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Title: Pathway Analysis of Renal Cell Carcinoma Genome-Wide Association Studies Identifies Novel Associations.
Authors: Purdue MP,  Song L,  Scélo G,  Houlston RS,  Wu X,  Sakoda LC,  Thai K,  Graff RE,  Rothman N,  Brennan P,  Chanock SJ,  Yu K
Journal: Cancer Epidemiol Biomarkers Prev
Date: 2020 Oct
Branches: BB, CGR, OD, OEEB
PubMed ID: 32732251
PMC ID: not available
Abstract: BACKGROUND: Much of the heritable risk of renal cell carcinoma (RCC) associated with common genetic variation is unexplained. New analytic approaches have been developed to increase the discovery of risk variants in genome-wide association studies (GWAS), including multi-locus testing through pathway analysis. METHODS: We conducted a pathway analysis using GWAS summary data from six previous scans (10,784 cases and 20,406 controls) and evaluated 3,678 pathways and gene sets drawn from the Molecular Signatures Database. To replicate findings, we analyzed GWAS summary data from the UK Biobank (903 cases and 451,361 controls) and the Genetic Epidemiology Research on Adult Health and Aging cohort (317 cases and 50,511 controls). RESULTS: We identified 14 pathways/gene sets associated with RCC in both the discovery (P < 1.36 × 10-5, the Bonferroni correction threshold) and replication (P < 0.05) sets, 10 of which include components of the PI3K/AKT pathway. In tests across 2,035 genes in these pathways, associations (Bonferroni corrected P < 2.46 × 10-5 in discovery and replication sets combined) were observed for CASP9, TIPIN, and CDKN2C. The strongest SNP signal was for rs12124078 (PDiscovery = 2.6 × 10-5; PReplication = 1.5 × 10-4; PCombined = 6.9 × 10-8), a CASP9 expression quantitative trait locus. CONCLUSIONS: Our pathway analysis implicates genetic variation within the PI3K/AKT pathway as a source of RCC heritability and identifies several promising novel susceptibility genes, including CASP9, which warrant further investigation. IMPACT: Our findings illustrate the value of pathway analysis as a complementary approach to analyzing GWAS data.