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Pathway Analysis for Genome-Wide Association Study of Basal Cell Carcinoma of the Skin

Authors
Journal
PLoS ONE
1932-6203
Publisher
Public Library of Science
Publication Date
Volume
6
Issue
7
Identifiers
DOI: 10.1371/journal.pone.0022760
Keywords
  • Research Article
  • Biology
  • Genetics
  • Human Genetics
  • Genetic Association Studies
  • Genome-Wide Association Studies
  • Population Biology
  • Epidemiology
  • Epidemiological Methods
  • Genetic Epidemiology
  • Population Genetics
  • Genetic Polymorphism
  • Medicine
Disciplines
  • Biology

Abstract

Background Recently, a pathway-based approach has been developed to evaluate the cumulative contribution of the functionally related genes for genome-wide association studies (GWASs), which may help utilize GWAS data to a greater extent. Methods In this study, we applied this approach for the GWAS of basal cell carcinoma (BCC) of the skin. We first conducted the BCC GWAS among 1,797 BCC cases and 5,197 controls in Caucasians with 740,760 genotyped SNPs. 115,688 SNPs were grouped into gene transcripts within 20 kb in distance and then into 174 Kyoto Encyclopedia of Genes and Genomes pathways, 205 BioCarta pathways, as well as two positive control gene sets (pigmentation gene set and BCC risk gene set). The association of each pathway with BCC risk was evaluated using the weighted Kolmogorov-Smirnov test. One thousand permutations were conducted to assess the significance. Results Both of the positive control gene sets reached pathway p-values<0.05. Four other pathways were also significantly associated with BCC risk: the heparan sulfate biosynthesis pathway (p  =  0.007, false discovery rate, FDR  =  0.35), the mCalpain pathway (p  =  0.002, FDR  =  0.12), the Rho cell motility signaling pathway (p  =  0.011, FDR  =  0.30), and the nitric oxide pathway (p  =  0.022, FDR  =  0.42). Conclusion We identified four pathways associated with BCC risk, which may offer new insights into the etiology of BCC upon further validation, and this approach may help identify potential biological pathways that might be missed by the standard GWAS approach.

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