Leveraging Health Systems Data to Characterize a Large Effect Variant Conferring Risk for Liver Disease in Puerto Ricans

Abstract

Broad-scale adoption of genomic data in health systems offers opportunities for extending methods for the discovery of variation linked to underlying genomic disease risk. We applied a population-scale linkage mapping approach in a large multi-ethnic biobank to a spectrum of disease outcomes derived from Electronic Health Records (EHRs) and uncovered a risk locus for liver disease. We used genome sequencing and in silico approaches to fine-map the signal to a non-coding variant (c.2784-12T>C) in the gene ABCB4. In vitro analysis confirmed the variant disrupted splicing of the ABCB4 pre-mRNA. Four of five homozygotes had evidence of advanced liver disease, and there was a significant association with liver disease among heterozygotes, suggesting the variant is linked to increased risk of liver disease in an allele dose-dependent manner. Population-level screening revealed the variant to be at a carrier rate of 1.95% in Puerto Rican individuals, likely as the result of a Puerto Rican founder effect. This work demonstrates that integrating EHR and genomic data at a population-scale can facilitate novel strategies for understanding the continuum of genomic risk for common diseases, particularly in populations underrepresented in genomic medicine.