Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging SNP sets. In order to maximize information gleaned from existing genotype data, we conducted a combined analysis of five independent studies of invasive epithelial ovarian cancer. Up to 2,120 cases and 3,382 controls were genotyped in the course of two collaborations at a variety of SNPs in 11 cell cycle genes (CDKN2C, CDKN1A, CCND3, CCND1, CCND2, CDKN1B, CDK2, CDK4, RB1, CDKN2D, CCNE1) and one gene region (CDKN2A-CDKN2B). Because of the semi-overlapping nature of the 123 assayed tagging SNPs, we performed multiple imputation based on fastPHASE using data from White non-Hispanic study participants and participants in the international HapMap Consortium and NIEHS SNPs Program. Logistic regression assuming a log-additive model was performed on combined and imputed data. We observed strengthened signals in imputation-based analyses at several SNPs, particularly CDKN2A-CDKN2B rs3731239, CCND1 rs602652, rs3212879, rs649392, and rs3212891, CDK2 rs2069391, rs2069414, and rs17528736, and CCNE1 rs3218036. These results lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls, and exemplify the utility of imputation in candidate gene studies

Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia

Genome-wide association studies (GWAS) have advanced our understanding of susceptibility to B-cell precursor acute lymphoblastic leukemia (BCP-ALL); however, much of the heritable risk remains unidentified. Here, we perform a GWAS and conduct a meta-analysis with two existing GWAS, totaling 2442 cases and 14,609 controls. We identify risk loci for BCP-ALL at 8q24.21 (rs28665337, P = 3.86 × 10−9, odds ratio (OR) = 1.34) and for ETV6-RUNX1 fusion-positive BCP-ALL at 2q22.3 (rs17481869, P = 3.20 × 10−8, OR = 2.14). Our findings provide further insights into genetic susceptibility to ALL and its biology

Rare germline copy number variants (CNVs) and breast cancer risk

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance