trials warrant comment. In a 2-year randomized trial of folic acid, vitamin B-12, and physical activity, folic acid supplementation was associated with improvements in the Telephone Interview for Cognitive Status-Modified (TICS-M) (56). In a randomized trial of 271 older adults with MCI (168 of whom had magnetic resonance imaging assessments), treatment with high dose folic acid, B12, and B6 was associated with lower brain atrophy following two years of treatment (57).  A three-year RCT among individuals with elevated homocysteine conducted in the Netherlands also reported positive findings. Participants randomized to receive folic acid showed improvements in memory, information processing speed, and sensorimotor speed compared with placebo (58). However, not all trials among individuals with elevated homocysteine have reported positive findings(59). In addition, two pilot studies among individuals with cognitive impairment have reported positive findings. Among individuals with AD, folic acid supplementation improved response to cholinesterase inhibitors and was associated with cognitive gains in instrumental activities of daily living and social behavior (60). Similarly, a small pilot study of 12 patients with mild-to-moderate AD showed cognitive gains following nine months of supplementation (61). Taken together, existing evidence linking folate and B vitamin supplementation with cognitive benefits is mixed. Although there is weak evidence that supplementation may be beneficial among individuals with pre-existing cognitive impairment or elevated homocysteine, these results have not been consistent.  

Fatty Acids

Observational Studies

Dietary fatty acids are classified by two general subtypes: saturated fatty acids and unsaturated fatty acids.  Among these subtypes, unsaturated fatty acids may be further divided into monounsaturated (MUFAs) and polyunsaturated fatty acids (PUFAs).  Saturated fatty acids are derived primarily from meat and dairy products, as well as other dietary sources utilizing animal fats.  An important component of dietary fat consumption is the levels of n-3 and n-6 PUFAs, commonly referred to as omega-3 and omega-6 fatty acids (62).  n-3 PUFAs are primarily derived from fish and marine sources and consist of eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and α-linoleic acid (ALA), among others. In contrast, n-6 PUFAs are primarily derived from legumes, nuts, and other plant-based sources and consist of linolenic acid and arachidonic acid, among others.

n-3 fatty acids may be associated with lower incidence of cognitive impairment through their direct influence on neuronal membrane integrity. The brain is enriched in DHA, which accounts for about eight percent of its dry weight (63), and DHA, a long-chain n-3, helps support both structural integrity and functionality of neurons. Cross-sectional studies have linked greater intake of n-3 fatty acids to greater total brain volume (64) and lower prevalence of white matter hyperintensities (38). Evidence from animal models also suggests that greater n-3 intake may impact cognitive decline by lessening the impact on amyloid deposition within the brain (65). In addition, n-3 consumption is known to reduce the impact cardiovascular morbidity (66, 67) and inflammation (68-71), although not all existing evidence supports this hypothesis (72).

Multiple prospective studies have examined the relative intake of these dietary components and subsequent cognitive dysfunction (69, 73).  The majority of extant studies have reported a similar pattern of findings: greater fat intake is associated with greater risk of cognitive dysfunction and dementia, whereas greater intake of n-3 relative to n-6 fatty acids is associated with lesser risk of these outcomes.  Results have also been relatively consistent across outcomes, with studies examining changes in cognitive function reporting similar findings to those studies examining the incidence of MCI, VaD, AD, and other types of dementia.

Two of the largest studies to examine this relationship come from the Cognitive Health and Aging Project (74) and the Atherosclerosis Risk in Communities project (ARIC)(67). Morris and colleagues (74) examined the relationship between saturated and trans-unsaturated fat in predicting cognitive decline among 2,560 individuals participating in the Chicago Health and Aging Project. Individuals in this trial did not have a history of stroke, heart disease, or diabetes at baseline. Examination of 6-year changes in cognitive function indicated that higher dietary intake of saturated or trans-unsaturated fats or low nonhydrogenated unsaturated fats was associated with a greater incidence of cognitive decline.  Beydoun and colleagues (67) conducted an analysis of ARIC in which 2,251 patients who were either hypertensive or dyslipidemic were analyzed as an at-risk group at three time points, spanning twelve years.  Consistent with previous findings, those individuals with higher plasma levels of n-3 PUFAs were less likely to exhibit decline on cognitive measures of verbal fluency, although these individuals did not exhibit improved performances on measures of delayed memory or psychomotor speed.

In addition to the existing relationship with cognitive decline, higher PUFA intake appears to be linked with lower incidence of clinician-diagnosed dementia. Modest dietary fat intake and greater fish consumption were both associated with reduced rates of dementia in a sample of 5,386 individuals participating in the Rotterdam study (75). During a two-year follow-up, the authors found that greater dietary intake of total fat, saturated fat, and cholesterol were all predictive of incident dementia and were most strongly associated with reduced risk of VaD.  Similar to their previous study, greater fish consumption was protective against the development of dementia and appeared to be most strongly protective against the development of AD.  A protective effect of fish consumption on the development of AD was also reported in the PAQUID (Personnes Agees QUID) cohort study (76) and in the Chicago Health and Aging project (77, 78). Solfrizzi and colleagues (79) have extended these findings, examining the relationship between PUFA intake and the development of MCI among 464 non-demented older adults participating in the Italian Longitudinal Study of Aging.  During an approximate 3-year follow-up of participants, higher intake of PUFAs appeared to protect against the development of MCI.  However, this relationship was attenuated following adjustment for possible confounders.  Given the small sample size of individuals who developed MCI in this study (n=18), the protective effects of PUFAs for MCI remain to be elucidated.

Although the results of longitudinal studies have been generally consistent, important negative findings also warrant attention.  Engelhart and colleagues (80), in a subsequent analysis of individuals from the Rotterdam study, failed to find an association between high intake of total fat, saturated fat, trans fats, cholesterol, and the subsequent development of dementia.  In contrast to the Kalmijn study, this analysis utilized a longer follow-up period (6 years instead of 2).  In addition to the negative findings for dietary fat intake, consumption of fatty acids did not appear to protect against the development of dementia. These discrepant findings have yet to be reconciled.

Interventional Studies

Despite the encouraging findings from observational data and small pilot trials (81-83), large, well-controlled randomized trials have generally failed to find significant benefits (84). In a randomized, double-blind, placebo-controlled trial, van de Rest and colleagues (85) found no effects of omega-3 supplementation among 321 healthy adults, aged 65 years and older.  In their study, participants were assigned to a 26-week treatment in which they received 1,800 mg/day, 400 mg/day, or placebo capsules.  Prior to treatment and again following the 26-week protocol, participants completed an extensive neuropsychological test battery, including measures of attention, sensorimotor speed, memory, and executive function.  Despite substantial increases in plasma concentrations of EPA and DHA, neither of the treatment groups exhibited improvements in cognitive performance.  In a 6-month randomized controlled trial of n-3 supplementation, Freund-Levi and colleagues (86) reported similar results among 204 patients with AD.  After 6-months of treatment, the groups did not differ in cognitive performance, although sensitivity analyzes revealed that individuals with very mild impairment (i.e., MMSE > 27 points) exhibited modest cognitive benefits. Recently a Cochrane analysis was conducted to examine the impact of omega-3 interventions on cognitive function (84). Following a literature review, the author identified three randomized trials for inclusion (87-89) incorporating data from 4,080 individuals. Results showed no differences in cognitive outcomes between treated and control participants when results were combined across the three trials.

Antioxidants

Observational Studies

Antioxidants, including vitamins A, C, and E, are found naturally in many fruits, vegetables, and berries, and also can be taken as supplements. Initial interest in the role of antioxidants in cognitive decline was generated from observational studies demonstrating that greater intake of fruits and vegetables were shown to be associated with better cognitive function and lower risk of cerebrovascular events (90, 91). Greater antioxidant intake is hypothesized to prevent age-related neurologic dysfunction because brain tissue contains low levels of endogenous antioxidants and is therefore particularly vulnerable to free-radical damage(92).  Oxidative stress has been implicated as one of the primary mechanisms of age-related neuronal decline (93, 94). Perhaps not surprisingly, greater intake of fruits and vegetables has been linked to lower rates of cognitive decline and dementia in multiple prospective studies, including the Chicago Health and Aging study, and this effect appears to be independent of cardiovascular comorbidities (95). Greater vitamin E intake was associated with better cognitive function in the same cohort (96) over an 18-month follow-up, and results suggested a dose-dependent protective effect of vitamin E intake, either from diet or supplement use, and lower rates of cognitive decline.  Secondary analyses revealed that the protective effects of vitamin E were strongest among individuals with higher intakes of vitamin E from dietary sources relative to individuals with low vitamin E dietary consumption taking supplements.  Interestingly, vitamin C was not protective against cognitive decline in this study.  Supplementation with either vitamin C or E also appears to be related to reduced risk of cognitive decline (97). In a sample of 3,385 men participating in the Honolulu-Asia Aging Study, use of either vitamin C or E was associated with better cognitive performance when participants were assessed 6-8 years later.  Participants who were taking both vitamin C and E tended to exhibit better cognitive performance than individuals taking only one of these supplements.  In contrast, individuals taking both supplements were less likely to develop VaD, and mixed/other dementias, although the use of supplements did not appear to protect against the development of AD.

Several studies have reported protective effects of vitamins C and E on the development of AD, including a study of 5,395 individuals participating in the Rotterdam study (98). Among adults 55 years of age or older, higher intake of vitamins C and E were associated with dose-dependent reductions in risk for AD over a 6-year follow-up, and this relationship was strongest among current smokers. In addition, current smokers with higher intakes of beta carotene and flavanoids showed lower rates of AD, although these factors did not appear to be protective among non-smoking participants.  This study was strengthened by its careful control of confounding variables including the use of antioxidant supplements, presence of carotid plaques, total energy intake, and baseline MMSE performance.  Finally, higher intake of flavonoids, phenolic compounds found in red wine and berries, have been associated with reduced rates of cognitive decline (99) and dementia (100) in several longitudinal studies.

Interventional Studies 

Several RCTs have investigated the effects of Vitamin E and/or C supplementation in the prevention of cognitive decline (101, 102). In one of the most comprehensive review of these trials to date, Isaac and colleagues (101) examined the effects of vitamin E in the treatment and prevention of AD and MCI.  Based on their comprehensive literature search, only two trials met inclusion criteria, incorporating data from two studies, one among AD patients (103) and the other among individuals with MCI (104).  In their study of 341 patients with AD of moderate severity, Sano and colleague s (104) examined the effects of selegiline, alpha-tocopherol, or placebo in slowing the progression of AD over a two-year period. Although the study’s primary outcome was the effects of medication on a composite end-point of death, institutionalization, or loss of activities of daily living, the authors found in secondary analyses that individuals randomized to receive either selegeline or alpha-tocopherol were less likely to be institutionalized during follow-up. In their study of 769 individuals with MCI, Peterson and colleagues (105) examined whether the administration of either vitamin E supplements or Donepezil might slow the progression to AD.  Although neither treatment group appeared to benefit from therapy after 3 years of follow-up, pre-planned analyses every 6-months demonstrated that both treatments showed a slower rate of conversion to AD during the first year of treatment and that this effects was most pronounced among individuals with the APOE-4 genotype. At least one study has suggested that treatment responsiveness may be a critical factor impacting AD outcomes in these trials. Lloret and colleagues (106) found that patients who responded to vitamin E treatment with reduced oxidative stress were less likely to develop AD(106). However, among individuals who did no experience a decrease in oxidative stress, cognitive function actually appeared to worsen relative to placebo controls, suggesting that patients’ response to treatment is an important factor impacting the impact of antioxidants on treatment outcomes. Finally, a recent Cochrane review suggested that progression of MCI to AD was not significantly impacted by vitamin E treatment (102). Taken together, results from the extant literature are mixed and do not provide compelling evidence for a beneficial effect of antioxidants on cognitive decline.

Observational Studies of Non-specific Diets: Analysis of Dietary Components

Several studies have examined multiple dietary patterns within a single sample by clustering various components of participants’ diets using principal components analysis. In contrast to many of the other studies cited above, these studies have simultaneously examined multiple dietary patterns without an a priori focus. In a study of older adults living in New York, a dietary pattern comprised of higher levels of n-3 and n-6 fatty acids, vitamin E, and folate, and lower levels of saturated fatty acids and B12 was associated with reduced risk of developing AD over a four-year follow-up (107). Individuals in the highest tertile of this dietary pattern were 38% less likely to develop AD compared with those in the lowest tertile. Another study of nutrient biomarkers examined the relationship between nutrient content from plasma samples and their association with brain imaging markers (38). In this study of 104 older adults (mean age 87 years), several nutrient patterns emerged and were found to be associated with both cognitive performance and neuroimaging markers of brain health. Nutrient patterns consisting of high levels of B vitamins, vitamins C, D, and E was associated with greater brain volume and cognitive performance within several domains, whereas dietary patterns consisting of higher levels of n-3 fatty acids were associated with lesser white matter hyperintensities and better executive function. A third pattern consisting of high levels of trans fatty acids was associated with lower total brain volume and also with worse cognitive performance across several domains.

Whole diet Eating Plans and Neurocognition

In contrast to the impact of specific nutrients, more general patterns of dietary intake emphasize the overall consumption of various dietary practices. The primary advantage of examining dietary eating plans compared to specific nutrients is that it allows for an examination of the ‘food matrix’ effect on biological systems, which includes additive, synergistic, and antagonist effects (108, 109). This approach may be particularly important in the study of cognitive decline, which is likely influenced by multiple factors (110). The primary limitations of studying patterns of dietary behavior are that the potential influence of individual nutrients might be obscured and the quantification of these scores is often sample-dependent. For example, the MeDi score, which is the most commonly used metric for the Mediterranean diet, is based on a sum of sex-specific medians of a population, in which a score of one is given if an individual is above the median for ‘beneficial’ components of MeDi (e.g. fruits, vegetables, whole grains, etc.) and a score of 0 is given when an individual falls below the median. Not only can two individuals with the same MeDi score have vastly different diets, but the scores may be different when derived from two different samples (108).

Several dietary patterns have been examined as they relate to cognitive decline, principally among them the Mediterranean Diet (MeDi) and the Dietary Approaches to Stop Hypertension Diet (DASH) eating plan. Other studies have examined the Alternative Healthy Eating Index (111), the Healthy Diet Indicato r(112), the Healthy Eating Index and the Canadian Healthy Eating Indices (113), the French National Nutrition and Health Programme Guideline Score (114), the Comprehensive Healthy Dietary Pattern(115), and the Recommended Food Score (116).

Mediterranean Diet (MeDi)

Observational Studies 

The Mediterranean diet has received substantial attention due to its focus on fish intake, vegetables, legumes, fruits, cereals, and unsaturated fatty acids (117, 118).  In addition, this diet is characterized by a low intake of dairy products, meat, and saturated fatty acids, as well as regular, modest intake of alcohol. Multiple prospective studies have shown that individuals with more Mediterranean diets are less likely to experience cognitive decline or develop dementia (118). Both the Mediterranean and DASH diets, discussed below, are believed to impact cognitive function indirectly through reducing CVD risk factors. The Mediterranean and DASH diets are known to have a beneficial effect on CVD health (119, 120) and there is substantial evidence that increasing CVD risk factors are associated with greater risk of cognitive impairment (121-124). For example, reducing lipid levels has been shown to reduce the incidence of stroke and VaD (125) and insulin resistance has been implicated in the pathogenesis of AD (126).

In a study of 2,258 community-dwelling, non-demented New Yorkers (118), adherence to the Mediterranean diet was associated with lower likelihood of developing AD over an approximate four-year follow-up.  Compared to individuals in the highest quartile of dietary adherence, individuals with poor Mediterranean dietary practices had an approximately 40% greater risk of developing AD. These results were unchanged in a subsequent study among the same cohort after controlling for measures of vascular functioning, leading the authors to conclude that the observed relationship between dietary fat and AD is not mediated by vascular health (117). Similar results were reported by the same group in examining the relationship between MeDi and the development of MCI: greater adherence was associated with dose-response protection against incident MCI, with an 8% reduction in risk of MCI for every one-unit increase in the MeDi score (127). Greater MeDi adherence has also been associated with lesser cognitive decline in several epidemiological studies (113, 127) as well as lower risk of cognitive impairment in the REGARDS cohort study, particularly among individuals with diabetes (128). Although the precise mechanisms linking the MeDi to reduced cognitive impairment are still being explored, at least two studies  have demonstrated that greater MeDi adherence is associated with preserved cortical thickness (129) and a lower incidence of MRI infarcts . A recent meta-analysis combining results across five studies found that higher adherence to the MeDi diet (highest tertile) was associated with a 27% reduced risk of MCI and a 36% reduced risk of AD among cognitively normal adults (131).

Interventional Studies 

Despite the encouraging findings from observational studies, only one RCT has examined the effects of the MeDi on cognitive performance. In the recently completed PREMEDI trial (120), 522 adults with elevated risk of CVD were randomized to receive a MeDi diet supplemented with extra-virgin olive oil, a MeDi diet supplemented with mixed nuts, or a control diet. The primary endpoint in this RCT was major cardiovascular events and the trial was stopped early after a median follow-up of 4.8 years.  Results showed that both the MeDi intervention arms had reduced rates of cardiovascular endpoints, particularly stroke, in comparison with the control arm. In addition to improving CVD outcomes, the MeDi interventions improved global cognitive performance as indexed by performance on the Clock Drawing Test and the MMSE (132). At least one other ongoing study is expected to examine the relationship between MeDi and neurocognition (133).

Dietary Approaches to Stop Hypertension (DASH)

Observational Studies 

The Dietary Approaches to Stop Hypertension (DASH) eating plan is similar to the MeDi diet in its emphasis on greater intake of fruits, vegetables, and whole grains. Similar to the MeDi, the DASH diet emphasizes consumption of low-fat dairy products, modest meat consumption, and modest alcohol consumption, although the DASH diet also emphasizes low sodium intake. The DASH diet was originally designed to reduce high blood pressure and its effectiveness has been demonstrated in several randomized trials in both ‘feeding studies’ (134, 135) and in free-living individuals (119). Greater DASH adherence has also been associated with greater blood pressure reductions (136) and reduced risk of stroke (137). Preliminary evidence suggests that, like the MeDi, individuals who are more adherent to a DASH-style diet have a lower incidence of cognitive decline. For example, DASH diet adherence was also associated with lower rates of cognitive decline among older adults participating in the Memory and Aging Project during a 4-year follow-up (138).

Interventional Studies

To knowledge, only the ENCORE study (119) has examined the effects of the DASH diet, alone and combined with exercise and caloric restriction, on neurocognition in overweight adults with high blood pressure. In this trial, 144 middle-aged, overweight or obese adults with high blood pressure were randomly assigned to one of three conditions for four months: the Dietary Approaches to Stop Hypertension (DASH) diet alone (DASH-A), the DASH diet in combination with a weight management intervention (DASH+WM), in which participants exercised regularly and reduced their caloric intake, or a Usual diet control group in which participants maintained their usual dietary habits and did not exercise or lose weight. The primary findings from the trial were that the DASH+WM and DASH-A groups showed significant reductions in blood pressure compared to controls, while the DASH+WM group also showed reductions in bodyweight and improvements in other markers of cardiovascular health including LVH, arterial stiffness, and insulin resistance (119, 139). In addition to measuring CVD health, participants completed a battery of cognitive tests assessing executive function, memory, learning, and psychomotor speed. Following the four-month intervention, individuals in the DASH-A group showed improvements in psychomotor speed compared with controls, while individuals in the DASH+WM group showed improvements in both psychomotor speed and a composite measure of executive function, learning, and memory (140). These improvements appeared to be greatest among individuals with greater levels of intima medial thickness, a surrogate marker of atherosclerosis, and were associated with improvements in fitness and weight loss.

Several ongoing studies are examining the effects of dietary factors on neurocognition. The ENLIGHTEN trial is an ongoing randomized trial examining the effects of the DASH diet and/or aerobic exercise on cognitive function among individuals with vascular CIND (141). In this trial, patients with vascular CIND will be randomized to receive supervised aerobic exercise, the DASH diet, a combined exercise and DASH intervention, or a health education condition for six months. Cognitive function, CVD risk factors, aerobic fitness, and dietary composition will be assessed before and after the intervention to examine mediators of any treatment improvements.

Caloric Restriction

Observational Studies

Accumulating evidence over the past two decades, particularly in animal models, suggests that lower caloric intake may be associated with reduced risk of cognitive decline (142, 143), although emerging evidence in humans suggests that caloric restriction and weight loss may be associated with improved cognitive function (144). Only a handful of studies in humans have been conducted in humans, although preliminary evidence suggests that caloric restriction confers cognitive benefits (145). For example, a prospective study of nearly 1,000 older adults in the United States found that greater caloric intake was associated with increased risk of AD and that this relationship was stronger among individuals with APOE-4 genotype (146). In addition, observational studies of Okinawan adults, the longest living population on the planet, has demonstrated through archival data that Okinawan centenarians have markedly reduced caloric intakes relative to a normative sample selected from the NHANES I study (147).  

Interventional Studies 

Several RCTs have examined the impact of caloric restriction on cognitive function, with varying results (145, 148-150). In one study, a three-month caloric restriction intervention improved memory performance among fifty healthy, elderly adults who were either normal weight or overweight. Following three months of treatment, individuals randomized to the caloric restriction group showed improvements in verbal memory performance. In addition, these improvements were associated with decreased levels of fasting insulin and C-reactive protein and were strongest among participants with the best adherence. Finally, in the ENCORE randomized trial mentioned above, participants in the exercise and DASH group, who were also asked to reduce their caloric restriction, showed the greatest cognitive benefits (140). Despite these positive findings, three other trials examining caloric restriction failed to find significant effects, which may partly due to the younger age of participants in these trials (148-150). Several ongoing trials are examining the impact of caloric restriction on cognitive performance among individuals with MCI (151, 152).

Summary and Future Directions

Existing evidence from observational studies suggests that dietary factors including antioxidants, fatty acids, folate, and B vitamins are associated with lower incidence of cognitive decline, stroke, and dementia in the majority of observational studies. However, despite a wealth of data from prospective studies, few interventions have reported positive effects of nutritional supplementation on cognitive outcomes. In contrast to intake of specific nutrients, emerging evidence suggests that dietary patterns may be important for cognitive health (108, 109, 153).  Observational studies have noted that the MeDi and DASH diets are associated with lower rates of dementia, and recent interventional trials have suggested that the DASH diet and weight loss (i.e., caloric restriction) may improve cognitive functioning. Several ongoing RCTs are investigating the effects of diet on neurocognition, including healthy older adults and older adults vulnerable to developing dementia (141, 154).

Future studies would benefit from more comprehensive examination of multiple dietary factors concurrently, as well as additional lifestyle factors known to be associated with dietary behavior and cognitive function, such as physical activity (155-158) and intellectual engagement (159, 160). Indeed, few studies have examined these interrelated behavioral factors concurrently, and those that have generally have reported independent associations between dietary factors and other lifestyle indices as they relate to risk of cognitive impairment (158, 161). It will also be important to gain a better understanding of the mechanisms underlying the relationship between nutritional intake and cognitive outcomes from human studies: although multiple causal factors have been hypothesized, including neuroinflammatory pathways (162), reductions in CVD risk factors (121, 141), alterations in cerebrovascular structure (130) and reserve functioning (163-165), and neuroprotection secondary to reductions in homocysteine (57), strikingly few studies have examined these relationships in the context of a randomized trial. Future randomized trials would benefit from multicomponent dietary change, such as that observed with the DASH and MeDi diets, so that the relationship between alterations in dietary intake of various nutrients and cognitive outcomes can be assessed concurrently. Additional mechanistic studies in humans are also needed to better understand the relationship between dietary intake and underlying changes in vascular mediators. Future observational studies would benefit from the adoption of uniform standards for the assessment of both dietary intake and cognitive outcomes, in order to facilitate better interpretation of these relationships across studies. This is particularly important for the adoption of dietary biomarkers that could be used to inform future prevention trials among individuals at risk for cognitive decline (166).

Conflict of interest: None.

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IMPACT OF DIETARY FACTORS AND INFLAMMATION ON COGNITION AMONG OLDER ADULTS

 

E.P. Handing1, B.J. Small1, S.L. Reynolds1, N.B. Kumar2

 

1. School of Aging Studies, University of South Florida, USA; 2. Moffitt Cancer Center, University of South Florida, USA

Corresponding Author: Elizabeth Handing, School of Aging Studies, University of South Florida, Tampa, FL 33612, USA. Email: handing@mail.usf.edu

J Prev Alz Dis 2015;2(4):220-226
Published online January 14, 2015, http://dx.doi.org/10.14283/jpad.2015.50


Abstract

OBJECTIVE: This study examined the influence of age, nutrition (as measured through food diaries and serum/plasma biomarkers) and inflammatory markers on cognitive performance in adults 60 years of age and older.

DESIGN: A cross-sectional population based study, data from the National Health and Nutrition Examination Survey (NHANES; 2001-2002 wave).

PARTICIPANTS: This study included 1,048 adults who had valid dietary data, blood biomarkers, were 60 years or older, completed the cognitive test, and had complete demographic information.

METHOD: A series of regression models were used to examine the relationship between cognitive function as measured by the Digit Symbol Substitution Task (DSST), dietary factors/biomarkers and inflammation. Mediation analyses were then utilized to examine whether individual nutrients accounted for the relationships between age and DSST performance.

RESULTS: Dietary fat intake, serum vitamin E, serum folate, serum iron, plasma homocysteine, and serum vitamin D were significantly associated with better DSST performance. Elevated fibrinogen and C-reactive protein, were significantly associated with poorer cognitive function, but did not remain statistically significant after controlling for age, gender, education, ethnicity, income, and total calorie intake. Serum vitamin D and plasma homocysteine accounted for a portion of age-related variance in DSST. Specifically, higher levels of vitamin D were related to better DSST performance, while higher homocysteine resulted in poorer cognitive performance.

CONCLUSION: Diet and nutrition are important modifiable factors that can influence health outcomes and may be beneficial to remediate age-related declines in cognition. Adequate nutrition may provide a primary preventive approach to healthy aging and maintenance of cognitive functioning in older adults.

 

Key words: Nutrition, cognition, older adults.


 

Introduction 

As the aging population is steadily on the rise, it is estimated that the number of adults in the United States 65 and older will reach 88.5 million by 2050 (1). The majority of older adults experience some form of cognitive decline (2, 3) and this has fueled research toward interventions aimed at ways for older adults to maintain and preserve their cognitive abilities. One potential intervention is through nutrition and dietary modification (2). A growing area of research in the aging field suggests that dietary components (antioxidant nutrients, fish, dietary fats, and B-vitamins) may play a role in the risk of age-related cognitive decline (4-6). This study will investigate the contribution of nutritional factors as well as inflammatory markers to cognitive function in older adults.

The relationship between diet and cognitive decline has mainly been investigated using a single nutrient approach (7, 8). For example, Morris et al (9) found that higher Vitamin E intake (from food alone and supplementation) was related to less cognitive decline in older adults across four cognitive tasks.  Llewellyn et al. (8) examined Vitamin D  (as measured by levels of serum 25-hydroxyvitamin D) and risk of cognitive decline finding that Vitamin D deficiency was related to an increase in cognitive decline over 6 years. Recently, vitamin D deficiency has also been linked to increased risk of dementia and Alzheimer’s disease (10). Although these studies provide insight into the link between diet and cognition, they are limited by viewing nutrients in isolation rather than considering nutrients from diet and have yet to include inflammation as a potential mediator in this pathway.

In these analyses, data from the National Health and Nutrition Examination Survey (NHANES) 2001-2002 wave were used to examine dietary macronutrients (fat, protein, and carbohydrates), and select blood serum/plasma biomarkers (vitamin B12, vitamin D, vitamin E, folate, iron, and homocysteine) (6). The purpose of this study is to examine the association between age, nutrition, cognitive performance (as measured by the Digit Symbol Substitution Task), and inflammatory markers in adults 60 and older.

Additional studies suggest an association between the pathogenesis of cognitive decline and inflammatory markers including C-reactive protein (CRP), ferritin, and fibrinogen (11, 12). The release of C- reactive protein (CRP) and other inflammatory markers may contribute to increased cognitive decline via the inflammatory pathway (13). Previous literature suggests that CRP levels are associated with mild cognitive impairment, a prodromal stage of Alzheimer’s Disease (14). Other biomarkers such as fibrinogen and ferritin have been related to cognitive decline (15), however few studies have analyzed the association between these inflammatory markers, cognitive function, and dietary factors.

This study examined how nutritional factors measured through diet and serum/plasma along with inflammatory markers may be associated with cognitive decline and investigates potential mediators to cognitive performance.

Method

Participants

This project used data from the National Health and Nutrition Examination Survey (NHANES) waves 2001-2002. NHANES conducts an extensive nutritional survey combining in-person interviews, questionnaires, and physical examinations on individuals varying from children to older adults. NHANES over-samples persons 60 and older, African Americans, and Hispanics to include a diverse sample population. Recruitment was performed using a stratified, multistage probability sample of non-institutionalized individuals living in the United States (16). Participation in the study required an in-home visit to administer questionnaires and cognitive testing, as well as a visit to a mobile examination center (MEC) for a comprehensive health examination. Our target population was adults 60 and older with valid dietary information and health measures.

Measures

Demographic variables 

Information on age, gender, ethnicity, education, and income was collected from a self-reported questionnaire. Age was coded as a continuous variable, gender was categorical, ethnicity was categorized as Non-Hispanic White, Non-Hispanic Black, Mexican American, other Hispanic, and other race, education was categorized as less than high school, high school, some college, or college graduate or above, and income was categorized as earning less than $14,999, earning $15,000-$49,000 or earning more than $50,000.

Cognitive assessment

Cognitive functioning was measured by the Digit Symbol Substitution Task (DSST) from a version of WAIS-IV. Participants were instructed to draw symbols corresponding to a number key, and the score is the number of correct symbols drawn within a period of 120 seconds. One point is given for each correctly drawn symbol completed within the time limit. The range in our sample was from 6-100 points, the average was 44.8 points.

Dietary analysis

Each participant completed a 24-hour dietary recall which was completed at the in-person interview. Participants were asked to describe their previous day’s consumption of foods and beverages using detailed diagrams and pictures for accurate portion size and ingredients. The second dietary recall was collected by telephone and was scheduled 3 to 10 days later. Dietary information from both days was averaged for total nutrient values. NHANES 2001-2002 nutrient intakes were calculated using USDA’s Food and Nutrient Database for Dietary Studies (FNDDS). The following dietary nutrients were included as predictors in the analyses: total fat (gm), protein (gm), and carbohydrates (gm).

Serum samples

Approximately 6 tablespoons of blood was drawn via venipuncture by a certified medical professional during the MEC visit. In the current study, the following serum/plasma samples were and used for analyses: serum vitamin B12 (pg/mL), serum folate (ng/mL), plasma homocysteine (μmol/L), serum iron (μg /dL), vitamin E serum (μg/mL), and vitamin D serum (ng/ mL).

Inflammatory markers

CRP (mg/dL), fibrinogen (mg/dL), and ferritin (ng/mL) were collected through the blood draw as part of the NHANES medical examination. Collection techniques and details can be found in the NHANES Laboratory/Medical Technologists Procedures Manual (17).

Statistical Analysis

The analytic strategy consisted of regression models to examine the predictive value of age, nutrients, and inflammation to cognitive performance among older adults. First, a series of univariate linear regression models were used to examine individual dietary and serum biomarkers and inflammatory markers on DSST, independent of demographic characteristics. Second, a multiple regression model was conducted based upon significant predictors from the previous models. Finally, mediation analyses were used to examine the effects of dietary/ serum biomarkers and age on DSST performance. It is known that areas of cognition decline with age, however it is not known how diet may influence cognition. By examining age, nutrient status, and cognitive function in a mediation model, we are better able to examine these continuous variables in relation to each other.  Mediation provides calculations of direct effects for the model X ->Y (where X represents age and Y represents DSST performance) as well as indirect effects X-> Z -> Y where Z represents nutrients as a mediator between age and DSST performance. The bootstrapping method (with bias correction and 5,000 iterations) was used to evaluate the direct and indirect mediating paths (18). All analyses were analyzed using SAS software (SAS Institute, Cary, NC) Version 9.3.

Results

A flowchart with the number of participants included in analyses is indicated in Figure 1. Participants were not included in analyses if they had missing dietary information (n=1,408), missing cognitive testing (n=8,361), were outliers by 3 standard deviations in cognitive testing (ie., score of <5; n=15), were outliers by 3 standard deviations in calorie intake (ie., <500 kcal/day or >5,000 kcal/day; n= 21), or missing demographic information (n=188). Our final analytic sample was 1,048 older adults. Table 1 displays the basic demographic characteristics of the sample. The mean age was approximately 71 years of age and mean calorie consumption was almost 1,800 calories per day.

Table 1. Sample demographic characteristics

 Note: NHANES= National Health And Nutrition Examination Survey

Table 2 presents the results of the univariate regression models examining demographic variables, nutrients, and inflammatory markers as predictors for cognitive functioning. Statistically significant demographic factors included, age, gender, ethnicity, education, income, and total calorie intake. Being older, male, non-Hispanic black, having a high school education or less, having less than $15,000 income, and a low calorie intake was related to worse DSST performance. All dietary macronutrients and serum biomarkers were significant predictors of DSST performance. All of the nutrients and biomarkers were positively related to DSST performance, except for homocysteine, which was related to worse cognitive performance. For the inflammatory markers, higher values of fibrinogen and CRP were related to worse DSST performance. Table 3 depicts the multivariate analyses of significant nutrient markers to DSST performance controlling for age, gender, education, ethnicity, income, and total calorie intake. Positive associations were found with higher intake of dietary fat, serum vitamin E, serum folate, serum iron, and serum vitamin D being related to better DSST performance, while a negative association was found for plasma homocysteine meaning higher values were related to lower DSST scores. There were no significant results for inflammatory factors.

Table 2. Univariate results for predictor variables with DSST performance as the outcome, n=1048

Note:  Vit= Vitamin, CRP= C-Reactive Protein, BMI= Body Mass Index; *=significance at the .05 alpha level; a. Estimates are based upon the covariates entered together on the first step; b. Estimates are based upon variables entered singly after controlling for covariates.

 

Table 3. Regression model of nutrients and inflammation with DSST as outcome controlling for age, sex, education, ethnicity, income, and total calorie intake. An asterisk indicates significance at the .05 alpha level

The final set of analyses examined the potential for the statistically significant nutrient markers to mediate age-related differences in DSST performance (Figure 2). The results indicated that serum vitamin D and plasma homocysteine acted as full mediators of age-related differences in performance (indirect effect and 95% CI in brackets): plasma homocysteine (-.036, CI [-.071 to -.01]), serum vitamin D (.017, CI [.004 to .038]). Homocysteine levels increased with age, but higher levels were associated with poorer performance. Vitamin D level increased with age and resulted in better DSST performance. Several nutrients acted as partial mediators (indirect effect and 95% CI in brackets): dietary fat (.001, CI [-.006 to .012]), serum vitamin E (.002, CI [-.008 to .017]), serum folate (.017, CI [-.008 to .047]) and serum iron (-.001 CI [-.015 to .013]. In the case of iron, older age was associated with lower values but not statistically significant, however higher iron values resulted in better cognitive performance. Vitamin E, and folate increased with age, but higher levels were not significantly related to DSST performance.

Figure 1. Flowchart of participants from the National Health And Nutrition Examination Survey (NHANES) 2001-2002

Figure 2. Multiple mediation with nutrient intake as mediators controlling for gender, education, ethnicity, income, and total calorie intake. The multiple mediation model of X -> Z -> Y (where X represents age, Z represents the nutrient, Y represents the Digit Symbol Substitution Task (DSST) performance. The bootstrapping method with bias corrected confidence estimates (based upon 5,000 iterations) was used to test the mediation hypothesis (18). Note: Vit= vitamin, hmcy= homocysteine, an asterisk indicates significance at the .05 alpha level.

 

Discussion

Findings from the univariate and multiple regression models suggest that several nutrients were associated with performance on the DSST including dietary fat, serum values for vitamin E, folate, iron, plasma homocysteine, and vitamin D. Mediation analyses further examined these relationships and found vitamin D and homocysteine acted as significant mediators between age and cognitive performance.

Mediation for biomarkers and cognitive performance

Recently Littlejohns and colleagues (10) reported that low serum vitamin D levels (< 25nmol/L) resulted in a two-fold increase in risk for dementia and Alzheimer’s Disease. Additional studies have found evidence suggesting a relationship between insufficient serum vitamin D and cognitive decline (19, 20). Our results indicate that higher serum vitamin D was related to better cognitive performance on the DSST.

A study by Bowman and colleagues (21) examining multiple biomarkers and cognitive function found that a dietary nutrient biomarker pattern high in antioxidant vitamins B, C, D, and E, was related to better executive function, attention, visuospatial function, and global cognition. Our findings of vitamin D and E as important nutrients for brain health and function are supported.

Additionally, plasma homocysteine was found to negatively mediate the relationship between age and cognitive performance. With age, homocysteine increased while higher values negatively affected DSST scores. Elevated plasma homocysteine concentrations have been consistently associated with both cognitive impairment and dementia and found to negatively mediate the relationship between age and cognitive performance (22). Research from the Framingham study found an association between higher homocysteine levels (>14 µmol per liter) and nearly a two-fold increase in risk of Alzheimer’s disease (23). Homocysteine is a sulfur-containing amino acid generated through the demethylation of the essential amino acid methionine. It is largely catabolized by trans-sulfuration to cysteine, but it may also be remethylated to methionine. Deficiencies in the homocysteine re-methylation cofactors cobalamin (B12) and folate, as well as the trans-sulfuration cofactor vitamin B6, are commonly seen in the elderly population, with a resultant increase in homocysteine with advancing age (24). Increasing number of studies have demonstrated that high red cell folate levels were associated with worse long-term episodic memory, total episodic memory, and global cognition (25-27). In a large population-based sample of elderly people, the association between high homocysteinemia and decreased cognition was only seen in participants with low folate levels (26). Similarly, Blasko et al (27) reported higher levels of homocysteine predictive of  moderate/severe global brain atrophy at five years while folate demonstrated a protective ability to reduce conversion to dementia in moderately cognitively impaired patients.  Based on these studies, hyperhomocysteinemia continues to be consistently associated with an increased risk of cognitive impairment in the elderly with more recent studies suggesting that folate levels may also influence the course of cognitive decline.

These observations may have significant implications for future interventions with nutritional cofactors for proper functioning of the methionine cycle which may ultimately improve methylation and protect the brain from damage.

Interpretation of partial mediators

Partial mediation was found for serum vitamin E and folate, which positively increased with age. Dietary fat intake and serum iron were not related to age, but were significantly related to better cognitive performance. Fat intake can be beneficial for cognition, but this interpretation should be evaluated with care. Presently, omega 3 fatty acids via dietary intake (i.e. higher amounts of fish) have been associated with a reduced risk for dementia (28). In a study by Morris et al. (5) older adults who consumed 1 or more fish meals per week compared with those with less than weekly consumption showed a reduced rate of decline by 10% to 13% as indicated by the Mini Mental Status Exam score. Conversely, high intake of saturated fat (found in cheese, red meat, and whole milk) has been related to an increased risk of dementia with the greatest effect for vascular type dementia (Relative Risk Ratio =2.9, 95% CI (0.6-13.8) p =0.01) (29). In our study, we further investigated the type of fat and found no significant effect for saturated fat, monounsaturated fat, or polyunsaturated fat on cognitive performance (data not shown). Therefore, our finding that dietary fat intake was associated with cognitive performance should be interpreted within a holistic dietary pattern, rather than individual fat values.

In our study, serum iron was predictive of better cognitive performance. The study population had an average of 86.36 µg/dL (normal range 60-170 µg/dL) meaning most older adults in our sample were receiving adequate iron from their diet and/or supplements. This finding is provocative in light of the association of the role of iron and other metals like copper in inducing oxidative stress and should be more thoroughly examined with additional studies, in particular its association with homocysteine. The involvement of homocysteine involving iron dysregulation and oxidative stress designated as the ferric cycle has also been implicated in AD (30).

Strengths & Limitations

Strengths of this study include the detailed dietary record information on over 1,000 older adults. NHANES over-recruits older adults with a focus on dietary assessment and health status of Americans. It is important to note that our results are from a cross sectional sample and longitudinal data would strengthen the results.

Our study is limited by containing a single assessment of cognition which may not capture the specific changes that occur with age. We were unable to examine the potential for reverse causation (i.e. lower cognition impacting dietary choices) which could be addressed in a longitudinal model.  Previous studies show that processing speed changes with age and this may be of interest given our aim was to examine cognitive performance in older adults. Our study also used self-reported dietary records, which are susceptible to over/under estimation.

Conclusion

In summary, age accounts for some of the decline in DSST performance, but a poorer performance may be exacerbated by an unhealthy diet. Initially, inflammatory markers showed an association with poorer cognitive performance, however after controlling for age, sex, education, ethnicity, income, and total calorie intake, results were no longer significant which limited the potential for examining them as mediators. From our mediation results from nutrients, we found that serum vitamin D served as a full mediator and was related to better cognitive performance. A significant negative meditation of plasma homocysteine was related to worse cognitive performance.

Future studies are warranted to provide longitudinal analysis of the effects of age, dietary, and inflammatory factors on cognitive functioning. Multiple cognitive tests should be included to examine whether nutrients affect certain parts of the brain more than others, which could have significant clinical public health implications such as revising diet recommendations for older adults. Dietary factors and nutrient values may play a pivotal role in brain health among older adults and can be translated into lifestyle modifications to promote healthy aging and remediate cognitive decline.

Conflict of interest: Authors have no conflicts of interest.

Ethical standards:  Institutional Review Board (IRB) approval and documented consent was obtained from all participants.

Funding: NHANES is funded by the U.S. government, National Center for Health Statistics, Centers for Disease Control and Prevention (CDC). The sponsors had no role in the design and conduct of study; in the collection, analysis, and interpretation of the data; in the preparation of the manuscript; or in the review and approval of the manuscript.

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