12 research outputs found

    Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer.

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    Genome-wide association studies have reported 56 independently associated colorectal cancer (CRC) risk variants, most of which are non-coding and believed to exert their effects by modulating gene expression. The computational method PrediXcan uses cis-regulatory variant predictors to impute expression and perform gene-level association tests in GWAS without directly measured transcriptomes. In this study, we used reference datasets from colon (n = 169) and whole blood (n = 922) transcriptomes to test CRC association with genetically determined expression levels in a genome-wide analysis of 12,186 cases and 14,718 controls. Three novel associations were discovered from colon transverse models at FDR ≀ 0.2 and further evaluated in an independent replication including 32,825 cases and 39,933 controls. After adjusting for multiple comparisons, we found statistically significant associations using colon transcriptome models with TRIM4 (discovery P = 2.2 × 10- 4, replication P = 0.01), and PYGL (discovery P = 2.3 × 10- 4, replication P = 6.7 × 10- 4). Interestingly, both genes encode proteins that influence redox homeostasis and are related to cellular metabolic reprogramming in tumors, implicating a novel CRC pathway linked to cell growth and proliferation. Defining CRC risk regions as one megabase up- and downstream of one of the 56 independent risk variants, we defined 44 non-overlapping CRC-risk regions. Among these risk regions, we identified genes associated with CRC (P < 0.05) in 34/44 CRC-risk regions. Importantly, CRC association was found for two genes in the previously reported 2q25 locus, CXCR1 and CXCR2, which are potential cancer therapeutic targets. These findings provide strong candidate genes to prioritize for subsequent laboratory follow-up of GWAS loci. This study is the first to implement PrediXcan in a large colorectal cancer study and findings highlight the utility of integrating transcriptome data in GWAS for discovery of, and biological insight into, risk loci

    Mendelian randomisation study of age at menarche and age at menopause and the risk of colorectal cancer

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    BACKGROUND: Substantial evidence supports an association between use of menopausal hormone therapy and decreased colorectal cancer (CRC) risk, indicating a role of exogenous sex hormones in CRC development. However, findings on endogenous oestrogen exposure and CRC are inconsistent. METHODS: We used a Mendelian randomisation approach to test for a causal effect of age at menarche and age at menopause as surrogates for endogenous oestrogen exposure on CRC risk. Weighted genetic risk scores based on 358 single-nucleotide polymorphisms associated with age at menarche and 51 single-nucleotide polymorphisms associated with age at menopause were used to estimate the association with CRC risk using logistic regression in 12,944 women diagnosed with CRC and 10,741 women without CRC from three consortia. Sensitivity analyses were conducted to address pleiotropy and possible confounding by body mass index. RESULTS: Genetic risk scores for age at menarche (odds ratio per year 0.98, 95% confidence interval: 0.95-1.02) and age at menopause (odds ratio 0.98, 95% confidence interval: 0.94-1.01) were not significantly associated with CRC risk. The sensitivity analyses yielded similar results. CONCLUSIONS: Our study does not support a causal relationship between genetic risk scores for age at menarche and age at menopause and CRC risk

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

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    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

    Sequence variants of estrogen receptor beta and risk of prostate cancer in the national cancer institute breast and prostate cancer cohort consortium

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    Background: Estrogen receptor beta (ESR2) may play a role in modulating prostate carcirtogenesis through the regulation of genes related to cell proliferation and apoptosis. Methods: We conducted nested case-control studies in the Breast and Prostate Cancer Cohort Consortium (BPC3) that pooled 8,323 prostate cancer cases and 9,412 controls from seven cohorts. Whites were the predominant ethnic group. We characterized genetic variation in ESR2 by resequencing exons in 190 breast and prostate cancer cases and genotyping a dense set of single nucleotide polymorphisms (SNP) spanning the locus in a multiethnic panel of 349 cancer-free subjects. We selected four haplotype-tagging SNPs (htSNP) to capture common ESR2 variation in Whites; these htSNPs were then genotyped in all cohorts. Conditional logistic regression models were used to assess the association between sequence variants of ESR2 and the risk of prostate cancer. We also investigated the effect modification by age, body mass index, and family history, as well as the association between sequence variants of ESR2 and advanced-stage (&gt;= T3b, N-1, or M-1) and high-grade (Gleason sum &gt;= 8) prostate cancer, respectively. Results: The four tag SNPs in ESR2 were not significantly associated with prostate cancer risk, individually. The global test for the influence of any haplotype on the risk of prostate cancer was not significant (P = 0.31). However, we observed that men carrying two copies of one of the variant haplotypes (TACC) had a 1.46-fold increased risk of prostate cancer (99% confidence interval, 1.06-2.01) compared with men carrying zero copies of this variant haplotype. No SNPs or haplotypes were associated with advanced stage or high grade of prostate cancer. Conclusion: In our analysis focused on genetic variation common in Whites, we observed little evidence for any substantial association of inherited variation in ESR2 with risk of prostate cancer. A nominally significant (P &lt; 0.01) association between the TACC haplotype and prostate cancer risk under the recessive model could be a chance finding and, in any event, would seem to contribute only slightly to the overall burden of prostate cancer

    Correction to: Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer

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    Every author has erroneously been assigned to the affiliation “62”. The affiliation 62 belongs to the author Graham Casey.</p
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