BACKGROUND: Epidemiologic studies have found evidence of an inverse association between diabetes status and prostate cancer risk. We explored the hypothesis that common genetic variation may explain, in part, the inverse association between diabetes and prostate cancer. METHODS: We tested 17 diabetes risk variants for association with prostate cancer risk in a prostate cancer case-control study of 2,746 cases and 3,317 controls from five racial/ethnic groups in the Multiethnic Cohort (MEC) study. RESULTS: After adjustment for multiple testing, none of the alleles were statistically significantly associated with prostate cancer risk. Aggregate scores that sum the risk alleles were also not significantly associated with risk. CONCLUSIONS: We did not find evidence of association of this set of diabetes risk alleles with prostate cancer. IMPACT: Resequencing and fine-mapping of the loci for diabetes and prostate cancer that were identified by genome-wide association studies are necessary to understand any genetic contribution for the inverse association between these common diseases.
BACKGROUND: Epidemiologic studies have found evidence of an inverse association between diabetes status and prostate cancer risk. We explored the hypothesis that common genetic variation may explain, in part, the inverse association between diabetes and prostate cancer. METHODS: We tested 17 diabetes risk variants for association with prostate cancer risk in a prostate cancer case-control study of 2,746 cases and 3,317 controls from five racial/ethnic groups in the Multiethnic Cohort (MEC) study. RESULTS: After adjustment for multiple testing, none of the alleles were statistically significantly associated with prostate cancer risk. Aggregate scores that sum the risk alleles were also not significantly associated with risk. CONCLUSIONS: We did not find evidence of association of this set of diabetes risk alleles with prostate cancer. IMPACT: Resequencing and fine-mapping of the loci for diabetes and prostate cancer that were identified by genome-wide association studies are necessary to understand any genetic contribution for the inverse association between these common diseases.
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