A combined analysis of genome-wide association studies in breast cancer

In an attempt to identify common disease susceptibility alleles for breast cancer, we performed a combined analysis of three genome-wide association studies (GWAS), involving 2,702 women of European ancestry with invasive breast cancer and 5,726 controls. Tests for association were performed for 285,984 SNPs. Evidence for association with SNPs in genes in specific pathways was assessed using a permutation-based approach. We confirmed associations with loci reported by previous GWAS on 1p11.2, 2q35, 3p, 5p12, 8q24, 10q23.13, 14q24.1 and 16q. Six SNPs with the strongest signals of association with breast cancer, and which have not been reported previously, were typed in two further studies; however, none of the associations could be confirmed. Suggestive evidence for an excess of associations was found for genes involved in the regulation of actin cytoskeleton, glycan degradation, alpha-linolenic acid metabolism, circadian rhythm, hematopoietic cell lineage and drug metabolism. Androgen and oestrogen metabolism, a pathway previously found to be associated with the development of postmenopausal breast cancer, was marginally significant (P = 0.051 [unadjusted]). These results suggest that further analysis of SNPs in these pathways may identify associations that would be difficult to detect through agnostic single SNP analyses. More effort focused in these aspects of oncology can potentially open up promising avenues for the understanding of breast cancer and its prevention.

[1]  Tony Fletcher,et al.  Sequence variant on 8q24 confers susceptibility to urinary bladder cancer , 2008, Nature Genetics.

[2]  M. Iles,et al.  Multi-Variant Pathway Association Analysis Reveals the Importance of Genetic Determinants of Estrogen Metabolism in Breast and Endometrial Cancer Susceptibility , 2010, PLoS genetics.

[3]  W. Willett,et al.  A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1) , 2009, Nature Genetics.

[4]  G. Galbraith,et al.  TRAF1-C5 as a Risk Locus for Rheumatoid Arthritis—A Genomewide Study , 2008 .

[5]  N. Tran,et al.  Regulation of the expression and activity by progestins of a member of the SOX gene family of transcriptional modulators. , 1999, Journal of molecular endocrinology.

[6]  A. Sigurdsson,et al.  Common variants on chromosome 5p12 confer susceptibility to estrogen receptor–positive breast cancer , 2008, Nature Genetics.

[7]  T. Holford,et al.  Non-synonymous polymorphisms in the circadian gene NPAS2 and breast cancer risk , 2008, Breast Cancer Research and Treatment.

[8]  Rinu Sharma,et al.  Differential expression of beta mannosidase in human esophageal cancer. , 2004, International journal of cancer.

[9]  David S. Wishart,et al.  Nucleic Acids Research Polysearch: a Web-based Text Mining System for Extracting Relationships between Human Diseases, Genes, Mutations, Drugs Polysearch: a Web-based Text Mining System for Extracting Relationships between Human Diseases, Genes, Mutations, Drugs and Metabolites , 2008 .

[10]  Lester L. Peters,et al.  Genome-wide association study identifies novel breast cancer susceptibility loci , 2007, Nature.

[11]  W. Willett,et al.  A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer , 2007, Nature Genetics.

[12]  Allan Peter Davis,et al.  Genetic and environmental pathways to complex diseases , 2009, BMC Systems Biology.

[13]  中尾 光輝,et al.  KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース) , 2000 .

[14]  D. Gudbjartsson,et al.  Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor–positive breast cancer , 2007, Nature Genetics.

[15]  Tao Cai,et al.  Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary , 2005, Bioinform..

[16]  Mark Daly,et al.  Haploview: analysis and visualization of LD and haplotype maps , 2005, Bioinform..

[17]  Joanne E Curran,et al.  Polymorphic variants of NFKB1 and its inhibitory protein NFKBIA, and their involvement in sporadic breast cancer. , 2002, Cancer letters.

[18]  J. Haines,et al.  Genome-wide association study identifies a novel breast cancer susceptibility locus at 6q25.1 , 2009, Nature Genetics.

[19]  Ming-Feng Hou,et al.  Deregulated expression of the PER1, PER2 and PER3 genes in breast cancers. , 2005, Carcinogenesis.

[20]  M. Thun,et al.  Newly discovered breast cancer susceptibility loci on 3p24 and 17q23.2 , 2009, Nature Genetics.

[21]  C. Hoggart,et al.  Genome-wide association analysis of metabolic traits in a birth cohort from a founder population , 2008, Nature Genetics.

[22]  K. Lange,et al.  Prioritizing GWAS results: A review of statistical methods and recommendations for their application. , 2010, American journal of human genetics.

[23]  Elizabeth A. Heron,et al.  The SNP ratio test: pathway analysis of genome-wide association datasets , 2009, Bioinform..

[24]  Michael R. Kosorok,et al.  Detection of gene pathways with predictive power for breast cancer prognosis , 2010, BMC Bioinformatics.

[25]  Judy H. Cho,et al.  A Genome-Wide Association Study Identifies IL23R as an Inflammatory Bowel Disease Gene , 2006, Science.

[26]  D. Reich,et al.  Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.

[27]  Päivi Rosenström,et al.  NordicDB: a Nordic pool and portal for genome-wide control data , 2010, European Journal of Human Genetics.

[28]  Wei Zhang,et al.  SCAN: SNP and copy number annotation , 2010, Bioinform..

[29]  Debashis Ghosh,et al.  Pathway analysis reveals functional convergence of gene expression profiles in breast cancer , 2008 .

[30]  Rinu Sharma,et al.  Differential expression of β mannosidase in human esophageal cancer , 2004 .

[31]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[32]  J. Yamashita,et al.  Increased expression of membrane‐associated phospholipase A2 shows malignant potential of human breast cancer cells , 1993, Cancer.

[33]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[34]  Kai Wang,et al.  Pathway-based approaches for analysis of genomewide association studies. , 2007, American journal of human genetics.

[35]  Nicholas J Wareham,et al.  Allelic association of the human homologue of the mouse modifier Ptprj with breast cancer. , 2005, Human molecular genetics.

[36]  Momiao Xiong,et al.  Gene and pathway-based second-wave analysis of genome-wide association studies , 2010, European Journal of Human Genetics.

[37]  Robert Tibshirani,et al.  Statistical methods for identifying differentially expressed genes in DNA microarrays. , 2003, Methods in molecular biology.

[38]  K. Mossman.  The Wellcome Trust Case Control Consortium, U.K. , 2008 .

[39]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[40]  Bin Ma,et al.  Better score function for peptide identification with ETD MS/MS spectra , 2010, BMC Bioinformatics.

[41]  Christian Gieger,et al.  Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts , 2009, Nature Genetics.

[42]  Murim Choi,et al.  Susceptibility loci for intracranial aneurysm in European and Japanese populations , 2008, Nature Genetics.

[43]  P. Hall,et al.  Risk Factors for Hormone Receptor-Defined Breast Cancer in Postmenopausal Women , 2006, Cancer Epidemiology Biomarkers & Prevention.

[44]  P. Pharoah,et al.  Polygenic susceptibility to breast cancer: current state-of-the-art. , 2009, Future oncology.