Pathway Analysis of GWAS Provides New Insights into Genetic Susceptibility to 3 Inflammatory Diseases

Abstract

Although the introduction of genome-wide association studies (GWAS) have greatly increased the number of genes associated with common diseases, only a small proportion of the predicted genetic contribution has so far been elucidated. Studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a complementary approach to the more common single SNP association approach in understanding genetic determinants of common disease. We developed a novel pathway-based method to assess the combined contribution of multiple genetic variants acting within canonical biological pathways and applied it to data from 14,000 UK individuals with 7 common diseases. We tested inflammatory pathways for association with Crohn's disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) with 4 non-inflammatory diseases as controls. Using a variable selection algorithm, we identified variants responsible for the pathway association and evaluated their use for disease prediction using a 10 fold cross-validation framework in order to calculate out-of-sample area under the Receiver Operating Curve (AUC). The generalisability of these predictive models was tested on an independent birth cohort from Northern Finland. Multiple canonical inflammatory pathways showed highly significant associations (p 10−3–10−20) with CD, T1D and RA. Variable selection identified on average a set of 205 SNPs (149 genes) for T1D, 350 SNPs (189 genes) for RA and 493 SNPs (277 genes) for CD. The pattern of polymorphisms at these SNPS were found to be highly predictive of T1D (91% AUC) and RA (85% AUC), and weakly predictive of CD (60% AUC). The predictive ability of the T1D model (without any parameter refitting) had good predictive ability (79% AUC) in the Finnish cohort. Our analysis suggests that genetic contribution to common inflammatory diseases operates through multiple genes interacting in functional pathways.

Integrated analysis of genome-wide genetic and epigenetic association data for identification of disease mechanisms

“…Their combined effects, however, may be detected through biological pathway based analysis of the GWAS data. 16,17 This may also hold true for EWAS data, especially if the sample size is very small, as in the present study. To test this possibility and identify potential epigenetically important pathways, a total of 211 biological pathways obtained from the KEGG database 18 were assessed for their combined effects on T1D using the present GWAS and EWAS data.…”

“…Biological pathway analysis of the GWAS data Our method of detecting the combined effects of all SNP main effects in a biological pathway is an adaptation of the method reported by Eleftherohorinou et al 17 Briefly, for each individual SNP, a chi-square value from the trend test was generated using Plink. 27 Permutations were performed to assess the significance of the sum of such chi-square statistic values (Sst) for all the SNPs in a pathway, and the resulting null distribution of the summary statistic was approximated using the Sinh-Arcsinh (SHASH) probability distribution.…”

“…The P value of the sum statistic was then obtained as P = , where Sst was the observed sum statistic of the real data and P(x|μ,σ,ν,τ) was the fitted SHASH distribution. This approach is an adaptation of the method described by Eleftherohorinou et al, 17 but with the 3-parameter skew-normal distribution replaced by the more general 4-parameter SHASH model, which improves the fit to the permutational distribution (Fig. 3).…”

Pathway-based analysis of genetic susceptibility to cervical cancer in situ: HLA-DPB1 affects risk in Swedish women

“…A third approach, which combines the ability to examine sets of genes with a specific function with a scanning of the genome, is a pathway-based analysis. 20 A number of different approaches for pathway-based analyses have been developed, [21][22][23] with most of them based on calculating a P-value from genome-wide association study data for sets of genes involved in predefined functions, based on one or several annotation tools such as KEGG (Kyoto Encyclopedia of Genes and Genomes) 24 or Gene Ontology. 25 In the current study, we have explored a pathwaybased analysis using genome-wide SNP data for cases diagnosed with at least cervical cancer in situ and controls.…”

Extraction of Sequence Conservation Features for the Prioritization of Candidate Single Amino Acid Polymorphisms

“…Over the past few years, remarkable success has been achieved by genome-wide association (GWA) studies in the discovery of genetic variants that are responsible for human inherited diseases [1], with examples including age-related macular degeneration [2], Diabetes [3], Hypertension [4], and many others [5][6][7]. Typically, a GWA study is designed to uncover potential associations of genetic variants with observable traits of a disease by examining whether these genetic variants occur in different frequencies between a case population and a control population.…”