Gene and Pathway-Based Analysis: Second Wave of Genome-wide Association Studies

Abstract

Despite great success of GWAS in identification of common genetic variants associated with complex diseases, the current GWAS have focused on single SNP analysis. However, single SNP analysis often identifies a number of the most significant SNPs that account for only a small proportion of the genetic variants and offers limited understanding of complex diseases. To overcome these limitations, we propose gene and pathway-based association analysis as a new paradigm for GWAS. As a proof of concept, we performed a comprehensive gene and pathway-based association analysis for thirteen published GWAS. Our results showed that the proposed new paradigm for GWAS not only identified the genes that include significant SNPs found by single SNP analysis, but also detected new genes in which each single SNP conferred small disease risk, but their joint actions were implicated in the development of diseases. The results also demonstrated that the new paradigm for GWAS was able to identify biologically meaningful pathways associated with the diseases which were confirmed by gene-set rich analysis using gene expression data. Genome-wide association studies (GWAS) armed with efficient genotyping technologies are emerging as a major tool to identify disease susceptibility loci and are successful to detect association of a number of SNPs with complex diseases 1-12. However, to only test for association of single SNP is insufficient to dissect complex genetic structure of complex diseases. To extract biological insight from GWAS and to understand the principles underlying complex phenomena that take place on various biological pathways remain a major challenge. In a typical GWAS, hundreds of thousands of SNPs are genotyped for thousands of individuals. By comparisons of differences in the DNA variations between the normal and affected individuals, the SNPs can be ordered according to their degrees of association. The common approach is to select dozens of the most significant SNPs in the list for further investigations. This approach

The regulation-of-autophagy pathway may influence Chinese stature variation: evidence from elder adults

“…Several methods are developed for pathway hunting recently 26–30. All of these methods used relatively complex model or simulation to improve the accuracy and statistical power.…”

Comparisons of multi‐marker association methods to detect association between a candidate region and disease

“…Fisher’s combination test summarizes information across SNPs by −2Σ log( P -value). This procedure was used by Peng et al [2008]. Because of the LD structure among SNPs, standard distribution theory used to calculate the P -value for this statistic does not apply here.…”

“…Recently, this type of analysis has been adopted and applied to GWAS [e.g. Peng et al, 2008]. However, unlike gene expression studies where it is relatively easy to summarize gene expression levels from a single gene, GWAS requires calculating a gene score based on a few up to, perhaps, hundreds of SNPs.…”

“…Similar types of studies have followed and used a variety of gene level scores. For example, Peng et al [2008] used several combination statistics (Fisher, Sidak, and Simes) where the overall evidence is summarized by combining information from all individual markers. The authors showed that despite the exclusion of linkage disequilibrium (LD) information among the markers, the gene level analysis had the ability to identify associations found using single SNP analysis and to identify new associations.…”

Database of genetic studies of bipolar disorder

“…Epistasis is a phenomenon whereby one genetic variant requires another genetic variant to reveal the trait. Networks of genes might be explored more thoroughly as the field advances (O'Dushlaine et al 2009; Peng et al 2009; Walsh et al 2008; Wang et al 2007; Zamar et al 2009). According to this approach a given variant might alone exert only small relative risk for the disease but may synergize through co -inheritance with other risk alleles in a biological pathway to produce a strong predisposition for the disease.…”