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- Haiman, Christopher A, et al.
(författare)
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Levels of Beta-Microseminoprotein in Blood and Risk of Prostate Cancer in Multiple Populations.
- 2012
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874.
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundA common genetic variant (rs10993994) in the 5' region of the gene encoding β-microseminoprotein (MSP) is associated with circulating levels of MSP and prostate cancer risk. Whether MSP levels are predictive of prostate cancer risk has not been evaluated.MethodsWe investigated the prospective relationship between circulating plasma levels of MSP and prostate cancer risk in a nested case-control study of 1503 case subjects and 1503 control subjects among black, Latino, Japanese, Native Hawaiian, and white men from the Multiethnic Cohort study. We also examined the ability of MSP to serve as a biomarker for discriminating prostate cancer case subjects from control subjects. All statistical tests are two-sided.ResultsIn all racial and ethnic groups, men with lower MSP levels were at greater risk of developing prostate cancer (odds ratio = 1.02 per one unit decrease in MSP, P < .001 in the prostate-specific antigen [PSA]-adjusted analysis). Compared with men in the highest decile of MSP, the multivariable PSA-adjusted odds ratio was 3.64 (95% confidence interval = 2.41 to 5.49) for men in the lowest decile. The positive association with lower MSP levels was observed consistently across racial and ethnic populations, by disease stage and Gleason score, for men with both high and low levels of PSA and across all genotype classes of rs10993994. However, we did not detect strong evidence of MSP levels in improving prostate cancer prediction beyond that of PSA.ConclusionsRegardless of race and ethnicity or rs10993994 genotype, men with low blood levels of MSP have increased risk of prostate cancer.
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| 2. |
- Waters, Kevin M., et al.
(författare)
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A Common Prostate Cancer Risk Variant 5 ' of Microseminoprotein-beta (MSMB) Is a Strong Predictor of Circulating beta-Microseminoprotein (MSP) Levels in Multiple Populations
- 2010
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Ingår i: Cancer Epidemiology Biomarkers & Prevention. - 1538-7755. ; 19:10, s. 2639-2646
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Tidskriftsartikel (refereegranskat)abstract
- Background: beta-Microseminoprotein (MSP) is one of the three most abundantly secreted proteins of the prostate and has been suggested as a biomarker for prostate cancer risk. A common variant, rs10993994, in the 5' region of the gene that encodes MSP (MSMB) has recently been identified as a risk factor for prostate cancer. Methods: We examined the association between rs10993994 genotype and MSP levels in a sample of 500 prostate cancer-free men from four racial/ethnic populations in the Multiethnic Cohort (European Americans, African Americans, Latinos, and Japanese Americans). Generalized linear models were used to estimate the association between rs10993994 genotype and MSP levels. Results: We observed robust associations between rs10994994 genotype and MSP levels in each racial/ethnic population (all P < 10(-8)), with carriers of the C allele having lower geometric mean MSP levels (ng/mL; CC/CT/TT genotypes: European Americans, 28.8/20.9/10.0; African Americans, 29.0/21.9/10.9; Latinos, 29.2/17.1/8.3; and Japanese Americans, 25.8/16.4/6.7). We estimated the variant accounts for 30% to 50% of the variation in MSP levels in each population. We also observed significant differences in MSP levels between populations (P = 3.5 x 10(-6)), with MSP levels observed to be highest in African Americans and lowest in Japanese Americans. Conclusions: Rs10993994 genotype is strongly associated with plasma MSP levels in multiple racial/ethnic populations. Impact: This supports the hypothesis that rs10993994 may be the biologically functional allele. Cancer Epidemiol Biomarkers Prev; 19(10); 2639-46. (C) 2010 AACR.
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| 3. |
- Zaitlen, Noah, et al.
(författare)
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Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies
- 2012
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Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 8:11
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Tidskriftsartikel (refereegranskat)abstract
- Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-controlcovariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled falsepositive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1x10(-9)). The improvement varied across diseases with a 16% median increase in chi(2) test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci.
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