scholarly journals Associations between potentially functional CORIN SNPs and serum corin levels in the Chinese Han population

BMC Genetics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Huan Zhang ◽  
Xingbo Mo ◽  
Qiyu Qian ◽  
Zhengyuan Zhou ◽  
Zhengbao Zhu ◽  
...  

Abstract Background Corin is an important convertase involved in the natriuretic peptide system and may indirectly regulate blood pressure. Genetic factors relate to corin remain unclear. The purpose of the current study was to comprehensively examine the associations among CORIN SNPs, methylations, serum corin levels and hypertension. Results We genotyped 9 tag-SNPs in the CORIN gene and measured serum corin levels in 731 new-onset hypertensive cases and 731 age- and sex-matched controls. DNA methylations were tested in 43 individuals. Mendelian randomization was used to investigate the causal associations. Under additive models, we observed associations of rs2289433 (p.Cys13Tyr), rs6823184, rs10517195, rs2271037 and rs12509275 with serum corin levels after adjustment for covariates (P = 0.0399, 0.0238, 0.0016, 0.0148 and 0.0038, respectively). The tag-SNP rs6823184 and SNPs that are in strong linkage disequilibrium with it, i.e., rs10049713, rs6823698 and rs1866689, were associated with CORIN gene expression (P = 2.38 × 10− 24, 5.94 × 10− 27, 6.31 × 10− 27 and 6.30 × 10− 27, respectively). Neither SNPs nor corin levels was found to be associated with hypertension. SNP rs6823184, which is located in a DNase hypersensitivity cluster, a CpG island and transcription factor binding sites, was significantly associated with cg02955940 methylation levels (P = 1.54 × 10− 7). A putative causal association between cg02955940 methylation and corin levels was detected (P = 0.0011). Conclusion This study identified potentially functional CORIN SNPs that were associated with serum corin level in the Chinese Han population. The effect of CORIN SNPs on corin level may be mediated by DNA methylation.

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jiaqi Cui ◽  
Rui Tong ◽  
Jing Xu ◽  
Yanni Tian ◽  
Juan Pan ◽  
...  

Abstract Background Evidence from genetic epidemiology indicates that type 2 diabetes (T2D) has a strong genetic basis. Activated STAT4 has an inflammatory effect, and STAT4 is an important mediator of inflammation in diabetes. Our study aimed to study the association between STAT4 single nucleotide polymorphisms (SNPs) and T2D susceptibility in Chinese Han population. Methods We conducted a 'case–control' study among 500 T2D patients and 501 healthy individuals. 5 candidate STAT4 SNPs were successfully genotyped. The association between SNPs and T2D susceptibility under different genetic models was evaluated by logistic regression analysis. ‘SNP-SNP’ interaction was analyzed and completed by multi-factor dimensionality reduction (MDR). Finally, we evaluated the differences of clinical characteristics under different genotypes by one-factor analysis of variance. Results The overall results showed that STAT4 rs3821236 was associated with increasing T2D risk under allele (OR 1.23, p = 0.020), homozygous (OR 1.51, p = 0.025), dominant (OR 1.36, p = 0.029), and additive models (OR 1.23, p = 0.020). The results of stratified analysis showed that rs3821236, rs11893432, and rs11889341 were risk factors for T2D among participants ≤ 60 years old. Only rs11893432 was associated with increased T2D risk among female participants. There was also a potential association between rs3821236 and T2D with nephropathy risk. STAT4 rs11893432, rs7574865 and rs897200 were significantly associated with lysophosphatidic acid, cystatin C and thyroxine t4, respectively. Conclusion The genetic polymorphisms of STAT4 is potentially associated with T2D susceptibility of Chinese population. In particular, rs3821236 is significantly associated with T2D risk both in the overall and several subgroup analyses. Our study may provide new ideas for T2D individualized diagnosis/protection.


2012 ◽  
Vol 34 (7) ◽  
pp. 474-481 ◽  
Author(s):  
Ping Gu ◽  
Weimin Jiang ◽  
Maowei Cheng ◽  
Bin Lu ◽  
Jiaqing Shao ◽  
...  

2020 ◽  
Vol 70 (7) ◽  
pp. 1130-1139
Author(s):  
Guolong Tu ◽  
Wenliang Zhan ◽  
Yao Sun ◽  
Jiamin Wu ◽  
Zichao Xiong ◽  
...  

2014 ◽  
Vol 34 (10) ◽  
pp. 1729-1736 ◽  
Author(s):  
Xinglin Yang ◽  
Ming Li ◽  
Liya Wang ◽  
Zhongdan Hu ◽  
Yuanchao Zhang ◽  
...  

Author(s):  
Yinan Yao ◽  
Yan Shen ◽  
Haifeng Shao ◽  
Yuchang Liu ◽  
Yan Ji ◽  
...  

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