Mueller Sabine C, Sommer Björn, Backes Christina, Haas Jan, Meder Benjamin, Meese Eckart, Keller Andreas
From the Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany,; Department of Human Genetics, Saarland University, 66421 Homburg, Germany,.
the Bio-/Medical Informatics Department, Faculty of Technology, Bielefeld University, 33501 Bielefeld, Germany,; Clayton School of Information Technology, Faculty of Information Technology, Monash University, Melbourne 3800, Australia.
J Biol Chem. 2016 Jan 22;291(4):1582-1590. doi: 10.1074/jbc.M115.695247. Epub 2015 Nov 24.
Understanding the role of genetics in disease has become a central part of medical research. Non-synonymous single nucleotide variants (nsSNVs) in coding regions of human genes frequently lead to pathological phenotypes. Beyond single variations, the individual combination of nsSNVs may add to pathogenic processes. We developed a multiscale pipeline to systematically analyze the existence of quantitative effects of multiple nsSNVs and gene combinations in single individuals on pathogenicity. Based on this pipeline, we detected in a data set of 842 nsSNVs discovered in 76 genes related to cardiomyopathies, associated nsSNV combinations in seven genes present in at least 70% of all 639 patient samples, but not in a control cohort of healthy humans. Structural analyses of these revealed primarily an influence on the protein stability. For amino acid substitutions located at the protein surface, we generally observed a proximity to putative binding pockets. To computationally analyze cumulative effects and their impact, pathogenicity methods are currently being developed. Our approach supports this process, as shown on the example of a cardiac phenotype but can be likewise applied to other diseases such as cancer.
了解遗传学在疾病中的作用已成为医学研究的核心部分。人类基因编码区的非同义单核苷酸变异（nsSNV）常常导致病理表型。除了单个变异外，nsSNV的个体组合可能会加剧致病过程。我们开发了一种多尺度流程，以系统地分析单一个体中多个nsSNV和基因组合对致病性的定量影响的存在情况。基于此流程，我们在与心肌病相关的76个基因中发现的842个nsSNV的数据集中检测到，在所有639例患者样本中至少70%存在的7个基因中的相关nsSNV组合，但在健康人类的对照队列中未发现。对这些的结构分析主要揭示了对蛋白质稳定性的影响。对于位于蛋白质表面的氨基酸取代，我们通常观察到其靠近假定的结合口袋。为了通过计算分析累积效应及其影响，目前正在开发致病性方法。我们的方法支持这一过程，如以心脏表型为例所示，但同样可应用于其他疾病，如癌症。
