| 21. |
- Shui, Irene M., et al.
(författare)
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Prostate Cancer (PCa) Risk Variants and Risk of Fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
- 2014
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Ingår i: European Urology. - : Elsevier BV. - 0302-2838 .- 1873-7560. ; 65:6, s. 1069-1075
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Tidskriftsartikel (refereegranskat)abstract
- Background: Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM). Objective: To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM. Design, setting, and participants: We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred. Outcome measurements and statistical analysis: The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls. Results and limitations: Among the cases, we found that 8 of the 47 SNPs were significantly associated (p < 0.05) with time to PCSM. The risk allele of rs11672691 (intergenic) was associated with an increased risk for PCSM, while 7 SNPs had risk alleles inversely associated (rs13385191 [C2orf43], rs17021918 [PDLIM5], rs10486567 [JAZF1], rs6465657 [LMTK2], rs7127900 (intergenic), rs2735839 [KLK3], rs10993994 [MSMB], rs13385191 [C2orf43]). In the case-control analysis, 22 SNPs were associated (p < 0.05) with the risk of fatal PCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only. Conclusions: Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa. Patient summary: In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that could aid prediction. (C) 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved.
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| 22. |
- 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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| 23. |
- 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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