Abstract
Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.
Highlights
Common genetic variants in over 150 genomic loci have been unequivocally associated to immune-mediated diseases by genome-wide association studies (GWAS) [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]
The ultimate promise of these studies is the understanding of disease biology; this goal, is not achieved because each disease has yielded numerous associations, each one pointing to a region of the genome, rather than a specific causal mutation
The causal variants affect components of common molecular processes, and a first step in understanding the disease biology perturbed in patients is to identify connections among regions associated to disease
Summary
Common genetic variants in over 150 genomic loci have been unequivocally associated to immune-mediated diseases by genome-wide association studies (GWAS) [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]. It is presumed that these associations represent perturbations to a common but limited set of underlying molecular processes that modulate risk to disease. The challenge – and the great promise of human genetics – is the identification of these disease-causing pathways so they may be targeted for diagnostics and therapeutic intervention. In identifying such processes, there are difficulties in both (i) identifying the specific genes at (and how they are molecularly impacted by) each association and (ii) inferring disease-causing mechanisms from the set of identified genes. Linkage disequilibrium blocks containing disease-associated SNPs can be hundreds of kilobases in size, and some contain tens of genes to consider.
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