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Large-scale pathway-based analysis of bladder cancer genome-wide association data from five studies of European background
Authors:Menashe Idan  Figueroa Jonine D  Garcia-Closas Montserrat  Chatterjee Nilanjan  Malats Nuria  Picornell Antoni  Maeder Dennis  Yang Qi  Prokunina-Olsson Ludmila  Wang Zhaoming  Real Francisco X  Jacobs Kevin B  Baris Dalsu  Thun Michael  Albanes Demetrius  Purdue Mark P  Kogevinas Manolis  Hutchinson Amy  Fu Yi-Ping  Tang Wei  Burdette Laurie  Tardón Adonina  Serra Consol  Carrato Alfredo  García-Closas Reina  Lloreta Josep  Johnson Alison  Schwenn Molly  Schned Alan  Andriole Gerald  Black Amanda  Jacobs Eric J  Diver Ryan W  Gapstur Susan M  Weinstein Stephanie J  Virtamo Jarmo  Caporaso Neil E  Landi Maria Teresa
Institution:Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America. menashei@mail.nih.gov
Abstract:Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n?=?5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ~90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis GSEA], and adapted rank-truncated product ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I2 statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways (‘Aromatic amine metabolism’ PGSEA?=?0.0100, PARTP?=?0.0020], ‘NAD biosynthesis’ PGSEA?=?0.0018, PARTP?=?0.0086], ‘NAD salvage’ PARTP?=?0.0068], ‘Clathrin derived vesicle budding’ PARTP?=?0.0018], ‘Lysosome vesicle biogenesis’ PGSEA?=?0.0023, PARTP<0.00012], ’Retrograde neurotrophin signaling’ PGSEA?=?0.00840], and ‘Mitotic metaphase/anaphase transition’ PGSEA?=?0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.
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