CellGenomicsPeer-reviewed journal article
Towards a Fine-scale Population Health Monitoring System
Gillian M. BelbiniD, Sinéad CullinaiD, Stéphane WenriciD, Emily R. SoperiD, Benjamin Scott GlicksbergiD, Denis TorreiD, Arden MoscatiiD, Genevieve L. WojcikiD, Ruhollah ShemiraniiD, Noam D. BeckmanniD, Ariella T. CohainiD, Elena P. SorokiniD, Danny S. ParkiD, José Luis AmbiteiD, Steve Ellis, Adam AutoniD, Erwin P. BöttingeriD, Judy H. ChoiD, Ruth J. F. LoosiD, Noura S. Abul‐HusniD, Noah ZaitleniD, Christopher R. GignouxiD, Eimear E. KennyiD
Abstract
Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens specific to sub-populations. Here we propose a framework for repurposing data from Electronic Health Records (EHRs) in concert with genomic data to explore enrichment of disease within sub-populations. Using data from a diverse biobank in New York City, we genetically identified 17 sub-populations, and noted the presence of genetic founder effects in 7. By then linking community membership to the EHR, we were able to identify over 600 health outcomes that were statistically enriched within a specific population, with many representing known associations, and many others being novel. This work reinforces the utility of linking genomic data to EHRs, and provides a framework towards fine-scale monitoring of population health.
- organism: human
- assay: electronic health records
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 142
- FWCI
- 13.56
- Field percentile
- top 1%
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