Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions.

Angela Wei, Richard Border, Boyang Fu, Sinead Cullina, Nadav Brandes, Seon-Kyeong Jang, Sriram Sankararaman, Eimear Kenny, Mariam S Udler, Vasilis Ntranos, Noah Zaitlen, Valerie Arboleda
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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 predicted phenotypes amongst pathogenic carriers and that epistatic effects can exceed main carrier effects by an order of magnitude.

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心脏代谢特征中致病突变外显率和表达率可变的遗传基础。
超过3%的人携带显性致病突变,但只有一小部分携带者患上了疾病(外显率不完全),同一基因突变的表型从轻度到重度不等(表现力可变)。在这里,我们研究了这种异质性的潜在机制:可变变异效应大小、携带者多基因背景和遗传背景对携带者效应的调节(上位性)。我们利用英国生物库和西奈山生物-Me生物库的外显子组和临床表型来确定影响心脏代谢特征的致病性变体的携带者。我们采用了最近开发的方法来研究这些队列,观察到变量外显率和表达率的所有三种机制都有强大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得分与临床变异携带者的表型密切相关,它们预测了意义未知的变异的影响,并区分了功能获得和丧失变异。我们还发现,多基因评分可以预测致病携带者的表型,上位效应可以超过主要携带者效应一个数量级。
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