NIH Reporter #5I01BX006500-02

Mitigating Genomic Research Disparities in the Million Veteran Program

This award supports research to reduce disparities in genomic studies of serious mental illness among Veterans by using advanced data integration and machine learning methods to improve genetic risk detection and promote equity in precision psychiatry.

Description

The project aims to mitigate disparities in genomic research by leveraging data quality heterogeneity and aggregating related traits in electronic health records (EHR) to perform meta-analyses that enhance the detection of genetic risk factors for serious mental illness (SMI) traits among Veterans. The study will utilize genome-wide and transcriptome-wide association studies, employing novel meta-analytic approaches such as PheMED, to integrate heterogeneous data and improve the discovery of genetic loci linked to SMI. Data-driven phenotypes for schizophrenia, bipolar disorder, and major depressive disorder will be constructed using machine learning techniques to increase sample sizes and improve risk prediction models. The research seeks to promote equity in genomic studies and advance precision psychiatry for Veterans across diverse demographic groups.

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