Improved Gene Set Enrichment Analysis Research Articles

Pathway analysis of a genome-wide gene by air pollution interaction study in asthmatic children.

We aimed to investigate the role of genetics in the respiratory response of asthmatic children to air pollution, with a genome-wide level analysis of gene by nitrogen dioxide (NO2) and carbon monoxide (CO) interaction on lung function and to identify biological pathways involved. We used a two-step method for fast linear mixed model computations for genome-wide association studies, exploring whether variants modify the longitudinal relationship between 4-month average pollution and post-bronchodilator FEV1 in 522 Caucasian and 88 African-American asthmatic children. Top hits were confirmed with classic linear mixed-effect models. We used the improved gene set enrichment analysis for GWAS (i-GSEA4GWAS) to identify plausible pathways. Two SNPs near the EPHA3 (rs13090972 and rs958144) and one in TXNDC8 (rs7041938) showed significant interactions with NO2 in Caucasians but we did not replicate this locus in African-Americans. SNP-CO interactions did not reach genome-wide significance. The i-GSEA4GWAS showed a pathway linked to the HO-1/CO system to be associated with CO-related FEV1 changes. For NO2-related FEV1 responses, we identified pathways involved in cellular adhesion, oxidative stress, inflammation, and metabolic responses. The host lung function response to long-term exposure to pollution is linked to genes involved in cellular adhesion, oxidative stress, inflammatory, and metabolic pathways.

EbGSEA: an improved Gene Set Enrichment Analysis method for Epigenome-Wide-Association Studies.

MotivationThe biological interpretation of differentially methylated sites derived from Epigenome-Wide-Association Studies (EWAS) remains a significant challenge. Gene Set Enrichment Analysis (GSEA) is a general tool to aid biological interpretation, yet its correct and unbiased implementation in the EWAS context is difficult due to the differential probe representation of Illumina Infinium DNA methylation beadchips.ResultsWe present a novel GSEA method, called ebGSEA, which ranks genes, not CpGs, according to the overall level of differential methylation, as assessed using all the probes mapping to the given gene. Applied on simulated and real EWAS data, we show how ebGSEA may exhibit higher sensitivity and specificity than the current state-of-the-art, whilst also avoiding differential probe representation bias. Thus, ebGSEA will be a useful additional tool to aid the interpretation of EWAS data.Availability and implementation ebGSEA is available from https://github.com/aet21/ebGSEA, and has been incorporated into the ChAMP Bioconductor package (https://www.bioconductor.org).Supplementary information Supplementary data are available at Bioinformatics online.

An exploratory genome-wide analysis of genetic risk for alcoholic hepatitis

Objectives: To elucidate the genetic variability between heavy drinkers with and without alcoholic hepatitis (AH).Materials and methods: An exploratory genome-wide association study (GWAS; NCT02172898) was conducted comparing 90 AH cases with 93 heavy drinking matched controls without liver disease in order to identify variants or genes associated with risk for AH. Individuals were genotyped using the multi-ethnic genotyping array, after which the data underwent conventional quality control. Using bioinformatics tools, pathways associated with AH were explored on the basis of individual variants, and based on genes with a higher ’burden’ of functional variation.Results: Although no single variant reached genome-wide significance, an association signal was observed for PNPLA3 rs738409 (p = .01, OR 1.9, 95% CI 1.1–3.1), a common single nucleotide polymorphism that has been associated with a variety of liver-related pathologies including alcoholic cirrhosis. Using the improved gene set enrichment analysis for GWAS tool, it was shown that, based on the single variants’ trait-association p-values, multiple pathways were associated with risk for AH with high confidence (false discovery rate [FDR] < 0.05), including several pathways involved in lymphocyte activation and chemokine signaling, which coincides with findings from other research groups. Several Tox Functions and Canonical Pathways were highlighted using Ingenuity Pathway Analysis, with an especially conspicuous role for pathways related to ethanol degradation, which is not surprising considering the phenotype of the genotyped individuals.Conclusion: This preliminary analysis suggests a role for PNPLA3 variation and several gene sets/pathways that may influence risk for AH among heavy drinkers.

Abstract 842: Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor

Abstract Genome-wide association (GWA) studies have reported 19 distinct susceptibility loci for testicular germ cell tumor (TGCT). The aim of the present study was to identify additional loci and gene sets associated with susceptibility to TGCT. A GWA study for TGCT was performed by genotyping 610,240 single nucleotide polymorphisms (SNPs) in 1,326 cases and 6,687 controls from Sweden and Norway. We put forward 34 SNPs from 17 novel regions and 11 SNPs previously reported, for replication in 710 case-parent triads and 289 cases and 290 controls. Predefined biological pathways and processes, in addition to a custom-built sex determination gene set, were subject to enrichment analyses using Meta-Analysis Gene Set Enrichment of Variant Associations (M) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (I). In the combined meta-analysis, we observed genome-wide significant association for rs7501939 on chromosome 17q12 (OR = 1.29, 95% CI = 1.19-1.40, P = 1.1 × 10-9) and rs2195987 on chromosome 19p12 (OR = 1.31, 95% CI: 1.19-1.45, P = 3.2 × 10-8). The marker rs7501939 on chromosome 17q12 is located in an intron of the HNF1B gene, encoding a member of the homeodomain-containing superfamily of transcription factors. The sex determination gene set (FDRM &amp;lt; 0.001, FDRI &amp;lt; 0.001) and pathways related to NF-κB, glycerophospholipid and ether lipid metabolism, as well as cancer and apoptosis, was associated with TGCT (FDR &amp;lt; 0.1). In addition to revealing two new TGCT susceptibility loci, our results support the notion that genes governing normal germ cell development in utero are implicated in the development of TGCT. Citation Format: Tom Grotmol, Wenche Kristiansen, Robert Karlsson, Trine B. Rounge, Thomas Whitington, Bettina K. Andreassen, Patrik KE Magnusson, Hans-Olov Adami, Clare Turnbull, Trine B. Haugen, Fredrik Wiklund. Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 842. doi:10.1158/1538-7445.AM2015-842

Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor.

Genome-wide association (GWA) studies have reported 19 distinct susceptibility loci for testicular germ cell tumor (TGCT). A GWA study for TGCT was performed by genotyping 610 240 single-nucleotide polymorphisms (SNPs) in 1326 cases and 6687 controls from Sweden and Norway. No novel genome-wide significant associations were observed in this discovery stage. We put forward 27 SNPs from 15 novel regions and 12 SNPs previously reported, for replication in 710 case-parent triads and 289 cases and 290 controls. Predefined biological pathways and processes, in addition to a custom-built sex-determination gene set, were subject to enrichment analyses using Meta-Analysis Gene Set Enrichment of Variant Associations (M) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (I). In the combined meta-analysis, we observed genome-wide significant association for rs7501939 on chromosome 17q12 (OR = 0.78, 95% CI = 0.72-0.84, P = 1.1 × 10(-9)) and rs2195987 on chromosome 19p12 (OR = 0.76, 95% CI: 0.69-0.84, P = 3.2 × 10(-8)). The marker rs7501939 on chromosome 17q12 is located in an intron of the HNF1B gene, encoding a member of the homeodomain-containing superfamily of transcription factors. The sex-determination gene set (false discovery rate, FDRM < 0.001, FDRI < 0.001) and pathways related to NF-κB, glycerophospholipid and ether lipid metabolism, as well as cancer and apoptosis, was associated with TGCT (FDR < 0.1). In addition to revealing two new TGCT susceptibility loci, our results continue to support the notion that genes governing normal germ cell development in utero are implicated in the development of TGCT.

Pathway analysis for a genome-wide association study of pneumoconiosis

ObjectiveThe aim of this investigation was to identify pathways involved in pneumoconiosis susceptibility, clarify their potential mechanisms, and generate SNP-to-gene to pathway hypotheses using an analytical pathway-based approach. MethodsThe identify candidate causal SNPs and pathways (ICSNPathway) was used to perform pathway analysis of a GWAS dataset for pneumoconiosis, which, after quality control filtering, harbored genotypes of 710,999 SNPs in 202 pneumoconiosis cases and 198 exposed controls. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and functional annotation of the most significant SNPs; the second stage involved annotation of biological mechanisms for the selected candidate SNPs using improved-gene set enrichment analysis. ResultsICSNPathway analysis identified 18 candidate SNPs, involving 13 genes and 30 candidate pathways and revealed 13 hypothetical biological mechanisms. The strongest hypothetical biological mechanism was that rs8120 and rs2292151 alters the role of TICAM1, a gene involved in various pathways and processes, including positive regulation of tumor necrosis factor (TNF) production, innate immune response-activating signal transduction, positive regulation of the innate immune response, and the biosynthesis of type I interferon (0.001<p<0.008; 0.001< false discovery rate (FDR) <0.035). The second strongest mechanism was that rs2230656 modulates HIST3H3 to affect its role in chromatin assembly processes (p<0.001; FDR <0.001). The third mechanism was that rs11592462 modulates CDH23, which regulates organization of the inner ear stereocilia, auditory receptor cell morphogenesis, ear morphogenesis, and cellular homeostasis (0.001<p<0.006; 0.001<FDR<0.044). Of 13 candidate genes, TICAM1, HIST3H3, CA1, CA3, PTPRZ1, and IL27RA are associated with fibrosis. Some of the 30 candidate pathways, which include positive regulation of TNF production, innate immune response-activating signal transduction, and regulation of innate immune response, may be associated with susceptibility to pneumoconiosis. Other candidate genes and pathways were novel or lacking fibrosis-related research. ConclusionBy applying ICSNPathway analysis to the pneumoconiosis GWAS data, we identified candidate SNPs, genes such as TICAM1 and HIST3H3, and pathways involved in the positive regulation of TNF production that may contribute to pneumoconiosis susceptibility. Further analyses are needed to validate the results.

Pathway-based analysis of GWAs data identifies association of sex determination genes with susceptibility to testicular germ cell tumors.

Genome-wide association (GWA) studies of testicular germ cell tumor (TGCT) have identified 18 susceptibility loci, some containing genes encoding proteins important in male germ cell development. Deletions of one of these genes, DMRT1, lead to male-to-female sex reversal and are associated with development of gonadoblastoma. To further explore genetic association with TGCT, we undertook a pathway-based analysis of SNP marker associations in the Penn GWAs (349 TGCT cases and 919 controls). We analyzed a custom-built sex determination gene set consisting of 32 genes using three different methods of pathway-based analysis. The sex determination gene set ranked highly compared with canonical gene sets, and it was associated with TGCT (FDRG = 2.28 × 10(-5), FDRM = 0.014 and FDRI = 0.008 for Gene Set Analysis-SNP (GSA-SNP), Meta-Analysis Gene Set Enrichment of Variant Associations (MAGENTA) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (i-GSEA4GWAS) analysis, respectively). The association remained after removal of DMRT1 from the gene set (FDRG = 0.0002, FDRM = 0.055 and FDRI = 0.009). Using data from the NCI GWA scan (582 TGCT cases and 1056 controls) and UK scan (986 TGCT cases and 4946 controls), we replicated these findings (NCI: FDRG = 0.006, FDRM = 0.014, FDRI = 0.033, and UK: FDRG = 1.04 × 10(-6), FDRM = 0.016, FDRI = 0.025). After removal of DMRT1 from the gene set, the sex determination gene set remains associated with TGCT in the NCI (FDRG = 0.039, FDRM = 0.050 and FDRI = 0.055) and UK scans (FDRG = 3.00 × 10(-5), FDRM = 0.056 and FDRI = 0.044). With the exception of DMRT1, genes in the sex determination gene set have not previously been identified as TGCT susceptibility loci in these GWA scans, demonstrating the complementary nature of a pathway-based approach for genome-wide analysis of TGCT.

Pathway analysis of a genome-wide association study in schizophrenia

ObjectiveThe aim of this study was to identify the candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms that contribute to schizophrenia susceptibility and to generate a SNP to gene to pathway hypothesis using an analytical pathway-based approach. MethodsWe used schizophrenia GWAS data of the genotypes of 660,259 SNPs in 1378 controls and 1351 cases of European descent after quality control filtering. ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the schizophrenia GWAS dataset. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate SNPs using improved-gene set enrichment analysis. ResultsICSNPathway analysis identified fifteen candidate SNPs, ten candidate pathways, and nine hypothetical biological mechanisms. The most strongly associated potential pathways were as follows. First, rs1644731 and rs1644730 to RDH8 to estrogen biosynthetic process (p<0.001, FDR<0.001). The genes involved in this pathway are RDH8 and HSD3B1 (p<0.05). All-trans-retinol dehydrogenase (RDH8) is a visual cycle enzyme that reduces all-trans-retinal to all-trans-retinol in the presence of NADPH. The chemical reactions and pathways involved result in the formation of estrogens, which are C18 steroid hormones that can stimulate the development of female sexual characteristics. Second, rs1146031 to ACVR1 to mesoderm formation and activin binding (p<0.001, FDR=0.032, 0.034). Two of 15 candidate genes are known genes associated with schizophrenia: KCNQ2 and APOL2. One of the 10 candidate pathways, estrogen biosynthetic process, is known to be associated with schizophrenia (p<0.001, FDR<0.001). However, 13 of candidate genes (RDH8, ACVR1, PSMD9, KCNAB1, SLC17A3, ARCN1, COG7, STAB2, LRPAP1, STAB1, CXCL16, COL4A4, EXOSC3) and 9 of candidate pathways were novel. ConclusionBy applying ICSNPathway analysis to schizophrenia GWAS data, we identified candidate SNPs, genes like KCNQ2 and APOL2 and pathways involving the estrogen biosynthetic process may contribute to schizophrenia susceptibility. Further analyses are needed to validate the results of this analysis.

Pathway analysis of genome-wide association studies for Parkinson’s disease

The study was done to identify the candidate causal single nucleotide polymorphisms (SNPs) and candidate causal mechanisms that contribute to Parkinson's disease (PD) susceptibility and to generate a SNP to ene to pathway hypothesis using an analytical pathway-based approach. We used a PD genome-wide association study (GWAS) meta-analysis data of the genotypes of 2,525,705 SNPs in 4,238 PD cases and 4,239 controls. Identify candidate Causal SNPs and Pathways (ICSNPathway) analysis was applied to the PD GWAS dataset. The first stage involved the pre-selection of candidate causal SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate causal SNPs using improved-gene set enrichment analysis. ICSNPathway analysis identified three candidate SNPs, two genes, twenty-one pathways, and three hypothetical biological mechanisms: (1) rs17651549 to microtubule-associated protein tau (MAPT) to protein domain specific binding (nominal p < 0.001, false discovery rate (FDR) < 0.001), neurogenesis (nominal p < 0.001, FDR < 0.001), regulation of neurogenesis (nominal p < 0.001, FDR = 0.001), positive regulation of axonogenesis (nominal p < 0.001, FDR = 0.001), regulation of protein polymerization (nominal p < 0.001, FDR = 0.004), negative regulation of organelle organization (nominal p < 0.001, FDR = 0.004), hsa01510 (nominal p < 0.001, FDR = 0.005), neuron differentiation (nominal p < 0.001, FDR = 0.009), and axonogenesis (nominal p < 0.001, FDR = 0.009); (2) rs10445337 to MAPT to protein domain specific binding (nominal p < 0.001, FDR < 0.001), neurogenesis (nominal p < 0.001, FDR < 0.001), regulation of neurogenesis (nominal p < 0.001, FDR = 0.001), and positive regulation of axonogenesis (nominal p < 0.001, FDR = 0.001); (3) rs9938550 to HSD3B7 to hsa00363 (nominal p < 0.001, FDR = 0.004), bile acid metabolic process (nominal p = 0.005, FDR = 0.019), and steroid metabolic process (nominal p = 0.010, FDR = 0.039). By applying the ICSNPathway analysis to PD GWAS meta-analysis data, three candidate SNPs, two genes (MAPT and HSD3B7), and 21 pathways involving protein domain specific binding and neurogenesis were identified, which may contribute to PD susceptibility.

Pathway analysis of genome-wide association study for bone mineral density

The aim of this study was to identify the candidate causal single nucleotide polymorphisms (SNPs) and candidate causal mechanisms that contribute to bone mineral density (BMD) and to generate a SNP to gene to pathway hypothesis using an analytical pathway-based approach. We used hip BMD GWAS data of the genotypes of 301,019 SNPs in 5,715 Europeans. ICSNPathway (identify candidate causal SNPs and pathways) analysis was applied to the BMD GWAS dataset. The first stage involved the pre-selection of candidate causal SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate causal SNPs using improved-gene set enrichment analysis. ICSNPathway analysis identified seven candidate SNPs, eight candidate pathways, and seven hypothetical biological mechanisms. Eight pathways are as follows; gamma-hexachlorocyclohexane degradation (nominal p-value < 0.001, false discovery rate (FDR) <0.001), regulation of the smoothened signaling pathway (nominal p-value < 0.001, FDR = 0.016), TACI and BCMA stimulation of B cell immune response (nominal p-value < 0.001, FDR = 0.021), endonuclease activity (nominal p-value = 0.001, FDR = 0,026), regulation of defense response to virus (nominal p-value = 0.001, FDR = 0.028), serine_type_endopeptidase_inhibitor_activity (nominal p-value = 0.001, FDR = 0.044), endoribonuclease activity (nominal p-value = 0.002, FDR = 0.045), and myeloid leukocyte differentiation (nominal p-value = 0.001, FDR = 0.050). The most significant causal pathway was gamma-hexachlorocyclohexane degradation. CYP3A5, PON2, PON3, CMBL, PON1, ALPL, CYP3A43, CYP3A7, ACP6, ACPP, and ALPI (p < 0.05) are involved in the pathway of gamma-hexachlorocyclohexane degradation. Further examination of the gene contents revealed that DBR1, DICER1, EXO1, FEN1, POP1, POP4, RPP30, and RPP38 were involved in 2 of the 8 pathways (p < 0.05). By applying ICSNPathway analysis to BMD GWAS data, we identified seven candidate SNPs and eight pathways involving gamma-hexachlorocyclohexane degradation, which may contribute to low BMD.

Cell adhesion molecules contribute to Alzheimer’s disease: multiple pathway analyses of two genome‐wide association studies

Alzheimer's disease (AD) is a kind of complex neurological disorder. The complex genetic architecture of AD makes genetic analysis difficult. Fortunately, a pathway-based method to study the existing genome-wide association studies datasets has been applied into AD. However, no shared Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway was reported. In this study, we performed multiple pathway analyses of French AD genome-wide association studies dataset (discovery dataset, n = 7360, 2032 cases and 5328 controls) and Pfizer dataset (validation dataset, n = 2220, 1034 cases and 1186 controls). First, we performed multiple pathway analyses by Hypergeometric test, improved gene set enrichment analysis (IGSEA) and Z-statistic test in KEGG. Using Hypergeometric test, we identified 54 and 25 significant pathways (p < 0.05) in discovery dataset and validation dataset, respectively. Using IGSEA method, we identified three significant pathways in both discovery and validation datasets, respectively. Using Z-statistic test, we identified 19 significant pathways in validation dataset. Among the significant pathways, cell adhesion molecules (CAM) pathway was identified to be the only consistent signal emerging across multiple analyses in KEGG. After permutation and multiple testing corrections, CAM pathway was significant with p = 2.40E-05 (Hypergeometric test) and p = 3.00E-03 (IGSEA) in discovery dataset. In validation dataset, CAM pathway was significant with p = 1.84E-06 (Hypergeometric test), p = 1.00E-02 (IGSEA) and p = 2.81E-03 (Z-statistic test). We replicated the association by multiple pathway analyses in Gene Ontology using Hypergeometric test (WebGestalt), modified Fisher's exact test (DAVID) and Binomial test (PANTHER). Our findings provided further evidence on the association between CAM pathway and AD susceptibility, which would be helpful to study the genetic mechanisms of AD and may significantly assist in the development of therapeutic strategies.

Pathway-based analysis for genome-wide association studies of schizophrenia to provide new insight in schizophrenia study

Schizophrenia (SZ) is an inheritable complex mental disease. There have been several genome-wide association studies (GWASs) of SZ to identify novel genetic susceptibility factors. To further interpret SZ GWASs, pathway-based analysis (PBA), which considers the combined effect of variants and identifies pathways associated with traits, provides a feasible solution to discover the biological function and mechanism of SZ. Furthermore, to investigate the common pathways between SZ and bipolar disorder (BD) will help explore common mechanism between psychiatric phenotypes. We performed a PBA, called improved gene set enrichment analysis (i-GSEA), on 3 independent GWASs of SZ to identify pathways associated with SZ. The results were further compared to the BD-associated pathways identified by i-GSEA for 2 BD GWASs and from literature reports. Our analysis identified a highly statistically significant association between SZ and pathway ‘substrate specific channel activity’ in all 3 SZ GWASs (false discovery rate (FDR) < 0.05). This association has not been reported elsewhere before. This pathway was also identified by PBA for 2 independent BD GWASs. Our results suggest that pathway ‘substrate specific channel activity’ is statistically significantly associated with SZ, and SZ and BD share the common biological function and mechanism represented by this pathway.

Abstract LB-441: The genome wide gene-environment interaction analysis for asbestos exposure on lung cancer susceptibility

Abstract Asbestos exposure is a known risk factor for lung cancer. Although recent genome wide association studies (GWAS) have identified a few novel loci for lung cancer risk, little is known about genome wide gene-environment interactions and lung cancer risk. To determine genetic variations involved in the interactions of gene-asbestos exposure on lung cancer risk, we conducted genome wide gene-environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using the Texas lung cancer GWAS dataset. This dataset included 307,870 SNPs from 1,154 lung cancer cases and 1,137 cancer-free controls. The initial SNP-level p values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models adjusted for age, sex, smoking status and pack-years. The p value for the most significant SNP rs12706823 was 1.37 × 10–4 and did not reach the genome-wide statistical significance. Using a versatile gene-based test approach to estimate the interactions at the gene level, we found the top significant gene was RNF121and was located on 11q13.4 (p value = 4 × 10–4). Interestingly, most of the genes with top significant p values were located in 11q13. When we used an improved gene set enrichment analysis approach (i-GSEA), however, we found a total of 249 pathways containing 16,079 genes, of which the Fas signaling pathway was the most significant pathway, significantly involved in the interactions between genetic variations and self-reported asbestos exposure (nominal p value &amp;lt; 0.001; false discovery rate (FDR) &amp;lt; 0.05). We believe our analysis is the first to comprehensively describe the genome wide gene-asbestos exposure interaction on lung cancer risk at the levels of SNPs, genes and pathways. Our findings suggested that the current designed GWAS may have a limited power to detect gene-environment interactions at the SNP or gene levels, but the pathway-based approach may be more powerful in performing genome wide gene-environment analyses. (This study was supported by NIH grants R01 ES 11740, R01CA 131274, R01CA055769, R01CA127219, R01CA121197 and P30CA016672) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-441. doi:10.1158/1538-7445.AM2011-LB-441

I-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study

Genome-wide association study (GWAS) is nowadays widely used to identify genes involved in human complex disease. The standard GWAS analysis examines SNPs/genes independently and identifies only a number of the most significant SNPs. It ignores the combined effect of weaker SNPs/genes, which leads to difficulties to explore biological function and mechanism from a systems point of view. Although gene set enrichment analysis (GSEA) has been introduced to GWAS to overcome these limitations by identifying the correlation between pathways/gene sets and traits, the heavy dependence on genotype data, which is not easily available for most published GWAS investigations, has led to limited application of it. In order to perform GSEA on a simple list of GWAS SNP P-values, we implemented GSEA by using SNP label permutation. We further improved GSEA (i-GSEA) by focusing on pathways/gene sets with high proportion of significant genes. To provide researchers an open platform to analyze GWAS data, we developed the i-GSEA4GWAS (improved GSEA for GWAS) web server. i-GSEA4GWAS implements the i-GSEA approach and aims to provide new insights in complex disease studies. i-GSEA4GWAS is freely available at http://gsea4gwas.psych.ac.cn/.