With the exception of two studies,25,37 ten of these PCa epidemiology studies have not included men of African descent. For instance, two independent studies Rapamycin molecular weight revealed a 2-fold increase in PCa risk among Japanese (OR = 2.4; 95% CI = 1.0�C5.6) or European (OR = 2.17; 95% CI = 1.08�C4.33) men who possessed one or more of the putative ��high-risk�� NAT1*10 alleles.14,15 Similar risk estimates were observed for carriers of the NAT2 slow or very slow acetylator genotypes in relation to PCa susceptibility among Japanese.22 However, nine subsequent published reports, as well as a paper in press (Kidd, L.R., ��unpublished data��, August 2010), did not substantiate the aforementioned marginal main effects for either NAT1 and/or NAT2 in relation to PCa.

25,37�C44 Failure to observe significant relationships between genetic polymorphisms and PCa may be partially attributed to small samples sizes, failure to consider gene combination effects or methodological differences. Two out of the twelve previously mentioned studies evaluated NAT1�CNAT2, NAT-heterocyclic aromatic amines, and/or NAT-tobacco smoking interactions.15,37 However, these two studies, like many genetic epidemiology studies, failed to implement MDR, a rigorous statistical tool with the capacity to detect and validate higher-order interactions that would remain undetected by conventional methods, such as logistic regression modeling. As a consequence, in the absence of studies with adequate statistical power or rigor, it is challenging to conclude with certainty whether these biomarkers are important in relation to prostate cancer.

The current study attempted to overcome statistical issues that often plague genetic epidemiology studies by evaluating both main and joint effects using MDR. In light of the genome wide association era, in a post-hoc analysis, we attempted to evaluate our findings in the context of those found in the Cancer Genetic Markers of Susceptibility (CGEMS) data portal that houses over a half million SNPs collected from 2277 Caucasian participants (1176 PCa cases, 1101 controls).45 The CGEMS data portal contains genotype data for 6 NAT1 and 10 NAT2 SNPs; however, none of these markers were related to either PCa or aggressive disease. Upon closer inspection, only the NAT2 SNP (rs1208; A803G, Lys268Arg) matched one out of 15 NAT SNPs analyzed in the current study.

Since the rs1208 SNP is one of 7 NAT2 SNPs that are used to generate various haplotypes to properly classify individuals as slow, intermediate and rapid acetylators, it was not feasible to compare our data to the CGEMS database. Unfortunately, NAT1 and NAT2 SNP data in relation to prostate cancer risk among men of African descent has not been collected AV-951 within the context of genome wide association studies, to our knowledge. Failure to consider all NAT sequence variants necessary to properly classify individuals as NAT1 and NAT2 rapid, intermedicate, and slow acetylators is not unique to the CGEMS database.