||7R03CA167741-03 Interpret this number
||Indiana Univ-Purdue Univ At Indianapolis
||Integrating Genetics of Gene Expression Into Pathway Analysis for Melanoma Gwas
The genome-wide association studies (GWASs) have successfully identified a number of single nucleotide
polymorphisms (SNPs) associated with melanoma risk. However, the traditional GWASs focus only on marginal
effects of individual markers and have incorporated external functional information only after identifying robust
statistical associations. It is often lack power to detect relatively small effects conferred by most genetic variants.
The pathway-based approaches, which evaluate the cumulative contribution of the genes within biological pathways,
may help collect the modest signals contained in the GWAS data and identify biological pathways in the etiology of
disease on a pathway level. As used in the traditional pathway approaches, assigning SNPs to their physical
location may introduce many false positive associations from multiple testing on non-functional SNPs and miss-
annotate SNPs that regulate the expression of genes in distance. Instead, defining the expression quantitative trait
loci (eQTLs) and assigning them into the genes they regulate may help functionally annotate SNPs and increase the
enrichment of functional variants in the pathway analysis. Among numerous SNPs with weak associations in GWAS,
the selection of those from the identified pathways by using the pathway analysis integrating the genetics of gene
expression and the GWAS data for replication may increase the likelihood of targeting true signals than by chance.
The integration of eQTLs of liver and adipose tissues into the pathway analysis for the GWAS of type 2 diabetes has
successfully identified several novel disease-related pathways. More recently, a GWAS on global gene expression
of the skin have systematically generated skin eQTLs. However, no pathway analysis has been conducted for
melanoma GWAS. The goal of the current proposal is to systematically assess the associations of biological
pathways with melanoma risk by applying this new approach to melanoma GWAS in the discovery stage and to
validate specific loci associated with melanoma risk within the identified pathways in the replication stage. Mediation
analysis on potentially intermediate phenotypes will also be conducted to investigate the etiological contribution of
the identified pathways/SNPs. We plan to use a nested melanoma case-control study of 420 melanoma cases and
2,284 controls in two large, well-characterized cohorts, the Nurses¿ Health Study (NHS) and the Health
Professionals Follow-up Study (HPFS) in the discovery stage, and use a melanoma case-control study of 1,804
melanoma cases and 1,026 controls from the MD Anderson Cancer Center in the replication stage. All the cases
and controls have been previously genotyped on Illumina chips. The pre-existing GWAS genotype data gives us a
cost-effective opportunity to apply the new approach to melanoma research. Our proposed study would be the first
to combine the genetics of gene expression and functional classification of genes as prior information to melanoma
GWAS. Findings from this study will pick up the genetic variants with modest effects from the GWAS data, which will
utilize the GWAS data to a greater extent and provide new insights into the etiology of melanoma.
Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma.
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, et al.
Nature genetics, 2015 Sep; 47(9), p. 987-995.