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Pavlik VN, Burnham SC, Kass JS, Helmer C, Palmqvist S, Vassilaki M, Dartigues JF, Hansson O, Masters CL, Pérès K, Petersen RC, Stomrud E, Butler L, Coloma PM, Teitsma XM, Doody R, Sano M. Connecting Cohorts to Diminish Alzheimer's Disease (CONCORD-AD): A Report of an International Research Collaboration Network. J Alzheimers Dis 2022; 85:31-45. [PMID: 34776434 PMCID: PMC8842789 DOI: 10.3233/jad-210525] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2021] [Indexed: 11/15/2022]
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.
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Affiliation(s)
- Valory N. Pavlik
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Samantha C. Burnham
- The Australian eHealth Research Centre, CSIRO Health and Biosecurity, Melbourne, VIC, Australia
| | - Joseph S. Kass
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Catherine Helmer
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR, Bordeaux, France
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Maria Vassilaki
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
| | - Jean-François Dartigues
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR, Bordeaux, France
- Department of Neurology, Memory Consultation, Bordeaux University Hospital, Bordeaux, France
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Colin L. Masters
- The Florey Institute and The University of Melbourne, Parkville, VIC, Australia
| | - Karine Pérès
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR, Bordeaux, France
| | - Ronald C. Petersen
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Lesley Butler
- Product Development Personalised Health Care – Data Science, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Preciosa M. Coloma
- Product Development Personalised Health Care – Data Science, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Xavier M. Teitsma
- Product Development Personalised Health Care – Data Science, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Rachelle Doody
- Product Development Neuroscience, F. Hoffmann-La Roche Ltd, Basel, Switzerland
- Product Development Neuroscience, Genentech, Inc., South San Francisco, CA, USA
| | - Mary Sano
- Department of Psychiatry, Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
| | - for the CONCORD-AD investigators
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
- The Australian eHealth Research Centre, CSIRO Health and Biosecurity, Melbourne, VIC, Australia
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR, Bordeaux, France
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Memory Consultation, Bordeaux University Hospital, Bordeaux, France
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
- The Florey Institute and The University of Melbourne, Parkville, VIC, Australia
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Product Development Personalised Health Care – Data Science, F. Hoffmann-La Roche Ltd, Basel, Switzerland
- Product Development Neuroscience, F. Hoffmann-La Roche Ltd, Basel, Switzerland
- Product Development Neuroscience, Genentech, Inc., South San Francisco, CA, USA
- Department of Psychiatry, Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
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