SNPs in five chromosomal regions plus a family history of prostate cancer have a cumulative and significant association with prostate cancer.

Deletions on human chromosome 8p22-23 in prostate cancer cells and linkage studies in families affected with hereditary prostate cancer (HPC) have implicated this region in the development of prostate cancer. The macrophage scavenger receptor 1 gene (MSR1, also known as SR-A) is located at 8p22 and functions in several processes proposed to be relevant to prostate carcinogenesis. Here we report the results of genetic analyses that indicate that mutations in MSR1 may be associated with risk of prostate cancer. Among families affected with HPC, we identified six rare missense mutations and one nonsense mutation in MSR1. A family-based linkage and association test indicated that these mutations co-segregate with prostate cancer (P = 0.0007). In addition, among men of European descent, MSR1 mutations were detected in 4.4% of individuals affected with non-HPC as compared with 0.8% of unaffected men (P = 0.009). Among African American men, these values were 12.5% and 1.8%, respectively (P = 0.01). These results show that MSR1 may be important in susceptibility to prostate cancer in men of both African American and European descent.

Inflammation has been implicated as an etiological factor in several human cancers. Growing evidence suggests that chronic inflammation may also play a role in the etiology of prostate cancer. Considering that genetic susceptibility is a major risk factor for this disease, we hypothesize that sequence variants in genes that regulate inflammation may modify individual susceptibility to prostate cancer. The lipopolysaccharide receptor Toll-like receptor 4 (TLR4) is a central player in the signaling pathways of the innate immune response to infection by Gram-negative bacteria and is an important candidate inflammatory gene. We performed a systematic genetic analysis of TLR4 sequence variants by evaluating eight single-nucleotide polymorphisms that span the entire gene among 1383 newly diagnosed prostate cancer patients and 780 age-and residencematched controls in Sweden. We found an association between a sequence variant (11381G/C) in the 3-untranslated region of the TLR4 gene and prostate cancer risk. The frequency of the variant genotypes (CG or CC) was significantly higher in the patients (24.1%) than in the controls (19.7%; P ‫؍‬ 0.02). The frequency of risk genotypes among patients diagnosed before the age of 65 years was even higher (26.3%). Compared with men who had the wild-type genotype of this single-nucleotide polymorphism (GG), those with GC or CC genotypes had a 26% increased risk for prostate cancer (odds ratio, 1.26; 95% confidence interval, 1.01-1.57) and 39% increased risk increased risk for early onset prostate cancer (before age 65 years; odds ratio, 1.39; 95% confidence interval, 1.02-1.91). The risk attributable to this variant for prostate cancer in Sweden was estimated to be 4.9%. Although the biological mechanism of the observed association remains to be elucidated, our finding supports a role for a bacteria-associated response pathway, possibly acting via inflammation, in the development of prostate cancer.

Case-control studies have been widely used to test for association between DNA sequence variants and complex diseases. The premise of genetic association studies is that the increased allele or genotype frequencies in cases compared with controls implicates sequence variants that either increase risk to a disease or are in strong linkage disequilibrium (LD) with a disease-causal mutation. However, many other factors can also lead to an observed difference in allele or genotype frequencies between cases and controls. While much attention has been devoted to the potential impact of incomparability between cases and controls in terms of sources of cases and controls, environmental exposures, and genetic background (population stratification), there is a clear lack of comprehension of the impact of genotyping error on the results of association studies. The accuracy and precision of genotyping becomes more critical in case-control studies of complex diseases because:(1) the effect of a specific risk allele under study is usually small, therefore even a low frequency of genotyping error may lead to a false positive or false negative finding; (2) no Mendelian inheritance check can be performed due to lack of family genotype data; (3) a large number of genotypes are usually generated. However, the degree of genotyping error in case-control studies remains unclear, due to the lack of direct measures of this type of error.To indirectly assess the prevalence and magnitude of genotyping error in case-control studies, we systematically reviewed reported association studies from PUBMED and performed Hardy-Weinberg equilibrium (HWE) tests in control subjects for each reported single nucleotide polymorphism (SNP). A significant difference between the observed and expected genotype frequencies under HWE may indicate genotyping error, because the conditions of HWE are generally applicable to the control subjects in any well-designed study population, i.e. (1) mating takes place at random with respect to genotype, (2) allelic frequencies are the same in males and females, and (3) mutation, selection, and migration are negligible. Although exceptions to the conditions of HWE may explain deviation, it is critical that investigators recognize the need to perform a test of HWE, and then evaluate the reason(s) for any observed deviation.We searched for articles with the keywords "association genotyp* genetic case control", and limited the search to articles in English, with human subjects, and 2000 publication date. The search yielded 157 articles, which we then limited to the 101 articles available among 1,721 journals received at the Wake Forest Baptist Medical Center Coy C. Carpenter Library. We disregarded 26 articles that did not include SNPs. This search and selection scheme resulted in a total of 75 articles describing 133 SNPs (the list of these articles is at www.wfubmc.edu/genomics). It is worth noting that limiting journals to our local library could bias toward higher profile journals and our findings may not be representat...

Background Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk. Objective To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa. Design, setting, and participants Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated. Outcome measurements and statistical analysis Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers. Results and limitations Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10−8). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p < 0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p = 0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥7) PCa. A major limitation of this study was its focus on white patients only. Conclusions Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.