Brain health registry GenePool study: A novel approach to online genetics research

June 1, 2021

Authors: Juliet Fockler, Winnie Kwang, Miriam T Ashford, Derek Flenniken, Joshua Hwang, Diana Truran, R Scott Mackin, Chengshi Jin, Ruth O'Hara, Joachim F Hallmayer, Jerome A Yesavage, Michael W Weiner, Rachel L Nosheny

Journal: Alzheimer's & Dementia

DOI: 10.1002/trc2.12118

Year Published: 2021


Remote data collection, including the establishment of online registries, is a novel approach to efficiently identify risk for cognitive decline and Alzheimer’s disease (AD) in older adults, with growing evidence for feasibility and validity. Addition of genetic data to online registries has the potential to facilitate identification of older adults at risk and to advance the understanding of genetic contributions to AD.


573 older adult participants with longitudinal online Brain Health Registry (BHR) data underwent apolipoprotein E (APOE) genotyping using remotely collected saliva samples and a novel, automated Biofluid Collection Management Portal. We evaluated acceptability of genetic sample collection and estimated associations between (1) sociodemographic variables and willingness to participate in genetics research and (2) APOE results and online cognitive and functional assessments. We also assessed acceptance of hypothetical genetics research participation by surveying a larger sample of 25,888 BHR participants.


51% of invited participants enrolled in the BHR genetics study, BHR-GenePool Study (BHR-GPS); 27% of participants had at least one APOE ε4 allele. Older participants and those with higher educational attainment were more likely to participate. In the remotely administered Cogstate Brief Battery, APOE ε4/ε4 homozygotes (HM) had worse online learning scores, and greater decline in processing speed and attention, compared to ε3/ε4 heterozygotes (HT) and ε4 non-carriers (NC).


APOE genotyping of more than 500 older adults enrolled in BHR supports the feasibility and validity of a novel, remote biofluids collection approach from a large cohort of older adults, with data linkage to longitudinal online cognitive data. This approach can be expanded for efficient collection of genetic data and other information from biofluids in the future.

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