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Pleiotropy between genetic markers of obesity and risk of prostate cancer.

ABSTRACT: To address inconsistent findings of obesity and prostate cancer risk, we analyzed the association between prostate cancer and genetic markers of obesity and metabolism.Analyses included 176,520 single-nucleotide polymorphisms (SNP) associated with 23 metabolic traits. We examined the association between SNPs and prostate cancer in 871 cases and 906 controls, including 427 high-grade cases with Gleason ? 7. Genetic risk scores (GRS) for body mass index (BMI) and waist-to-hip ratio (WHR) were also created by summing alleles associated with increasing BMI or WHR.Prostate cancer was associated with five loci, including cyclin M2, with P values less than 1 × 10(-4). In addition, the WHR GRS was associated with high-grade prostate cancer versus controls [OR, 1.05; 95% confidence interval (CI), 1.00-1.11; P = 0.048] and high-grade prostate cancer versus low-grade prostate cancer (OR, 1.07; 95% CI, 1.01-1.13; P = 0.03). None of these findings exceeds the threshold for significance after correction for multiple testing.Variants in genes known to be associated with metabolism and obesity may be associated with prostate cancer. We show evidence for pleiotropy between WHR GRS and prostate cancer grade. This finding is consistent with the function of several WHR genes and previously described relationships with cancer traits.Limitations in standard obesity measures suggest alternative characterizations of obesity may be needed to understand the role of metabolic dysregulation in prostate cancer. The underlying genetics of WHR or other Metabochip SNPs, while not statistically significant beyond multiple testing thresholds within our sample size, support the metabolic hypothesis of prostate carcinogenesis and warrant further investigation in independent samples.

SUBMITTER: Edwards TL

PROVIDER: S-EPMC3769483 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Pleiotropy between genetic markers of obesity and risk of prostate cancer.

Edwards Todd L TL Giri Ayush A Motley Saundra S Duong Wynne W Fowke Jay H JH

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20130627 9

<h4>Background</h4>To address inconsistent findings of obesity and prostate cancer risk, we analyzed the association between prostate cancer and genetic markers of obesity and metabolism.<h4>Methods</h4>Analyses included 176,520 single-nucleotide polymorphisms (SNP) associated with 23 metabolic traits. We examined the association between SNPs and prostate cancer in 871 cases and 906 controls, including 427 high-grade cases with Gleason ≥ 7. Genetic risk scores (GRS) for body mass index (BMI) and ...[more]

PMID: 23810916

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Project description:BackgroundNo single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS).ObjectiveTo test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.Design, setting, and participantsSNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.Outcome measurements and statistical analysisOdds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.Results and limitationsA total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.ConclusionsWe did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.Patient summaryWe evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.

Project description:Prostate cancer (PCa) is a common malignancy and a leading cause of cancer death among men in the United States with African-American (AA) men having the highest incidence and mortality rates. Given recent results from admixture mapping and genome-wide association studies for PCa in AA men, it is clear that many risk alleles are enriched in men with West African genetic ancestry.A total of 77 ancestry informative markers (AIMs) within surrounding candidate gene regions were genotyped and haplotyped using Pyrosequencing in 358 unrelated men enrolled in a PCa genetic association study at the Howard University Hospital between 2000 and 2004. Sequence analysis of promoter region single-nucleotide polymorphisms (SNPs) to evaluate disruption of transcription factor-binding sites was conducted using in silico methods.Eight AIMs were significantly associated with PCa risk after adjusting for age and West African ancestry. SNP rs1993973 (intervening sequences) had the strongest association with PCa using the log-additive genetic model (P=0.002). SNPs rs1561131 (genotypic, P=0.007), rs1963562 (dominant, P=0.01) and rs615382 (recessive, P=0.009) remained highly significant after adjusting for both age and ancestry. We also tested the independent effect of each significantly associated SNP and rs1561131 (P=0.04) and rs1963562 (P=0.04) remained significantly associated with PCa development. After multiple comparisons testing using the false discovery rate, rs1993973 remained significant. Analysis of the rs156113-, rs1963562-rs615382l and rs1993973-rs585224 haplotypes revealed that the least frequently found haplotypes in this population were significantly associated with a decreased risk of PCa (P=0.032 and 0.0017, respectively).The approach for SNP selection utilized herein showed that AIMs may not only leverage increased linkage disequilibrium in populations to identify risk and protective alleles, but may also be informative in dissecting the biology of PCa and other health disparities.

Dataset Information

Pleiotropy between genetic markers of obesity and risk of prostate cancer.

Publications

Pleiotropy between genetic markers of obesity and risk of prostate cancer.

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