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

Abstract

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.

Keywords: Association; Autoimmune diseases; Celiac disease (CeD); Crohn’s disease (CD); MINA; Molecular Interaction Network Approach; Molecular network; Multiple sclerosis (MS); Psoriasis (PSO); Rheumatoid arthritis (RA); Systemic lupus erythematosus (SLE); Type-1 diabetes (T1D); Type-2 diabetes (T2D).

Fig. 1

Schematic representation of MINA Workflow. Numbers in bold represent the MINA steps; 1- Seed genes selected, 2- Ingenuity Pathway Analysis (IPA) core tool created and score-ranked networks, 3- Top ranking network selected with the highest p-value, 4- Candidate genes are identified, 5- Candidate genes Validation, in primary database, and 6- Candidate genes replication in different GWAS and/ or new case: control study.

Fig. 2

Autoimmune disease specific molecular interaction network. Seed genes (highlighted in green) and candidate genes are displayed in their identified cellular compartment for seven autoimmune diseases (PSO, CeD, CD, MS, RA, SLE and T1D). Genes or gene products are represented as nodes/shapes, and the biological relationship between two nodes is represented as an edge (line). Genes highlighted in green represent the seed genes. All nodes and edges are supported by at least 1 reference from the literature, from a textbook, or from a database that was incorporated into Ingenuity knowledge base. Nodes are displayed using various shapes that represent the functional class of the gene product or molecule class. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

The distribution of the most significant SNPs associated with each disease. Bold genes represent the nine seed genes.