The All of Us Research Program: data quality, utility, and diversity
Andrea H Ramirez,
David J Schlueter,
Karthik N Muthuraman,
Cheryl R Clark,
Brian K Ahmedani,
Robert M Cronin,
David B. Goldstein,
Scott J Hebbring,
Elizabeth W. Karlson,
Jordan W Smoller,
Stephanie A Devaney,
Joshua C Denny,
Robert J. Carroll,
Paul A Harris,
Dan M. Roden,
On behalf of the All of Us Research Program
Posted 03 Jun 2020
medRxiv DOI: 10.1101/2020.05.29.20116905
Posted 03 Jun 2020
Importance: The All of Us Research Program hypothesizes that accruing one million or more diverse participants engaged in a longitudinal research cohort will advance precision medicine and ultimately improve human health. Launched nationally in 2018, to date All of Us has recruited more than 345,000 participants. All of Us plans to open beta access to researchers in May 2020. Objective: To demonstrate the quality, utility, and diversity of the All of Us Research Programs initial data release and beta launch of the cloud-based analysis platform, the cloud-based Researcher Workbench. Evidence: We analyzed the initial All of Us data release, comprising surveys, physical measurements (PM), and electronic health record (EHR) data, to characterize All of Us participants including self-reported descriptors of diversity. Data depth, density, and quality were evaluated using medication sequencing analyses for depression and type 2 diabetes. Replication of known oncologic associations with smoking exposure ascertained by EHR and survey data and calculation of population-based atherosclerotic cardiovascular disease risk scores demonstrated the utility of data and platform capability. Findings: The beta launch of the All of Us Researcher Workbench contains data on 224,143 participants. Seventy-seven percent of this cohort were identified as Underrepresented in Biomedical Research (UBR) including over forty-eight percent self-reporting non-White race. Medication usage patterns in common diseases depression and type 2 diabetes replicated prior findings previously reported in the literature and showed differences based on race. Oncologic associations with smoking were replicated and effect sizes compared for EHR and survey exposures finding general agreement. A cardiovascular disease score was calculated utilizing multiple data elements curated across sources. The cloud-based architecture built in the Researcher Workbench provided secure access and powerful computational resources at a low cost. All analyses have been made available for replication and reuse by registered researchers. Conclusions and Relevance: The All of Us Research Programs initial release of cohort data contains longitudinal and multidimensional data on diverse participants that replicate known associations. This dataset and the cloud-based Researcher Workbench advance the mission of All of Us to make data widely and securely available to researchers to improve human health and advance precision medicine.
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