Leveraging health systems data to characterize a large effect variant conferring risk for liver disease in Puerto Ricans

Gillian M. Belbin, Stephanie Rutledge, Tetyana Dodatko, Sinead Cullina, Michael C. Turchin, Sumita Kohli, Denis Torre, Muh Ching Yee, Christopher R. Gignoux, Noura S. Abul-Husn, Sander M. Houten, Eimear E. Kenny

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The integration of genomic data into health systems offers opportunities to identify genomic factors underlying the continuum of rare and common disease. We applied a population-scale haplotype association approach based on identity-by-descent (IBD) 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 strategies for understanding the continuum of genomic risk for common diseases, particularly in populations underrepresented in genomic medicine.

Original languageEnglish
Pages (from-to)2099-2111
Number of pages13
JournalAmerican Journal of Human Genetics
Issue number11
StatePublished - 4 Nov 2021


  • electronic health records
  • identity-by-descent
  • liver disease
  • liver serum measures
  • phenome wide association studies
  • population genetics
  • statistical genetics


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