Quantifying penetrance in a dominant disease gene using large population control cohorts
By E. Minikel, S. M. Vallabh, M. Lek, K. Estrada, Kaitlin E. Samocha, Jarupon Fah Sathirapongsasuti, Cory Y. McLean, J. Tung, L. P. Yu, P. Gambetti and 55 more. 2016
400 citations recorded by the source corpus.
Large genomic reference data sets reveal a spectrum of pathogenicity in the prion protein gene and provide genetic validation for a therapeutic strategy in prion disease. Share trumps rare No longer just buzz words, “patient empowerment” and “data sharing” are enabling breakthrough research on rare genetic diseases. Although more than 100,000 genetic variants are believed to drive disease in humans, little is known about penetrance—the probability that a mutation will actually cause disease in the carrier. This conundrum persists because small sample sizes breed imperfect alliance estimates between mutations and disease risk. Now, a patient-turned-scientist joined with a large bioinformatics team to analyze vast amounts of shared data—from the Exome Aggregation Consortium and the 23andMe database—to provide insights into genetic-variant penetrance and possible treatment approaches for a rare, fatal genetic prion disease. More than 100,000 genetic variants are reported to cause Mendelian disease in humans, but the penetrance—the probability that a carrier of the purported disease-causing genotype will indeed develop the disease—is generally unknown. We assess the impact of variants in the prion protein gene (PRNP) on the risk of prion disease by analyzing 16,025 prion disease cases, 60,706 population control exomes, and 531,575 individuals genotyped by 23andMe Inc. We show that missense variants in PRNP previously reported to be pathogenic are at least 30 times more common in the population than expected on the basis of genetic prion disease prevalence. Although some of this excess can be attributed to benign variants falsely assigned as pathogenic, other variants have genuine effects on disease susceptibility but confer lifetime risks ranging from <0.1 to ~100%. We also show that truncating variants in PRNP have position-dependent effects, with true loss-of-function alleles found in healthy older individuals, a finding that supports the safety of therapeutic suppression of prion protein expression.
Subfields: Molecular Biology, Neurology, Nutrition and Dietetics
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Citations in the corpus
- Variant interpretation using population databases: lessons from gnomAD (2021, background): “…intolerance of mouse and human genes (Dickinson et al., 2016), estimation of selection coefficients (Cassa et al., 2017), assessment of the relative evidence for reported disease genes (Walsh et al., 2017), and determination of the pene-trance of dominant disease variants (Minikel et al., 2016).”
- Using high-resolution variant frequencies to empower clinical genome interpretation (2016, background): “8,9 This rule must, however, be refined to account for different inheritance modes, genetic and allelic heterogeneity, and reduced penetrance.”
- Integrative omics for health and disease (2018, result): “In particular, a causal variant would be expected to have a significantly higher frequency in affected individuals than in a wider asymptomatic population, which can lend support to or negate previous suggestions of pathogenicity 91,92 .”
- Evaluating drug targets through human loss-of-function genetic variation (2019, neutral): “On the order of ~1 in 100,000 people in gnomAD and 23andMe harbor high-penetrance PRNP variants 36,41 , although as noted 1 in 50,000 gene basis for genetic prevalence estimation estimate above, we expect these datasets to be depleted compared to the population at birth, because prion disease is…”