COSMIC:

Cohort Studies of Memory in an International Consortium —Combining data from population-based longitudinal cohorts studies to identify common risk factors for dementia and cognitive decline.

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COSMIC: Cohort Studies of Memory in an International Consortium logo

New members: We encourage suitable cohort studies to join COSMIC, particularly those from under-represented regions or populations. Please see the membership criteria and contact information below.

Data use: Qualified researchers from anywhere in the world can apply to use COSMIC data via Dementias Platform Australia (DPAU).

About COSMIC

Ageing is intricately connected with cognitive decline, and there is an increasing proportion of life lived with cognitive impairment as the lifespan increases. If an impact is to be made on this disability burden, we must understand the risk and protective factors for cognitive decline, frailty and chronic disease associated with ageing. The best approach is to study this using population-based ageing cohorts. A large number of such studies are ongoing internationally, and have identified a diverse range of factors, but there is considerable inconsistency in the results produced and the existing evidence needs further systematic examination. This also relates to the evidence for vascular risk factors as risk factors for Alzheimer’s Disease (AD). While many publications have previously argued for this, a recent review concluded that “at the present time, there is no consistent body of evidence to show that vascular risk factors increase AD pathology”.

Researchers of brain ageing from around the world come together in the COSMIC collaboration to determine what factors are common for cognitive decline and dementia in all human populations irrespective of race, ethnicity and socioeconomic development.

We argue that the way to deal with inconsistencies in the literature is to harmonise international studies so that data can be pooled and risk factors examined with greatly increased power. Accordingly, COSMIC (Cohort Studies of Memory in an International Consortium) has so far brought together 60 cohort studies of cognitive ageing from 38 countries across 6 continents, with a combined sample size of almost 186,000 individuals. The aim of the collaboration is to facilitate a better understanding of the determinants of cognitive ageing and neurocognitive disorders. This is being achieved by:

  1. Harmonising shared, non-identifiable data from cohort studies that longitudinally examine change in cognitive function and the development of dementia in older individuals (60+ years).
  2. Performing joint or mega-analyses using combined, harmonised data sets that yield collated results with enhanced statistical power, in addition to comparisons across diverse ethno-regional groups.

We believe COSMIC to be a unique endeavor, as other consortia with similar or related aims do not have the same level of international scope, or have a focus such as genomic epidemiology: CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) and ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis).


NIH Grant Helps Support COSMIC to Late 2028

In August 2023, Professor Perminder Sachdev, Co-Director of CHeBA and head of COSMIC, was awarded US$7.27 million over 5 years from the National Institute on Aging (NIA) of the National Institutes of Health (NIH), USA.  This is in addition to a previous grant of US$2,57 million granted by the NIH in September 2017. The grants awarded allow further work in identifying risk and protective factors and biomarkers of cognitive ageing and dementia.

Investigators on the current grant include Professor Louisa Jorm, director of the UNSW Centre for Big Data Research in Health and CHeBA Co-Director Professor Henry Brodaty, as well as leading researchers from the USA (Professors Mary Ganguli, Richard Lipton), France (Dr. Maeleen Guerchet), Peru (Professor Jaime Miranda), India (Dr. Murali Krishna), UK (Professor Sarah Bauermeister) & Sweden (Professor Henrik Zetterberg). 

  • The COSMIC Research Scientific Committee (RSC) is comprised of one leading researcher from each of the contributing studies:

    Study

    RSC member

    Additional study leader

    AGELESS

    Maw Pin Tan

     

    10/66 Cuba (Cuban Health and Alzheimer Study)

    Juan J. Llibre-Rodriguez

     

    10/66 Dominican Republic

    Daisy Acosta

     

    10/66 Mexico

    Ana Luisa Sosa

     

    10/66 Peru

    Mariella Guerra Arteaga

     

    10/66 Puerto Rico

    Ivonne Z. Jimenez-Velazquez

     

    10/66 Venezuela

    Aquiles Salas

     

    Atma Jaya Cognitive & Aging Research (ACtive Aging Research)

    Yuda Turana

     

    The Atahualpa Project

    Oscar H. Del Brutto

     

    Bambui Cohort Study of Aging

    Erico Costa

     

    Boston Puerto Rican Health Study

    Sabrina Noel

     

    Canadian Study of Health & Aging (CSHA)

    Kenneth Rockwood

     

    Chinese Longitudinal Aging Study (CLAS)

    Xiao Shifu

     

    Cognitive Function and Ageing Studies (CFAS)

    Carol Brayne

     

    Einstein Aging Study (EAS)

    Richard Lipton

    Mindy J Katz

    Epidemiology of Dementia in Central Africa (EPIDEMCA)

    Maëlenn Guerchet

    Pierre-Marie Preux

    EpiFloripa Aging Study

    Eleonora d’Orsi

     

    Etude Santé Psychologique Prévalence Risques et Traitement (ESPRIT)

    Karen Ritchie

    Marie-Laure Ancelin

    Faroese Septuagenarian Cohort

    Maria Skaalum Petersen

     

    Framingham Heart Study (FHS)

    Rhoda Au

     

    Gothenburg H70 Birth Cohort Studies

    Ingmar Skoog

     

    Hellenic Longitudinal Investigation of Aging and Diet (HELIAD)

    Nikolaos Scarmeas

     

    Hisayama Study

    Toshiharu Ninimiya

     

    Hong Kong Memory and Ageing Prospective Study (HK-MAPS)

    Linda Lam

     

    Ibadan Study of Ageing (ISA)

    Oye Gureje

     

    Identification and Intervention for Dementia in Elderly Africans (IDEA) Study

    Stella-Maria Paddick

    Richard Walker

    I-Lan Longitudinal Aging Study (ILAS)

    Liang-Kung Chen

     

    IMIAS (International Mobility in Aging Study)

    Mohammad Auais

    Ricardo Oliveira Guerra

    Indianapolis Ibadan Dementia Project

    Hugh Hendrie

     

    Invecchiamento Cerebrale in Abbiategrasso (Invece.Ab)

    Elena Rolandi 

     

    The Irish Longitudinal Study on Ageing (TILDA)

    Ann Hever 

    Rose Anne Kenny

    KLOSCAD (Korean Longitudinal Study on Cognitive Aging and Dementia)

    Ki-Woong Kim

     

    Kurihara Project

    Kenichi Meguro

     

    Leiden 85-plus study

    Jacobijn Gussekloo

     

    Leipzig Longitudinal Study of the Aged (LEILA75+)

    Steffi Riedel-Heller

     

    LRGS TUA: Neuroprotective Model for Healthy Longevity among Malaysian Older Adults

    Suzana Shahar

     

    Maastricht Aging Study (MAAS)

    Sebastian Koehler

    Kay Deckers

    Marikina Memory and Aging Project (MMAP)

    Jacqueline Dominguez

     

    Monongahela-Youghiogheny Healthy Aging Team (MYHAT)

    Mary Ganguli

     

    MYNAH (MYsore studies of Natal effects on Ageing and Health)

    Murali Krishna

     

    Neuroepidemiology of cognitive impairment in adults from marginal urban areas: a door-to-door population study in the Puente Piedra district, Lima, Perú

    Nilton Custodio

     

    Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA)

    Bernadette McGuinness

    Frank Kee

    Personality & Total Health (PATH) Through Life project

    Kaarin Anstey

     

    Puerto Rican Elderly: Health Conditions Study (PREHCO)

    Michael Crowe

     

    Sacramento Area Latino Study on Aging (SALSA)

    Allison Aiello

     

    Sasaguri Genkimon Study

    Kenji Narazaki

     

    Shanghai Aging Study (SAS)

    Ding Ding

     

    Singapore Longitudinal Ageing Studies (SLAS I & II)

    Roger Ho

     

    São Paulo Ageing & Health Study (SPAH)

    Marcia Scazufca

     

    Sydney Memory & Ageing Study (MAS)

    Henry Brodaty

    Perminder Sachdev

    Taiwan Initiative for Geriatric Epidemiological Research (TIGER)

    Yen-Ching Chen

    Jen-Hau Chen

    Tajiri Project

    Kenichi Meguro

     

    Ugandan study

    Vincent Mubangizi

     

    Vallecas Project

    Pascual Sanchez-Juan

     

    Washington Heights Inwood and Columbia Aging Project (WHICAP)

    Richard Mayeux

    Nicole Schupf

    Whitehall II

    Mika Kivimaki

     

    ZARADEMP Project

    Antonio Lobo

     
    • Perminder Sachdev: Scientia Professor of Neuropsychiatry; Co-Director, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney; Director, Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia; 
    • Richard Lipton: Edwin S. Lowe Professor and Vice Chair of Neurology, Albert Einstein College of Medicine;
    • Henry Brodaty: Scientia Professor of Ageing & Mental Health; Co-Director, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney; Director, Dementia Collaborative Research Centre (DCRC); Senior Consultant, Old Age Psychiatry, Prince of Wales Hospital;
    • Louisa Jorm: Director, Centre for Big Data Research in Health and Professor, Faculty of Medicine, UNSW Sydney, Australia;
    • Maëlenn Guerchet: Senior Researcher, Institut de Recherche pour le Developpement, France
    • Sarah Bauermeister: Associate Professor of Cognitive Neuropsychology, Department of Psychiatry, University of Oxford; Senior Scientist and Senior Data Manager, Dementias Platform UK (DPUK)
    • Henrik Zetterberg: Professor of Neurochemistry & Department Head, Psychiatry and Neurochemistry, University of Gothenburg, Sweden;
    • Ester Cerin: Professor & Program Leader, Behaviour, Environment and Cognition Research Program, Australian Catholic University Limited, Australia;
    • Jaime Miranda: Research Professor at the Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Peru;
    • Mary Ganguli: Professor of Psychiatry, Neurology, and Epidemiology, University of Pittsburgh, USA; 
    • Murali Krishna: Senior Research Fellow, Centre for Mental Health and Society, University of Bangor, India;
    • Wei Wen: Associate Professor, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney, Australia;
    • Vibeke Catts: Postdoctoral Fellow, Research Manager, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney, Australia;
    • Mindy Katz: Senior Associate, The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, USA;
    • John Crawford: Senior Research Officer, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney, Australia;
    • Nicole Kochan: Senior Research Fellow, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney, Australia;
    • Louise Mewton: Associate Professor and Program Lead in Lifespan and Brain Health Research at the Matilda Centre, University of Sydney, Australia;
    • Thomas Karikari: Assistant Professor of Psychiatry, University of Pittsburgh, USA;
    • Anbupalam Thalamuthu, Senior Research Fellow, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney, Australia;
    • Karen Mather, Senior Research Fellow, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney, Australia. 

COSMIC Publications

No.PublicationFree PMC Article
1Sachdev et al. COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups. BMC Neurol.  2013;13:165. https://bmcneurol.biomedcentral.com/articles/10.1186/1471-2377-13-165.DOI: 10.1186/1471-2377-13-165. PMID: 24195705. PMC3827845PMC3827845
2Sachdev et al. The prevalence of mild cognitive impairment in diverse geographical and ethnocultural regions: The COSMIC collaboration. PLOS One. 2015;10:e0142388. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142388. DOI: 10.1371/journal.pone.0142388. PMID:26539987. PMC4634954PMC4634954
3Lipnicki et al. Age-related cognitive decline and associations with sex, education and apolipoprotein E genotype across ethnocultural groups and geographic regions: a collaborative cohort study. PLoS Med. 2017;14(3):e1002261. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002261. DOI: 10.1371/journal.pmed.1002261. PMID:28323832. PMC5360220PMC5360220
4Jang et al. Differential effects of completed and incomplete pregnancies on the risk of Alzheimer disease. Neurology. 2018;91(7):e643-e651. Neurology. 2018;91(7):e643-e651 (PFD). DOI:10.1212/WNL.0000000000006000. PMID:30021919. PMC9811944PMC9811944
5Oltra-Cucarella et al. Visual memory tests enhance the identification of amnestic MCI cases at greater risk of Alzheimer’s disease. Int Psychogeriatr. 2018 Oct 25:1-10. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6483891/. DOI: 10.1017/S104161021800145X. PMID:30355384. PMC6483891PMC6483891
6Lipnicki et al. Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study. PLoS Med. 2019;16:e1002853. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002853. DOI: 10.1371/journal.pmed.1002853. PMID:31335910. PMC6650056PMC6650056
7Maasakkers et al. The association of sedentary behaviour and cognitive function in people without dementia: A coordinated analysis across five cohort studies. Sports Med. 2020 Feb;50(2):403-413. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6985182/. DOI: 10.1007/s40279-019-01186-7. PMID: 31529300. PMC6985182PMC6985182
8Turana et al. Factors associated with odour identification in older Indonesian and white Australian adults. Aging Clin Exp Res. 2020 Feb;32(2):215-221. https://link.springer.com/article/10.1007/s40520-019-01419-9. DOI: 10.1007/s40520-019-01419-9. PMID:31755024. PMC7519881PMC7519881
9Makkar et al. APOE ε4 and the Influence of Sex, Age, Vascular Risk Factors, and Ethnicity on Cognitive Decline. J Gerontol A Biol Sci Med Sci. 2020 May 12;glaa116. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518559/. DOI: 10.1093/gerona/glaa116. PMID:32396611. PMC7518559PMC7518559
10Makkar et al. Education and the moderating roles of age, sex, ethnicity and apolipoprotein epsilon 4 on the risk of cognitive impairment. Arch Gerontol Geriatr. 2020 Jul 13;91:104112. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724926/. DOI:10.1016/j.archger.2020.104112. PMID:32738518. PMC7724926PMC7724926
11Bae et al. Does parity matter in women’s risk of dementia?: a COSMIC collaboration cohort study. BMC Med. 2020 Aug 5;18(1):210. doi: 10.1186/s12916-020-01671-1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406389/. DOI:10.1186/s12916-020-01671-1. PMID:32753059. PMC7406389PMC7406389
12Carles et al. A Cross-National Study of Depression in Pre-clinical Alzheimer’s Disease: a COSMIC Collaboration Study. Alzheimers Dement. 2020 Sep 3. doi: 10.1002/alz.12149. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666102/. DOI: 10.1002/alz.12149. PMID: 32881298. PMC7666102PMC7666102
13Bae et al. Parity and the risk of incident dementia: a COSMIC collaboration cohort study. Epidemiol Psychiatr Sci. 2020 Oct 20;29:e176. DOI: 10.1017/S2045796020000876. PMID:33077022. PMC7681107PMC7681107
14Roehr et al. Estimating prevalence of subjective cognitive decline across international cohort studies of ageing: A COSMIC study. Alzheimers Res Ther. 2020;12(1):167. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749505/. DOI: 10.1186/s13195-020-00734-y. PMID: 33339532. PMC7749505PMC7749505
15Hyun et al. Education, occupational complexity, and incident dementia: A COSMIC collaborative cohort study. J Alzheimers Dis. 2021 Nov 11. doi: 10.3233/JAD-210627. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748312/. DOI: 10.3233/JAD-210627. PMID: 34776437. PMC8748312PMC8748312
16Wu et al. Dose-response relationship between late-life physical activity and incident dementia: a pooled analysis of 10 cohort studies of memory in an international consortium. Physical activity and cognitive decline in older adults. Alzheimers Dement. 2022 Mar 15. doi: 10.1002/alz.12628. Online ahead of print. DOI: 10.1002/alz.12628. PMID: 35290713. PMC9652610 PMC9652610
17Mewton et al. The relationship between alcohol use and dementia in adults aged over 60 years: A combined analysis of prospective, individual-participant data from 15 international studies. Addiction. 2023;118(3):412-424. doi: 10.1111/add.16035. PMID: 35993434. PMC9898084PMC9898084
18Samtani et al. Associations between social connections and cognition: a global collaborative individual participant data meta-analysis. Lancet Healthy Longev. 2022 Nov;3(11):e740-e753. DOI: 10.1016/S2666-7568(22)00199-4. Epub 2022 Oct 20. PMID: 36273484. PMC9750173PMC9750173
19Gong et al. Sex differences in dementia risk and risk factors: individual-participant data analysis using 21 cohorts across six continents from the COSMIC consortium. Alzheimers Dement. 2023;19(8):3365-3378. DOI: 10.1002/alz.12962. PMID:36790027. PMC10955774PMC10955774
20Lipnicki et al. Harmonizing ethno-regionally diverse datasets to advance the global epidemiology of dementia. Clin Geriatr Med. 2023 February ; 39(1): 177–190. DOI:10.1016/j.cger.2022.07.009. PMID: 36404030. PMC: 9767705PMC9767705
21Mahalingam, Samtani et al. Social connections and risk of incident mild cognitive impairment, dementia and mortality in 13 longitudinal cohort studies of ageing. Alzheimers Dement. 2023;19(11):5114-5128. DOI: 10.1002/alz.13072. PMID:37102417. PMC10603208PMC10603208
22Sprague et al. Correlates of gait speed among older adults from six countries: Findings from the COSMIC collaboration. J Gerontol A Biol Sci Med Sci. 2023;78(12):2396-2406. DOI: 10.1093/gerona/glad090. PMID: 36975099. PMC10692426PMC10692426
23Oh et al. Parental History of Dementia and the Risk of Dementia: A cross-sectional analysis of a global collaborative study. Psychiatry and Clinical Neurosciences 2023 Aug;77(8):449-456. DOI: 10.1111/pcn.13561. PMID: 37165609. PMC10524874PMC10524874
24Lennon et al. Use of Antihypertensives, Blood Pressure, and Estimated Risk of Dementia in Late -Life: An Individual Participant Data Systematic Review and Meta-Analysis. JAMA Netw Open. 2023 Sep 5;6(9):e2333353. DOI:10.1001/jamanetworkopen.2023.33353. PMID: 37698858. PMC10498335PMC10498335
25Lin et al. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: the COSMIC consortium. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring (accepted 2024 Feb 2). DOI: 10.1002/dad2.12567. PMID: 38487075. PMC10937819PMC10937819
26Van Asbroeck et al. Lifestyle and incident dementia: A COSMIC individual participant data meta‐analysis. Alzheimers Dement. 2024 Apr 27. DOI: 10.1002/alz.13846. PMID: 38676366PMC38676366
27Zhao, et al. Independent and joint associations of cardiometabolic multimorbidity and depression on cognitive function: findings from multi-regional cohorts and generalisation from community to clinic. The Lancet regional health. Western Pacific, 51, 101198. PMCID: PMC11416683. PMID: 39308753 39308753
28Lo, et al. Trajectory of Cognitive Decline Before and After Stroke in 14 Population Cohorts. JAMA Netw Open. 2024;7(10):e2437133. PMCID: PMC11447567  PMID: 3935650439356504
29Matison, et al. Associations between fruit and vegetable intakes and incident depression in middle-aged and older adults from 10 diverse international longitudinal cohorts. J Affect Disord. 2024 Aug 15;359:373-381. PMID: 38788860 DOI: 10.1016/j.jad.2024.05.096PMID 38788860
30Lennon, et al. Blood Pressure, Antihypertensive Use, and Late-Life Alzheimer and Non-Alzheimer Dementia Risk: An Individual Participant Data Meta-Analysis. Neurology. 2024 SepPMC11329294
31Samtani S, et al. Emotional and instrumental social support and older adults' depressive symptoms: collaborative individual participant data meta-analysis of 11 population-based studies of aging. Cohort Studies of Memory in an International Consortium (COSMIC). Am J Epidemiol. 2025 Oct 7;194(10):3041-3049. DOI: 10.1093/aje/kwaf137 PMID: 40643376
32Lipnicki DM et al. Addressing global diversity in dementia research with the COSMIC collaboration. Neuroscience. 2025 Aug 30;582:180-194. DOI: 10.1016/j.neuroscience.2025.07.036[RT1] . Epub 2025 Jul 24. PMID: 40714148 PMID: 40714148 [RT2]
  • Project aimLeadAffiliation
    Associations of cardiovascular-kidney-metabolic syndrome with cognitive decline and dementia X XuZhejiang University
    Association of type 2 diabetes and prediabetes with post-stroke cognitive declineJ LoCHeBA UNSW
    Associations of olfactory function and snoring with cognition and dementia R ShiNational Taiwan University
    Education, educational complexity, socioeconomic status and incident dementia A MatisonCHeBA UNSW
    Clinical and sociodemographic pathways linking hearing loss and dementiaR ChanderCHeBA UNSW
    Alcohol, cognition, and mortalityL MewtonUNSW, Sydney
    Antihypertensives, blood pressure, and dementia riskM LennonUNSW, Sydney
    Social support and depressive symptomsS SamtaniUNSW, Sydney
    Sleep, MCI, and dementiaS Wan SuhSeoul National University
    Nutrition & cognitive healthC AnastasiouHarokopio University, Athens
    Risk models for prediction of dementia in LMICsE PakpahanNorthumbria University, UK
    Maximizing dementia risk reductionK DeckersMaastricht University
    Global burden of dementiaL MewtonUNSW, Sydney
    Diet and depressionA MatisonUNSW, Sydney
    Cognitive decline before and after strokeJ LoUNSW, Sydney
    Heart and brain health: AI assisted dementia risk modelsB StephanCurtin University, Australia
    Sex-specific risks for MCI and dementiaC WangAlbert Einstein College of Medicine, New York
    Cardiometabolic multimorbidity, depression, and dementiaX XuZhejiang University, Hangzhou
    Social health and cognitive health trajectoriesL BraasRadboud University, The Netherlands
    Nightmares, cognitive decline and dementiaD LipnickiUNSW, Sydney
    ENIGMA group harmonization of cognitive domain scoresE DennisUniversity of Utah
    Neuropsychiatric symptoms and dementia riskDJ OhKangbuk Samsung Hospital, Seoul
    Cerebrovascular burden in vascular cognitive impairmentN HuseinUNSW, Sydney
    Polygenic risk scores and dementiaK MatherUNSW, Sydney
    A Thalamuthu
    Predicting dementia risk in LMICs with machine learningJ JiangUNSW, Sydney
    Climate factors and dementia riskD DingFudan University, Shanghai
    Illiteracy, gender, and dementia riskDJ OhKangbuk Samsung Hospital, Seoul
    Physical activity, traumatic brain injury, and cognitive outcomesB TariUniversity of Oxford, UK
  • Project aimLeadAffiliation
    Grip strength and cognitionYH SuNational Taiwan University
    Pet ownership, social health and cognitionS SamtaniUNSW, Sydney

COSMIC welcomes research proposals from member studies, and from outside investigators wishing to utilise the wealth and diversity of data held by the COSMIC cohorts. All proposals will be reviewed by the COSMIC Scientific Steering Committee, and should be submitted via the Dementias Platform Australia website using the link below:

Dementias Platform Australia – Apply for Data Access

Please note that COSMIC member studies are not committed to providing data for all projects and elect to participate on a project-by-project basis. It is a requirement that any publication using a study’s data involve consultation with the study leader and include them and other members as co-authors.

Also note that proposals from outside investigators require sponsorship by a lead investigator of a COSMIC member study. Details of the member studies and contact details of the lead investigators can be found on this website, and it may be appropriate to seek sponsorship from the leader of a study that has investigated similar issues or holds particularly relevant data.

For any enquiries, contact Darren Lipnicki. d.lipnicki@unsw.edu

Dementias Platform UK (DPUK) and Dementias Platform Australia (DPAU)

Dementias Platform UK (DPUK; https://www.dementiasplatform.uk/) offers researchers dementia-optimised cohort data from more than 50 population and clinical cohort studies, comprising records for over 3.5 million people. In partnership with DPUK, CHeBA has launched Dementias Platform Australia (DPAU; http://www.dementiasplatform.com.au/). DPAU will complement DPUK and other satellite dementias platforms, and allow access to research data from multiple dementia studies carried out in Australia, the Asia-Pacific region and beyond to all six continents. The close partnership between DPUK and DPAU enables a sharing of technical assets and best practice, and will facilitate international data analysis. COSMIC studies will be the first to upload data to DPAU in 2022.

Institute for Health Metrics and Evaluation (IHME) at the University of Washington

Coordinated through the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, the Global Burden of Disease (GBD; https://www.healthdata.org/gbd/2019) study provides consistent and comparative descriptions of the major causes of mortality and morbidity for over 350 diseases and injuries. GBD estimates are regularly updated to ensure the most complete and highly comparable set of estimates possible. In partnership with the IHME, COSMIC studies are providing data to inform global dementia estimates. This includes data from countries previously under-represented in GBD estimates (e.g., Cuba, Tanzania and Malaysia). By providing new data COSMIC will help to produce more accurate estimations of the global burden of disease associated with dementia.

Davos Alzheimer’s Collaborative (DAC)

The Davos Alzheimer’s Collaborative (DAC; https://www.davosalzheimerscollaborative.org/) is “uniting leading organizations worldwide to build an innovation ecosystem that will accelerate breakthroughs, develop and scale promising solutions and equip every healthcare system to end Alzheimer's disease everywhere.” Through its Global Cohort Development program (https://www.davosalzheimerscollaborative.org/cohorts), DAC is building global cohorts to advance understanding of Alzheimer’s disease among diverse populations. COSMIC cohorts from regions including the Philippines, Malaysia and Singapore are among the first participants in this program, and are receiving resources from DAC to obtain new digital phenotyping and blood-based genetic and biomarker data. These data will be made available via the Alzheimer’s Disease Data Initiative (ADDI) platform (https://www.alzheimersdata.org/) as well as DPAU.

COSMIC Membership Criteria

Studies are eligible to participate in COSMIC if they meet the following membership criteria:

  1. Are epidemiological, and therefore population-based.
  2. Have a minimum sample size of 500.
  3. Examine individuals aged 60 years and over.
  4. Are longitudinal, with a minimum of two assessments.
  5. Include assessment of cognitive function as an important, if not central, objective.
  6. The outcome measures include dementia and/or cognitive impairment and/or cognitive decline.
  7. Studies from Africa, South America and Eastern Europe are particularly encouraged to join.

Sydney Cosmic team

Contact

Dr Darren Lipnickid.lipnicki@unsw.edu.au
Research Fellow, CHeBA (Centre for Healthy Brain Ageing), UNSW Medicine

Renecia Lowe: r.lowe@unsw.edu.au
COSMIC Project Officer, CHeBA (Centre for Healthy Brain Ageing), UNSW Medicine.

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