Integrating pathway analysis and genetics of gene expression for genome-wide association study of basal cell carcinoma.

Abstract

Genome-wide association studies (GWASs) have primarily focused on marginal effects for individual markers and have incorporated external functional information only after identifying robust statistical associations. We applied a new approach combining the genetics of gene expression and functional classification of genes to the GWAS of basal cell carcinoma (BCC) to identify potential biological pathways associated with BCC. We first identified 322,324 expression-associated single-nucleotide polymorphisms (eSNPs) from two existing GWASs of global gene expression in lymphoblastoid cell lines (n=955), and evaluated the association of these functionally annotated SNPs with BCC among 2,045 BCC cases and 6,013 controls in Caucasians. We then grouped them into 99 KEGG pathways for pathway analysis and identified two pathways associated with BCC with p value <0.05 and false discovery rate (FDR) <0.5: the autoimmune thyroid disease pathway (mainly HLA class I and II antigens, p<0.001, FDR=0.24) and Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway (p=0.02, FDR=0.49). Seventy-nine (25.7%) out of 307 significant eSNPs in the JAK-STAT pathway were associated with BCC risk (p<0.05) in an independent replication set of 278 BCC cases and 1,262 controls. In addition, the association of JAK-STAT signaling pathway was marginally validated using 16,691 eSNPs identified from 110 normal skin samples (p=0.08). Based on the evidence of biological functions of the JAK-STAT pathway on oncogenesis, it is plausible that this pathway is involved in BCC pathogenesis.