Meta-analysis

Association between adiponectin gene T45G polymorphism and nonalcoholic fatty liver disease risk: a meta-analysis

W. Zhang, Zhu, L. Q., Huo, X. L., Qin, J., Yuan, G. Y., Zhang, W., Zhu, L. Q., Huo, X. L., Qin, J., Yuan, G. Y., Zhang, W., Zhu, L. Q., Huo, X. L., Qin, J., and Yuan, G. Y., Association between adiponectin gene T45G polymorphism and nonalcoholic fatty liver disease risk: a meta-analysis, vol. 15, p. -, 2016.

Numerous epidemiological investigations have evaluated the association between adiponectin gene T45G polymorphism and risk of nonalcoholic fatty liver disease (NAFLD). However, the results of these studies have proven to be inconsistent. Therefore, we conducted a meta-analysis to obtain a more accurate estimation of this association. Published articles were retrieved from PubMed and Web of Science databases and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using fixed- or random-effect models.

APOA5 -1131T/C polymorphism and coronary artery disease susceptibility in Chinese population: an updated meta-analysis

J. Zhang, Wan, D. G., Song, H. L., and Zhang, W. G., APOA5 -1131T/C polymorphism and coronary artery disease susceptibility in Chinese population: an updated meta-analysis, vol. 14. pp. 12330-12339, 2015.

Although many studies have investigated the association of the APOA5 -1131T/C polymorphism with coronary artery disease (CAD), definite conclusions have not been drawn. To understand the effects of the APOA5 -1131T/C polymorphism on the risk of developing CAD, we performed an updated meta-analysis in the Chinese population. Relevant studies published till April 2015 were identified from databases such as PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure, and Chinese Biology Medicine.

CCDC26 rs4295627 polymorphism (8q24.21) and glioma risk: a meta-analysis

H. W. Lu, Huang, M., Wang, J. H., Sun, X. L., and Ke, Y. Q., CCDC26 rs4295627 polymorphism (8q24.21) and glioma risk: a meta-analysis, vol. 14, pp. 12074-12084, 2015.

The association between the CCDC26 rs4295627 single nucleotide polymorphism (SNP) and the glioma risk has been studied previously, but these studies have yielded conflicting results. The aim of the present study is to analyze this association more vigorously, by means of a meta-analysis. A comprehensive literature search was performed in databases PubMed and EMBASE. Six articles including 12 case-control studies in English with 11,368 controls and 5891 cases were eligible for the meta-analysis.

Association between the ERCC2 rs13181 polymorphism and the risk of glioma: a meta-analysis

T. L. Jia, Wu, H. J., Wang, H. B., Ma, W. B., and Xing, B., Association between the ERCC2 rs13181 polymorphism and the risk of glioma: a meta-analysis, vol. 14, pp. 12577-12584, 2015.

Several studies have focused on the association between the ERCC2 rs13181 polymorphism and glioma risk, but the results were inconclusive. We aimed to conduct a meta-analysis to investigate the role of ERCC2 rs13181 on the risk of glioma. We searched and collated the relevant studies in both Chinese and English through the PubMed, Web of Science, Cochrane Library, and EMBASE databases published through June 1, 2014. A total of 11 studies for ERCC2 rs13181 were selected; these included 3456 glioma cases and 4957 controls.

Association of the IL6 polymorphism rs1800796 with cancer risk: a meta-analysis

Y. Du, Gao, L., Zhang, K., and Wang, J., Association of the IL6 polymorphism rs1800796 with cancer risk: a meta-analysis, vol. 14, pp. 13236-13246, 2015.

The human IL6 [interleukin 6 (interferon, beta 2)] gene encodes IL-6, a cytokine which not only plays regulatory roles in inflammation, but may be also involved in the progression of cancer. Rs1800796 is a single nucleotide polymorphism (SNP) in the promoter region of IL6, and is associated with IL-6 production. A number of studies have been carried out to determine whether this SNP is associated with cancer risk. However, the results are inconsistent due to small sample sizes of individual studies and limited statistical power.

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