The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Objective: We perform a comprehensive heritability study on multiple phenotypes related to metabolic syndrome using Chinese twins to assess the genetic and environmental effects in determining the variation and covariation of the phenotypes in the Chinese population. Methods: The studied sample contains 654 twins collected in the Qingdao municipality. A total of 10 phenotypes covering anthropometric measurements, plasma glucose levels, lipids, blood pressures etc. were examined. Univariate and bivariate structural equation models were fitted for assessing the genetic and environmental contributions. Results: The AE model combining additive genetic (A) and unique environmental (E) factors produced the best fit for all phenotypes except for triglyceride. Modest to high heritability estimates were obtained in univariate analysis ranging from 0.5 for total cholesterol to 0.78 for weight. The bivariate model estimated high genetic correlations between systolic and diastolic blood pressures, between total cholesterol and low density lipoprotein cholesterol, modest genetic correlations between BMI and blood pressures. No significant common environmental correlation was found between any pair of the phenotypes. Conclusions: Our results showed significant genetic contributions to the sub-phenotypes of metabolic syndrome. Although pleiotropic genetic control may exist for some physiologically similar phenotypes, our results do not support a common genetic mechanism among the phenotypes covered in our study.

Serum uric acid (SUA), as the end product of purine metabolism, has proven emerging roles in human disorders. Here based on a sample of 379 middle and old-aged Chinese twin pairs, we aimed to explore the magnitude of genetic impact on SUA variation by performing sex-limitation twin modeling analyses and further detect specific genetic variants related to SUA by conducting a genome-wide association study. Monozygotic (MZ) twin correlation for SUA level (rMZ = 0.56) was larger than for dizygotic (DZ) twin correlation (rDZ = 0.39). The common effects sex-limitation model provided the best fit with additive genetic parameter (A) accounting for 46.3%, common or shared environmental parameter (C) accounting for 26.3% and unique/nonshared environmental parameter (E) accounting for 27.5% for females and 29.9, 33.1, and 37.0% for males, respectively. Although no SUA-related genetic variants reached genome-wide significance level, 25 SNPs were suggestive of association (P < 1 × 10⁻⁵). Most of the SNPs were located in an intronic region and detected to have regulatory effects on gene transcription. The cell-type specific enhancer of skeletal muscle was detected which has been reported to implicate SUA. Two promising genetic regions on chromosome 17 around rs2253277 and chromosome 14 around rs11621523 were found. Gene-based analysis found 167 genes nominally associated with SUA level (P < 0.05), including PTGR2, ENTPD5, well-known SLC2A9, etc. Enrichment analysis identified one pathway of transmembrane transport of small molecules and 20 GO gene sets involving in ion transport, transmembrane transporter activity, hydrolase activity acting on acid anhydrides, etc. In conclusion, SUA shows moderate heritability in women and low heritability in men in the Chinese population and genetic variations are significantly involved in functional genes and regulatory domains that mediate SUA level. Our findings provide clues to further elucidate molecular physiology of SUA homeostasis and identify new diagnostic biomarkers and therapeutic targets for hyperuricemia and gout.

Objectives: The heritability of age-related hearing loss has been studied mostly in developed countries. The authors aimed to estimate the heritability of better ear hearing level (BEHL), defined as hearing level of the better ear at a given frequency, and pure-tone averages at the middle (0.5, 1.0, and 2.0 kHz) and high (4.0, 8.0, and 12.5 kHz) frequencies among middle-aged and elderly Chinese twins, and to explore their genetic correlations. Design: This population-based twin study included 226 monozygotic and 132 dizygotic twin-pairs and 1 triplet (age range, 33 to 80 years; mean age, 51.55 years). Pure-tone air-conducted hearing thresholds in each ear were measured at the frequencies of 0.5, 1.0, 2.0, 4.0, 8.0, and 12.5 kHz with a diagnostic audiometer. Univariate and multivariate twin models were fitted to evaluate heritability and genetic correlations. Results: Our data showed a reverse J-shaped pattern of BEHLs at six frequencies by age and sex. Univariate analysis showed that the heritability of BEHLs at the frequencies between 2.0 and 12.5 kHz ranged from 47.08 to 54.20%, but the heritability at the frequencies of 0.5 and 1.0 kHz was 1.65% and 18.68%, respectively. The heritability of pure-tone average at the middle and high frequencies was 34.77% and 43.26%, respectively. Multivariate analysis showed significant genetic correlations among BEHLs at all six frequencies, with the correlation coefficients ranging from 0.48 to 0.83 at middle frequencies, and from 0.46 to 0.75 at high frequencies. Conclusions: This population-based twin study suggests that genetic factors are associated with age-related hearing loss at middle and high frequencies among middle-aged and elderly Chinese.

Background. Age‐related hearing impairment (ARHI) is considered an unpreventable disorder. We aimed to detect specific genetic variants that are potentially related to ARHI via genome‐wide association study (GWAS). Methods. A sample of 131 dizygotic twins was genotyped for single‐nucleotide polymorphism‐ (SNP‐) based GWAS. Gene‐based test was performed using VEGAS2. Pathway enrichment analysis was conducted by PASCAL. Results. The twins are with a median age of 49 years, of which 128 were females and 134 were males. rs6633657 was the only SNP that reached the genome‐wide significance level for better ear hearing level (BEHL) at 2.0 kHz (P = 1.19 × 10⁻⁸). Totally, 9, 10, 42, 7, 17, and 5 SNPs were suggestive evidence level for (P < 1 × 10⁻⁵) BEHLs at 0.5, 1.0, 2.0, 4.0, and 8.0 kHz and pure tone average (PTA), respectively. Several promising genetic regions in chromosomes (near the C20orf196, AQPEP, UBQLN3, OR51B5, OR51I2, OR52D1, GLTP, GIT2, and PARK2) nominally associated with ARHI were identified. Gene‐based analysis revealed 165, 173, 77, 178, 170, and 145 genes nominally associated with BEHLs at 0.5, 1.0, 2.0, 4.0, and 8.0 kHz and PTA, respectively (P < 0.05). For BEHLs at 0.5, 1.0, and 2.0 kHz, the main enriched pathways were phosphatidylinositol signaling system, regulation of ornithine decarboxylase, eukaryotic translation initiation factor (EIF) pathway, amine compound solute carrier (SLC) transporters, synthesis of phosphoinositides (PIPS) at the plasma membrane, and phosphatidylinositols (PI) metabolism. Conclusions. The genetic variations reported herein are significantly involved in functional genes and regulatory domains that mediate ARHI pathogenesis. These findings provide clues for the further unraveling of the molecular physiology of hearing functions and identifying novel diagnostic biomarkers and therapeutic targets of ARHI.