A systematic analysis of gene-gene interaction in multiple sclerosis

Abstract

Background: For the most part, genome-wide association studies (GWAS) have only partially explained the heritability of complex diseases. One of their limitations is to assume independent contributions of individual variants to the phenotype. Many tools have therefore been developed to investigate the interactions between distant loci, or epistasis. Among them, the recently proposed EpiGWAS models the interactions between a target variant and the rest of the genome. However, applying this approach to studying interactions along all genes of a disease map is not straightforward. Here, we propose a pipeline to that effect, which we illustrate by investigating a multiple sclerosis GWAS dataset from the Wellcome Trust Case Control Consortium 2 through 19 disease maps from the MetaCore pathway database.

Results: For each disease map, we build an epistatic network by connecting the genes that are deemed to interact. These networks tend to be connected, complementary to the disease maps and contain hubs. In addition, we report 4 epistatic gene pairs involving missense variants, and 25 gene pairs with a deleterious epistatic effect mediated by eQTLs. Among these, we highlight the interaction of GLI-1 and SUFU, and of IP10 and NF-[Formula: see text]B, as they both match known biological interactions. The latter pair is particularly promising for therapeutic development, as both genes have known inhibitors.

Conclusions: Our study showcases the ability of EpiGWAS to uncover biologically interpretable epistatic interactions that are potentially actionable for the development of combination therapy.

Keywords: Causal inference; Epistasis; GWAS; Gene–gene interaction; Multiple sclerosis.

Fig. 1

Epistatic interaction discovery pipeline

Fig. 2

Examples of epistatic pairs detected on two disease maps. a The 2% top-scoring pairs in DM 3306 for eQTL and physical mappings. b The 2% top-scoring pairs in DM 4455 for eQTL and physical mappings

Fig. 3

The $2\%$ top-scoring pairs in DM 3305 for eQTL and physical mappings. Note the GL1–SUFU pair

Fig. 4

The $2\%$ top-scoring pairs in DM 5199 for eQTL and physical mappings. Note the NF-$\kappa$B – IP10 pair

Fig. 5

Schematic representation of the role played by the gene pairs NF-$\kappa$B/IP10 in the development of demyelination in MS. a Transformation of astrocytes in immuno-competent cells and T-cells recruitment following the NF-B/IP10 axis activation in MS. b After recruitment of T-cells, adhesion of T-cell/astrocyte leads to in ammatory and immune response inducing neuron damage