Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system

Cell Rep Med. 2024 May 21;5(5):101518. doi: 10.1016/j.xcrm.2024.101518. Epub 2024 Apr 19.

Abstract

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Keywords: American College of Medical Genetics and Genomics; biobank; breast cancer; cardiomyopathy; electronic health record; exome sequence; genome-first; penetrance; precision medicine; underdiagnosis.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Delivery of Health Care
  • Electronic Health Records
  • Exome Sequencing* / methods
  • Exome* / genetics
  • Female
  • Genetic Diseases, Inborn / diagnosis
  • Genetic Diseases, Inborn / epidemiology
  • Genetic Diseases, Inborn / genetics
  • Genetic Predisposition to Disease
  • Genetic Testing / methods
  • Genome, Human
  • Genomics / methods
  • Humans
  • Male
  • Middle Aged
  • Young Adult