Polycystic ovarian syndrome (PCOS) is an endocrine disorder that is characterized by hyperandrogenism. Therefore, information about androgen-induced molecular changes can be obtained using the tissues of patients with PCOS. We analyzed two microarray datasets of normal and PCOS muscle samples (GSE8157 and GSE6798) to identify androgen-responsive genes (ARGs). Differentially expressed genes were determined using the t-test and a meta-analysis of the datasets. The overlap between significant results of the meta-analysis and ARGs predicted from an external database was determined, and differential coexpression analysis was then applied between these genes and the other genes. We found 313 significant genes in the meta-analysis using the Benjamini–Hochberg multiple testing correction. Of these genes, 61 were in the list of predicted ARGs. When the differential coexpression between these 61 genes and 13,545 genes filtered by variance was analyzed, 540 significant gene pairs were obtained using the Benjamini–Hochberg correction. While no significant results were obtained regarding the functional enrichment of the differentially expressed genes, top-level gene ontology terms were significantly enriched in the list of differentially coexpressed genes, which indicates that a broad range of cellular processes is affected by androgen administration. Our findings provide valuable information for the identification of ARGs.

Genome-wide association studies have expanded our understanding of the genetic variation of hypertension. Hypertension and blood pressure are influenced by sex-specific differences; therefore, genetic variants may have sex-specific effects on phenotype. To identify the genetic factors influencing the sex-specific differences concerning hypertension, we conducted a heterogeneity analysis of a genome-wide association study (GWAS) on 13,926 samples from a Korean population. Using the Illumina exome chip data of the population, we performed GWASs of the male and female population independently and applied a statistical test that identified heterogeneous effects of the variants between the two groups. To gain information about the biological implication of the genetic heterogeneity, we used gene set enrichment analysis with GWAS catalog and pathway gene sets. The heterogeneity analysis revealed that the rs11066015 of ACAD10 was a significant locus that had sex-specific genetic effects on the development of hypertension. The rs2074356 of HECTD4 also showed significant genetic heterogeneity in systolic blood pressure. The enrichment analysis showed significant results that are consistent with the pathophysiology of hypertension. These results indicate a sex-specific genetic susceptibility to hypertension that should be considered in future genetic studies of hypertension.