Gene polymorphism associated with TGF ‐β1 and susceptibility to preeclampsia: A meta‐analysis and trial sequential analysis

Author(s):  
Jing Liu ◽  
Guang Song ◽  
Ge Zhao ◽  
Tao Meng
2021 ◽  
Vol 9 ◽  
Author(s):  
Daojing Ying ◽  
Mengjie Jiang ◽  
Liping Rong ◽  
Hongjie Zhuang ◽  
Lizhi Chen ◽  
...  

Background: Studies have identified that MIF -173 G>C gene polymorphism is associated with idiopathic nephrotic syndrome (INS) susceptibility and steroid resistance, but the results remain inconclusive.Methods: We searched PubMed, Embase, and Web of Science for relevant studies published before 31 March 2021. Pooled data were reported as odds ratio (OR) with 95% confidence interval (CI). Noteworthiness of significant OR was estimated by the false positive report probability (FPRP) test. Trial sequential analysis (TSA) was used to control type I and type II errors.Results: We selected seven case-control studies that included 1,026 INS children (362 were steroid-resistant NS and 564 were steroid-sensitive NS) and 870 controls. The results showed that MIF -173 G>C polymorphism was significantly associated with INS susceptibility in allelic, heterozygous and dominant genetic models (C vs. G: OR = 1.325, 95% CI: 1.011-1.738; GC vs. GG: OR = 1.540, 95% CI: 1.249-1.899; CC + GC vs. GG: OR = 1.507, 95% CI: 1.231-1.845), and FPRP test and TSA indicated that the associations were true in heterozygous and dominant models. The pooled results also revealed that MIF -173 G>C polymorphism was significantly associated with steroid resistance in allelic, homozygous and recessive models (C vs. G: OR = 1.707, 95% CI: 1.013-2.876; CC vs. GG: OR = 4.789, 95% CI: 2.109-10.877; CC vs. GC + GG: OR = 4.188, 95% CI: 1.831-9.578), but FPRP test indicated that all these associations were not noteworthy. Furthermore, TSA revealed that the non-significant associations between MIF -173 G>C polymorphism and steroid resistance in heterozygous and dominant models were potential false negative.Conclusions: This meta-analysis could draw a firm conclusion that MIF -173 G>C polymorphism was significantly associated with increased INS risk in heterozygous and dominant genetic models. MIF -173 G>C polymorphism was not likely to affect steroid responsiveness, but more studies were needed to confirm.


Genes ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 705
Author(s):  
Hsiang-Cheng Chen ◽  
Wei-Teing Chen ◽  
Tzu-Ling Sung ◽  
Dung-Jang Tsai ◽  
Chin Lin ◽  
...  

Background: So far, numerous meta-analyses have been published regarding the correlation between peroxisome proliferator-activated receptor gamma (PPARG) proline 12 alanine (Pro12Ala) gene polymorphism and chronic kidney disease (CKD); however, the results appear to be contradictory. Hence, this study is formulated with the objective of using existing meta-analysis data together with our research population to study the correlation between PPARG Pro12Ala gene polymorphism and CKD and evaluate whether an accurate result can be obtained. Methods: First, literature related to CKD and PPARG Pro12Ala available on the PubMed and EMBASE databases up to December 2016 was gathered from 20 publications. Then, the gathered results were combined with our case-control study of 1693 enrolled subjects and a trial sequential analysis (TSA) was performed to verify existing evidence and determine whether a firm conclusion can be drawn. Results: The TSA results showed that the cumulative sample size for the Asian sample was 6078 and was sufficient to support a definite result. The results of this study confirmed that there is no obvious correlation between PPARG Pro12Ala and CKD for Asians (OR = 0.82 (95% CI = 0.66–1.02), I2 = 63.1%), but this was not confirmed for Caucasians. Furthermore, the case-control sample in our study was shown to be the key for reaching this conclusion. Conclusions: The meta-analysis results of this study suggest no significant correlation between PPARG Pro12Ala gene polymorphism and CKD for Asians after adding our samples, but not for Caucasian.


Oncotarget ◽  
2017 ◽  
Vol 9 (5) ◽  
pp. 6572-6585
Author(s):  
Raju K. Mandal ◽  
Sajad A. Dar ◽  
Arshad Jawed ◽  
Mohd Wahid ◽  
Mohtashim Lohani ◽  
...  

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