Identification of novel susceptibility genes associated with seven autoimmune disorders using whole genome molecular interaction networks.

Convergent evidence from multiple and independent genetics studies implicate a small number of genes that predispose individuals to multiple autoimmune disorders (AuD). These intersecting loci reinforced the hypothesis that disorders with overlapping etiology group into a cluster of closely related genes within a whole genome molecular interaction network. We tested the hypothesis that "biological network proximity" within a whole genome molecular interaction network can be used to inform the search for multigene inheritance. Using a set of nine previously published genome wide association studies (GWAS) of AuD genes, we generated AuD-specific molecular interaction networks to identify networks of associated genes. We show that all nine "seed genes" can be connected within a 35-member network via interactions with 26 connecting genes. We show that this network is more connected than expected by chance, and 13 of the connecting genes showed association with multiple AuD upon GWAS reanalysis. Furthermore, we report association of SNPs in five new genes (IL10RA, DGKA, GRB2, STAT5A, and NFATC2) which were not previously considered as AuD candidates, and show significant association in novel disease samples of Crohn's disease and systemic lupus erythematosus. Furthermore, we show that the connecting genes show no association in four non-AuD GWAS. Finally, we test the connecting genes in psoriasis GWAS, and show association to previously identified loci and report new loci. These findings support the hypothesis that molecular interaction networks can be used to inform the search for multigene disease etiology, especially for disorders with overlapping etiology.

Molecular Interaction Network Approach (MINA) identifies association of novel candidate disease genes.

Molecular 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 [2], Wang et al., 2011 [3], and Barrenas et al., 2009 [4]). 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 interactions The method could provide a critical toll for understanding the genetic architecture of common traits and disorders.