Computational Tool Provides Pathogenic Variant Penetrance Estimates From Population Data

In Genome Medicine, investigators at King's College London outline a computational tool for estimating the penetrance of pathogenic variants contributing to autosomal dominant conditions. The approach is designed to "estimate penetrance for variants with an autosomal dominant inheritance pattern using population-level data from unrelated people who are and are not affected by the associated phenotype," the team writes, adding that the approach "can be operated using variant information drawn only from affected populations, stratified according to the family history between 'familial' and 'sporadic' disease presentations." The authors applied the method to four pathogenic variants: an LRRK2 alteration involved in Parkinson's disease, a heritable pulmonary arterial hypertension-related variant in BMPR2 gene, and variants involved in amyotrophic lateral sclerosis from the SOD1 and C9orf72 genes. Across the conditions, the approach led to penetrance patterns consistent with those reported in the past or provided new, disease-relevant penetrance information, they report, noting that it "serves to expand the range of genetic diseases and variants for which high-quality penetrance estimates can be obtained."