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从多重共病网络中厘清个体疾病的遗传和环境风险因素。

Disentangling genetic and environmental risk factors for individual diseases from multiplex comorbidity networks.

机构信息

Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Spitalgasse 23, A-1090, Austria.

Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.

出版信息

Sci Rep. 2016 Dec 23;6:39658. doi: 10.1038/srep39658.

Abstract

Most disorders are caused by a combination of multiple genetic and/or environmental factors. If two diseases are caused by the same molecular mechanism, they tend to co-occur in patients. Here we provide a quantitative method to disentangle how much genetic or environmental risk factors contribute to the pathogenesis of 358 individual diseases, respectively. We pool data on genetic, pathway-based, and toxicogenomic disease-causing mechanisms with disease co-occurrence data obtained from almost two million patients. From this data we construct a multiplex network where nodes represent disorders that are connected by links that either represent phenotypic comorbidity of the patients or the involvement of a certain molecular mechanism. From the similarity of phenotypic and mechanism-based networks for each disorder we derive measure that allows us to quantify the relative importance of various molecular mechanisms for a given disease. We find that most diseases are dominated by genetic risk factors, while environmental influences prevail for disorders such as depressions, cancers, or dermatitis. Almost never we find that more than one type of mechanisms is involved in the pathogenesis of diseases.

摘要

大多数疾病是由多种遗传和/或环境因素共同引起的。如果两种疾病由相同的分子机制引起,它们往往会在患者中同时发生。在这里,我们提供了一种定量方法,可以分别分解 358 种个体疾病的遗传和环境风险因素分别有多少。我们汇集了有关遗传、基于途径和毒理基因组学疾病致病机制的数据,以及从近 200 万名患者中获得的疾病共现数据。从这些数据中,我们构建了一个多重网络,其中节点代表疾病,节点之间通过链接连接,这些链接要么代表患者的表型共病,要么代表特定分子机制的参与。从每个疾病的表型和基于机制的网络的相似性,我们得出了一个度量标准,可以量化各种分子机制对特定疾病的相对重要性。我们发现,大多数疾病主要由遗传风险因素引起,而环境影响则在抑郁症、癌症或皮炎等疾病中占主导地位。我们几乎从未发现一种以上的机制参与疾病的发病机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76c1/5180180/4f5313e06d7a/srep39658-f1.jpg

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