| Title: | Extracting and calibrating evidence of variant pathogenicity from population biobank data |
| Journal: | American Journal of Human Genetics |
| Published: | 9 Jul 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40639380/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2025.06.012 |
Publication 16656
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Abstract
Genomic medicine requires a robust evidence base of variant phenotypic impacts, which remains incomplete even in extensively studied genes with monogenic disease associations. Here, we evaluated the broad potential of using population cohort data to identify evidence that can be used in variant assessment. Across 41 genes related to 18 clinically actionable monogenic phenotypes, we calculated variant-level odds ratios of disease enrichment using data from 469,803 UK Biobank participants. We found significant differences in odds ratio values between ClinVar-labeled pathogenic and benign variants in 11 phenotypes, spanning both common and rare disorders. To facilitate clinical translation, we calibrated the strength of evidence provided by variant-level odds ratios to align with American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) interpretation guidelines (PS4 criterion) and found that odds ratios may reach "moderate," "strong," or "very strong" evidence, varying by phenotype and gene. Overall, we found that 2.6% (N = 12,350) of participants harbor a rare variant of uncertain significance (VUS) with at least moderate evidence of pathogenicity-an indication of potentially unrecognized disease risk. Finally, by incorporating computational and functional data alongside population-based odds ratios, we identified variants that met the criteria for clinical reclassification. Notably, using this approach, we identified that 12.4% of rare VUSs in LDLR seen in participants meet diagnostic criteria to be classified as likely pathogenic, demonstrating its potential to scale the reclassification of VUSs.</p>
9 Keywords
- Biological Specimen Banks
- Cohort Studies
- Genetic Predisposition to Disease
- Genetic Variation
- Genomics
- Humans
- Odds Ratio
- Phenotype
- United Kingdom
7 Authors
- Vineel Bhat
- Tian Yu
- Lara Brown
- Vikas Pejaver
- Matthew Lebo
- Steven Harrison
- Christopher A Cassa
1 Application
| Application ID | Title |
|---|---|
| 41250 | Prioritizing Mendelian variants using GWAS and exome sequencing data |
Enabling scientific discoveries that improve human health