Abstract SY29-01: Gene-based and pathway-based analysis applied to cancer genome-wide association studies

Abstract

Abstract Genome-wide association studies (GWAS) have proved successful in identifying new loci underlying susceptibility to a wide variety of traits including many cancers. It is becoming clear that in addition to relatively large genetic effects, such as pigmentation-related genetic effects on cancers such as melanoma, there exist a large number of smaller genetic effects which are more difficult to identify (“the polygenic tail” in the distribution of effects). Identifying and characterizing such smaller effects will require approaches which do more than simply focus on the very top hits from GWAS. Gene-based and pathway-based approaches are two approaches which complement single marker based GWAS analysis. We recently developed a versatile gene-based test for genome-wide association studies (GWAS)1. Our approach, called VEGAS (VErsatile Gene-based Association Study), is applicable to all GWAS designs, including family-based GWAS, meta-analyses of GWAS on the basis of summary data, and DNA-pooling-based GWAS, where existing approaches based on permutation are not possible, as well as singleton data, where they are. The test incorporates information from a full set of markers (or a defined subset) within a gene and accounts for linkage disequilibrium between markers by using simulations from the multivariate normal distribution. For an association study using singletons, our approach produces results equivalent to those obtained via permutation in a fraction of the computation time. Applying VEGAS to a DNA-pooling-based GWAS for melanoma (1200 cases with relevant controls), we previously showed that several pigmentation-related genes are clearly associated at the gene-based level. We have subsequently applied VEGAS to an extended melanoma data based on individually genotyped samples (2200 cases with relevant controls), obtaining stronger confirmation of the role of pigmentation related genes (MC1R, ASIP, OCA2, MTAP, TYR, SLC45A2) and suggestive evidence for a number of novel nonpigmentation related genes in melanoma. We also applied VEGAS to two further smaller (500 and 1000 cases, respectively) GWASs of melanoma, again highlighting some, but not all of the pigmentation genes listed above. Work is underway in applying VEGAS to several other cancer types including breast cancer, ovarian cancer, prostate cancer, pancreatic cancer and lung cancer. VEGAS has been extended to use gene-based results in a pathway analysis (VEGAS-pathway). VEGAS-pathway, like VEGAS, uses summary data and is not limited to situations where raw genotypes are available. Currently, this implementation combines gene-based test statistics across genes in a predefined pathway, taking into account situations where genes within the pathway are close to each other in the genome. This implementation has been evaluated using pathways defined by Gene Ontology and Ingenuity. Work is ongoing to extend the approach to further sets of predefined pathways. Applying VEGAS-pathway to the N=2200 melanoma data set using GO defined pathways, several pathways that made good biological sense (e.g., “melanin biosynthetic process,” “pigmentation”) were apparent. VEGAS-pathway results on the smaller (N=500, 1000) melanoma data sets did not clearly identify these GO pathways, indicating that large sample size remains crucial, even for situations such as pigmentation-related pathways in melanoma. Using Ingenuity-defined pathways, it was not possible to identify any statistically significant pathways that made good biological sense in any of the melanoma data sets – at least in this case, the more narrowly defined Ingenuity pathways offered less insight into the trait than the more broadly defined and numerous GO pathways. After removal of the known pigmentation genes, the most significant GO pathway in the N=2200 data set was the small pathway “regulation of growth rate”. This pathway showed nominal replication in a further set of N=1800 melanoma cases (with relevant controls). VEGAS-pathway results for several other cancer types (breast cancer, ovarian cancer, prostate cancer, pancreatic cancer and lung cancer) will be presented at the meeting. 1 Liu JZ, McRae AF, Nyholt DR, Medland SE, Wray NR, Brown KM, Hayward NK, Montgomery GW, Visscher PM, Martin NG, Macgregor S, A versatile gene-based test for genome-wide association studies. Am J Hum Genet 2010, 87(1):139-145. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr SY29-01. doi:10.1158/1538-7445.AM2011-SY29-01