Connecting Cohorts to Diminish Alzheimer's Disease (CONCORD-AD): A Report of an International Research Collaboration Network

Abstract

Longitudinal observational cohort studies are being conducted worldwide to understand cognition, biomarkers, and the health of the aging population better. Cross-cohort comparisons and networks of registries in Alzheimer's disease (AD) foster scientific exchange, generate insights, and contribute to the evolving clinical science in AD. A scientific working group was convened with invited investigators from established cohort studies in AD, in order to form a research collaboration network as a resource to address important research questions. The Connecting Cohorts to Diminish Alzheimer's Disease (CONCORD-AD) collaboration network was created to bring together global resources and expertise, to generate insights and improve understanding of the natural history of AD, to inform design of clinical trials in all disease stages, and to plan for optimal patient access to disease-modifying therapies once they become available. The network brings together expertise and data insights from 7 cohorts across Australia, Europe, and North America. Notably, the network includes populations recruited through memory clinics as well as population-based cohorts, representing observations from individuals across the AD spectrum. This report aims to introduce the CONCORD-AD network, providing an overview of the cohorts involved, reporting the common assessments used, and describing the key characteristics of the cohort populations. Cohort study designs and baseline population characteristics are compared, and available cognitive, functional, and neuropsychiatric symptom data, as well as the frequency of biomarker assessments, are summarized. Finally, the challenges and opportunities of cross-cohort studies in AD are discussed.

Keywords: Alzheimer’s disease; CONCORD-AD network; biomarkers; cognitive function; cohort; dementia; observational study; population characteristics.

Fig. 1

Assessments conducted in at least two of the CONCORD-AD cohorts. Includes assessments performed in cohort studies in different geographic regions. Aβ, amyloid-β; AD, Alzheimer’s disease; ADAS-Cog, Alzheimer’s Disease Assessment Scale–Cognitive subscale; ADL, Activities of daily living; AIBL, Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing; AMI, AGRICA-MSA-Institut fédératif de recherche en santé publique/Aging Multidisciplinary Investigation; BioFINDER-1, Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably; BVRT, Benton Visual Retention test; CDR-SB, Clinical Dementia Rating–Sum of Boxes; CES-D, Centre for Epidemiologic Studies Depression; CSF, cerebrospinal fluid; CU, cognitively unimpaired; DSST, Digit Symbol Substitution Test; FAQ, Functional Assessment Questionnaire; FCSRT, Free and Cued Selective Reminding Test; GDS, Geriatric Depression Scale; IADL, Instrumental Activities of Daily Living; IST, Isaacs Set Test; MCI, mild cognitive impairment; MCSA, Mayo Clinic Study of Aging; MINI, Mini-International Neuropsychiatric Interview; MMSE, Mini-Mental State Examination; ND, non-demented; NPI-Q, Neuropsychiatric Inventory Questionnaire; NPS, neuropsychiatric symptoms; PET, positron emission tomography; pTau, phosphorylated tau; tTau, total tau; WAIS-III, Wechsler Adult Intelligence Scale–Third Edition; WAIS-R, Wechsler Adult Intelligence Scale–Revised; WMS-R, Wechsler Memory Scale–Revised; 3C Bordeaux, Three-City Study. ^aUsed in the COGICARE sub-study of 3C Bordeaux in all participants with dementia; ^bDSST can be derived from the WAIS-R used in Baylor and from WAIS-III in AIBL; ^cMMSE score can be derived from the Short Test of Mental Status used in MCSA; ^dWAIS-R in Baylor, WAIS-III in AIBL; ^eWechsler similarities test used; ^fWechsler story memory test; ^gADL Inventory; ^hLawton and Brody instrumental ADL Scales; ⁱKatz scale; ^jShort form used in the COGICARE sub-study of 3C; ^kAmyloid-PET available only on a subsample at the follow-up.

Fig. 2

Comparison of baseline MMSE scores across the cohorts in (A) CU, (B) MCI, and (C) AD participants. Note that for population-based cohorts, AD at baseline are prevalent cases, and not incident cases or cases recently referred to a memory clinic. AD, Alzheimer’s disease; AIBL, Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing; AMI, AGRICA-MSA-Institut fédératif de recherche en santé publique/Aging Multidisciplinary Investigation; Baylor, Alzheimer’s Disease and Memory Disorders Center at Baylor College of Medicine; BioFINDER-1, Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably; CU, cognitively unimpaired; MCSA, Mayo Clinic Study of Aging; MMSE, Mini-Mental State Examination; ND, no data; PAQUID, Personnes Agées QUID; 3C Bordeaux, Three-City Study. ^aThe PAQUID, 3C Bordeaux and AMI studies scores are presented of non-demented participants; ^bThe AIBL, Baylor, and BioFINDER-1, data presented is specific to AD dementia (clinically defined AD or biomarker-confirmed AD; BioFINDER-1 includes AD with other pathologies where AD is the dominant etiology); ^cMCSA included dementia of any cause; ^d3C Bordeaux, PAQUID, and AMI included AD or AD plus another form of dementia (with another type of lesion or atypical clinical presentation).

Fig. 3

Frequency of NPS, as assessed by NPI-Q, and displayed by disease stage in the MCSA^a, 3C^b, and Baylor cohorts^c. AD, Alzheimer’s Disease; MCSA, Mayo Clinic Study of Aging; Baylor, Alzheimer’s Disease and Memory Disorders Center at Baylor College of Medicine; CU, cognitively unimpaired; MCI, mild cognitive impairment; 3C, Three-City Study; NPI-Q, Neuropsychiatric Inventory–Questionnaire; NPS, Neuropsychiatric symptoms. ^aIn non-demented and≥50 years of age participants, with a concurrent, valid NPS assessment and amyloid positron emission tomography (PET) neuroimaging. MCSA data have been reported previously [65]; ^bResults presented from COGICARE, a sub-study of 3C; ^cData were not available from the other cohorts.