Integrating Pathway Analysis and Genetics of Gene Expression for Genome-wide Association Studies

Abstract

Genome-wide association studies (GWAS) have achieved great success identifying common genetic variants associated with common human diseases. However, to date, the massive amounts of data generated from GWAS have not been maximally leveraged and integrated with other types of data to identify associations beyond those associations that meet the stringent genome-wide significance threshold. Here, we present a novel approach that leverages information from genetics of gene expression studies to identify biological pathways enriched for expression-associated genetic loci associated with disease in publicly available GWAS results. Specifically, we first identify SNPs in population-based human cohorts that associate with the expression of genes (eSNPs) in the metabolically active tissues liver, subcutaneous adipose, and omental adipose. We then use this functionally annotated set of SNPs to investigate pathways enriched for eSNPs associated with disease in publicly available GWAS data. As an example, we tested 110 pathways from the Kyoto Encylopedia of Genes and Genomes (KEGG) database and identified 16 pathways enriched for genes corresponding to eSNPs that show evidence of association with type 2 diabetes (T2D) in the Wellcome Trust Case Control Consortium (WTCCC) T2D GWAS. We then replicated these findings in the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) study. Many of the pathways identified have been proposed as important candidate pathways for T2D, including the calcium signaling pathway, the PPAR signaling pathway, and TGF-beta signaling. Importantly, we identified other pathways not previously associated with T2D, including the tight junction, complement and coagulation pathway, and antigen processing and presentation pathway. The integration of pathways and eSNPs provides putative functional bridges between GWAS and candidate genes or pathways, thus serving as a potential powerful approach to identifying biological mechanisms underlying GWAS findings.

Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits

“…Given that susceptibility loci for complex traits are unlikely to be randomly distributed in the genome (3), we might expect that the genes associated with a disease will be more likely to be present within the same pathways or functional groupings. In published cases, pathway based GWAS analysis provides an alternative approach to the dissection of complex disease traits (4,5). In addition, nominal GWAS p values superimposed upon the human molecular network have been used to identify genes associated with multiple sclerosis (6), and the disease association protein-protein link evaluator (DAPPLE) has been used to find significant interactions among proteins encoded by genes in loci associated with other particular diseases (7) .…”

AQP2 in human urine is predominantly localized to exosomes with preserved water channel activities

“…Non-labeled quantification was made by normalized spectral index (SI N ) values. The identified proteins were annotated by KEGG pathway analysis of DAVID Bioinformatics Resources (NIAID, NIH) [14].…”

“…2 The intracellular localization of the identified proteins in AQP2-bearing EVs that are annotated as endocytosis pathway by the KEGG analysis. The figure was modified from the data provided KEGG [14]. Gene names shown in red were observed in this analysis temperature before measurements suppressed the Pf by 63% to 1.76 ± 0.39 × 10 −4 cm s −1 (n = 5, p < 0.05 compared to the control).…”

Diabetes and Biomarkers

“…Type 2 diabetes mellitus was shown to be associated with pathways already known to be associated with the disease, such as peroxisome proliferator-activated receptor signaling, calcium signaling, tumor growth factor beta signaling, cell communication, and pancreatic cancer pathway. 30 However, additional less-characterized candidate pathways, including tight junction, adherens junction, complement and coagulation, and antigen processing and presentation were also implicated. 30 Some of these pathways have been linked to complications of diabetes as well as in the pathogenesis of type 1 diabetes but now serve as candidates for a pathogenic role in T2DM as well.…”

“…30 However, additional less-characterized candidate pathways, including tight junction, adherens junction, complement and coagulation, and antigen processing and presentation were also implicated. 30 Some of these pathways have been linked to complications of diabetes as well as in the pathogenesis of type 1 diabetes but now serve as candidates for a pathogenic role in T2DM as well.…”