Wei Angela, Border Richard, Fu Boyang, Cullina Sinéad, Brandes Nadav, Jang Seon-Kyeong, Sankararaman Sriram, Kenny Eimear E, Udler Miriam S, Ntranos Vasilis, Zaitlen Noah, Arboleda Valerie A
Interdepartmental Bioinformatics Program, UCLA, Los Angeles, CA, USA.
Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Nat Commun. 2025 Jun 5;16(1):5223. doi: 10.1038/s41467-025-60339-7.
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.
超过3%的人携带显性致病变异,但只有一小部分携带者会发病。同一基因变异携带者的疾病表型从轻度到重度不等。在此,我们研究这种异质性的潜在机制:变异效应大小可变、携带者多基因背景以及遗传背景对携带者效应的调节(边际上位性)。我们利用英国生物银行和西奈山生物医学银行的外显子组和临床表型来识别影响心脏代谢性状的致病变异携带者。我们采用最近开发的方法来研究这些队列,观察到可变携带者外显率和疾病严重程度的所有三种机制都有强有力的统计支持和临床转化潜力。例如,我们最近的变异致病性模型的分数与临床变异携带者的表型紧密相关,它们预测了意义未明变异的效应,并且区分了功能获得性变异和功能丧失性变异。我们还发现多基因分数会改变致病携带者的表型,并且遗传背景还会通过相互作用额外改变致病变异的效应。