DOI: 10.1101/19009076Nov 2, 2019Paper

An Environment-Wide Study of Adult Cognitive Performance in the 23andMe Cohort

MedRxiv : the Preprint Server for Health Sciences
Y. HuangStella Aslibekyan

Abstract

BACKGROUND: With the emergence of web-based data collection methods, large digital health cohorts offer the opportunity to conduct behavioral and epidemiologic research at an unprecedented scale. The size and breadth of such data sets enable discovery of novel associations across the phenotypic spectrum. METHODS: We deployed the digital symbol substitution test (DSST) online to consented 23andMe research participants 50-85 years of age. We tested cross-sectional associations between DSST performance and 824 phenotypes using linear regression models adjusted for age, sex, age*sex interaction, device, time of cohort entry, and ancestry, separately among discovery (n=144,786) and replication (n=93,428) samples; additional analyses further adjusted for education. We post-stratified association estimates on age, sex, and education to adjust for discrepancies across subsamples. Leveraging the rich genetic and phenotypic data available at 23andMe, we also estimated genetic and environmental correlations between DSST and its top correlates using linkage disequilibrium score regression. RESULTS: 97 phenotypes were significantly (false discovery rate < 0.05) and strongly (standardized effect size > |0.5|) associated with DSST performance...Continue Reading

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