The HOXB13 variant X285K is associated with clinical significance and early age at diagnosis in African American prostate cancer patients.

BACKGROUND: Recently, a novel HOXB13 variant (X285K) was observed in men of African descent with prostate cancer (PCa) in Martinique. Little is known about this or other variants in HOXB13 which may play a role in PCa susceptibility in African-American (AA) men. METHODS: We sequenced HOXB13 in an AA population of 1048 men undergoing surgical treatment for PCa at Johns Hopkins Hospital. RESULTS: Seven non-synonymous germline variants were observed in the patient population. While six of these variants were seen only once, X285K was found in eight patients. In a case-case analysis, we find that carriers of this latter variant are at increased risk of clinically significant PCa (1.2% carrier rate in Gleason Score ≥7 PCa vs. 0% in Gleason Score <7 PCa, odds ratio, OR = inf; 95% Confidence Interval, 95%CI:1.05-inf, P = 0.028), as well as PCa with early age at diagnosis (2.4% carrier rate in patients <50 year vs. 0.5% carrier rate in patients ≥50 year, OR = 5.25, 95% CI:1.00-28.52, P = 0.03). CONCLUSIONS: While this variant is rare in the AA population (~0.2% MAF), its ancestry-specific occurrence and apparent preferential association with risk for the more aggressive disease at an early age emphasizes its translational potential as an important, novel PCa susceptibility marker in the high-risk AA population.

A genome-wide assessment of variability in human serum metabolism.

The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10(-13) -10(-91)). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.

A genome-wide search for loci interacting with known prostate cancer risk-associated genetic variants.

Genome-wide association studies (GWAS) have identified ∼30 single-nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. To test the hypothesis that other sequence variants in the genome may interact with those 32 known PCa risk-associated SNPs identified from GWAS to affect PCa risk, we performed a systematic evaluation among three existing PCa GWAS populations: CAncer of the Prostate in Sweden population, a Johns Hopkins Hospital population, and the Cancer Genetic Markers of Susceptibility population, with a total sample size of 4723 PCa cases and 4792 control subjects. Meta-analysis of the interaction term between each of those 32 SNPs and SNPs in the genome was performed in three PCa GWAS populations. The most significant interaction detected was between rs12418451 in MYEOV and rs784411 in CEP152, with a P(interaction) of 1.15 × 10(-7) in the meta-analysis. In addition, we emphasized two pairs of interactions with potential biological implication, including an interaction between rs7127900 near insulin-like growth factor-2 (IGF2)/IGF2AS and rs12628051 in TNRC6B, with a P(interaction) of 3.39 × 10(-6) and an interaction between rs7679763 near TET2 and rs290258 in SYK, with a P(interaction) of 1.49 × 10(-6). Those results show statistical evidence for novel loci interacting with known risk-associated SNPs to modify PCa risk. The interacting loci identified provide hints on the underlying molecular mechanism of the associations with PCa risk for the known risk-associated SNPs. Additional studies are warranted to further confirm the interaction effects detected in this study.