Association between IGF2BP2 Polymorphisms and Type 2 Diabetes Mellitus: A Case–Control Study and Meta-Analysis
Abstract
:1. Introduction
2. Experimental Section
2.1. Study Participants
2.2. SNPs Genotyping
2.3. Data Collection
2.4. Statistical Analysis
2.5. Meta-Analysis
3. Results
3.1. Case-Control Study
3.2. Meta-Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Ginter, E.; Simko, V. Type 2 diabetes mellitus, pandemic in 21st century. Adv. Exp. Med. Biol. 2012, 771, 42–50. [Google Scholar] [PubMed]
- Xu, Y.; Wang, L.; He, J.; Bi, Y.; Li, M.; Wang, T.; Wang, L.; Jiang, Y.; Dai, M.; Lu, J.; et al. Prevalence and control of diabetes in Chinese adults. JAMA 2013, 310, 948–959. [Google Scholar] [CrossRef] [PubMed]
- Almgren, P.; Lehtovirta, M.; Isomaa, B.; Sarelin, L.; Taskinen, M.R.; Lyssenko, V.; Tuomi, T.; Groop, L. Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia Study. Diabetologia 2011, 54, 2811–2819. [Google Scholar] [CrossRef] [PubMed]
- Ding, D.; Chong, S.; Jalaludin, B.; Comino, E.; Bauman, A.E. Risk factors of incident type 2-diabetes mellitus over a 3-year follow-up: Results from a large Australian sample. Diabetes Res. Clin. Pract. 2015, 108, 306–315. [Google Scholar] [CrossRef] [PubMed]
- Imamura, M.; Shigemizu, D.; Tsunoda, T.; Iwata, M.; Maegawa, H.; Watada, H.; Hirose, H.; Tanaka, Y.; Tobe, K.; Kaku, K.; et al. Assessing the Clinical Utility of a Genetic Risk Score Constructed Using 49 Susceptibility Alleles for Type 2 Diabetes in a Japanese Population. J. Clin. Endocrinol. Metab. 2013, 98, E1667–E1673. [Google Scholar] [CrossRef] [PubMed]
- Saxena, R.; Voight, B.F.; Lyssenko, V.; Burtt, N.P.; de Bakker, P.I.; Chen, H.; Roix, J.J.; Kathiresan, S.; Hirschhorn, J.N.; Daly, M.J.; et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 2007, 316, 1331–1336. [Google Scholar] [PubMed]
- Scott, L.J.; Mohlke, K.L.; Bonnycastle, L.L.; Willer, C.J.; Li, Y.; Duren, W.L.; Erdos, M.R.; Stringham, H.M.; Chines, P.S.; Jackson, A.U.; et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 2007, 316, 1341–1345. [Google Scholar] [CrossRef] [PubMed]
- Zeggini, E.; Weedon, M.N.; Lindgren, C.M.; Frayling, T.M.; Elliott, K.S.; Lango, H.; Timpson, N.J.; Perry, J.R.; Rayner, N.W.; Freathy, R.M.; et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 2007, 316, 1336–1341. [Google Scholar] [CrossRef] [PubMed]
- Christiansen, J.; Kolte, A.M.; Hansen, T.; Nielsen, F.C. IGF2 mRNA-binding protein 2: Biological function and putative role in type 2 diabetes. J. Mol. Endocrinol. 2009, 43, 187–195. [Google Scholar] [CrossRef] [PubMed]
- Groenewoud, M.J.; Dekker, J.M.; Fritsche, A.; Reiling, E.; Nijpels, G.; Heine, R.J.; Maassen, J.A.; Machicao, F.; Schafer, S.A.; Haring, H.U.; et al. Variants of CDKAL1 and IGF2BP2 affect first-phase insulin secretion during hyperglycaemic clamps. Diabetologia 2008, 51, 1659–1663. [Google Scholar] [CrossRef] [PubMed]
- Duesing, K.; Fatemifar, G.; Charpentier, G.; Marre, M.; Tichet, J.; Hercberg, S.; Balkau, B.; Froguel, P.; Gibson, F. Evaluation of the Association of IGF2BP2 Variants with Type 2 Diabetes in French Caucasians. Diabetes 2008, 57, 1992–1996. [Google Scholar] [CrossRef] [PubMed]
- Cui, B.; Zhu, X.; Xu, M.; Guo, T.; Zhu, D.; Chen, G.; Li, X.; Xu, L.; Bi, Y.; Chen, Y.; et al. A genome-wide association study confirms previously reported loci for type 2 diabetes in Han Chinese. PLoS ONE 2011, 6, e22353. [Google Scholar] [CrossRef] [PubMed]
- Sladek, R.; Rocheleau, G.; Rung, J.; Dina, C.; Shen, L.; Serre, D.; Boutin, P.; Vincent, D.; Belisle, A.; Hadjadj, S.; et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 2007, 445, 881–885. [Google Scholar] [CrossRef] [PubMed]
- Cooke, J.N.; Hester, J.M.; Ng, M.C.Y.; Freedman, B.I.; Palmer, N.D.; Langefeld, C.D.; An, S.S.; Bowden, D.W. Genentic risk assessment of type 2 diabetes-associated polymorphisms in African Americans. Diabetes Care 2012, 35, 287–292. [Google Scholar] [CrossRef] [PubMed]
- Xu, M.; Bi, Y.; Xu, Y.; Yu, B.; Huang, Y.; Gu, L.; Wu, Y.; Zhu, X.; Li, M.; Wang, T.; et al. Combined effects of 19 common variations on type 2 diabetes in Chinese: Results from two community-based studies. PLoS ONE 2010, 5, e14022. [Google Scholar] [CrossRef] [PubMed]
- Gella, L.; Raman, R.; Pal, S.S.; Ganesan, S.; Sharma, T. Incidence, Progression, and Associated Risk Factors of Posterior Vitreous Detachment in Type 2 Diabetes Mellitus: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetic Study (SN-DREAMS II, Report No. 7). Semin. Ophthalmol. 2015. [Google Scholar] [CrossRef] [PubMed]
- Genuth, S.; Alberti, K.G.; Bennett, P.; Buse, J.; Defronzo, R.; Kahn, R.; Kitzmiller, J.; Knowler, W.C.; Lebovitz, H.; Lernmark, A.; et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003, 26, 3160–3167. [Google Scholar] [PubMed]
- Stroup, D.F.; Berlin, J.A.; Morton, S.C.; Olkin, I.; Williamson, G.D.; Rennie, D.; Moher, D.; Becker, B.J.; Sipe, T.A.; Thacker, S.B. Meta-analysis of observational studies in epidemiology: A proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000, 283, 2008–2012. [Google Scholar] [CrossRef] [PubMed]
- Higgins, J.P.; Thompson, S.G.; Deeks, J.J.; Altman, D.G. Measuring inconsistency in meta-analyses. BMJ 2003, 327, 557–560. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Egger, M.; Davey, S.G.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997, 315, 629–634. [Google Scholar] [CrossRef] [PubMed]
- Chang, Y.C.; Liu, P.H.; Yu, Y.H.; Kuo, S.S.; Chang, T.J.; Jiang, Y.D.; Nong, J.Y.; Hwang, J.J.; Chuang, L.M. Validation of type 2 diabetes risk variants identified by genome-wide association studies in Han Chinese population: A replication study and meta-analysis. PLoS ONE 2014, 9, e95045. [Google Scholar] [CrossRef] [PubMed]
- Chauhan, G.; Spurgeon, C.J.; Tabassum, R.; Bhaskar, S.; Kulkarni, S.R.; Mahajan, A.; Chavali, S.; Kumar, M.V.; Prakash, S.; Dwivedi, O.P.; et al. Impact of common variants of PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 on the risk of type 2 diabetes in 5164 Indians. Diabetes 2010, 59, 2068–2074. [Google Scholar] [CrossRef] [PubMed]
- Chen, G.; Xu, Y.; Lin, Y.; Lai, X.; Yao, J.; Huang, B.; Chen, Z.; Huang, H.; Fu, X.; Lin, L.; et al. Association study of genetic variants of 17 diabetes-related genes/loci and cardiovascular risk and diabetic nephropathy in the Chinese She population. J. Diabetes 2013, 5, 136–145. [Google Scholar] [CrossRef] [PubMed]
- Han, X.; Luo, Y.; Ren, Q.; Zhang, X.; Wang, F.; Sun, X.; Zhou, X.; Ji, L. Implication of genetic variants near SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, FTO, TCF2, KCNQ1, and WFS1 in type 2 diabetes in a Chinese population. BMC Med. Genet. 2010, 11, 81. [Google Scholar] [CrossRef] [PubMed]
- Horikoshi, M.; Hara, K.; Ito, C.; Shojima, N.; Nagai, R.; Ueki, K.; Froguel, P.; Kadowaki, T. Variations in the HHEX gene are associated with increased risk of type 2 diabetes in the Japanese population. Diabetologia 2007, 50, 2461–2466. [Google Scholar] [CrossRef] [PubMed]
- Horikawa, Y.; Miyake, K.; Yasuda, K.; Enya, M.; Hirota, Y.; Yamagata, K.; Hinokio, Y.; Oka, Y.; Iwasaki, N.; Iwamoto, Y.; et al. Replication of genome-wide association studies of type 2 diabetes susceptibility in Japan. J. Clin. Endocrinol. Metab. 2008, 93, 3136–3141. [Google Scholar] [CrossRef] [PubMed]
- Huang, Q.; Yin, J.Y.; Dai, X.P.; Pei, Q.; Dong, M.; Zhou, Z.G.; Huang, X.; Yu, M.; Zhou, H.H.; Liu, Z.Q. IGF2BP2 variations influence repaglinide response and risk of type 2 diabetes in Chinese population. Acta Pharmacol. Sin. 2010, 31, 709–717. [Google Scholar] [CrossRef] [PubMed]
- Kommoju, U.J.; Maruda, J.; Kadarkarai, S.; Irgam, K.; Kotla, J.P.; Velaga, L.; Mohan, R.B. No detectable association of IGF2BP2 and SLC30A8 genes with type 2 diabetes in the population of Hyderabad, India. Meta Gene 2013, 1, 15–23. [Google Scholar] [CrossRef] [PubMed]
- Kuo, J.Z.; Sheu, W.H.; Assimes, T.L.; Hung, Y.J.; Absher, D.; Chiu, Y.F.; Mak, J.; Wang, J.S.; Kwon, S.; Hsu, C.C.; et al. Trans-ethnic fine mapping identifies a novel independent locus at the 3′ end of CDKAL1 and novel variants of several susceptibility loci for type 2 diabetes in a Han Chinese population. Diabetologia 2013, 56, 2619–2628. [Google Scholar] [CrossRef] [PubMed]
- Lee, Y.H.; Kang, E.S.; Kim, S.H.; Han, S.J.; Kim, C.H.; Kim, H.J.; Ahn, C.W.; Cha, B.S.; Nam, M.; Nam, C.M.; et al. Association between polymorphisms in SLC30A8, HHEX, CDKN2A/B, IGF2BP2, FTO, WFS1, CDKAL1, KCNQ1 and type 2 diabetes in the Korean population. J. Hum. Genet. 2008, 53, 991–998. [Google Scholar] [CrossRef] [PubMed]
- Lin, Y.; Li, P.; Cai, L.; Zhang, B.; Tang, X.; Zhang, X.; Li, Y.; Xian, Y.; Yang, Y.; Wang, L.; et al. Association study of genetic variants in eight genes/loci with type 2 diabetes in a Han Chinese population. BMC Med. Genet. 2010, 11, 97. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Yu, L.; Zhang, D.; Chen, Z.; Zhou, D.Z.; Zhao, T.; Li, S.; Wang, T.; Hu, X.; Feng, G.Y.; et al. Positive association between variations in CDKAL1 and type 2 diabetes in Han Chinese individuals. Diabetologia 2008, 51, 2134–2137. [Google Scholar] [CrossRef] [PubMed]
- Miyake, K.; Yang, W.; Hara, K.; Yasuda, K.; Horikawa, Y.; Osawa, H.; Furuta, H.; Ng, M.C.; Hirota, Y.; Mori, H.; et al. Construction of a prediction model for type 2 diabetes mellitus in the Japanese population based on 11 genes with strong evidence of the association. J. Hum. Genet. 2009, 54, 236–241. [Google Scholar] [CrossRef] [PubMed]
- Ng, M.C.; Park, K.S.; Oh, B.; Tam, C.H.; Cho, Y.M.; Shin, H.D.; Lam, V.K.; Ma, R.C.; So, W.Y.; Cho, Y.S.; et al. Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6719 Asians. Diabetes 2008, 57, 2226–2233. [Google Scholar] [CrossRef] [PubMed]
- Omori, S.; Tanaka, Y.; Takahashi, A.; Hirose, H.; Kashiwagi, A.; Kaku, K.; Kawamori, R.; Nakamura, Y.; Maeda, S. Association of CDKAL1, IGF2BP2, CDKN2A/B, HHEX, SLC30A8, and KCNJ11 with susceptibility to type 2 diabetes in a Japanese population. Diabetes 2008, 57, 791–795. [Google Scholar] [CrossRef] [PubMed]
- Rees, S.D.; Hydrie, M.Z.; Shera, A.S.; Kumar, S.; O’Hare, J.P.; Barnett, A.H.; Basit, A.; Kelly, M.A. Replication of 13 genome-wide association (GWA)-validated risk variants for type 2 diabetes in Pakistani populations. Diabetologia 2011, 54, 1368–1374. [Google Scholar] [CrossRef] [PubMed]
- Sanghera, D.K.; Ortega, L.; Han, S.; Singh, J.; Ralhan, S.K.; Wander, G.S.; Mehra, N.K.; Mulvihill, J.J.; Ferrell, R.E.; Nath, S.K.; et al. Impact of nine common type 2 diabetes risk polymorphisms in Asian Indian Sikhs: PPARG2 (Pro12Ala), IGF2BP2, TCF7L2 and FTO variants confer a significant risk. BMC Med. Genet. 2008, 9, 59. [Google Scholar] [CrossRef] [PubMed]
- Shu, X.O.; Long, J.; Cai, Q.; Qi, L.; Xiang, Y.B.; Cho, Y.S.; Tai, E.S.; Li, X.; Lin, X.; Chow, W.H.; et al. Identification of new genetic risk variants for type 2 diabetes. PLoS Genet. 2010, 6, e1001127. [Google Scholar] [CrossRef] [PubMed]
- Song, M.; Zhao, F.; Ran, L.; Dolikun, M.; Wu, L.; Ge, S.; Dong, H.; Gao, Q.; Zhai, Y.; Zhang, L.; et al. The Uyghur population and genetic susceptibility to type 2 diabetes: Potential role for variants in CDKAL1, JAZF1, and IGF1 genes. OMICS 2015, 19, 230–237. [Google Scholar] [CrossRef] [PubMed]
- Tabara, Y.; Osawa, H.; Kawamoto, R.; Onuma, H.; Shimizu, I.; Miki, T.; Kohara, K.; Makino, H. Replication study of candidate genes associated with type 2 diabetes based on genome-wide screening. Diabetes 2009, 58, 493–498. [Google Scholar] [CrossRef] [PubMed]
- Takeuchi, F.; Ochiai, Y.; Serizawa, M.; Yanai, K.; Kuzuya, N.; Kajio, H.; Honjo, S.; Takeda, N.; Kaburagi, Y.; Yasuda, K.; et al. Search for type 2 diabetes susceptibility genes on chromosomes 1q, 3q and 12q. J. Hum. Genet. 2008, 53, 314–324. [Google Scholar] [CrossRef] [PubMed]
- Takeuchi, F.; Serizawa, M.; Yamamoto, K.; Fujisawa, T.; Nakashima, E.; Ohnaka, K.; Ikegami, H.; Sugiyama, T.; Katsuya, T.; Miyagishi, M.; et al. Confirmation of multiple risk Loci and genetic impacts by a genome-wide association study of type 2 diabetes in the Japanese population. Diabetes 2009, 58, 1690–1699. [Google Scholar] [CrossRef] [PubMed]
- Tan, J.T.; Ng, D.P.; Nurbaya, S.; Ye, S.; Lim, X.L.; Leong, H.; Seet, L.T.; Siew, W.F.; Kon, W.; Wong, T.Y.; et al. Polymorphisms identified through genome-wide association studies and their associations with type 2 diabetes in Chinese, Malays, and Asian-Indians in Singapore. J. Clin. Endocrinol. Metab. 2010, 95, 390–397. [Google Scholar] [CrossRef] [PubMed]
- Wen, J.; Ronn, T.; Olsson, A.; Yang, Z.; Lu, B.; Du, Y.; Groop, L.; Ling, C.; Hu, R. Investigation of type 2 diabetes risk alleles support CDKN2A/B, CDKAL1, and TCF7L2 as susceptibility genes in a Han Chinese cohort. PLoS ONE 2010, 5, e9153. [Google Scholar] [CrossRef] [PubMed]
- Wu, Y.; Li, H.; Loos, R.J.; Yu, Z.; Ye, X.; Chen, L.; Pan, A.; Hu, F.B.; Lin, X. Common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, and HHEX/IDE genes are associated with type 2 diabetes and impaired fasting glucose in a Chinese Han population. Diabetes 2008, 57, 2834–2842. [Google Scholar] [CrossRef] [PubMed]
- Zhang, S.M.; Xiao, J.Z.; Ren, Q.; Han, X.Y.; Tang, Y.; Yang, W.Y.; Ji, L.N. Replication of association study between type 2 diabetes mellitus and IGF2BP2 in Han Chinese population. Chin. Med. J. (Engl.) 2013, 126, 4013–4018. [Google Scholar] [PubMed]
- Jia, H.X.; Gao, B.; Fang, Y.J.; Huang, Q.; Ji, Q.H. Association study between insulin resistance and IGF2BP2gene polymorphism in the northwest people without diabetes. Chin. J. Clin. 2012, 623, 7528–7531. (In Chinese) [Google Scholar]
- Jiao, H.X.; Cai, C.Y.; Wei, F.J.; Li, W.D. Correlation analysis of type 2 diabetes related gene and genotype interaction research in Chinese patients. J. Tianjin Med. Univ. 2013, 1, 6–9. (In Chinese) [Google Scholar]
- Yamauchi, T.; Hara, K.; Maeda, S.; Yasuda, K.; Takahashi, A.; Horikoshi, M.; Nakamura, M.; Fujita, H.; Grarup, N.; Cauchi, S.; et al. A genome-wide association study in the Japanese population identifies susceptibility loci for type 2 diabetes at UBE2E2 and C2CD4A-C2CD4B. Nat. Genet. 2010, 42, 864–868. [Google Scholar] [CrossRef] [PubMed]
- Li, H.; Gan, W.; Lu, L.; Dong, X.; Han, X.; Hu, C.; Yang, Z.; Sun, L.; Bao, W.; Li, P.; et al. A genome-wide association study identifies GRK5 and RASGRP1 as type 2 diabetes loci in Chinese Hans. Diabetes 2013, 62, 291–298. [Google Scholar] [CrossRef] [PubMed]
- Iwata, M.; Maeda, S.; Kamura, Y.; Takano, A.; Kato, H.; Murakami, S.; Higuchi, K.; Takahashi, A.; Fujita, H.; Hara, K.; et al. Genetic risk score constructed using 14 susceptibility alleles for type 2 diabetes is associated with the early onset of diabetes and may predict the future requirement of insulin injections among Japanese individuals. Diabetes Care 2012, 35, 1763–1770. [Google Scholar] [CrossRef] [PubMed]
- Al-Sinani, S.; Woodhouse, N.; Al-Mamari, A.; Al-Shafie, O.; Al-Shafaee, M.; Al-Yahyaee, S.; Hassan, M.; Jaju, D.; Al-Hashmi, K.; Al-Abri, M.; et al. Association of gene variants with susceptibility to type 2 diabetes among Omanis. World J. Diabetes 2015, 6, 358–366. [Google Scholar] [CrossRef] [PubMed]
- Li, X.; Su, Y.; Yan, C.; Gu, L.; Qin, W.; Li, C.; Li, A. The association of rs4402960(IGF2BP2) between T2DM in Han Chinese in Inner Mongolia. J. Second Mil. Med. Univ. 2012, 8, 915–917. [Google Scholar]
- Ioannidis, J.P.; Ntzani, E.E.; Trikalinos, T.A.; Contopoulos-Ioannidis, D.G. Replication validity of genetic association studies. Nat. Genet. 2001, 29, 306–309. [Google Scholar] [CrossRef] [PubMed]
- Salanti, G.; Southam, L.; Altshuler, D.; Ardlie, K.; Barroso, I.; Boehnke, M.; Cornelis, M.C.; Frayling, T.M.; Grallert, H.; Grarup, N.; et al. Underlying genetic models of inheritance in established type 2 diabetes associations. Am. J. Epidemiol. 2009, 170, 537–545. [Google Scholar] [CrossRef] [PubMed]
- Grarup, N.; Rose, C.S.; Andersson, E.A.; Gitte Andersen, G.; Nielsen, A.L.; Albrechtsen, A.; Clausen, J.O.; Rasmussen, S.S.; Jørgensen, T.; Sandbæk, A.; et al. Studies of association of variants near the HHEX, CDKN2A/B, and IGF2BP2 genes with type 2 diabetes and impaired insulin release in 10,705 Danish subjects: Validation and extension of genome-wide association studies. Diabetes 2007, 56, 3105–3111. [Google Scholar] [CrossRef]
- Rotondi, M.A.; Donner, A.; Koval, J.J. Evidence-based sample size estimation based upon an updated meta-regression analysis. Res Synth Methods 2012, 3, 269–284. [Google Scholar] [CrossRef] [PubMed]
- Runkel, M.; Muller, S.; Brydniak, R.; Runkel, N. Downgrading of type 2 diabetes mellitus (T2DM) after obesity surgery: Duration and severity matter. Obes. Surg. 2015, 25, 494–499. [Google Scholar] [CrossRef] [PubMed]
- Baier, L.J.; Hanson, R.L. Genetic studies of the etiology of type 2 diabetes in Pima Indians: Hunting for pieces to a complicated puzzle. Diabetes 2004, 53, 1181–1186. [Google Scholar] [CrossRef] [PubMed]
- Rodriguez, S.; Eiriksdottir, G.; Gaunt, T.R.; Harris, T.B.; Launer, L.J.; Gudnason, V.; Day, I.N. IGF2BP1, IGF2BP2 and IGF2BP3 genotype, haplotype and genetic model studies in metabolic syndrome traits and diabetes. Growth Horm. IGF Res. 2010, 20, 310–318. [Google Scholar] [CrossRef] [PubMed]
- Li, X.; Allayee, H.; Xiang, A.H.; Trigo, E.; Hartiala, J.; Lawrence, J.M.; Buchanan, T.A.; Watanabe, R.M. Variation in IGF2BP2 interacts with adiposity to alter insulin sensitivity in Mexican Americans. Obesity (Silver Spring) 2009, 17, 729–736. [Google Scholar] [CrossRef] [PubMed]
- Lasram, K.; Ben, H.N.; Benrahma, H.; Mediene-Benchekor, S.; Arfa, I.; Hsouna, S.; Kefi, R.; Jamoussi, H.; Ben, A.S.; Bahri, S.; et al. Contribution of CDKAL1 rs7756992 and IGF2BP2 rs4402960 polymorphisms in type 2 diabetes, diabetic complications, obesity risk and hypertension in the Tunisian population. J. Diabetes 2015, 7, 102–113. [Google Scholar] [CrossRef] [PubMed]
- Wagner, M.; Kunsch, S.; Duerschmied, D.; Beil, M.; Adler, G.; Mueller, F.; Gress, T.M. Transgenic overexpression of the oncofetal RNA binding protein KOC leads to remodeling of the exocrine pancreas. Gastroenterology 2003, 124, 1901–1914. [Google Scholar] [CrossRef]
- Spagnoli, F.M.; Brivanlou, A.H. The RNA-binding protein, Vg1RBP, is required for pancreatic fate specification. Dev. Biol. 2006, 292, 442–456. [Google Scholar] [CrossRef] [PubMed]
- Ruchat, S.M.; Elks, C.E.; Loos, R.J.; Vohl, M.C.; Weisnagel, S.J.; Rankinen, T.; Bouchard, C.; Perusse, L. Association between insulin secretion, insulin sensitivity and type 2 diabetes susceptibility variants identified in genome-wide association studies. Acta Diabetol. 2009, 46, 217–226. [Google Scholar] [CrossRef] [PubMed]
- Van Hoek, M.; Dehghan, A.; Witteman, J.C.M.; van Duijn, C.M.; Uitterlinden, A.G.; Oostra, B.A.; Hofman, A.; Sijbrands, E.J.G.; Janssens, A.C.J.W. Predicting Type 2 Diabetes Based on Polymorphisms from Genome-Wide Association Studies: A Population-Based Study. Diabetes 2008, 57, 3122–3128. [Google Scholar] [CrossRef] [PubMed]
- Doria, A.; Patti, M.E.; Kahn, C.R. The emerging genetic architecture of type 2 diabetes. Cell Metab. 2008, 8, 186–200. [Google Scholar] [CrossRef] [PubMed]
Characteristic | T2DM | Controls | p |
---|---|---|---|
Gender (male/female) | 274/187 | 249/185 | 0.53 |
Age (years) | 53.48 ± 11.33 | 51.82 ± 12.67 | 0.039 |
BMI (kg/m2) | 27.05 ± 3.96 | 24.65 ± 3.57 | <0.001 |
FPG (mmol/L) | 7.26 ± 2.49 | 6.20 ± 1.95 | <0.001 |
TG (mmol/L) | 2.15 ± 1.96 | 1.63 ± 1.19 | <0.001 |
TC (mmol/L) | 4.81 ± 1.13 | 4.65 ± 0.93 | <0.001 |
LDL-C (mmol/L) | 2.79 ± 0.75 | 2.56 ± 0.64 | <0.001 |
SBP (mmHg) | 141.41 ± 20.97 | 128.33 ± 20.92 | <0.001 |
DBP (mmHg) | 87.79 ± 13.40 | 81.69 ± 13.72 | <0.001 |
UA (mmol/L) | 292.95 ± 80.69 | 300.25 ± 83.93 | 0.19 |
IGF2BP2 Polymorphisms | Cases | Controls | Crude Model | Adjusted Model * | ||
---|---|---|---|---|---|---|
OR (95% CI) | p | OR (95% CI) | p | |||
rs4402960 | n = 457 | n = 420 | ||||
Allele (%) | ||||||
T | 230(25.2) | 209 (24.9) | ||||
G | 914(74.8) | 631 (75.1) | 1.02 (0.82–1.26) | 0.89 | 1.04 (0.82–1.31) | 0.76 |
Genotype(%) | ||||||
GG | 261 (57.1) | 230 (54.8) | ||||
TG | 162 (35.5) | 171 (40.7) | 0.84(0.63–1.11) | 0.20 | 0.84 (0.62–1.13) | 0.24 |
TT | 34 (7.4) | 19 (4.5) | 1.58(0.88–2.84) | 0.13 | 1.73 (0.92–3.23) | 0.09 |
Dominant model (%) | ||||||
GG | 261 (57.1) | 230 (54.8) | ||||
TT + TG | 196 (42.9) | 190 (45.2) | 0.91(0.70–1.19) | 0.48 | 0.93 (0.70–1.24) | 0.63 |
Recessive model (%) | ||||||
TG + GG | 423 (93.6) | 401 (95.5) | ||||
TT | 34 (7.4) | 19 (4.5) | 1.70 (0.95–3.02) | 0.07 | 1.96 (1.07–3.61) | 0.03 |
rs1470579 | n = 459 | n = 419 | ||||
Allele (%) | ||||||
A | 674 (73.4) | 621 (74.1) | ||||
C | 244 (26.6) | 217 (25.9) | 1.04(0.84–1.28) | 0.75 | 1.05 (0.83–1.31) | 0.73 |
Genotype(%) | ||||||
AA | 253 (55.1) | 222 (53) | ||||
CA | 168 (36.6) | 177 (42.2) | 0.82(0.63–1.10) | 0.19 | 0.83 (0.62–1.11) | 0.21 |
CC | 38 (8.3) | 20 (4.8) | 1.67 (0.94–2.95) | 0.08 | 1.76 (0.95–3.23) | 0.07 |
Dominant model (%) | ||||||
AA | 253 (55.1) | 222 (53) | ||||
CC + CA | 206 (44.9) | 197 (47) | 0.92 (0.70–1.20) | 0.53 | 0.93 (0.70–1.23) | 0.62 |
Recessive model (%) | ||||||
AA + CA | 421 (91.7) | 399 (95.2) | ||||
CC | 38 (8.3) | 20 (4.8) | 1.80 (1.03–3.15) | 0.04 | 2.01 (1.11–3.64) | 0.02 |
Overall and Subgroup | Number of Studies | T Allele | Number of Studies | Dominant Model | Number of Studies | Recessive Model | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
OR (95% CI) | p(Z) | p(Q) | OR (95% CI) | p(Z) | p(Q) | OR (95% CI) | p(Z) | p(Q) | ||||
All | 40 | 1.16 (1.13–1.19) | 10−5 | 0.04 | 22 | 1.19 (1.15–1.24) | 10−5 | 0.59 | 22 | 1.24 (1.17–1.32) | 10−5 | 0.53 |
Ethnicity | ||||||||||||
Chinese | 20 | 1.15 (1.1–1.2) | 10−5 | 0.01 | 9 | 1.16 (1.08–1.25) | 10−4 | 0.35 | 9 | 1.28 (1.16–1.41) | 10−5 | 0.4 |
Japanese | 10 | 1.18 (1.14–1.23) | 10−5 | 0.57 | 9 | 1.21 (1.15–1.28) | 10−5 | 0.93 | 9 | 1.24 (1.14–1.35) | 10−5 | 0.34 |
Korean | 2 | 1.15 (1.08–1.23) | 10−5 | 0.69 | 2 | 1.17 (1.07–1.27) | 7 × 10−4 | 0.74 | 2 | 1.16 (0.98–1.36) | 0.08 | 0.76 |
Indian | 5 | 1.17 (1.08–1.27) | 10−5 | 0.74 | 2 | 1.31 (1.09–1.58) | 4 × 10−3 | 0.52 | 2 | 1.11 (0.91–1.36) | 0.29 | 0.98 |
others | 3 | 1.09 (0.99–1.21) | 0.09 | 0.48 | ||||||||
Diagnostic criterion | ||||||||||||
WHO | 24 | 1.15 (1.11–1.19) | 10−5 | 0.008 | 15 | 1.19 (1.15–1.24) | 10−5 | 0.75 | 15 | 1.25 (1.17–1.33) | 10−5 | 0.36 |
Others | 15 | 1.17 (1.13–1.21) | 10−5 | 0.57 | 7 | 1.18 (1.05–1.33) | 6 × 10−3 | 0.19 | 7 | 1.24 (1.07–1.42) | 0.003 | 0.59 |
Sample size | ||||||||||||
<500 | 9 | 1.1 (1.02–1.18) | 0.01 | 0.55 | 5 | 1.11 (1.01–1.4) | 0.04 | 0.5 | 5 | 1.48 (1.14–1.92) | 0.003 | 0.59 |
>500 | 30 | 1.16 (1.13–1.19) | 10−5 | 0.01 | 18 | 1.2 (1.16–1.25) | 10−5 | 0.67 | 17 | 1.23 (1.16–1.31) | 10−5 | 0.5 |
Mean BMI of cases | ||||||||||||
<25 | 10 | 1.21 (1.16–1.27) | 10−5 | 0.41 | 8 | 1.21 (1.14–1.3) | 10−5 | 0.88 | 8 | 1.31 (1.17–1.46) | 10−5 | 0.44 |
25–30 | 22 | 1.16 (1.13–1.19) | 10−5 | 0.69 | 13 | 1.18 (1.13–1.24) | 10−5 | 0.2 | 13 | 1.25 (1.14–1.36) | 10−5 | 0.54 |
Mean age of cases | ||||||||||||
<55 | 10 | 1.15 (1.1–1.2) | 10−5 | 0.51 | 7 | 1.18 (1.1–1.28) | 10−4 | 0.26 | 7 | 1.17 (1.03–1.32) | 0.02 | 0.71 |
55–60 | 12 | 1.2 (1.15–1.24) | 10−5 | 0.33 | 5 | 1.21 (1.13–1.29) | 10−5 | 0.42 | 5 | 1.41 (1.24–1.61) | 10−5 | 0.43 |
>60 | 12 | 1.16 (1.12–1.2) | 10−5 | 0.42 | 10 | 1.19 (1.13–1.25) | 10−5 | 0.6 | 10 | 1.22 (1.12–1.32) | 10−5 | 0.6 |
Overall and Subgroup | Number of Studies | C Allele | Number of Studies | Dominant Model | Number of Studies | Recessive Model | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
OR (95% CI) | p(Z) | p(Q) | OR (95% CI) | p(Z) | p(Q) | OR (95% CI) | p(Z) | p(Q) | ||||
All | 16 | 1.14 (1.11–1.18) | 10−5 | 0.65 | 8 | 1.11 (1.03–1.19) | 0.004 | 0.09 | 8 | 1.21 (1.09–1.36) | 6 × 10−4 | 0.05 |
Ethnicity | ||||||||||||
Chinese | 9 | 1.11 (1.06–1.16) | 10−5 | 0.63 | 4 | 1.04 (0.93–1.16) | 0.45 | 0.16 | 4 | 1.14 (0.92–1.4) | 0.23 | 0.25 |
Japanese | 6 | 1.17 (1.13–1.21) | 10−5 | 0.73 | 3 | 1.16 (1.04–1.28) | 5 × 10−3 | 0.09 | 3 | 1.31 (1.12–1.53) | 6 × 10−4 | 0.02 |
Indian | 1 | 1.10 (0.95–1.28) | 0.2 | NA | 1 | 1.19 (0.93–1.52) | 0.16 | NA | 1 | 1.1 (0.86–1.4) | 0.45 | NA |
Diagnostic criterion | ||||||||||||
WHO | 9 | 1.14 (1.1–1.18) | 10−5 | 0.6 | 4 | 1.15 (1.06–1.25) | 9 × 10−4 | 0.11 | 4 | 1.17 (1.03–1.34) | 0.02 | 0.16 |
Others | 7 | 1.15 (1.09–1.21) | 10−5 | 0.43 | 4 | 0.99 (0.86–1.15) | 0.94 | 0.36 | 4 | 1.3 (1.07–1.58) | 0.008 | 0.05 |
Sample size | ||||||||||||
<500 | 5 | 1.17 (1.06–1.29) | 0.002 | 0.25 | 4 | 1.01 (0.86–1.17) | 0.97 | 0.1 | 4 | 1.57 (1.19–2.08) | 0.001 | 0.22 |
>500 | 11 | 1.14 (1.11–1.17) | 10−5 | 0.74 | 4 | 1.14 (1.05–1.23) | 0.001 | 0.27 | 4 | 1.16 (1.02–1.3) | 0.02 | 0.15 |
Mean BMI of cases | ||||||||||||
<25 | 6 | 1.17 (1.13–1.21) | 10−5 | 0.73 | 3 | 1.16 (1.04–1.28) | 0.005 | 0.09 | 3 | 1.31 (1.12–1.53) | 6 × 10−4 | 0.02 |
25–30 | 9 | 1.11 (1.06–1.16) | 10−5 | 0.62 | 5 | 1.07 (0.96–1.18) | 0.21 | 0.19 | 5 | 1.12 (0.96–1.31) | 0.16 | 0.39 |
Mean age of cases | ||||||||||||
<55 | 3 | 1.11 (0.99–1.24) | 0.08 | 0.34 | 3 | 1.14 (0.97–1.33) | 0.12 | 0.08 | 3 | 1.19 (0.97–1.47) | 0.1 | 0.28 |
55–60 | 4 | 1.16 (1.09–1.24) | 10−5 | 0.54 | 1 | 0.88 (0.68–1.15) | 0.36 | NA | 1 | 1.93 (1.26–2.95) | 0.002 | NA |
>60 | 8 | 1.14 (1.11–1.18) | 10−5 | 0.39 | 4 | 1.13 (1.04–1.23) | 0.005 | 0.23 | 4 | 1.16 (1.01–1.34) | 0.03 | 0.09 |
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Rao, P.; Wang, H.; Fang, H.; Gao, Q.; Zhang, J.; Song, M.; Zhou, Y.; Wang, Y.; Wang, W. Association between IGF2BP2 Polymorphisms and Type 2 Diabetes Mellitus: A Case–Control Study and Meta-Analysis. Int. J. Environ. Res. Public Health 2016, 13, 574. https://doi.org/10.3390/ijerph13060574
Rao P, Wang H, Fang H, Gao Q, Zhang J, Song M, Zhou Y, Wang Y, Wang W. Association between IGF2BP2 Polymorphisms and Type 2 Diabetes Mellitus: A Case–Control Study and Meta-Analysis. International Journal of Environmental Research and Public Health. 2016; 13(6):574. https://doi.org/10.3390/ijerph13060574
Chicago/Turabian StyleRao, Ping, Hao Wang, Honghong Fang, Qing Gao, Jie Zhang, Manshu Song, Yong Zhou, Youxin Wang, and Wei Wang. 2016. "Association between IGF2BP2 Polymorphisms and Type 2 Diabetes Mellitus: A Case–Control Study and Meta-Analysis" International Journal of Environmental Research and Public Health 13, no. 6: 574. https://doi.org/10.3390/ijerph13060574