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DIAGNOSIS OF EARLY ALZHEIMER’S DISEASE: CLINICAL PRACTICE IN 2021

 

A.P. Porsteinsson1, R.S. Isaacson2, S. Knox3, M.N. Sabbagh4, I. Rubino5

 

1. University of Rochester School of Medicine and Dentistry, Rochester, NY, USA; 2. Weill Cornell Medical Center and New York-Presbyterian, New York, NY, USA; 3. Biogen International GmbH, Baar, Switzerland; 4. Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; 5. Biogen Inc, Cambridge, MA, USA

Corresponding Author: Sean Knox, MBChB. Biogen International GmBH, Neuhofstrasse 30, 6340 Baar, Switzerland. Phone: +41413921976; Email: sean.knox@biogen.com

J Prev Alz Dis 2021;
Published online May 12, 2021, http://dx.doi.org/10.14283/jpad.2021.23

 


Abstract

Alzheimer’s disease is a progressive, irreversible neurodegenerative disease impacting cognition, function, and behavior. Alzheimer’s disease progresses along a continuum from preclinical disease, to mild cognitive and/or behavioral impairment and then Alzheimer’s disease dementia. Recently, clinicians have been encouraged to diagnose Alzheimer’s earlier, before patients have progressed to Alzheimer’s disease dementia. The early and accurate detection of Alzheimer’s disease-associated symptoms and underlying disease pathology by clinicians is fundamental for the screening, diagnosis, and subsequent management of Alzheimer’s disease patients. It also enables patients and their caregivers to plan for the future and make appropriate lifestyle changes that could help maintain their quality of life for longer. Unfortunately, detecting early-stage Alzheimer’s disease in clinical practice can be challenging and is hindered by several barriers including constraints on clinicians’ time, difficulty accurately diagnosing Alzheimer’s pathology, and that patients and healthcare providers often dismiss symptoms as part of the normal aging process. As the prevalence of this disease continues to grow, the current model for Alzheimer’s disease diagnosis and patient management will need to evolve to integrate care across clinical disciplines and the disease continuum, beginning with primary care. This review summarizes the importance of establishing an early diagnosis of Alzheimer’s disease, related practical ‘how-to’ guidance and considerations, and tools that can be used by healthcare providers throughout the diagnostic journey.

Key words: Alzheimer’s disease, early diagnosis, diagnostic work-up.


 

Introduction

Dementia is among the greatest global health crises of the 21st century. Currently, more than 50 million people are living with dementia worldwide (1), with this number estimated to triple to 152 million by 2050 as the world’s population grows older (2). Alzheimer’s disease (AD) is the most common cause of dementia and is thought to account for 60–80% of dementia cases (3). Currently, the total annual cost for AD and other dementias in the USA is $305 billion and is predicted to increase to more than $1.1 trillion by 2050 (3). This substantial economic burden includes not only healthcare and hospice support for patients with AD (3) but also lost productivity from patients and caregivers (4).
AD is a progressive, neurodegenerative disease associated with cognitive, functional, and behavioral impairments, and characterized by two underlying pathological hallmarks: the progressive accumulation of extracellular amyloid beta (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) (3). In AD, aggregated Aβ plaques are deposited within the brain as a result of either reduced Aβ clearance or excessive production (5); plaque deposition typically occurs ~20 years before the onset of cognitive impairment (6,7). NFTs are formed by the abnormal accumulation of hyperphosphorylated-tau protein (5); these can be detected 10–15 years before the onset of symptoms (6, 7).
AD follows a progressive disease continuum that extends from an asymptomatic phase with biomarker evidence of AD (preclinical AD), through minor cognitive (mild cognitive impairment [MCI]) and/or neurobehavioral (mild behavioral impairment [MBI]) changes to, ultimately, AD dementia. A number of staging systems have been developed to categorize AD across this continuum (7–9). While these systems vary in terms of how each stage is defined, all encompass the presence/absence of pathologic Aβ and NFTs, as well as deficits in cognition, function, and behavior (7–9). As a result, subtle but important differences exist in the nomenclature for each stage of AD depending on the selected clinical and research classifications (Figure 1).

Figure 1. Stages within the Alzheimer’s disease continuum

The AD continuum can be classified into different stages from preclinical AD to severe AD dementia; the nomenclature associated with each stage varies between the different clinical and research classifications. This figure provides a summary of the different naming conventions that are used within the AD community and the symptoms associated with each stage of the continuum; *Mild behavioral impairment is a construct that describes the emergence of sustained and impactful neuropsychiatric symptoms that may occur in patients ≥50 years old prior to cognitive decline and dementia (112); Abbreviations: Aβ, amyloid beta. AD, Alzheimer’s disease. FDA, Food and Drug Administration. IWG, International Working Group. MCI, mild cognitive impairment. NIA-AA, National Institute on Aging—Alzheimer’s Association

 

Preclinical AD, as the earliest stage in the AD continuum, comprises a long asymptomatic phase, in which individuals have evidence of AD pathology but no evidence of cognitive or functional decline, and their daily life is unaffected (8) (Figure 1). The duration of preclinical AD can vary between individuals, but typically lasts 6–10 years depending on the age of onset (10,11). The risk of progression from preclinical AD to MCI due to AD (with/without MBI) depends on a number of factors, including age, sex, and apolipoprotein E (ApoE) status (11,12); however, not all individuals who have underlying AD pathology will go on to develop MCI or AD dementia (13,14). A recent meta-analysis of six longitudinal cohorts followed up for an average of 3.8 years found that 20% of patients with preclinical AD progressed to MCI due to AD (11). A further study by Cho et al., with an average follow-up rate of 4 years, found that 29.1% of patients with preclinical AD progressed to MCI due to AD (12).
For patients who do progress to MCI due to AD (with/without MBI), initial clinical symptoms typically include short-term memory impairment, followed by subsequent decline in additional cognitive domains (15) (Figure 1). On a day-to-day basis, an individual with MCI due to AD may struggle to find the right word (language), forget recent conversations (episodic memory), struggle with completing familiar tasks (executive function), or get lost in familiar surroundings (visuospatial function) (15,16). As individuals have varying coping mechanisms and levels of cognitive reserve, patients’ experiences and symptomology vary widely; however, patients tend to remain relatively independent at this stage, despite potential marginal deficits in function. The prognosis for patients with MCI due to AD can be uncertain; one study that followed up patients with MCI due to AD for an average of 4 years found that 43.4% progressed to AD dementia (12). Other studies reported 32.7% and 70.0% of individuals with MCI due to AD progress to AD dementia within 3.2 and 3.6 years of follow-up, respectively (17,18). Patients who do progress to AD dementia will develop severe cognitive deficits that interfere with social functioning and will require assistance with activities of daily living (7) (Figure 1). As the disease progresses further, increasingly severe behavioral symptoms will develop that significantly burden patients and their caregivers, and the disease ultimately results in severe loss of independence and the need for round-the-clock care (3).
An early diagnosis of AD can provide patients the opportunity to collaborate in the development of advanced care plans with their family, caregivers, clinicians, and other members of the wider support team. Importantly, it also enables patients to seek early intervention with symptomatic treatment, lifestyle changes to maintain quality of life, and risk-reduction strategies that can provide clinically meaningful reductions in cognitive, functional, and behavioral decline (19–22). It can also help reduce healthcare system costs and constraints: a study by the Alzheimer’s Association found that diagnosing AD in the early stages could save approximately $7 trillion. These savings were due to lower medical and long-term care costs for patients with managed MCI than for those with unmanaged MCI and dementia (3). Furthermore, an early diagnosis will be vital for patients when a therapy addressing the underlying pathology of AD becomes available; currently 19 biologic compounds are under Phase 2 or 3 investigation (23). Physicians will need to be prepared for the approval of these treatments, to optimize the potential benefit and prolong preservation of patients’ cognitive function and independence beyond that associated with current standard of care (19).
As the prevalence of AD continues to grow, the advancement of AD patient diagnosis will require an orchestrated effort, starting in the primary care setting and subsequently involving multiple healthcare provider (HCP) specialties (e.g., nurse practitioner [NP] or physician assistant [PA]) throughout the disease continuum. Galvin et al. recently highlighted the need for HCPs to work as an integrated, patient-centered care team to accommodate the growing and diverse population of patients with AD, beginning with diagnosis (24). For patients to receive a timely diagnosis, it is vital to implement an approach that minimizes the burden placed on the patient, clinician, and healthcare system (25). Here, we summarize the importance of establishing an early diagnosis of AD, related practical ‘how-to’ guidance and considerations, and tools that can be used by healthcare providers throughout the diagnostic journey.

 

The importance of an early diagnosis

Historically, a diagnosis of AD has been one of exclusion, and one only made in the latter stages of disease (26); however, the disease process can take years to play out, exacting a significant toll on the patient, caregiver, and healthcare system along the way (27).
To mitigate this burden, the early and accurate detection of AD-associated symptoms in clinical practice represents a critically needed but challenging advancement in AD care (19, 28–30). Usually, a patient with early signs/symptoms of AD will initially present in a primary care setting (30). For some patients, minor changes in cognition and/or behavior may be detected during a routine wellness visit or an appointment to discuss other comorbidities (24). As the PCP is often the first to observe a patient’s initial symptomatology, it is vital they recognize the early signs and symptoms, and understand how to use the most appropriate assessment tools designed to detect these early clinical effects of the disease.
Because the neuropathologic hallmarks of AD (Aβ plaques and NFTs) can be detected decades prior to the onset of symptoms (6, 7), biomarkers reflecting this underlying pathology represent an important opportunity for early identification of patients at greatest risk of developing MCI due to AD. Biomarkers support the diagnosis of AD (especially important early on when symptoms can be subtle), and the U.S. Food and Drug Administration (FDA) has recently published guidelines that endorse their use in this population (9). The National Institute on Aging—Alzheimer’s Association (NIA-AA) has recently created a research framework that acknowledges the use of biomarkers for diagnosing AD in vivo and monitoring disease progression (7).
Important biomarker information can be gathered from imaging modalities such as magnetic resonance imaging (MRI) and positive emission tomography (PET) that visualize early structural and molecular changes in the brain, respectively (25, 30). Fluid biomarker testing, such as cerebrospinal fluid (CSF) can also be used; CSF biomarkers can directly reflect the presence of Aβ and aggregated tau within the brain (7, 31). As will be discussed in more depth later in this article, a large number of clinical studies have shown that Aβ and tau biomarkers can contribute diagnostically important information in the early stages of disease (32). There is ongoing research to expand the current range of tests that can be used by clinicians as part of the multistage diagnostic process (25). For instance, once approved, blood-based biomarkers could be used to identify patients at risk of developing AD and for monitoring disease progression (33, 34), which would also reduce the current capacity constraints associated with PET imaging (25).

 

Practical guide for an early diagnosis of Alzheimer’s disease in clinical practice

As already raised, recent recommendations for evolving AD care to a more patient-centric, transdisciplinary model include guidance on realizing an efficient diagnostic process—one in which HCPs, payers, and specialists are encouraged to combine their efforts to ensure the early warning signs of AD are not overlooked (24). The recommendations include dividing the diagnosis of AD into the following steps: detect, assess/differentiate, diagnose, and treat (Figure 2). We present here a practical guide for the early diagnosis of AD, based on this outlined approach, including a case study to highlight each of these key steps.

Figure 2. A stepwise infographic to highlight key stages within the diagnostic process, along with the recommended tests to support each step

The diagnostic process for AD can be divided into the following steps: detect, assess/differentiate, diagnose, and treat. It is important for clinicians to utilize appropriate tests when investigating a patient suspected of having AD in the early stages. Here, we highlight the most valuable tests for each step and which ones should be used in a primary care or specialist setting; *FDG-PET is usually considered after a diagnostic work-up; Abbreviations: A-IADL-Q, Amsterdam Instrumental Activities of Daily Living Questionnaire. Aβ, amyloid beta. Ach, acetylcholine. BG, blood glucose. CSF, cerebrospinal fluid. FAQ, Functional Activities Questionnaire. FAST, Functional Analysis Screening Tool. FDG-PET, fluorodeoxyglucose-PET. GDS, Geriatric Depression Scale. IQCODE, Informant Questionnaire on Cognitive Decline in the Elderly. Mini-Cog, Mini Cognitive Assessment Instrument. MMSE, Mini-Mental State Examination. MoCA, Montreal Cognitive Assessment. MRI, magnetic resonance imaging. NMDA, N-Methyl-D-aspartic acid. NPI-Q, Neuropsychiatric Inventory Questionnaire. PCP, primary care physician. PET, positive emission tomography. p-tau, phosphorylated tau. QDRS, Quick Dementia Rating System. TSH, thyroid-stimulating hormone. t-tau, total tau

 

Step 1: Detect

The role of primary care in the early detection of AD

The insidious and variable emergence of symptoms associated with AD and other dementias can make recognition extremely challenging, particularly in a primary care setting (30, 35). Clinicians often have limited time with patients, so it is vital that they are able to quickly and accurately recognize the early signs and symptoms associated with AD (Table 2) (3, 30, 36), and training for nurses, NPs, and PAs who may have more time to observe patients should provide substantial benefits. Although extremely variable, initial symptoms may include short-term memory loss or psychological concerns, including depressive symptoms and a loss of purpose (36).
Patients, family members, and even HCPs themselves may present barriers to the diagnosis of early-stage AD. Patients may hide their symptoms or even avoid making an appointment until their symptoms significantly affect their day-to-day life due to fear of the stigma associated with a diagnosis of AD (19). Additionally, patients, family members, and PCPs/HCPs may dismiss or misinterpret symptoms as simply part of the normal aging process (30). Retrieving information from a trusted family member or informant/caregiver is essential when trying to assess a patient for suspected AD, as this perspective can provide a more objective understanding of the daily routine, mood, and behavior of the patient, and how this may have changed over time (30). For patients presenting with even subtle symptoms associated with AD, it is important that the PCP/HCP conducts an initial assessment to confirm the presence of symptoms using a validated assessment for early-stage AD detection (Figure 2; Step 2: Assess/Differentiate).

Case study: Presentation

A 63-year-old Caucasian male (J.K.) presented to his PCP with short-term memory loss over the last 2 years (Table 1A). Accompanied by his wife, he acknowledged his job had been affected by issues with his short-term memory; however, he considered his memory similar to that of his peers. His wife reported that people at work had started to notice him struggling to keep up, and also that family had to remind him of his upcoming appointments. He admitted to having intermittent depressive symptoms and anxiety, as well as irritability. Based on the patient’s symptoms, the PCP felt his presentation warranted further clinical assessment.

Table 1. Patient case study

Abbreviations: Aβ, amyloid beta. ApoE, apolipoprotein E. HgbA1c, hemoglobin A1c. MoCA, Montreal Cognitive Assessment. MRI, magnetic resonance imaging. PCP, primary care physician. p-tau, phosphorylated tau. t-tau, total tau

Table 2. Symptoms associated with suspected early stage Alzheimer’s disease

 

Step 2: Assess and differentiate

Primary care: Initial assessment when a patient presents

When a patient initially presents with symptoms consistent with early stages of AD, a clinician must first conduct a comprehensive clinical assessment to rule out other potential non-AD causes of cognitive impairment (Figure 2). PCPs are well placed to conduct these initial assessments, as they may not require specialist input or hospital tests. During the initial assessment, the primary objective of the clinician should be to exclude possible reversible causes of cognitive impairment, such as depression, or vitamin, hormone, and electrolyte deficiencies (37). The initial assessment should include a thorough history to identify potential risk factors associated with AD, including a family history of AD or related dementias in first-degree relatives (31, 38). Other known risk factors for AD that should be identified include age, female sex, ApoE ε4 status, physical inactivity, low education, diabetes, and obesity (3). It is also important to review for pre-existing medical conditions or prescribed medications that could be a cause of the patient’s cognitive impairment (36). Additionally, when conducting a thorough history, open-ended, probing questions should be directed to both the patient and the informant to ascertain how the patient’s cognition has changed over time and how the cognitive deficits affect their everyday activities; example questions for the initial assessment are detailed in Table 3 (30). Engaging with informants/caregivers is key to capturing additional information to help support all assessments. A routine differential diagnosis of AD begins with a detailed history, physical and neurologic examinations, and bloodwork analyses, followed by cognitive assessments and functional evaluation (Figure 2).

Table 3. Example questions for a clinician conducting an initial assessment with a patient and caregiver (30)

 

Primary care: Physical examination and blood analyses

A physical examination and blood tests can identify comorbid contributory medical conditions and reversible causes of cognitive impairment. A physical examination, including a mental status and neurological assessment, should be conducted to detect conditions such as depression and, for example, to look for signs such as issues with speaking or hearing as well as signs that could indicate a stroke (37). As part of the physical exam, a physician may ask the patient about diet and nutrition, review all medications (to see if these are the cause of any cognitive impairment, e.g. anti-cholinergics, analgesics, or sleep aids and anxiolytics), check blood pressure, temperature and pulse, and listen to the heart and lungs (36, 39).
Blood tests can rule out potentially treatable illnesses as a cause of cognitive impairment, such as vitamin B12 deficiency or thyroid disease (37). Suggested blood analyses include: 1) complete blood cell count; 2) blood glucose; 3) thyroid-stimulating hormone; 4) serum B12 and folate; 5) serum electrolytes; 6) liver function; and 7) renal function tests (30). Although not routinely used in clinical practice, clinicians may request ApoE genotyping, as this can help assess the genetic risk of developing AD. ApoE is the dominant cholesterol carrier within the brain that supports lipid transport and injury repair (40,41), and the APOE gene exists as three polymorphic alleles: APOE ε2, ε3, and ε4. The ε4 allele of ApoE is associated with increased AD risk, whereas the ε2 allele is protective (40,42). The number of ApoE ε4 alleles a person carries increases their risk of developing AD and the age of disease onset (43). Homozygous ε4 carriers (those with two copies of the ε4 allele) have the greatest risk of developing AD and the lowest average age of onset (43). In some practice settings, ApoE genotyping can only be conducted by a genetic counselor; a referral for more comprehensive genetic testing may be considered by the HCP if there is a family history of early-onset AD or dementia. Consumer tests are also becoming more readily available for patients wanting to determine their risk of developing diseases such as AD based on genetic risk factors (44).

Primary care: Cognitive, functional, and behavioral assessments

Cognitive assessments

If a patient is suspected of having AD following an initial assessment in primary care, and they are <65 years old, or if the case is complex, a referral to a dementia specialist such as a neurologist, geriatrician, or geriatric psychiatrist may be required for further evaluation. The specialist would then use an appropriate battery of cognitive, functional, and behavioral tests to assess the different aspects of disease, and ultimately to confirm diagnosis. However, not all patients with suspected cognitive deficits are immediately referred to a dementia specialist at this stage, which is only partly due to limited numbers of specialists (25) (Figure 2). In clinical practice, a two-stage process is often employed. This involves an initial ‘triage’ step conducted by non-specialists to clinically assess and select those patients who require further evaluation by a dementia specialist (45). During this ‘triage’ step, there are several clinical assessments available to non-specialists for assessing the presence of cognitive and functional impairments and behavioral symptoms (Table 4) (28, 35, 46–55)
Previous research has shown that clinicians have a tendency to choose one assessment over another due to their familiarity with the assessment, time constraints, or specific resources available to them within their clinic (30), but clinicians need to be aware of, and prepared to use, the most patient-appropriate assessments: the cultural, educational, and linguistic needs of the patient are important considerations (30,36,56–58). Some assessments have been translated into different languages or shortened, or have education-adjusted scoring classifications, where required (56–58).
Cognitive assessments that can be conducted quickly (<10 minutes), such as the Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MoCA), can be used by non-specialists to identify the presence and severity of cognitive impairment in patients before referring to a dementia specialist (Table 4) (36). Both the MMSE and MoCA are used globally in clinical practice, particularly in primary care, but vary in terms of their sensitivity to identify AD in the early stages (28,59). The MMSE is sensitive and reliable for identifying memory and language deficits in general but has limitations in identifying impairments in executive functioning (59). MoCA was originally developed to improve the detection of MCI (28) and is more sensitive than the MMSE in its assessment of memory, visuospatial, executive, and language function, and orientation to time and place (59). Both tests are relatively easy to administer and take around 10 minutes to complete. Neither assessment requires extensive training by the clinician, although MoCA users do need to undergo a 1-hour certification as mandated by the MoCA Clinic and Institute (28,60).
For time-constrained clinicians, the Mini Cognitive Assessment Instrument (Mini-Cog) may be an appropriate tool to assess cognitive deficits that focus on memory, and components of visuospatial and executive function (Table 4). The assessment includes the individual learning three items from a list, drawing a clock, and then recalling the three-item list. The Mini-Cog can be useful for clinicians in primary care, as it requires no training and the results are easy to interpret. As an alternative to these tests, PCPs might also consider using an informant-based structured questionnaire such as the AD8 or Informant Questionnaire on Cognitive Decline in the Elderly to help guide discussions with the patient and caregiver (Table 4) (28).

Table 4. Cognitive, functional, and behavioral assessments to support the diagnosis of Alzheimer’s disease in a primary care and specialist setting

*Personal communication; Abbreviations: AD, Alzheimer’s disease. A-IADL-Q, Amsterdam Instrumental Activities of Daily Living Questionnaire. FAQ, Functional Activities Questionnaire. FAST, Functional Assessment Screening Tool. GDS, Geriatric Depression Scale. IQCODE, Informant Questionnaire on Cognitive Decline in the Elderly. MCI, mild cognitive impairment. Mini-Cog, Mini Cognitive Assessment Instrument. MMSE, Mini-Mental State Examination. MoCA, Montreal Cognitive Assessment. NPI-Q, Neuropsychiatric Inventory Questionnaire. QDRS, Quick Dementia Rating System

 

Functional assessments

Functional assessments are valuable in identifying changes in a patient’s day-to-day functioning through the evaluation of their instrumental activities of daily living (IADLs). IADLs are complex activities that are necessary for the individual to function independently (e.g., cooking, shopping, and managing finances) and can be impaired during the early stages of cognitive impairment. While it is possible that functional decline may occur as a part of normal aging, a decline in a person’s IADL performance is strongly associated with neurodegenerative diseases such as AD (61). In the early stages of AD, patients may be functionally independent, and any impairment in IADLs may be subtle, such as difficulties paying bills or driving to new places. A patient’s functional independence is essential for their well-being and mental health (62), particularly in the early stages of the disease when the individual may still be working and socializing relatively independently (3). Consequently, functional independence is one of the most important clinical features for patients with AD. As the disease progresses, and patients have increasing functional impairment, this significantly impacts on their independence, and subsequently their and their family/caregiver’s quality of life.
Functional assessment is, therefore, an integral part of the diagnostic process for AD. The Functional Activities Questionnaire (FAQ) is an informant questionnaire that assesses the patient’s performance over a 4-week period and may take only a few minutes to complete (Table 4). The questionnaire is scored from ‘normal’ to ‘dependent’, using numerical values assigned to categories, with higher scores indicative of increasing impairment (47). Previous research has shown that the FAQ has high sensitivity and reliability for detecting mild functional impairment in patients with MCI (47).
Determining an individual’s functional independence can be challenging and the clinician may require additional input from an informant to determine a patient’s functional decline and their ongoing ability to conduct activities of daily living (37). The clinician can gain greater insight through the informant into the patient’s day-to-day life and any issues the patient is having at home. This type of information is vital to the clinician, and when combined with other assessment tools, can help to narrow the differential diagnosis.

Behavioral assessments

Patients with suspected AD may experience several behavioral symptoms such as anxiety, disinhibition, apathy, and depression (Table 2). In the early stages of disease, such symptoms are generally associated with poor long-term outcomes and caregiver burden, and are particularly distressing to both patients and their families (63). It is important for clinicians to use appropriate assessments to identify behavioral and psychiatric symptoms that are caused by neurodegenerative diseases, such as AD, rather than by alternative causes, such as a mood disorder.
The Geriatric Depression Scale (GDS) and Neuropsychiatric Inventory Questionnaire (NPI-Q) can be used by clinicians to assess neuropsychiatric symptoms in patients for whom early-stage AD is suspected (Table 4). The GDS is a 15-item (or longer 30-item) questionnaire that assesses mood, has good reliability in older populations for detecting depression, and can be completed by the patient within 5–10 minutes (63). The NPI-Q can be used in conjunction with or as an alternative to the GDS. The NPI-Q is completed by a knowledgeable informant or caregiver who can report on the patient’s neuropsychiatric symptoms. The NPI-Q can be conducted in around 5 minutes to determine both the presence and severity of symptoms across several neuropsychiatric domains including depression, apathy, irritability, and disinhibition (49). Consequently, as it assesses depression, it can be used as an alternative to GDS if time constraints do not allow for both to be completed.
Behavioral symptoms can be non-specific, so it is important for clinicians to consider and rule out other potentially treatable causes of impairment when assessing this domain. For example, depression is associated with concentration and memory issues (64); apathy can occur in non-depressed elderly individuals and can impact cognitive function (65). Signs/symptoms such as social withdrawal, feelings of helplessness, or loss of purpose should be investigated closely, as these could be indicative of depression alone. It is important for clinicians to recognize that if changes over time in cognitive symptoms and mood symptoms match, then depression is most likely to be the root cause of subtle cognitive decline, rather than AD (28).

Primary care clinician checklist

If AD is still suspected following clinical assessment, referral to a specialist for further diagnostic testing, including imaging and fluid biomarkers, may be required. It is important the clinician confirms the following checks/assessments before the patient undergoes further evaluation:

Primary care clinician checklist

• Confirm medical and family history
• Review the patient’s medications for any that could cause cognitive impairment
• Perform blood tests to eliminate potential reversible causes of cognitive impairment
• Conduct a quick clinical assessment to confirm the presence of cognitive impairment

Specialist role in assessment

Following the initial assessment in primary care, further cognitive, behavioral, functional, and imaging assessments can be carried out in a specialist setting. With their additional AD experience, access to other specialties, and possibly fewer time constraints than the PCP, the specialist is able to conduct a more comprehensive testing battery, using additional clinical assessments and biomarkers to determine causes of impairment and confirm diagnosis (Figure 2).

Cognitive assessments

Because the cognitive impacts of early-stage AD may vary from patient to patient, it is important to consider which cognitive domains are affected in these early stages when considering which assessments to use. Specialists are able to conduct a full neuropsychological test battery that covers the major cognitive domains (executive function, social cognition/emotions, language, attention/concentration, visuospatial and motor function, learning and memory); preferably, a battery should contain more than one test per domain to ensure adequate sensitivity in capturing cognitive impairment (66). This step can help with obtaining an in-depth understanding of the subtle changes in cognition seen in the early stages of AD and enables the clinician to monitor subsequent changes over time.
Typically, episodic memory, executive function, visuospatial function, and language are the most affected cognitive domains in the early stages of AD (29,67,68). Currently, most cognitive assessment tools focus on a subset of the overall dimensions of cognition; it is therefore vital the clinician chooses the correct test to assess impairment in these specific cognitive domains that could be indicative of AD in the early stages. As cognitive impairment in the early stages of AD can be subtle and vary significantly between individuals (29), clinicians must choose appropriate, sensitive tests that can detect these changes and account for a patient’s level of activity and cognitive reserve (29). If there is large disparity in results across cognitive assessments, it is important for the clinician to shape their assessments based on the patient’s history. If the patient’s history is positive for neurodegenerative disease, but one assessment does not reflect this, it is important to conduct further tests to ascertain the cause of the cognitive impairment.
The Quick Dementia Rating System (QDRS) can be used by specialists to assess cognitive impairment (Table 4). This short questionnaire (<5 minutes) is completed by a caregiver/informant and requires no training. The QDRS assesses several cognitive domains known to be affected by AD, including memory, language and communication abilities, and attention. The questionnaire can reliably discriminate between individuals with and without cognitive impairment and provides accurate staging for disease severity (28).

Functional assessments

The Amsterdam IADL Questionnaire (A-IADL-Q) and Functional Assessment Screening Tool (FAST) can both be used to assess a patient’s functional ability (Table 4) (53). The A-IADL-Q is a reliable computerized questionnaire that monitors a patient’s cognition, memory, and executive functioning over time. This questionnaire is completed by an informant of the patient and takes 10 minutes to complete (53). For patients with suspected early stage AD, the A-IADL-Q is a useful tool to monitor subtle changes in IADL independence over time and is less influenced by education, gender, and age than other functional assessments (53). The FAST is a useful assessment for clinicians to identify the occurrence of functional and behavioral problems in patients with suspected AD. The questionnaire is completed by informants who interact with the patient regularly; informants are required to answer Yes/No to a number of questions focusing on social and non-social scenarios (55).

Structural imaging

Structural imaging, such as MRI, provides clinically useful information when investigating causes of cognitive impairment (69) (Figure 2). MRI is routinely conducted to exclude alternative causes of cognitive impairment, rather than support a diagnosis of AD (37,70). It is well known that medial temporal lobe atrophy is the best MRI marker for identifying patients in the earliest stages of AD (70,71); however, specific patterns of atrophy may also be indicative of other neurodegenerative diseases. Atrophy alone is rarely sufficient to make a diagnosis. MRI findings can help to narrow the differential diagnosis, and the results should be considered in the context of the patient’s age and clinical examination (69–71).
Clinicians are advised to take a stepwise approach when reviewing structural imaging reports of a patient with suspected AD. These steps include: 1) excluding brain pathology that may be amenable to surgical intervention (e.g., the scan will show regions of hyper- or hypointensity rather than a uniform signal); 2) assessing for brain microbleeds (e.g., looking at signal changes within different areas of the brain can identify vascular comorbidities); and 3) assessing atrophy (e.g., medial temporal lobe atrophy is characteristic of AD) (69). Radiologists can conduct a quick and easy visual rating of any medial temporal lobe atrophy; these results can then be utilized by the specialist, in conjunction with a clinical assessment, to determine the likely cause of cognitive impairment. If the clinician is unable to determine a differential diagnosis, additional confirmatory tests can be requested.
Fluorodeoxyglucose-PET (FDG-PET) is a useful structural imaging biomarker that can support an early and differential diagnosis (72); however, specialists usually prefer to use this after their initial diagnostic work-up. As the brain relies almost exclusively on glucose as its source of energy, FDG (a glucose analog) can be combined with PET to identify regional patterns of reduced brain metabolism and neurodegeneration (70,72). FDG-PET is not recommended for diagnosing patients with preclinical AD, as there is no way to ascertain whether the hypometabolism is directly related to AD pathology (73); however, clinicians may refer patients with more established symptomatology for an FDG-PET scan to identify regions of glucose hypometabolism and neurodegeneration that could be indicative of AD (70).

Case study: Assess/differentiate

The initial assessment by the primary care clinician revealed that J.K.’s medical history was significant for hypertension, dyslipidemia, mild obesity, and glucose intolerance (Table 1B). There was no history of cerebrovascular events, significant head injuries, or focal findings on the neurologic exam. Besides the vascular risk factors, no medical conditions or current medications were found to be likely contributors to the cognitive deficit. The patient had a positive family history of dementia, where the onset typically occurred in the late 60s. Genotyping showed the patient to be a homozygous carrier of two ApoE ε4 alleles. Blood tests revealed elevated serum glucose and C-reactive protein but were otherwise normal. The patient had an unremarkable mental status examination, and his MoCA score was 21/30, with points lost on orientation, recall, and naming (Table 1C).
The patient was referred to a memory clinic for further assessment. The dementia specialist referred the patient for an MRI that predominantly showed mild small vessel disease and mild generalized atrophy with a significant reduction in hippocampal volume and ratio. Based on his medical and family history, cognitive assessments, and structural imaging results, the specialist deemed the severity of cognitive impairment to be in the mild range; consequently, the specialist referred the patient for biomarker assessment to determine the underlying cause.

Step 3: Diagnose

Historically, AD was only diagnosed postmortem until we developed the ability to ascertain the underlying pathology associated with the disease in new ways, namely imaging and fluid biomarkers. However, despite supportive results from single- and multicenter trials, the use and reimbursement of imaging and fluid biomarkers to support the diagnosis of AD still vary considerably between countries (70).

Imaging biomarkers

Recent advances have allowed physicians to visualize the proteins associated with AD, namely Aβ and tau, via PET scanning. Amyloid PET is currently the only imaging approach recommended by the Alzheimer’s Association and the Amyloid Imaging Task Force to support the diagnosis of AD (70). Amyloid PET utilizes tracers (florbetapir, flutemetamol, and florbetaben) that specifically bind to Aβ within amyloid plaques; a positive amyloid PET scan will show increased cortical retention of the tracer in regions of Aβ deposition within the brain (74), thus confirming the presence of Aβ plaques in the brain (74,75) and directly quantify brain amyloid pathology (76), thus making it a useful tool to supplement a clinical battery to diagnose AD (3,74). However, a positive amyloid PET scan alone does not definitively diagnose clinical AD, and these results must be combined with other clinical assessments, such as cognitive assessment, for an accurate diagnosis (74). It is also important to note that amyloid PET is expensive and not readily reimbursed by health insurance providers (70); if it is not possible to access amyloid PET, biomarker confirmation can be assessed using CSF.

Fluid biomarkers

An additional or alternative tool to amyloid PET is the collection and analysis of CSF for the presence of biomarkers associated with AD pathology. Patients who have symptoms suggestive of AD can be referred for a lumbar puncture to analyze their CSF for specific AD-associated biomarkers (3). CSF biomarkers are measures of the concentrations of proteins in CSF from the lumbar sac that reflect the rates of both protein production and clearance at a given timepoint (7). Lumbar punctures can be conducted safely and routinely in an outpatient setting or memory clinic (77). However, many patients still worry about the pain and possible side effects associated with the procedure and may require additional information and support from the clinician to undertake the procedure (77). Appropriate use criteria are available for HCPs to help identify suitable patients for lumbar puncture and CSF testing (78). For example, individuals presenting with persistent, progressing, and unexplained MCI, or those with symptoms suggestive of possible AD, should be referred for lumbar puncture and CSF testing (78). However, lumbar puncture and CSF testing are not recommended for determining disease severity in patients who have already received a diagnosis of AD or in lieu of genotyping for suspected autosomal dominant mutation carriers (78).
Because there is strong concordance between CSF biomarkers and amyloid PET, either can be used to confirm Aβ burden (79). As such, CSF biomarkers are widely accepted within the AD community to support a diagnosis (80). AD biomarkers from the brain can be detected in CSF well before the onset of overt clinical symptoms in early-stage AD (6,7). Core AD CSF biomarkers, such as Aβ42 (one of two main isoforms of Aβ and a major constituent of Aβ plaques) and phosphorylated tau (p-tau) and total tau (t-tau), can be measured to determine the presence of disease (80).
When interpreting CSF analyses for a patient with suspected AD, it is important to remember that AD is associated with decreased CSF Aβ42 and increased tau isoforms (32). Decreased CSF Aβ42 levels are a reflection of increased Aβ aggregation and deposition within the brain (32), and the concentration of CSF Aβ42 directly relates to the patient’s amyloid status (e.g., the presence or absence of significant amyloid pathology) and the total amount of Aβ peptides (e.g., Aβ42 and Aβ40) (32). Specialists’ use of ratios of these CSF biomarkers (e.g., Aβ42/40) rather than single CSF biomarkers alone has been shown to adjust for potential differences in Aβ production and provide a better index of the patient’s underlying amyloid-related pathology (81). The increase in CSF p-tau and t-tau associated with AD may directly reflect the aggregation of tau within the brain and neurodegeneration, respectively (32). P-tau in CSF provides a direct measure of the amount of hyperphosphorylated tau in the brain, which is strongly suggestive of the presence of NFTs, whereas CSF t-tau can predict the level of neurodegeneration in a patient with suspected AD; however, t-tau is also increased in other neurologic conditions (32).
Ultimately, the clinical decision to use amyloid PET or CSF to confirm amyloid and tau pathology can be affected by several practical factors (Table 5) (70,77,80,82–85).

Table 5. Comparison of key CSF and amyloid PET considerations for amyloid confirmation

Abbreviations: CSF, cerebrospinal fluid. PET, positron emission tomography

 

Emerging diagnostic tools

Access constraints for amyloid PET have driven the need for alternative sensitive and specific CSF and blood-based biomarkers that can detect AD-associated pathology in the early stages (86). Significant efforts have been undertaken over the last decade to identify blood-based biomarkers to: 1) detect AD pathology; 2) identify those at risk of developing AD in the future; and 3) monitor disease progression (33,34,87). At present, only a limited number of approved blood-based assays are available to clinicians to detect AD pathology (88); however, several novel assays are currently under investigation, including those measuring various phosphorylated forms of tau, including p-tau181 and p-tau217 (89). Investigational use of plasma p-tau181 (an isoform of tau) has been shown to differentiate AD from other neurodegenerative diseases and predict cognitive decline in patients with AD (33). CSF p-tau217 (a different isoform of tau) is a promising biomarker under investigation for detecting preclinical and advanced AD (86,90). Given that blood testing is already a well-established part of clinical routines globally and can easily be performed in a variety of clinical settings, blood-based biomarkers could in future serve as the potential first step of a multistage diagnostic process. This would be a benefit to clinicians, particularly those in primary care, by helping to identify individuals requiring a referral to a specialist for diagnostic testing (87).

Case study: Diagnose

J.K. underwent a lumbar puncture for CSF analysis, which showed decreased Aβ42 and increased p-tau and t-tau protein (Table 1D). Based on the results from the genotyping, cognitive assessments, MRI, and CSF biomarkers, the clinician confirmed that the likely cause of the patient’s cognitive deficits was early-stage AD, especially in view of a positive family history of dementia with similar age of onset.

Step 4: Treat

The role of the clinician following a diagnosis of early-stage AD is to discuss the available management and treatment options while providing emotional and practical support to the patient, caregiver, and family where appropriate (37). Clinicians can also refer the patient and their caregiver(s) to social services for further support, as well as help connect them with reliable sources of information and even local research opportunities and clinical trials.
One important role for a clinician treating a patient diagnosed with early-stage AD is to closely monitor the patient’s disease progression through regular follow-up appointments (e.g., every 6–12 months); clinicians should encourage patients (and the caregiver) to make additional follow-up appointments, especially should symptoms worsen. Routine cognitive and functional assessments (Table 4) should be used to monitor disease progression; these tools can be used to identify unexpected trends, such as rapid decline, which could prompt the need for additional medical evaluation such as blood tests, imaging, or biomarker analyses. Results from such tests could help guide management and/or treatment decisions over the course of the patient’s disease.
Non-pharmacologic therapies (e.g., diet and exercise) may be employed for patients with early AD, with the goal to maintain or even improve cognitive function and retain their ability to perform activities of daily living. For patients in the early stages of disease, dietary changes (e.g., following a healthy diet high in green, leafy vegetables, fish, nuts, and berries), physical exercise, and cognitive training have demonstrated small but significant improvements in cognition (36,91). Non-pharmacologic therapies can have a positive impact on quality of life and are generally safe and inexpensive (36); however, compliance with these non-pharmacologic therapies should be monitored by the clinician. Research suggests that multimodal therapies, such as cognitive stimulation therapy, may also be more effective when used in combination with pharmacologic treatments (91).
Several pharmacologic treatments have received regulatory approval to treat the symptoms of mild to severe AD dementia. Acetylcholinesterase inhibitors (donepezil, rivastigmine, and galantamine) and N-methyl-D-aspartate receptor antagonists (memantine) can be prescribed to patients to temporarily ameliorate the symptoms of AD dementia such as cognitive and functional decline (92–96). Meta-analyses of donepezil, rivastigmine, and galantamine have shown that patients with mild-to-moderate AD dementia experience some benefits in cognitive function, activities of daily living, and clinician-rated global clinical state (93,94,97). Furthermore, treatment with acetylcholinesterase inhibitors and/or memantine has also been shown to modestly improve measures of global function and temporarily stabilize measures of activities of daily living (96). However, it is important to note that these drugs provide only temporary, symptomatic benefit and that not all patients respond to treatment (36,98). Critically, none of the current drugs available address the underlying pathophysiology or alter the ultimate disease course.
Following AD diagnosis, a comprehensive approach toward clinical care can be individualized based on the patient’s specific AD risk factors (20,21). Clinicians should consider managing uncontrolled vascular risk factors (e.g., hypertension, hyperlipidemia, diabetes) with antithrombotics, antihypertensives, lipid-lowering, and/or antidiabetic agents, respectively, to reduce the risk of cerebrovascular ischemia and stroke, and subsequent cognitive decline (36,99). They should also consider the management of the patient’s behavioral symptoms. For most patients in the early stages of disease, behavioral symptoms will be relatively mild, and no pharmacologic management is required; however, pharmacologic treatment, such as a low-dose selective serotonin reuptake inhibitor, can be prescribed for patients with AD-associated depression and anxiety (100,101).

Specialist clinician checklist

The specialist’s role is critical to further evaluating the initial checks/assessments, providing the diagnosis, and developing the individualized patient management plan:
• Identify deficits to specific cognitive domains using appropriate tests
• Confirm functional performance, using patient and caregiver assessments
• Perform structural imaging to complete assessment of the patient
• Confirm diagnosis with imaging or fluid biomarkers
• Develop a personalized management and follow-up plan
• Direct the patient to additional support resources such as the Alzheimer’s Association

Case study: Treat

Following diagnosis, J.K. was advised on the available management options and research opportunities (Table 1E). The specialist emphasized the need to control his vascular risk factors and suggested lifestyle modifications to optimize the management of his other medical problems. The patient’s neuropsychiatric symptoms were considered mild and did not require pharmacologic intervention. The patient was also provided with details for a local social worker and directed toward further disease-specific information from the Alzheimer’s Association related to his disease. The patient was encouraged to return for additional follow-up visits so that his disease and associated symptoms could be appropriately monitored and managed.

 

Future perspectives

An early diagnosis of AD will become increasingly important as treatments that alter the underlying disease pathology become available—particularly given the expectation that such treatments will be more effective in preserving cognitive function, and thus prolonging independence, when given early in the course of the disease (19). The approval of such treatments will likely lead to an increased awareness of cognitive impairment and other AD-associated symptoms among both the public and non-specialists, such as those in primary care settings. This may encourage more patients/family members to seek help at an earlier stage of disease than is currently seen in community practice. Increased use of sensitive screening measures to proactively assess for the presence of AD symptoms will help identify patients suspected of having early AD. Assessment of cognitive impairment during a Medicare Annual Wellness Visit is inconsistent; the U.S. Preventative Services Task Force, whilst recognizing the importance of MCI, has maintained its decision that there is insufficient evidence to support the mandate of cognitive screening. However, sensitive screening procedures, along with the availability of disease-modifying treatments, are likely to change their recommendations. There is also a need for a mandated, standardized screening approach internationally. Together, this will result in an increase in patients requiring diagnosis, increasing the demand for specialists to evaluate and diagnose, the need for amyloid confirmation, and wait times for patients, which will collectively put further pressure on an already-stretched healthcare infrastructure (25).
Nevertheless, efforts continue within the AD field to streamline the diagnostic process. Planning for and implementing change will not only improve patient management now but also help prepare healthcare systems for an approved disease-modifying treatment for AD. A flexible, multidisciplinary team approach is recommended to integrate the care needed to detect, assess, differentiate, diagnose, treat, and monitor a diverse AD population (24). The development of tests that could be carried out routinely in a primary care setting, such as blood-based AD biomarkers, would help PCPs and non-specialists identify which patients may need further evaluation or referral to a specialist (25). Interest also remains high in advancing imaging techniques, such as amyloid and tau PET, to support a diagnosis of AD. Although amyloid and tau PET are not currently readily available, they may be useful for specialists in the future to determine disease staging or track progression, or as a surrogate marker of cognitive status (74). The introduction of new screening and diagnostic tools could ultimately help lower the burden on specialists and ensure patients are diagnosed in a timely manner.

 

Conclusions

Consensus within the AD community has recently shifted to encourage the diagnosis of AD as early as possible. This shift will enable patients to plan their future and consider symptomatic therapies and lifestyle changes that could reduce cognitive deficits and ultimately help preserve their quality of life. Promisingly, new, potentially disease-modifying therapeutic candidates are on the horizon that could be effective in early AD by targeting and ameliorating the underlying biological mechanisms (92,102). This paper has outlined a menu of practical tools for clinicians to use in the real world to support an early diagnosis of AD and how they may best be incorporated into current clinical practice. Ultimately, a coordinated, multidisciplinary approach that encompasses primary care and specialist expertise is required to ensure timely detection, assessment and differentiation, diagnosis, and management of patients with AD.

 

Authors’ contributions: All authors participated in the review of the literature and in the drafting and reviewing of the manuscript. All authors read and approved the final version of the manuscript for submission.

Funding: The authors developed this manuscript concept during an assessment of Alzheimer’s disease educational needs. The development of this manuscript was funded by Biogen. Editorial support was provided by Jodie Penney, MSc, PhD, Helios Medical Communications, Cheshire, UK, which was funded by Biogen.

Acknowledgements: The authors would like to acknowledge and thank Dr. Giovanni Frisoni, Geneva University Neurocenter, for his contribution towards the development of this manuscript.

Conflict of Interest: AP reports personal fees from Acadia Pharmaceuticals, Alzheon, Avanir, Biogen, Cadent Therapeutics, Eisai, Functional Neuromodulation, MapLight Therapeutics, Premier Healthcare Solutions, Sunovion, and Syneos; grants from Alector, Athira, Avanir, Biogen, Biohaven, Eisai, Eli Lilly, Genentech/Roche, and Vaccinex. RI has nothing to disclose. MS reports personal fees from Alzheon, Athira, Biogen, Cortexyme, Danone, Neurotrope, Regeneron, Roche-Genentech, and Stage 2 Innovations; stock options from Brain Health Inc, NeuroReserve, NeuroTau, Neurotrope, Optimal Cognitive Health Company, uMethod Health, and Versanum Inc. Additionally, he has intellectual property rights with Harper Collins. SK and IR report employment with Biogen.

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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THE ROSAS COHORT: A PROSPECTIVE, LONGITUDINAL STUDY OF BIOMARKERS FOR ALZHEIMER’S DISEASE. STRATEGY, METHODS AND INITIAL RESULTS

 

A. de Mauléon1, M. Soto1, V. Kiyasova2, J. Delrieu1, I. Guignot2, S. Galtier2, M. Lilamand1,3, C. Cantet1, F. Lala1, N. Sastre1, S. Andrieu1, M. Pueyo2, P.J. Ousset1, B. Vellas1

 

1. Gerontopôle, INSERM U 1027, Alzheimer’s Disease Research and Clinical Center, CHU Toulouse, CMRR Midi-Pyrénées, France; 2. Institut de Recherches Internationales SERVIER, Suresnes, France; 3. APHP, Department of Geriatrics, Bichat Hospital, Paris, France

Corresponding Author: Adelaide de Mauleon, MD, Gérontopôle de Toulouse, Department of Geriatric Medicine, Toulouse University Hospital, 224, avenue de Casselardit, 31059 TOULOUSE Cedex 9, France; Phone: 33.5.61.77.64.26, Fax: 33.5.61.77.64.78; E-mail: demauleon.a@chu-toulouse.fr

J Prev Alz Dis 2017;4(3):183-193
Published online March 7, 2017, http://dx.doi.org/10.14283/jpad.2017.8

 


Abstract

Objective: The aims of the Research Of biomarkers in Alzheimer’s diseaSe (ROSAS) study were to determine the biofluid and imaging biomarkers permitting an early diagnosis of Alzheimer’s disease and better characterisation of cognitive and behavioural course of the pathology. This paper outlines the overall strategy, methodology of the study, baseline characteristics of the population and first longitudinal results from the ROSAS cohort.
Methods: Longitudinal prospective monocentric observational study performed at the Alzheimer’s disease Research centre in Toulouse. A total of 387 patients were studied and analyzed in 3 groups: 184 patients with dementia of Alzheimer’s type, 96 patients with memory disorders without dementia (Mild Cognitive Impairment) and 107 patients without abnormal memory tests (control group), and were followed up during 4 years. Patient’s sociodemographic characteristics, risk factors, medical conditions, previous and current medications, neuropsychological assessment and overall cognitive status were recorded. Blood and urine samples were collected at every year, Magnetic Resonance Imaging were performed at inclusion, after one year of follow-up and at the end of the study.
Results: At baseline, three different groups of the cohort differed interestingly in age, level of education, and in percentage of ApoEε4 carriers whereas the history of cardiovascular and endocrine pathologies were similar among the groups. During the follow-up period (3-4 years) 42 mild cognitive impairment patients (43.8%) progressed to dementia, 7 controls progressed into mild cognitive impairment and 1 patient in the control group converted from mild cognitive impairment group to dementia of Alzheimer’s type group. During the first year of follow up, the incidence of progression from mild cognitive impairment to dementia of Alzheimer’s type was 12.7 per 100, during the second year 33.9 per 100 and 46.7 per 100 for the third year.
Conclusion: This paper presents the baseline characteristics of the unique French prospective monocenter study in which the natural course of dementia of Alzheimer’s type was evaluated. Future analysis of blood and urine samples collection from the ROSAS study will permit to identify possible biofluid biomarkers predicting the early stages of the dementia of Alzheimer’s type and risk of progression from Mild Cognitive Impairment to Alzheimer’s disease. .

Key words: Biofluid biomarkers, imaging biomarkers, Alzheimer’s disease, early diagnosis.


 

Introduction

Alzheimer’s disease (AD) is the leading cause of dementia, and because the primary risk factor for AD is old age, the prevalence of the disease is increasing dramatically with ageing population worldwide. AD is a progressive, unremitting, neurodegenerative disorder that affects wide areas of the cerebral cortex and hippocampus. Abnormalities are usually first detected in the frontal and temporal lobes, and then slowly progress to other areas of the neocortex at rates that vary between individuals (1). The natural history of AD is characterized by a long preclinical stage that begins years or maybe decades prior to the onset of clinical symptoms (2).
The diagnosis of AD in clinical care is made however at the symptomatic – dementia stage. Overlapping but slightly different sets of criteria for dementia were provided by the International Classification of Diseases (ICD-10), used in Europe, and the US Diagnostic and statistical Manual of Mental Disorders (DSM – 5). These criteria list clinical features, necessary to make the clinical diagnosis of typical AD, and acknowledge atypical presentations as well. However, several studies demonstrated that people with the clinical diagnosis of AD, when followed to postmortem, do not always have AD-type pathology, with around 20% suggested to be misclassified (3). Making a diagnosis of Alzheimer’s Disease on purely clinical grounds is thus very challenging. New robust and affordable methods are needed for the exact diagnosis of the disease at its early stages and validation of dementia progression.
In the past years, several accurate AD biomarkers that can help the disease diagnosis have emerged (4). These are amyloid β1-42, total tau and phosphorylated tau levels measured in the cerebrospinal fluid (CSF)(5). Functional  and molecular  imaging technologies have confirmed that brain amyloid deposition begins decades before dementia ( in asymptomatic subjects) and precedes cognitive decline and brain atrophy (6). The complete biomarker profile may thus help to identify individuals at early stages, who may draw substantial benefit from disease-modifying therapy or intervention, aiming to change the course of the disease from the preclinical stage.
Not only clinical but also potential economic benefits of early AD diagnosis have been extensively described (7). The sooner a patient is diagnosed with AD, the sooner an appropriate management and targeted interventions might be offered and might thus permit to decrease the economic impact. However, the current biomarkers present some limitations restricting their implementation in clinical routine. Invasive collection methods (e.g. lumbar puncture), additional costs, limited access to neuroimaging centers and the absence of reliable validated standardized blood biomarkers raise major issues. Additional efforts are still needed for identifying reliable, easily exploitable and sensitive circulating biomarkers of AD pathophysiology (e.g. metabolic and inflammatory markers, intra- and extracellular proteins, hormones, miRNA) that will provide highly specific diagnosis of the disease.
The aim of the Research Of biomarkerS in Alzheimer’s diseaSe (ROSAS) study is to determine new biofluid and imaging biomarkers that are associated with earlier diagnosis of AD and better characterising of the cognitive and behavioural course of the disease, in 3 groups: patients with dementia due to AD (AD), patients with memory disorders without dementia (Mild Cognitive Impairment (MCI)) and participants with a normal neuropsychological performance (control group). This paper outlines the overall strategy, methodology of the study, baseline characteristics of the population and first results of their longitudinal evolution longitudinal.

 

Methods

Design

The prospective ROSAS cohort is a longitudinal monocentric observational study performed at the AD- Research centre in Toulouse, France. The population was comprised of 3 groups of subjects:
(a) patients with dementia of Alzheimer’s Type (mild to moderate stage),
(b) patients with memory disorders without dementia (MCI),
(c) subjects with normal neuropsychological performance (control group). Clinical visits were scheduled at baseline and twice a year for AD and MCI patients and once a year for control participants, during a 4-year follow up period (Table 1). Participants were included between July 2007 and March 2011. The last follow up visit took place in March 2014.

Table 1. Investigation schedule

Table 1. Investigation schedule

* Only for patients with demonstrated memory disorders or Alzheimer’s disease; ** Sample of cerebrospinal fluid is performed only if a lumbar puncture is indicated as part of the patient’s follow-up outside the study; ˚ Memory complaint and cognitive impairment only for AD and MCI subjects.

Population

Study population was recruited in a memory clinic setting of Toulouse University Hospital. Participants were men and women, aged 65 years and older, enrolled in 3 following groups:
(a) Patients with Alzheimer’s dementia met Alzheimer’s dementia criteria of Diagnostic and Statistical Manual version IV revised (DSM-IV-TR)(8), had a Mini-Mental State Examination (MMSE)(9) score of 12-26 and global Clinical Dementia Rating Scale (CDR)(10) score of 0.5 or higher (mild to moderate stage); (b) MCI patients did not meet diagnostic criteria of dementia due to AD of DSM-IV-RT, had memory disorder detected by the Rey Auditory Verbal Learning test (RAVLT)(11) (<1 standard deviation (SD) of the age-adjusted mean), a MMSE score of 24 or higher and a CDR global score of 0.5;
(c) Control subjects could have or not memory complaint at the interview and had no memory impairment detected by the RAVLT (value within±1 SD of the age-adjusted mean), had a MMSE score of 26 and higher and a CDR global score of 0.
Participants unable to speak or write French, under legal protection, subjects with brain tumor, stroke or other neurologic diseases that may explain cognitive deficit (e.g. Parkinson’s disease, multiple sclerosis, epilepsy…), with a diagnoses of vascular dementia according to the NINDS-AIREN criteria (12), or other types of dementia, with serious illness or participating in a clinical trial were excluded.
Participants and their informal caregiver took part in the study on voluntary basis, and, they gave their written informed consent at selection. Ethics committee of Toulouse University Hospital approved the study protocol and all its amendments.

Data collection

At baseline and at every follow-up visit face-to-face interviews were held for neuropsychological evaluation of study participant by trained neurologist. Table 1 shows the investigation schedule according to the cognitive status of participants.
Clinical examination of study participants, recording of on-going treatments and reporting of adverse events were done twice a year for patients with dementia due to AD and MCI and once a year for control subjects. Neuropsychological assessments and records of cognitive decline progression (control to MCI and/or AD, MCI to AD) were conducted by trained neuropsychologists at the same periodicity for three different groups.
Brain Magnetic Resonance Imagings (MRIs) were performed on optional basis at enrolment, and then at 12 months and 4-year time points using 3-Tesla scan and included the acquisition of several different sequences: 3 dimensional T1 and T2; 2-dimensional Axial Fluid Attenuated Inversion Recovery (FLAIR), axial Diffusion – Weighted Imaging (DWI), axial Diffusion-Tensor Imaging (DTI); and axial Susceptibility Weighted Imaging (SWI).
Biological samples (blood and urine) were collected in this study at the following timepoints:  the first visit (month 0-M0) and at M12, M24, M36 and M48. Samples were stored in the Cellular Biology and Cytology Laboratory of Toulouse University Hospital and later transferred to specialized CRO B&C (Mechelen, Belgium). The blood cell samples were used for the analysis of the cellular proteins and RNA extraction. The DNA extracted from the whole blood sample at baseline was used for participants’ APOE genotyping. Other genes are planned to be analysed further.
Compulsory lumbar punctures were not a part of the protocol. However, if a lumbar puncture was performed before the participants’ enrolment into ROSAS cohort or it was part of his/her clinical follow-up, 1ml of CSF could have been used for the purposes of this study with the participant’s consent.

Demographics

Subjects’ level of education, age, gender and living arrangement were collected using a structured questionnaire directed to patient and/or their caregivers.

Medical characteristics

Medical history of past and current clinical conditions was recorded with focus on risk factors, cardiac, vascular and psychiatric diseases. At each clinical visit, a neurological examination was performed, height and weight were measured and body mass index was calculated.
Pharmacological treatments with focus on psychotropic medications (anxiolytic, antipsychotic, sedative, antidepressant drugs) as well as cardiac treatment (renin-angiotensin system inhibitors, beta blockers, calcic inhibitors and diuretics) were recorded by a structured questionnaire.
As for anti-dementia treatments, specific drugs including memantine and acetylcholinesterase inhibitors were recorded separately from other non- specific treatments: herbal mixtures, vitamins, traditional medicine.

Clinical assessment

Cognitive assessment included

– MMSE to evaluate orientation, memory, attention, concentration, denomination, repetition, comprehension, ability to formulate a whole sentence and to copy polygons. The disease severity was defined as mild (MMSE>20) and moderate (12-20). Patients at severe stage (MMSE<12) were excluded.
– Global CDR score in order to provide a global rating of severity of dementia on a scale ranging from 0 (no impairment) to 3 (severe impairment). Ratings were taken for 3 cognitive domains (memory, orientation, judgment and problem solving) and 3 functional domains (community affairs, home and hobbies, personal care.). All patients included with a diagnosis of AD had a CDR of 0.5 or above. The severity of disease was defined according to global score as none (CDR =0), questionable (CDR=0.5), mild (CDR=1), moderate (CDR=2) and severe (CDR=3). Patients at severe stage (CDR=3) were excluded. The CDR sum of boxes (CDR SOB) represents the addition of all scores of cognitive and functional domains.
– Alzheimer Disease Assessment Scale (ADAS-Cog 11 items)(13), to assess various cognitive functions: language, comprehension, denomination, orientation, memory and execution of orders. The total score ranges from 0 to 70, with higher scores indicating the more severe cognitive impairment. This scale was administered to patients with dementia due to AD and those with MCI.
– RAVLT to evaluate the explicit verbal episodic memory via learning and recall of sum of words. This test was administered only to control subjects and patients with MCI.
– Trail Making Test (TMT) A and B (14) to judge  perceptive-cognitive-motor speed in part A and mental flexibility capacities in part B. This test was administered only to control subjects and patients with MCI.
– Time of onset and duration (in months) of cognitive impairment and memory complaints in AD and MCI subjects.
– Worsening of cognitive status according to the baseline status of participants: conversion of controls to MCI, conversion of controls to AD and conversion of MCI to AD. In this study, the definition of conversion included changes in psychometric scores (inclusion criteria for each group) combined with clinical judgment of neuropsychiatrist having evaluated the patient. If one of the total scores (MMSE or CDR) were not exactly as defined per protocol for the particular group – final decision on conversion or not was taken by the MD.

Functional evaluation was performed by administration of

– Physical impairment based on Alzheimer’s Disease Cooperative Study-Activities of Daily Living  (ADCS-MCI-ADL) scale (15). This is a 24-item scale to measure daily living activities. Total score ranges from 0 to 78. A higher score indicates less functional impairment.
Neuropsychiatric symptoms (NPS) were measured by total and individual items of the neuropsychiatric inventory (NPI-12) scale (16). The score ranges from 0 to 144, with higher scores indicating the presence of more (severe) NPS.

Laboratory test assessment

Blood

At baseline, complete blood cells count, proteinaemia, albuminaemia, creatininaemia; total cholesterol, triglycerides, C Reactive Protein (CRP), vitamin B12, folates and homocysteine were evaluated in blood samples. Each year, laboratory test assessment included complete blood cells count, proteinaemia, albuminaemia, creatininaemia, total cholesterol, triglycerides and CRP.
In addition, a part of sample collection was oriented for research purpose. Proteomic, metabolomic and transcriptomic analyses were performed in order to identify new potential biomarkers, and to compare protein, metabolic and RNA profiles of different groups of patients.

Urine

Urine strip test was performed at inclusion and urine samples collected once a year were destined for research purposes.

CSF

Total tau protein, phosphorylated tau protein and amyloid protein (Aβ42) were analysed in CSF using ELISA (Innotest hTAU-Ag and Innotest b-amyloid (1-42), Innogenetics) for clinical diagnosis confirmation. Remaining CSF was used for the research of new markers qualified of unidentified markers.

Genetic data

ApoEε4 genotyping was performed for all participants and defined the presence of one or both alleles (” carrier” status) or the absence of ApoEε4 allele (“non-carrier status”).

Statistical analysis

Descriptive statistics were provided by participants group. For quantitative data, the mean and standard deviation (SD) were presented. For qualitative data, number of observed values, number and percentage of participants were presented. All analyses were performed on observed values, missing data were not imputed. Comparisons between groups were performed, using Chi2 statistics (or Fisher exact test for expected values <5) for discrete outcome, and using a General Linear Model for continuous outcomes. Time to conversion was analyzed by Kaplan-Meier method to estimate the percentage of converted participants with 95% confidence interval. Moreover, subgroups analysis was performed, defined according to the phenotype of participants at enrolment (control, MCI, AD; severity of AD; age class; gender; ApoEε4), and their status of conversion or not during the study.
Data were analyzed with SAS software.

 

Results

408 participants were included at baseline visit: 110 controls, 99 MCI and 199 AD patients. Among the total population, twenty-one subjects were excluded from the analysis because of the protocol deviations: age (<65 years), neurological disease (epilepsy, Parkinson’s disease) and MMSE<12. The current results concern 387 participants who completed their baseline visit: 107 controls, 96 MCI and 184 AD (Figure 1). For all the analyses described in this article participants were divided into groups according to their baseline status. At the end of the study, 78 participants in the control group, 64 patients in the MCI group and 107 AD patients completed the 4-year follow up visit. One hundred thirty-eight study participants (35.7%) dropped out of the study for non-medical and medical reasons. At baseline, two thirds of the population were female. The mean age was 79.5±6.0 for patients with dementia due to AD, 78.7±5.6 for MCI patients and 75.6±6.0 for controls (p<0.001). Almost half of the patients with AD, one-third of MCI subjects and one-fifth of controls were ApoE ε4 carriers (p<0.001). Table 2 shows the baseline socio demographic characteristics, known risk factors (cardiovascular included) of the population of the ROSAS study, comparing the 3 groups. Major risk factors showed no statistically significant difference among groups.

Figure 1. Flow chart of the ROSAS study

Figure 1. Flow chart of the ROSAS study

Table 2. Baseline demographic characteristics and risk factors of study participants

Table 2. Baseline demographic characteristics and risk factors of study participants

*Mean±Standard Deviation; ˚ Including patients smoking and those who have smoked; ⁿ During the study period; Abbreviations: AD= Alzheimer’s disease; MCI= Mild Cognitive Impairment; BMI=Body Mass Index; ARAS=Agent acting on the rennin-angiotensin system.

As for the medical history (Table 3), the main difference was observed in psychiatric diseases – AD patients presented more often history of depression than controls (p=0.01). In the panel of blood analysis, the only slight difference was observed in homocysteine concentrations – elevated in AD vs. MCI vs. controls (p<0.001). The pharmacological treatments, prescribed to the participants before and during the study are listed in Table 3. The psychotropic treatments were prescribed most commonly in the patients with AD than in controls (p<0.001) whereas the prescription of cardio- vascular medications was similar in different groups. It is important to note that data on anti-dementia treatments was reported for both: specific and non – specific treatments (“others” – multivitamins, ginkgo biloba, etc.). As mentioned earlier, baseline status of study participants was taken into account for this analysis, however, some of them progressed during the study duration to MCI or to AD. Thus, 3 control participants using acetylcholinesterase inhibitors are those who progressed to MCI and to AD. As for 18.7% of control subjects to whom “other anti-dementia drugs” were prescribed, these are participants who have been receiving mostly Gingko preparations for dementia prevention.

Table 3. Medical history and treatments (previous and ongoing) of study participants

Table 3. Medical history and treatments (previous and ongoing) of study participants

*Mean±Standard Deviation; ⁿ During the study period; Abbreviations: AD= Alzheimer’s disease; MCI= Mild Cognitive Impairment; ARAS=Agent acting on the rennin-angiotensin system.

Table 4 highlights the results of cognitive, functional and neuropsychological assessment of ROSAS study participants at baseline. As expected, the cognitive impairment was significantly more severe in AD population than in MCI subjects or controls (p<0.001). As for the functional and behavioral impairment, the patients with dementia were significantly more functionally (p<0.001) and behaviorally (p<0.001) disabled than MCI and control participants. Interestingly, when baseline cognitive scores were compared among ApoEε4 carriers and non-carriers trends to difference were observed in all three groups including controls despite the small sample size (Supplementary Table 1).

Table 4. Baseline characteristics of patient assessment (cognitive, functional and neuropsychological symptoms)

Table 4. Baseline characteristics of patient assessment (cognitive, functional and neuropsychological symptoms)

*Mean±Standard Deviation; Abbreviations: AD= Alzheimer’s disease; NPI= NeuroPsychiatric Inventory-Questionnaire; MCI= Mild Cognitive Impairment; MMSE=Mini Mental State Examination; CDR= Clinical Dementia Rating scale; ADAS-cog=Alzheimer Disease Assessment Scale; TMT= Trail Making Test; ADCS-MCI-ADLI=Alzheimer’s Disease Cooperative Study-Activities of Daily Living Prevention.

During the 4-year follow up, 42 MCI patients converted to dementia, 5 controls progressed into MCI group and 4 control subjects evolved to AD group. Figure 2 describes the time to conversion from patients with MCI to AD status. During the first year follow up, the incidence of progression from MCI to AD was 12.7% (95% Confidence Interval (CI) =7.3%-21.8%), during the second year 33.9% (95% CI=24.7%-45.2%) and 46.7% (95% CI=36.2%-58.4%) in the third year respectively. The incidence rate of conversions from MCI to AD status on the M0-M12 period was 12.9 events for 100 patient-years, 19.5 events for 100 patient-years on M0-M24 period, 20 events for 100 patient-years on M0-M36 period and on M0-M48 period, 20.1 events for 100 patient-years.
Since lumbar punctures were not compulsory for this study, only 21 CSF samples requested by clinician for diagnosis confirmation had been obtained and analysed. One lumbar puncture was performed before the participant’s enrolment into the study, whereas others were performed during 4-year follow up: 11 AD patients, 8 MCI and 1 normal control (Supplementary Table 2). In 5 cases from 21, biological evaluation helped to confirm the diagnosis of AD. When the CSF profile was unhelpful, the final diagnosis relied on clinical judgment.

Figure 2. Time to conversion from MCI to AD status of the ROSAS study (months). N=96

Figure 2. Time to conversion from MCI to AD status of the ROSAS study (months). N=96

Discussion

During the past two decades, the steady incremental progress was being made in understanding the natural history of Alzheimer’s disease, the kinetics of the disease evolution, its interaction with co-morbidities and normal brain ageing. Epidemiological and genetic studies have identified many risk factors that increase the risk of AD. Prevention studies have highlighted the possibility of targeting both risks and protective factors to delay the onset of the dementia. Several longitudinal cohorts providing better understanding of the disease naturalistic course and aiming the identification of biomarkers for its early diagnosis were launched in the North America (ADNI) and Australia (AIBL). However, taking into account notable differences in ethnic, cultural, socio-economic factors and life style between USA and Europe, the results of such studies should be extrapolated on European population with caution. Specific longitudinal European cohorts are thus of a particular need.

ROSAS baseline

To our knowledge, the ROSAS cohort is the first and unique French monocenter study (2007 – 2014) that aimed better understanding of the course of the disease and creation of a biobank of samples from control subjects, MCI and dementia patients for further biomarkers’ research. The findings of this study demonstrate a certain number of similarities when baseline characteristics of the ROSAS cohort population are compared with that of ADNI (or AIBL). However, the important differences were observed in the level of education, percentage of ApoEε4 carriers and concomitant medications per group between ROSAS and ADNI.
From the point of view of natural disease progression, the main finding of the ROSAS cohort was that almost half of the patients with MCI (n=42(43.8%)) converted to dementia during the 4-year follow-up period, whereas in control group only 9 subjects (8.4%) declined cognitively during the same period converting to MCI, to MCI and AD or to AD directly.
The summary of the baseline characteristics of the subjects indicated significant differences in socio-demographic characteristics among groups, including age, gender and the number of years of former education. The AD patients were the oldest and with the lowest level of education. These observations are in accordance with some baseline data from ADNI (mean age and gender). As for the level of formal education the population enrolled in the ROSAS cohort seems closer to data from ICTUS study and corresponds to “real-life” elderly subjects from Western European countries (14.7 years of education in ADNI vs. 7.6 in ROSAS vs. 9.7 in ICTUS)(17–19).

Risk factors

Dementia is a multifactorial disorder determined by the interplay of the genetic susceptibility and different risk factors, among which cardiovascular risk factors (hypertension, diabetes, obesity, etc.) and smoking (even second hand smoking) were shown to be associated with 50% increased risk of dementia (20). In the ROSAS cohort, no statistically significant differences were identified in vascular and metabolic factors. Main cardiovascular pathologies as well as endocrine diseases were comparable among phenotypes. Pharmacological treatment for these pathologies was similar for 3 groups.
However, an interesting parameter that showed significant difference was the concentration of homocysteine in blood. Elevated homocysteine levels have been associated with an increased risk of cognitive impairment and dementia. However, the capacity of this parameter alone or in combination with other factors to predict the cognitive decline is being still actively debated. Kim et al, have analyzed the relationship of cognitive function with homocysteine, vitamin B and tissue factor pathway inhibitor in cognitively impaired elderly in a cross-sectional survey and demonstrated that plasma homocysteine levels were higher in patients with AD and MCI than those in normal subjects and were negatively correlated with Word List Memory and Constructional Recall Test (21). Another study, performed in Europe – in a community dwelling cohort of older adults from the Vienna Transdanube aging study with MCI showed that hyperhomocysteinaemia at baseline was a predictor of moderate to severe brain atrophy in these subjects in five years (22). As for the results from AIBL – homocysteine levels were increased in female AD patients compared to female Healthy Control subjects (p-value < 0.001), but not in males. However composite z-scores of short- and long-term episodic memory, total episodic memory, and global cognition showed significant negative correlations with homocysteine, in all clinical categories, underscoring the association of this parameter with cognitive deterioration (23). The specificity of this parameter alone is still being discussed, since homocysteine imbalance has long been linked to cognitive dysfunction in schizophrenia for example (24). However, recent publication from Doody et al. demonstrated that elevated homocysteine was associated with AD, suggesting that it might promote the accumulation of the DNA damage in neurons and sensitize them to amyloid beta protein toxicity (25). We can thus suggest that in further multi-modal analyses the combination of homocysteine concentration in blood with specific MRI parameters standardized for neurodegenerative diseases and cognitive scales scores at baseline in the ROSAS cohort patients may be explored as a combined predictive factor of conversion from MCI to AD.
Recent intensive genetic research has identified Apo-ε4 as a susceptibility gene for sporadic AD. But only 50% of the late-onset AD subjects were shown to be Apo- ε4 carriers and thus, it is not currently used alone as a biomarker of AD diagnosis and progression. It is known that humans expressing ApoE4 protein develop more plaques and vascular β-amyloid deposits than those expressing only ApoE3 (26) and this has been confirmed in genetically engineered mice (27). In the ROSAS study, almost half of patients with dementia of AD type were Apo- ε4 – carriers (48%), whereas in ADNI and AIBL this percentage was slightly higher for both AD patients (66% and 61%) and healthy controls (26% and 27%) respectively with a higher sample size as well (28). It is to note that when carriers and non-carriers were compared in each subgroup (control vs. MCI vs. AD) and the differences in cognitive performances evaluated by several scales were documented already at baseline. The data from AIBL study demonstrated same slight variations in baseline cognitive performances among subjects with different genotype. Moreover, the proportion of APOE ε4 carriers differed between stable MCI stable (36.9% APOE ε4 positive) and MCI patients who progressed to AD (78.1% APOE ε4 positive) after 18 months of follow-up (29) indicating its important impact on increasing the risk of cognitive decline progression. Further analysis of several genes that might be potential risk factors for AD and conversion from MCI to AD, including triggering receptor expressed on myeloid cells 2 (TREM2), cluster of differentiation 33 (CD33), clusterin (CLU), complement receptor 1 (CR1), phosphatidylinositol binding clathrin assembly protein (PICALM), and sortilin-related receptor (SORL1) will be performed shortly.

Treatments

In the present cohort, we found high rates of specific anti-dementia treatment including memantine, anticholinesterases drugs. Almost 100% of patients with AD dementia and a half of patients with MCI had a treatment. Interestingly in north American cohorts as ADNI (30) or Canadian Outcomes Study in Dementia (COSID)(18), the percentage of AD subjects using these therapies at baseline is slightly lower and is around 85%. A possible reason for higher prevalence of specific treatment in our cohort is that it is quite recent; subjects have been identified relying on multiplicity of specific criteria, evaluated by experienced neuropsychologists in a center for memory disorders and AD research, which does not reflect the real clinical practice. Moreover, it could be hypothesized that anti-dementia use would be variable because of national dementia policies and the existing guidelines. For example, a recent European cohort with AD subjects shows instead a higher rate of use of anti-dementia medication than in USA of 90% (31).
The fact that can seem surprising is the level of prescription of nonspecific anti-dementia treatment found in our normal group. One-fifth on the control subjects were either, on vitamin E or gingko biloba, since our AD research center was participating in GUIDAGE study at the moment and participants who terminated the trial had the right to be enrolled in the ROSAS cohort. Another possible reason of the higher prevalence of treatment in the control population was the analysis bias – the definition of groups was done according to the baseline status of participants without taking account the change of cognitive status (e.g. conversion of MCI to AD group), thus suggesting the possibility that 3 control subjects receiving anticholinesterase drugs were those from 9 progressors.
However, when the prescription of psychotropic drugs was analyzed, we observed that they were prescribed most commonly in patients with AD. Previous studies in Europe (31) showed similar results and demonstrated that the prevalence of psychotropic treatment increases with the AD and with the stage of dementia. In ROSAS cohort antidepressants prescription was only slightly different between MCI and AD patients (43% vs. 51%), whereas the use antipsychotics was increased in AD patients. 18% of AD patients received antipsychotics vs. 3% of MCI participants. These drugs are more likely to be used in clinically severe patients and might be prescribed for various reasons, including hallucination, delusion, aggression, agitation, irritability, and sleep disturbances. The similar use of antidepressants in both groups might suggest that depression neither increased nor decreased over time but persisted as stable symptom present independently of cognitive decline progression. Finally, the different groups did not differ in terms of cerebrovascular or cardiovascular diseases or cardiac treatment.

Longitudinal conversion

During the 1st year of follow up, the conversion from MCI to AD status showed an incidence rate of 12.9 events from patient-years (12.7% (95% Confidence Interval (CI) =7.3%; 21.8%). while on M0-M24 period the incidence increased to 19.5 events for 100 patient-years (33.9% (95% Confidence Interval (CI) = 24.7%; 45.2%), when 4-year period (M0-M48) was analyzed, the incidence of conversions in the ROSAS cohort was estimated as 20.1 events for 100 patient-years. In ADNI study, this progression concerned a rate of 16% per year during the first twelve months of the study (17) and previous studies defined a conversion between 10% and 17% per year (32), suggesting thus that our results were comparable and quite similar to the data from current cohorts.
The ROSAS cohort is a unique and large French monocentric longitudinal prospective study that followed different patterns of cognitive evolution of MCI and AD subjects. To our knowledge, this study has been the largest monocentric cohort performed in the AD research and clinical memory center in France. Subsequently, the inclusion of participants in a highly-experienced memory center permitted homogeneity of the cohort and patients’ evaluation, without a significant inter-center variation. In addition, this monocentric study was not only rich in clinical data collected but was improved by radiological data and biocollection. The ROSAS study provides a major opportunity, during a longer 4-year follow up, twice a year for participants with AD and MCI and once a year for subjects with normal neuropsychological tests, to describe and to analyze the evolution of decline and biomarkers in these three groups. Finally, the withdrawals for different reasons (medical reasons (deaths included) and non-medical reasons) represented 1/3 of the cohort population. This result was lower than previously reported in other cohorts. In REAL.FR study (33), a French prospective multi centric cohort of AD patients, 2/3 of subjects did not complete a 4-year follow up.
The ROSAS study had some limitations however. Firstly, the population recruited was not representative of AD and MCI subjects with “real populations”. Secondly, the definition of the different groups (AD, MCI and control group) was based only on clinical criteria (DSM-IV) since the lumbar puncture was only performed in few patients. Therefore, we did not have complete physio pathological biomarkers to confirm the diagnosis. However, the bio-collection from this cohort as well as neuroimaging data will be analyzed and should retrospectively improve the information on disease early phases and permit more precise diagnosis.
This current cohort will allow for additional analyses including imaging studies with brain MRI or protein biomarkers and will highlight important data on the earlier diagnosis. To date, the existing biochemical or neuroimaging biomarkers of AD have paved the way for an earlier diagnosis and a better understanding of the natural course of dementia. In the perspective of large population screening, ROSAS study focused mostly on blood or urinary samples that had been easier to collect and process – similar to current clinical practice in Europe. Multiple biomarkers have been used separately to quantify the disease progression. But, the identification of optional markers for predicting this process and explaining it for future therapies still remains unresolved. Nowadays, methods are also needed to integrate these multiple biomarkers to obtain a better recognition of the disease (34) predicting the emerging of AD with the ultimate goal of providing a platform for therapeutic intervention with disease modifying therapies. (35)
Further analysis involving MRI, metabolomics analysis or clinical criteria (e.g. NPI) and results from the ROSAS study will help better characterization of the cognitive and behavioural course of the disease. Deeper analysis of factors differentiating MCI patients progressing to dementia from non -converters will be of particular value in addition to previous major studies (28, 32, 35).

Supplementary table 1. Main Neuropsychological endpoints at inclusion in the ApoE ε4 carriers and non-carriers participants

Supplementary table 1. Main Neuropsychological endpoints at inclusion in the ApoE ε4 carriers and non-carriers participants

Supplementary table 2. Results of cerebrospinal fluid (CSF) samples analyses

Supplementary table 2. Results of cerebrospinal fluid (CSF) samples analyses

Funding: This study was supported by Institut De Recherche SERVIER – CL2-NEURO-003 study protocol (registration number DGS 20060500).

Conflict of interest disclosure: Dr. Vera Kiyasova, Dr. Maria Pueyo, Mrs. Stéphanie Galtier, Mrs. Isabelle Guignot are  employees of SERVIER Laboratories..,

Ethical standards: Ethics committee of Toulouse University Hospital approved the study protocol and all its amendments. The study was conducted in compliance with the protocol, GCP, the ethical principles that have their origin in the Declaration of Helsinki and the applicable regulatory requirements.

 

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