| Title: | Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions |
| Journal: | Nature Communications |
| Published: | 5 Jun 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40473624/ |
| DOI: | https://doi.org/10.1038/s41467-025-60339-7 |
| URL: | https://www.nature.com/articles/s41467-025-60339-7.pdf |
Publication 15061
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Abstract
Over three percent of people carry a dominant pathogenic variant, yet only a fraction of carriers develop disease. Disease phenotypes from carriers of variants in the same gene range from mild to severe. Here, we investigate underlying mechanisms for this heterogeneity: variable variant effect sizes, carrier polygenic backgrounds, and modulation of carrier effect by genetic background (marginal epistasis). We leveraged exomes and clinical phenotypes from the UK Biobank and the Mt. Sinai BioMe Biobank to identify carriers of pathogenic variants affecting cardiometabolic traits. We employed recently developed methods to study these cohorts, observing strong statistical support and clinical translational potential for all three mechanisms of variable carrier penetrance and disease severity. For example, scores from our recent model of variant pathogenicity were tightly correlated with phenotype amongst clinical variant carriers, they predicted effects of variants of unknown significance, and they distinguished gain- from loss-of-function variants. We also found that polygenic scores modify phenotypes amongst pathogenic carriers and that genetic background additionally alters the effects of pathogenic variants through interactions.</p>
13 Keywords
- Biological Specimen Banks
- Epistasis, Genetic
- Exome
- Genetic Background
- Genetic Predisposition to Disease
- Genetic Variation
- Heterozygote
- Humans
- Metabolic Diseases
- Multifactorial Inheritance
- Penetrance
- Phenotype
- United Kingdom
12 Authors
- Angela Wei
- Richard Border
- Boyang Fu
- Sinéad Cullina
- Nadav Brandes
- Seon-Kyeong Jang
- Sriram Sankararaman
- Eimear E. Kenny
- Miriam S. Udler
- Vasilis Ntranos
- Noah Zaitlen
- Valerie A. Arboleda
1 Application
| Application ID | Title |
|---|---|
| 33127 | Methods for large-scale medical and population genetic data |
Enabling scientific discoveries that improve human health