Prostate enlargement leading to clinical benign prostatic hyperplasia (BPH) is associated with metabolic dysregulation and obesity. The genetic basis of this association is unclear. Our objective was Show more
Prostate enlargement leading to clinical benign prostatic hyperplasia (BPH) is associated with metabolic dysregulation and obesity. The genetic basis of this association is unclear. Our objective was to evaluate whether single nucleotide polymorphisms (SNPs) previously associated with metabolic disorders are also associated with prostate volume (PV). Participants included 876 men referred for prostate biopsy and found to be prostate cancer free. PV was measured by transrectal ultrasound. Samples were genotyped using the Illumina Cardio-MetaboChip platform. Multivariable adjusted linear regression models were used to evaluate SNPs (additive coding) in relation to natural-log transformed (log) PV. We compared SNP-PV results from biopsy-negative men to 442 men with low-grade prostate cancer with similar levels of obesity and PV. Beta-coefficients from the discovery and replication samples were then aggregated with fixed effects inverse variance weighted meta-analysis. SNP rs11736129 (near the pseudo-gene LOC100131429) was significantly associated with log-PV (beta: 0.16, p-value 1.16x10(-8)) after adjusting for multiple testing. Other noteworthy SNPs that were nominally associated (p-value < 1x10(-4)) with log-PV included rs9583484 (intronic SNP in COL4A2), rs10146527 (intronic SNP in NRXN3), rs9909466 (SNP near RPL32P31), and rs2241606 (synonymous SNP in SLC12A7). We found several SNPs in metabolic loci associated with PV. Further studies are needed to confirm our results and elucidate the mechanism between these genetic loci, PV, and clinical BPH. Show less
Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whet Show more
Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci. Show less