ObjectivePrecise genetic analyses were conducted with ring finger protein 213 (RNF213) in relation to a particular clinical phenotype in Chinese patients with moyamoya disease (MMD) to determine whether heterozygosity is responsible for the early-onset and severe form of this disease.MethodsA case–control study for RNF213 p.R4810K involving 1,385 Chinese patients with MMD and 2,903 normal control participants was performed. Correlation analyses between genotype and phenotype or different clinical features were also statistically explored.ResultsAn obvious trend was observed: the carrying rate of RNF213 p.R4810K gradually decreased when moving from coastal cities in northeast, north, and east China to southern cities or inland areas. Higher frequencies of p.R4810K were observed in patients with MMD compared with control participants (odds ratio, 48.1; 95% confidence interval, 29.1–79.6; p = 1.6 × 10−141). In addition, the onset age of all patients with the GA and AA genotypes were lower than with the GG genotype, and the median onset age was 40.0, 36.0, and 11.5 years with GG, GA, and AA, respectively, thereby confirming that those with GA or AA could acquire MMD during early life stages. Patients with MMD with the GA genotype were more susceptible to posterior cerebral artery (PCA) involvement compared to those with the GG genotype (38.4% vs 23.3%, p = 8.3 × 10−7).ConclusionsStrong evidence suggests that the carrying rate of RNF213 p.R4810K is closely related MMD risk in China and has given rise to an earlier onset age and more severe PCA involvement.

Diabetes has been a disease of public health concern for a number of decades. It was in the 1930s when scientists made an interesting discovery that the disease is actually divided into two types as some patients were insensitive to insulin treatment then. Type 2 Diabetes which happens to be the non-insulin dependent one is the most common form of the disease and is caused by the interaction between genetic and non-genetic factors. Despite conflicting results, numerous studies have identified genetic and non-genetic factors associated with this common type of diabetes. This review has summarized literature on some genes and non-genetic factors which have been identified to be associated with Type 2 diabetes. It has sourced literature from PubMed, Web of Science and Medline without any limitation to regions, publication types, or languages. The paper has started with the introduction, the play of non-genetic factors, the impact of genes in general, and ended with the interaction between some genes and environmental factors.

Background and Purpose— A growing body of evidence indicates genetic components play critical roles in moyamoya disease (MMD). Firm conclusions from studies of this disease have been stymied by small sample sizes and a lack of replicative results. This meta-analysis was conducted to determine whether these genetic polymorphisms are associated with MMD. Methods— PubMed, Google Scholar, Embase, Wanfang, Web of Science, and China National Knowledge Infrastructure databases were used to identify potentially relevant studies published until January 2020. The Review Manager 5.2 and Stata 15.0 software programs were used to perform the statistical analysis. Heterogeneity was assessed using the Cochran Q test and quantified using the I 2 test. Results— Four thousand seven hundred eleven MMD cases and 8704 controls in 24 studies were included, evaluating 7 polymorphisms in 6 genes. The fixed-effect odds ratios (95% CI) in allelic model of MMP-2 rs243865 were 0.60 (0.41–0.88) ( P =0.008). In the country-based subgroup analysis, the fixed-effect odds ratios (95% CI) of RNF213 rs112735431 in allelic model were China, 39.74 (26.63–59.31), Japan, 74.65 (42.79–130.24) and Korea, 50.04 (28.83–86.88; all P <0.00001). In the sensitivity analysis, the fixed-effect odds ratios (95% CI) of allelic and dominant models were the RNF213 rs148731719 variant, 2.17 (1.36–3.48; P =0.001), 2.20 (1.35–3.61; P =0.002), the TIMP-2 rs8179090 variant, 0.33 (0.25–0.43; P <0.00001), 0.88 (0.65–1.21; P =0.440) and the MMP-3 rs3025058 variant, 0.61 (0.47–0.79; P =0.0002), 0.55 (0.41–0.75; P =0.0001), respectively. Conclusions— RNF213 rs112735431 and rs148731719 were positively, and TIMP-2 rs8179090, MMP-2 rs243865, and MMP-3 rs3025058 were inversely associated with MMD using multiple pathophysiologic pathways. Studies in larger population should be conducted to clarify whether and how these variants are associated with MMD.

Background Nonalcoholic fatty liver disease (NAFLD) is a significant contributor to global hepatic disorders. ADIPOQ gene single‐nucleotide polymorphisms have been associated with NAFLD susceptibility, but with inconsistent results across the studies. This study aimed to investigate the association between ADIPOQ polymorphisms (+276G>T, rs1501299 and −11377C>G, rs266729) and the risk of NAFLD. Methods PubMed, Embase, Wanfang, Web of Science, and China National Knowledge Infrastructure databases were used to identify the relevant published literature. Statistical analyses were calculated with STATA 11.0 software and RevMan 5.2. Summary odds ratios (OR) and 95% confidence intervals (CIs) were generated to assess the strength of the associations. Results Eleven relevant articles with a total of 3,644 participants (1,847 cases/1,797 controls) were included. Our meta‐analysis results revealed that ADIPOQ gene +276G>T polymorphism was not associated with NAFLD under various genetic models (allele model: OR = 0.99, 95% CI [0.69, 1.41]; dominant model: OR = 1.06, 95% CI [0.71, 1.58]; recessive model: OR = 0.83, 95% CI [0.42, 1.65]; homozygous model: OR = 0.86, 95% CI [0.38, 1.95]; heterozygous model: OR = 1.10, 95% CI [0.80, 1.53]; respectively). Moreover, no statistical significant association was found between +276G>T and NAFLD risk in the subgroups. ADIPOQ gene −11377C>G polymorphism significantly increased the risk of NAFLD (allele model: OR = 1.49, 95% CI [1.28, 1.75]; dominant model: OR = 1.64, 95% CI [1.35, 1.99]; recessive model: OR = 1.77, 95% CI [1.16, 2.70]; homozygous model: OR = 2.13, 95% CI [1.38, 3.28]; heterozygous model: OR = 1.58, 95% CI [1.29, 1.93]; respectively). Conclusion ADIPOQ gene −11377C>G may be a risk factor for NAFLD, while there was no association between ADIPOQ gene +276G>T polymorphism and the risk of NAFLD. Further studies are needed to detect the relationship between these ADIPOQ polymorphisms and NAFLD.

Methylenetetrahydrofolate reductase gene (MTHFR), transcobalaminII (TCN2) and ring finger protein 213 (RNF213) are related to homocysteine (Hcy) level and are of great significance for hypertension. We aimed to evaluate the associations of MTHFR (rs1801133, rs1801131, rs9651118), TCN2 (rs117353193) and RNF213 (rs9916351) with hypertension and blood pressure (BP). A total of 953 patients with hypertension and 1103 controls were enrolled. Genotyping was performed by Taqman. Logistic regression analysis indicated that A allele of TCN2 rs117353193 under the dominant model had a significantly protective effect (P=0.045) after adjustment, which showed that AA+GA genotype has a lower risk than GG. Additionally, the average diastolic BP (DBP) (P=0.044) and mean arterial pressure (MAP) (P=0.035) levels were significantly different between genotypes of RNF213 rs9916351. Further pairwise comparison showed that the average systolic BP (SBP) level of the TT genotype carriers were significantly higher than in CC (P=0.024), and the average DBP and MAP levels of the TT genotype carriers were higher than in CT (P=0.044, P=0.012, respectively) and CC (P=0.048, P=0.010, respectively). In the recessive model, the average SBP (P=0.043), DBP (P=0.018) and MAP (P=0.017) levels with the TT genotype carriers were significantly higher than in CT+CC. Multiple linear regression analysis suggested that RNF213 rs9916351 in the recessive model had significant effects on SBP (P=0.025), DBP (P=0.017) and MAP (P=0.010) as a risk factor. However, no associations were observed between MTHFR and hypertension. TCN2 rs117353193 might serve as a protective factor in hypertension, and RNF213 rs9916351 might be a risk factor that is linked to increase BP level in Northeast Chinese population.