FTO, GCKR, CDKAL1 and CDKN2A/B gene polymorphisms and the risk of gestational diabetes mellitus: a meta-analysis
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Studies had examined the associations between genetic polymorphisms and the risk of gestational diabetes mellitus (GDM). However, conclusions of these studies were controversial due to the smaller sample size and limited statistical power. We carried out a meta-analysis with the aim of providing a more comprehensive summary of the currently available research to evaluate the relationship between FTO, GCKR, CDKAL1 and CDKN2A/B gene polymorphisms and GDM risk.
Literature search was carried out in the PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure and Wangfang databases up to November 2017. Data were extracted by two independent reviewers and statistical analyses were performed with STATA software. Pooled odds ratios and 95% confidence intervals were calculated by Z test to assess the association between genetic polymorphisms and GDM risk. Stratified analysis was performed based on ethnicity. Heterogeneity and publication bias between studies were evaluated by Cochran’s Q test and Egger regression test, respectively.
14 eligible studies were included. CDKAL1 rs7754840 and rs7756992 showed significant correlation with GDM risk under the allele, recessive, dominant, homozygote and heterozygote models. GCKR rs780094 and CDKN2A/B rs10811661 also showed the same association under the allele, recessive and heterozygote models. No associations between FTO rs9939609 and rs8050136, GCKR rs1260326 and GDM risk were found.
Our meta-analysis showed that two SNPs in particular(rs7754840 and rs7756992 in CDKAL1) were very strongly associated with GDM risk. GCKR rs780094 and CDKN2A/B rs10811661 polymorphisms were moderately associated with GDM risk.
KeywordsGestational diabetes mellitus FTO GCKR CDKAL1 CDKN2A/B Gene polymorphism
This work was supported by Changzhou science and technology support project (Social Development CE20175021). We thank Dr. Xuejiao Chen for the help of data collection and Dr. Rui Yang for the help of data analysis. We are grateful to the researchers who provided their data for these analyses and for subjects who participated in the original studies.
Fang Guo: Protocol development, Data Collection, Manuscript writing. Wei Long: Data Collection, Data analysis. Wenbai Zhou: Data Collection. Bin Zhang: Data Collection. Jianbing Liu: Data analysis. Bin Yu: Review and revise the manuscript.
Compliance with ethical standards
Conflict of interest
The authors declare that we have no conflict of interest.
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