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BackgroundWe reported that some, but not all single nucleotide polymorphisms (SNPs) in select immune response genes are associated with prostate cancer, but not individually with the prevalence of intraprostatic inflammation in the Prostate Cancer Prevention Trial (PCPT) placebo arm. Here, we investigated whether these same SNPs are associated with risk of lower- and higher-grade prostate cancer in men randomized to finasteride, and with prevalence of intraprostatic inflammation among controls. Methods A total of 16 candidate SNPs in IL1β, IL2, IL4, IL6, IL8, IL10, IL12(p40), IFNG, MSR1, RNASEL, TLR4, and TNFA and 7 tagSNPs in IL10 were genotyped in 625 white prostate cancer cases, and 532 white controls negative for cancer on an end-of-study biopsy nested in the PCPT finasteride arm. We used logistic regression to estimate log-additive odds ratios (OR) and 95% confidence intervals (CI) adjusting for age and family history.ResultsMinor alleles of rs2243250 (T) in IL4 (OR = 1.46, 95% CI 1.03-2.08, P-trend = 0.03), rs1800896 (G) in IL10 (OR = 0.77, 95% CI 0.61-0.96, P-trend = 0.02), rs2430561 (A) in IFNG (OR = 1.33, 95% CI 1.02-1.74; P-trend = 0.04), rs3747531 (C) in MSR1 (OR = 0.55, 95% CI 0.32-0.95; P-trend = 0.03), and possibly rs4073 (A) in IL8 (OR = 0.81, 95% CI 0.64-1.01, P-trend = 0.06) were associated with higher- (Gleason 7-10; N = 222), but not lower- (Gleason 2-6; N = 380) grade prostate cancer. In men with low PSA (

The 8q24 region harbors multiple risk variants for distinct cancers, including >8 for prostate cancer. In this study, we conducted fine mapping of the 8q24 risk region (127.8-128.8Mb) in search of novel associations with common and rare variation in 4853 prostate cancer case patients and 4678 control subjects of African ancestry. All statistical tests were two-sided. We identified three independent associations at P values of less than 5.00×10(-8), all of which were replicated in studies from Ghana and Uganda (combined sample = 5869 case patients, 5615 control subjects; rs114798100: risk allele frequency [RAF] = 0.04, per-allele odds ratio [OR] = 2.31, 95% confidence interval [CI] = 2.04 to 2.61, P = 2.38×10(-40); rs72725879: RAF = 0.33, OR = 1.37, 95% CI = 1.30 to 1.45, P = 3.04×10(-27); and rs111906932: RAF = 0.03, OR = 1.79, 95% CI = 1.53 to 2.08, P = 1.39×10(-13)). Risk variants rs114798100 and rs111906923 are only found in men of African ancestry, with rs111906923 representing a novel association signal. The three variants are located within or near a number of prostate cancer-associated long noncoding RNAs (lncRNAs), including PRNCR1, PCAT1, and PCAT2. These findings highlight ancestry-specific risk variation and implicate prostate-specific lncRNAs at the 8q24 prostate cancer susceptibility region.

BackgroundWe previously reported that both intraprostatic inflammation and SNPs in genes involved in the immune response are associated with prostate cancer risk and disease grade. In the present study, we evaluated the association between these SNPs and intraprostatic inflammation in men without a prostate cancer diagnosis.MethodsIncluded in this cross-sectional study were 205 white controls from a case-control study nested in the placebo arm of the Prostate Cancer Prevention Trial. We analyzed inflammation data from the review of H&E-stained prostate tissue sections from biopsies performed per protocol at the end of the trial irrespective of clinical indication, and data for 16 SNPs in key genes involved in the immune response (IL1β, IL2, IL4, IL6, IL8, IL10, IL12(p40), IFNG, MSR1, RNASEL, TLR4, TNFA; 7 tagSNPs in IL10). Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between carrying at least one minor allele and having at least one biopsy core (of a mean of three reviewed) with inflammation.ResultsNone of the SNPs evaluated was statistically significantly associated with having at least one core with inflammation. However, possible inverse associations were present for carrying the minor allele of rs2069762 (G) in IL2 (OR = 0.51, 95%CI 0.25-1.02); carrying two copies of the minor allele of rs1800871 (T) of IL10 (OR = 0.29, 95%CI 0.08-1.00); and carrying the minor allele of rs486907 (A) in RNASEL (OR = 0.52, 95%CI 0.26-1.06). After creating a genetic risk score from the three SNPs possibly associated with inflammation, the odds of inflammation increased with increasing number of risk alleles (P-trend = 0.008).ConclusionWhile our findings do not generally support a cross-sectional link between individual SNPs in key genes involved in the immune response and intraprostatic inflammation in men without a prostate cancer diagnosis, they do suggest that some of these variants when in combination may be associated with intraprostatic inflammation in benign tissue.

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.

Genome-wide association studies have identified more than 80 risk variants for prostate cancer, mainly in European or Asian populations. The generalizability of these variants in other racial/ethnic populations needs to be understood before the loci can be used widely in risk modeling. In our study, we examined 82 previously reported risk variants in 4,853 prostate cancer cases and 4,678 controls of African ancestry. We performed association testing for each variant using logistic regression adjusted for age, study and global ancestry. Of the 82 known risk variants, 68 (83%) had effects that were directionally consistent in their association with prostate cancer risk and 30 (37%) were significantly associated with risk at p < 0.05, with the most statistically significant variants being rs116041037 (p = 3.7 × 10(-26) ) and rs6983561 (p = 1.1 × 10(-16) ) at 8q24, as well as rs7210100 (p = 5.4 × 10(-8) ) at 17q21. By exploring each locus in search of better markers, the number of variants that captured risk in men of African ancestry (p < 0.05) increased from 30 (37%) to 44 (54%). An aggregate score comprised of these 44 markers was strongly associated with prostate cancer risk [per-allele odds ratio (OR) = 1.12, p = 7.3 × 10(-98) ]. In summary, the consistent directions of effects for the vast majority of variants in men of African ancestry indicate common functional alleles that are shared across populations. Further exploration of these susceptibility loci is needed to identify the underlying biologically relevant variants to improve prostate cancer risk modeling in populations of African ancestry.

In search of common risk alleles for prostate cancer that could contribute to high rates of the disease in men of African ancestry, we conducted a genome-wide association study, with 1,047,986 SNP markers examined in 3,425 African-Americans with prostate cancer (cases) and 3,290 African-American male controls. We followed up the most significant 17 new associations from stage 1 in 1,844 cases and 3,269 controls of African ancestry. We identified a new risk variant on chromosome 17q21 (rs7210100, odds ratio per allele = 1.51, P = 3.4 × 10(-13)). The frequency of the risk allele is ∼5% in men of African descent, whereas it is rare in other populations (

Context Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations. Objective This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D. Methods Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients. Results The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than.001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D. Conclusion PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes. [ABSTRACT FROM AUTHOR]