scholarly journals TCF7L2 gene polymorphisms and type 2 diabetes risk: a comprehensive and updated meta-analysis involving 121 174 subjects

Mutagenesis ◽  
2012 ◽  
Vol 28 (1) ◽  
pp. 25-37 ◽  
Author(s):  
Sihua Peng ◽  
Yimin Zhu ◽  
Bingjian Lü ◽  
Fangying Xu ◽  
Xiaobo Li ◽  
...  
2020 ◽  
Vol 48 (8) ◽  
pp. 030006052093131
Author(s):  
Liqing Cheng ◽  
Min Zhou ◽  
Dongmei Zhang ◽  
Bing Chen

Objective Circulating miR-146a is aberrantly expressed in patients with type 2 diabetes (T2D), probably resulting from gene polymorphisms. However, the role of polymorphism rs2910164 in T2D pathogenesis remains controversial. Thus, we designed a meta-analysis to investigate the association between rs2910164 and T2D. Methods PubMed and Embase were searched for eligible papers in English published through September 2, 2019. Random or fixed effect models were used to determine risk estimates according to heterogeneities. Results Four studies, involving 2,069 patients and 1,950 controls, were included. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to pool the effect size. The pooled ORs and 95% CIs were 1.501 (0.887–2.541), 1.102 (0.931–1.304), 1.276 (0.900–1.811), 1.204 (0.878–1.652), 1.238 (0.880–1.740), and 1.350 (0.904–2.016) under the homozygote, heterozygote (CG vs. GG and CC vs. CG), dominant, allele, and recessive models, respectively. Heterogeneity was detected in most genetic models, with subgroup analyses performed by ethnicity, genotyping method, and disease duration. The co-dominant model was determined to be the most appropriate genetic model. Conclusions Our findings suggested that polymorphism rs2910164 is not correlated with T2D susceptibility. However, the results should be interpreted with caution because of confounding factors.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiao-xuan Yu ◽  
Min-qi Liao ◽  
Yu-fei Zeng ◽  
Xu-ping Gao ◽  
Yan-hua Liu ◽  
...  

Background. Previous studies have examined the role of the KQT-like subfamily Q member1 (KCNQ1) gene polymorphisms on the risk of type 2 diabetes mellitus (T2DM), but the findings are inconclusive. Objective. To examine the association between the KCNQ1 gene polymorphisms and the risk of T2DM using an updated meta-analysis with an almost tripled number of studies. Methods. Five electronic databases, such as PubMed and Embase, were searched thoroughly for relevant studies on the associations between seven most studied KCNQ1 gene polymorphisms, including rs2237892, rs2237897, rs2237895, rs2283228, rs231362, rs151290, and rs2074196, and T2DM risk up to September 14, 2019. The summary odds ratios (ORs) with their 95% confidence intervals (CIs) were applied to assess the strength of associations in the random-effects models. We used the trial sequential analysis (TSA) to measure the robustness of the evidence. Results. 49 publications including 55 case-control studies (68,378 cases and 66,673 controls) were finally enrolled. In overall analyses, generally, increased T2DM risk was detected for rs2237892, rs2237895, rs2283228, rs151290, and rs2074196, but not for rs231362 under all genetic models. The ORs and 95% CIs for allelic comparison were 1.23 (1.14-1.33) for rs2237892, 1.21 (1.16-1.27) for rs2237895, 1.27 (1.11-1.46) for rs2237897, 1.25 (1.09-1.42) for rs2283228, 1.14 (1.03-1.27) for rs151290, 1.31 (1.23-1.39) for rs2074196, and 1.16 (0.83, 1.61) for rs231362. Stratified analyses showed that associations for rs2237892, rs2237895, rs2283228, and rs151290 were more evident among Asians than Caucasians. TSA demonstrated that the evidence was sufficient for all polymorphisms in this study. The genotypes of the three SNPs (rs2237892, rs2283228, and rs231362) were significantly correlated with altered KCNQ1 gene expression. Conclusion. This meta-analysis suggested that KCNQ1 gene polymorphisms (rs2237892, rs2283228, rs2237895, rs151290, and rs2074196) might be the susceptible factors for T2DM, especially among Asian population.


2012 ◽  
Vol 50 (5) ◽  
pp. 789-799 ◽  
Author(s):  
Cinzia Ciccacci ◽  
Davide Di Fusco ◽  
Laura Cacciotti ◽  
Roberto Morganti ◽  
Cinzia D’Amato ◽  
...  

2015 ◽  
pp. 5835
Author(s):  
Behnam Kamalidehghan ◽  
Mojgan Allahdini ◽  
Leila Akbari ◽  
Parisa Azadfar ◽  
Ali Rahmani ◽  
...  

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