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标题：Molecular Interaction Network Approach (MINA) identifies association of novel candidate disease genes
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作者：Sam Kara ; Alaa Hanna ; Gerardo A. Pirela-Morillo 等
期刊名称：MethodsX
印刷版ISSN：2215-0161
电子版ISSN：2215-0161
出版年度：2019
卷号：6
页码：1286-1291
DOI：10.1016/j.mex.2019.05.031
语种：English
出版社：Elsevier
摘要：AbstractMolecular Interaction Network Approach (MINA) was used to elucidate candidate disease genes. The approach was implemented to identify novel gene association with commonly known autoimmune diseases [1]. In MINA, we evaluated the hypothesis that “network proximity” within a whole genome molecular interaction network can be used to inform the search for multigene inheritance. There are now numerous examples of gene discoveries based upon network proximity between novel and previously identified disease genes (Yin et al., 2017 [], Wang et al., 2011 [], and Barrenas et al., 2009 []). This study extends the application of interaction networks to the interrogation of Genome Wide Association studies: first, by showing that a group of nine autoimmune diseases (AuD) genes “seed genes”, are connected in a highly non-random manner within a whole genome network; and second, by showing that the minimal number of connecting genes required to connect a maximal number of AuD candidate genes are highly enriched as candidate genes for AuD predisposing mutations. The findings imply that a threshold number of candidate genes for any heritable disorder can be used to “seed” a molecular interaction network that•Serves to validate the disease status of closely associated seed genes•Identifies genes that are highly enriched as novel candidate disease genes•Provides a strategy for elucidation of epistatic gene x gene interactionsThe method could provide a critical toll for understanding the genetic architecture of common traits and disorders.
关键词：Autoimmune diseases;Crohn’s disease (CD);Systemic lupus erythematosus (SLE);Rheumatoid arthritis (RA), Psoriasis (PSO);Type-1 diabetes (T1D);Type-2 diabetes (T2D);Celiac disease (CeD);Multiple sclerosis (MS);Association, Molecular network