Meta-analysis of new genome-wide association studies of colorectal cancer risk

Abstract

Colorectal cancer is the second leading cause of cancer death in developed countries. Genome-wide association studies (GWAS) have successfully identified novel susceptibility loci for colorectal cancer. To follow-up on these findings, and try to identify novel colorectal cancer susceptibility loci, we present results for genome-wide association studies (GWAS) of colorectal cancer (2,906 cases, 3,416 controls) that have not previously published main associations. Specifically, we calculated odds ratios (ORs) and 95% confidence intervals (CIs) using log-additive models for each study. In order to improve our power to detect novel colorectal cancer susceptibility loci, we performed a meta-analysis combining the results across studies. We selected the most statistically significant single nucleotide polymorphisms (SNPs) for replication using 10 independent studies (8,161 cases and 9,101 controls). We again used a meta-analysis to summarize results for the replication studies alone, and for a combined analysis of GWAS and replication studies. We measured 10 SNPs previously identified in colorectal cancer susceptibility loci and found eight to be associated with colorectal cancer (p-value range: 0.02 to 1.8 × 10−8). When we excluded studies that have previously published on these SNPs, five SNPs remained significant at p<0.05 in the combined analysis. No novel susceptibility loci were significant in the replication study after adjustment for multiple testing, and none reached genome-wide significance from a combined analysis of GWAS and replication. We observed marginally significant evidence for a second independent SNP in the BMP2 region at chromosomal location 20p12 (rs4813802; replication p-value 0.03; combined p-value 7.3 × 10−5). In a region on 5p33.15, which includes the coding regions of the TERT-CLPTM1L genes and has been identified in GWAS to be associated with susceptibility to at least seven other cancers, we observed a marginally significant association with rs2853668 (replication p-value 0.03; combined p-value 1.9 × 10−4). Our study suggests a complex nature of the contribution of common genetic variants to risk for colorectal cancer.

Quantifying the Utility of Single Nucleotide Polymorphisms to Guide Colorectal Cancer Screening

“…There was considerable overlap for the number of risk alleles for the simulated people with and without colorectal cancer (for those with colorectal cancer: median 42 [22] 1q25.3 LAMC1 rs10911251 1.05 0.54 1.0006 0.07% [23,24] 1q41 DUSP10; CICP13 rs6687758 1.09 0.2 1.0012 0.15% [25] 2q32.3 NABP1; MYO1B; SDPR rs11903757 1.06 0.36 1.003 0.37% [25,26] 3p14.1 LRIG1 rs812481 1.09 0.58 1.0018 0.22% [27] 3p22.1 RP11; CTNNB1 rs35360328 1.14 0.16 1.0023 0.29% [27] 3q26.2 MYNN; TERC rs10936599 1.08 0.75 1.0011 0.14% [25] 4q26 NDST3 rs3987 1.36 0.44 1.0235 2.87% [28] 4q32.2 FSTL5 rs35509282 1.53 0.09 1.0149 1.83% [29] 5q31.1 PITX1; H2AFY rs647161 1.11 0.67 1.0024 0.30% [30] 6p21.31 CDKN1A rs1321311 1.1 0.23 1.0016 0.20% [18] 8q23. [32,34] 10p13 CUBN rs10904849 1.14 0.68 1.0037 0.46% [22] 10p14 GATA3 rs10795668 1.12 0.67 1.0028 0.35% [31] 10q22.3 ZMIZ1; AS1 rs704017 1.06 0.57 1.0008 0.10% [17] 10q24.2 SLC25A28; ENTPD7; COX15; CUTC; ABCC2 rs11190164 1.09 0.29 1.0015 0.19% [27] 10q25 VTI1A rs12241008 1.13 0.09 1.0012 0.15% [17] 11q12.2 FADS1; FEN1 11qhap ‡ 1.4 0.57 1.0281 3.41% [17] 11q13.4 POLD3 rs3824999 1.08 0.5 1.0015 0.18% [18] 11q23.1 COLCA2 rs3802842 1.11 0.29 1.0022 0.28% [35] 12p13.32 CCND2 rs3217810 1.2 0.16 1.0045 0.55% [23,24] 12p13.32 CCND2 rs3217901 1.1 0.41 1.0022 0.27% [23,24] 12p13.32 CCND2 rs10774214 1.09 0.38 1.0018 0.22% [30] 12q13.13 DIP2B; ATF1 rs11169552 1.09 0.72 1.0015 0.18% [25] 12q13.13 LARP4; DIP2B rs7136702 1.06 0.35 1.0008 0.10% [25] 12q24.12 SH2B3 rs3184504 1.09 0.53 1.0019 0.23% [27] 12q24.21 TBX3 rs59336 1.09 0.48 1.0019 0.23% [26] 12q24.22 NOS1 rs73208120 1.16 0.11 1.0021 0.26% …”

“…[32,34] 10p13 CUBN rs10904849 1.14 0.68 1.0037 0.46% [22] 10p14 GATA3 rs10795668 1.12 0.67 1.0028 0.35% [31] 10q22.3 ZMIZ1; AS1 rs704017 1.06 0.57 1.0008 0.10% [17] 10q24.2 SLC25A28; ENTPD7; COX15; CUTC; ABCC2 rs11190164 1.09 0.29 1.0015 0.19% [27] 10q25 VTI1A rs12241008 1.13 0.09 1.0012 0.15% [17] 11q12.2 FADS1; FEN1 11qhap ‡ 1.4 0.57 1.0281 3.41% [17] 11q13.4 POLD3 rs3824999 1.08 0.5 1.0015 0.18% [18] 11q23.1 COLCA2 rs3802842 1.11 0.29 1.0022 0.28% [35] 12p13.32 CCND2 rs3217810 1.2 0.16 1.0045 0.55% [23,24] 12p13.32 CCND2 rs3217901 1.1 0.41 1.0022 0.27% [23,24] 12p13.32 CCND2 rs10774214 1.09 0.38 1.0018 0.22% [30] 12q13.13 DIP2B; ATF1 rs11169552 1.09 0.72 1.0015 0.18% [25] 12q13.13 LARP4; DIP2B rs7136702 1.06 0.35 1.0008 0.10% [25] 12q24.12 SH2B3 rs3184504 1.09 0.53 1.0019 0.23% [27] 12q24.21 TBX3 rs59336 1.09 0.48 1.0019 0.23% [26] 12q24.22 NOS1 rs73208120 1.16 0.11 1.0021 0.26% [27] 14q22.2 BMP4 rs1957636 1.08 0.4 1.0014 0.18% [36] 14q22.2 BMP4 rs4444235 1.11 0.46 1.0027 0.33% [36,37] 15q13.3 SCG5; GREM1 rs11632715 1.12 0.47 1.0032 0.39% [36] 15q13.3 SCG5; GREM1 rs16969681 1.18 0.09 1.0022 0.28% [36] 16q22.1 CDH1 rs9929218 1.1 0.71 1.0019 0.23% [37] 16q24.1 FOXL1 rs16941835 1.15 0.21 1.0032 0.40% [22] 17q21 STAT3 rs744166 1.27 0.55 1.0142 1.74% [38] 18q21.1 SMAD7 rs4939827 1.18 0.52 1.0069 0.84% [35,39] 19q13.11 RHPN2 rs10411210 1.15 0.9 1.0018 0.22% [37] 19q13.2 TMEM91; TGFB1 19qhap ‡ 1.16 0.49 1.0055 0.68% [17] 20p12.3 FERMT1; BMP2 rs2423279, 1.14 0.3 1.0036 0.44% [24,30] 20p12.3 FERMT1; BMP2 rs4813802 1.09 0.36 1.0017 0.21% …”

Congenital Pouch Colon: Role of Genetics or Environmental Influence?

“…Nos1AP gene leads to the inactivation of the proto-oncogene protein Akt (Akt) signaling pathway [40]. ITGB5, COLCA2, and SSTR5 genes are associated with Villous adenocarcinoma, colorectal cancer [41], and uveal melanomas respectively [42]. The MLL gene regulates the expression of target genes, including multiple HOX genes and also a frequent target for recurrent translocations in acute leukemias [43].…”

Rare allelic forms of PRDM9 associated with childhood leukemogenesis

“…Genetic approaches aim to find genomic regions predisposing individuals to cancer, to capture inherited predisposing mutations segregating in the population by using genetic linkage or association studies. For late-onset cancers, such as breast and colorectal cancers (Turnbull et al 2010;Peters et al 2012), many predisposing allelic variants have been described, supporting a polygenic model of susceptibility (Easton and Eeles 2008), but only a few genetic risk factors for pediatric cancer have been established (Healy et al 2007;Sherborne et al 2010). Dominant mutations causing cancer early in life are likely to be rapidly eliminated from the population, and as a result, it is unlikely that affected children will share inherited mutations.…”