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      Meta-analysis of association between TCF7L2 polymorphism rs7903146 and type 2 diabetes mellitus

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          Abstract

          Background

          Large scale association studies have found a significant association between type 2 diabetes mellitus (T2DM) and transcription factor 7-like 2 (TCF7L2) polymorphism rs7903146. However, the quality of data varies greatly, as the studies report inconsistent results in different populations. Hence, we perform this meta-analysis to give a more convincing result.

          Methods

          The articles, published from January 1st, 2000 to April 1st, 2017, were identified by searching in PubMed and Google Scholar. A total of 56628 participants (34232 cases and 22396 controls) were included in the meta-analysis. A total of 28 studies were divided into 4 subgroups: Caucasian (10 studies), East Asian (5 studies), South Asian (5 studies) and Others (8 studies). All the data analyses were analyzed by the R package meta.

          Results

          The significant association was observed by using the dominant model (OR = 1.41, CI = 1.36 - 1.47, p < 0.0001), recessive model (OR = 1.58, CI = 1.48 - 1.69, p < 0.0001), additive model(CT vs CC) (OR = 1.34, CI = 1.28-1.39, p < 0.0001), additive model(TT vs CC) (OR = 1.81, CI = 1.69-1.94, p < 0.0001)and allele model (OR = 1.35, CI = 1.31-1.39, p < 0.0001).

          Conclusion

          The meta-analysis suggested that rs7903146 was significantly associated with T2DM in Caucasian, East Asian, South Asian and other ethnicities.

          Electronic supplementary material

          The online version of this article (10.1186/s12881-018-0553-5) contains supplementary material, which is available to authorized users.

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          Most cited references49

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          The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes.

          D. Altshuler, J. Hirschhorn, M Klannemark … (2000)
          Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.
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            Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes.

            Valeriya Lyssenko, Roberto Lupi, Piero Marchetti … (2007)
            Genetic variants in the gene encoding for transcription factor-7-like 2 (TCF7L2) have been associated with type 2 diabetes (T2D) and impaired beta cell function, but the mechanisms have remained unknown. We therefore studied prospectively the ability of common variants in TCF7L2 to predict future T2D and explored the mechanisms by which they would do this. Scandinavian subjects followed for up to 22 years were genotyped for 3 SNPs (rs7903146, rs12255372, and rs10885406) in TCF7L2, and a subset of them underwent extensive metabolic studies. Expression of TCF7L2 was related to genotype and metabolic parameters in human islets. The CT/TT genotypes of SNP rs7903146 strongly predicted future T2D in 2 independent cohorts (Swedish and Finnish). The risk T allele was associated with impaired insulin secretion, incretin effects, and enhanced rate of hepatic glucose production. TCF7L2 expression in human islets was increased 5-fold in T2D, particularly in carriers of the TT genotype. Overexpression of TCF7L2 in human islets reduced glucose-stimulated insulin secretion. In conclusion, the increased risk of T2D conferred by variants in TCF7L2 involves the enteroinsular axis, enhanced expression of the gene in islets, and impaired insulin secretion.
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              Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes.

              Timothy Frayling, Graham A. Hitman, Mark McCarthy … (2003)
              The genes ABCC8 and KCNJ11, which encode the subunits sulfonylurea receptor 1 (SUR1) and inwardly rectifying potassium channel (Kir6.2) of the beta-cell ATP-sensitive potassium (K(ATP)) channel, control insulin secretion. Common polymorphisms in these genes (ABCC8 exon 16-3t/c, exon 18 T/C, KCNJ11 E23K) have been variably associated with type 2 diabetes, but no large ( approximately 2,000 subjects) case-control studies have been performed. We evaluated the role of these three variants by studying 2,486 U.K. subjects: 854 with type 2 diabetes, 1,182 population control subjects, and 150 parent-offspring type 2 diabetic trios. The E23K allele was associated with diabetes in the case-control study (odds ratio [OR] 1.18 [95% CI 1.04-1.34], P = 0.01) but did not show familial association with diabetes. Neither the exon 16 nor the exon 18 ABCC8 variants were associated with diabetes (1.04 [0.91-1.18], P = 0.57; 0.93 [0.71-1.23], P = 0.63, respectively). Meta-analysis of all case-control data showed that the E23K allele was associated with type 2 diabetes (K allele OR 1.23 [1.12-1.36], P = 0.000015; KK genotype 1.65 [1.34-2.02], P = 0.000002); but the ABCC8 variants were not associated. Our results confirm that E23K increases risk of type 2 diabetes and show that large-scale association studies are important for the identification of diabetes susceptibility alleles.
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                Author and article information

                Contributors
                Weiyue Ding: williamding@hrbeu.edu.cn
                Li Xu: xuli@hrbeu.edu.cn
                Shuilin Jin: jinsl@hit.edu.cn
                Journal
                Journal ID (nlm-ta): BMC Med Genet
                Journal ID (iso-abbrev): BMC Med. Genet
                Title: BMC Medical Genetics
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1471-2350
                Publication date (Electronic): 7 March 2018
                Publication date PMC-release: 7 March 2018
                Publication date Collection: 2018
                Volume: 19
                Electronic Location Identifier: 38
                Affiliations
                [1 ]ISNI 0000 0001 0476 2430, GRID grid.33764.35, College of Computer Science and Technology, Harbin Engineering University, ; No.145 Nantong Street, Nangang District, Harbin, 150001 China
                [2 ]GRID grid.268415.c, School of Information Engineering, Yangzhou University, ; No.196, Huayang West Road, Yangzhou, 225127 China
                [3 ]ISNI 0000 0001 0193 3564, GRID grid.19373.3f, School of Life Science and Technology, Harbin Institute of Technology, ; No.92 Xidazhi Street, Nangang District, Harbin, 150001 China
                [4 ]ISNI 0000 0004 1760 5735, GRID grid.64924.3d, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, ; No.2699, Qianjin Avenue, Qianweinan District, Changchun, 130012 China
                [5 ]ISNI 0000 0001 0193 3564, GRID grid.19373.3f, Department of Mathematics, , Harbin Institute of Technology, ; No.92, Xidazhi Street, Nangang District, Harbin, 150001 China
                Article
                Publisher ID: 553
                DOI: 10.1186/s12881-018-0553-5
                PMC ID: 5842570
                PubMed ID: 29514658
                SO-VID: 0e6b35f4-366d-4144-95c0-528950afbd65
                Copyright © © The Author(s) 2018
                License:

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 1 May 2017
                Date accepted : 23 February 2018
                Funding
                Funded by: NSFC
                Award ID: 11301110
                Categories
                Subject: Research Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2018

                ScienceOpen disciplines: Genetics
                Keywords: t2dm,polymorphism,rs7903146,meta-analysis
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: t2dm, polymorphism, rs7903146, meta-analysis

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