IGF2BP2 and obesity interaction analysis for type 2 diabetes mellitus in Chinese Han population
© Wu et al.; licensee BioMed Central Ltd. 2014
Received: 6 June 2014
Accepted: 16 July 2014
Published: 25 July 2014
The objective of this study was to systematically evaluate the contribution of the insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) to type 2 diabetes mellitus (T2DM) and its interaction with obesity to T2DM susceptibility.
To clarify whether IGF2BP2 is an independent risk factor for T2DM in Chinese population, we conducted a study with a total of 2,301 Chinese Han subjects, including 1,166 T2DM patients and 1,135 controls, for the genotype of a most common and widely studied polymorphism—rs4402960 of IGF2BP2. Genotyping was performed by iPLEX technology. Gene and environment interaction analysis was performed by using multiple logistic regression models.
The repeatedly confirmed association between IGF2BP2 (rs4402960) and T2DM had not been replicated in this cohort (P = 0.182). Interestingly, we found that obese subjects (body mass index (BMI) ≥ 28.0 kg/m2) bearing the minor A allele had an increased risk to develop T2DM (P = 0.008 for allele analysis and P < 0.001 for genotype analysis).
The present study provided data suggesting that the wild C allele of IGF2BP2 (rs4402960) had a protective effect against T2DM in obese subjects of Chinese Han population.
Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder characterized by hyperglycemia as a result of pancreatic beta cell dysfunction and insulin resistance. Multiple environmental factors and genetic determinants are considered to be involved in the pathogenesis of the disease. Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying novel genetic variants contributing to the risk of T2DM and further facilitate the elucidation of the genetic etiology of diabetes. Among the variants relating to glucose metabolism revealed by GWAS, insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) was the most extensively studied and supposed to be a T2DM susceptibility gene [1–3].
IGF2BP2 is encoded by the IGF2BP2 gene which is located on chromosome 3q27. Its strong association with β cell function is established by regulating IGF2 post-translation . Several variants of the IGF2BP2 gene were investigated for relationship with T2DM, of which rs4402960 was the most extensively studied. However, due to the ethnic difference in risk allele frequency, the contribution of this common variant to T2DM appears to be race dependent which makes it a highly controversial candidate for T2DM [1–3, 5]. To get a thorough understanding of the effect of IGF2BP2 on the susceptibility of T2DM, we therefore genotyped for IGF2BP2 rs4402960 in a total of 2,301 Chinese Han individuals in our present study.
Given that environment/lifestyle changes can modify the risk of T2DM, likely contributing factors such as gender, body mass index (BMI), and smoking behavior of subjects to T2DM would also be interesting to investigate . Obesity (BMI ≥ 28.0 kg/m2) is especially widely recognized as an independent risk factor for T2DM in Chinese population . Therefore, it would be valuable to conduct a particular analysis for obesity in this cohort. Previous studies provided evidence for gene-obesity interaction in human complex disease [8, 9]. Studies also supported the assumption that IGF2 is strongly associated with obesity . It is evident that obesity is associated with T2DM, and IGF2 levels in T2DM patients are associated with T2DM. We hypothesize that obesity may modify the association between IGF2BP2 and T2DM—also called the interaction of IGF2BP2 and obesity with T2DM. Since some variants are known to affect the risk of T2DM through obesity [11, 12], this work aimed to evaluate the interaction effect of IGF2BP2 and obesity on T2DM susceptibility.
Individuals enrolled in the cohort, including 1,166 T2DM patients and 1,135 controls, were of Southern Han Chinese ancestry residing in the Shanghai metropolitan area. T2DM patients registered in the analysis were recruited from the Endocrinology and Metabolism outpatient clinics at Fudan University Huashan Hospital in Shanghai. All subjects in the cohort were informed and consented to take part in the study. The protocol was approved by the Ethics Committee of Huashan Hospital affiliated to Fudan University.
The subjects were interviewed for the documentation of medical histories, medications, regular physical examinations, and laboratory assessment of T2DM risk factors. BMI was calculated as the weight in kilograms divided by the square of height in meters. Systolic and diastolic blood pressure (BP) values were the means of two physician-obtained measurements on the left arm of a seated participant.
Peripheral venous blood samples were collected in tubes in the fasting state and 2 h after diet in all subjects. The blood was centrifuged at 3,000 rpm for 10 min for plasma separation and immediately used to measure biomarkers. Fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) were quantified by the glucose oxidase-peroxidase procedure. Serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL) cholesterol, urea nitrogen (UN), uric acid (UA), and alanine transaminase (ALT) levels were measured by an enzymatic method with a chemical analyzer (Hitachi 7600-020, Tokyo, Japan). Low-density lipoprotein (LDL) cholesterol levels were calculated using the Friedewald formula. The day-to-day and inter-assay coefficients of variation at the central laboratory in our hospital for all analyses were between 1% and 3%.
The clinical characteristics of the subjects
65.46 ± 10.56
59.09 ± 7.85
160.20 ± 8.64
161.09 ± 7.65
64.85 ± 10.71
62.78 ± 10.15
139.52 ± 19.92
126.44 ± 16.92
82.88 ± 10.98
80.52 ± 10.13
6.08 ± 1.63
5.62 ± 1.37
0.30 ± 0.08
0.31 ± 0.08
8.39 ± 3.03
5.22 ± 0.38
15.05 ± 5.34
6.03 ± 1.04
5.43 ± 1.11
5.35 ± 1.00
2.00 ± 1.46
1.47 ± 1.06
1.29 ± 0.34
1.43 ± 0.36
3.10 ± 0.86
3.10 ± 0.79
28.44 ± 16.08
24.04 ± 13.69
Peripheral venous blood samples were collected from all study subjects, and the genomic DNA was extracted from peripheral blood leukocytes by the conventional proteinase K-phenol-chloroform extraction method. A total of 2,301 Chinese Han individuals were genotyped for IGF2BP2 rs4402960 by using iPLEX (Sequenom, San Diego, CA, USA); the single nucleotide polymorphism (SNP) involved was detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The genotype distribution was in Hardy-Weinberg equilibrium (P > 0.05), and there was a 99.9% genotype concordance rate when duplicated samples were compared across plates.
Continuous variables were detected when the variables followed normal distribution using the Kolmogorov-Smirnov test. Variables that were not normally distributed were log-transformed to approximate normal distribution for analysis. Results are described as mean ± SD or median unless stated otherwise. Differences in variables between T2DM and control were determined by unpaired t test. Between-group differences in properties were accessed by χ2 analysis. Univariate logistic regression was performed to determine variables associated with T2DM and to estimate confounding factors possibly disturbing the relation of BMI and/or IGF2BP2 to T2DM. Multivariable logistic regression (MLR) was carried out to control potential confounders for determining the independent contribution of variables to T2DM. For interaction analysis, MLR was conducted to include two main variables and their interaction item to determine the interaction effect. In order to better investigate the interaction between BMI and IGF2BP2 on T2DM, we performed two analyses according to the following variables: the allele and genotype of IGF2BP2. Odds ratios (OR) with 95% confidence intervals (CI) were calculated for the relative risk of BMI and/or IGF2BP2 with T2DM. Results were analyzed using the Statistical Package for the Social Sciences for Windows version 16.0 (SPSS, Chicago, IL, USA). Tests were two-sided, and a P value of <0.05 was considered significant.
Clinical characteristics of the subjects
The baseline clinical characteristics of the 2,301 subjects are listed in Table 1. There are 456 males and 710 females (mean age, 65.46 ± 10.56 years) in the cases and 352 males and 783 females (mean age, 59.09 ± 7.85 years) in the controls. Diabetic patients had more weight than controls. Systolic blood pressure (SBP), diastolic blood pressure (DBP), FPG, PPG, TC, and TG levels were higher in the cases than in the controls, while the HDL level was lower in the cases. Serum UA, UN, ALT, and LDL levels were similar between the two groups. The minor allele (A) frequency of rs4402960 was 25.27% and 27.03% in the cases and controls, respectively.
Univariate and multiple logistic regression analyses for diabetes
Univariate logistic regression analysis for diabetes
BMI by IGF2BP2 interaction analysis for diabetes
The interaction effect analysis of BMI and allele of IGF2BP2 (rs4402690) for diabetes
BMI by rs4402690
The interaction effect analysis of BMI and genotype of IGF2BP2 (rs4402690) for diabetes
BMI by rs4402960
We conducted a study to evaluate the interaction effect of IGF2BP2 and obesity on T2DM in a large case-control sample of Chinese population. To our knowledge, this is the first investigation of the evaluation of interaction effect on T2DM based on variables of obesity and IGF2BP2.
Genotyping was performed for IGF2BP2 (rs4402960) in a T2DM case-control cohort comprising of 2,301 Chinese Han individuals. However, the documented association of IGF2BP2 (rs4402960) with T2DM in various ethnic populations [15–18] had not been replicated. In line with our finding, subsequent large-scale population studies also reported a lack of association in Caucasians [19–21]. Such conflicting results of various association studies may be attributed to the diverse ethnic/regional backgrounds, as well as the limited number of participants which had insufficient statistical power to detect a slight effect of the common polymorphism IGF2BP2 (rs4402960) on T2DM susceptibility. Therefore, a larger sample size is necessary to detect the association between this IGF2BP2 genetic variant and T2DM.
IGF2BP2 in pancreatic and adipose tissues can downregulate the expression of IGF2, a growth factor that plays a pivotal role in controlling adipogenesis  and pancreatic development . Therefore, IGF2BP2 may contribute to T2DM through impaired β cell function or alterations in adipose tissue as well. Consistent with the hypothesis, a study observed a more than twofold increase in IGF2BP2 expression level in the adipose tissue of diabetic patients compared to controls . Similarly, an altered expression of IGF2BP2 in adipocytes of T2DM subjects compared with healthy people was also detected . Unfortunately, the current study did not find a significant association between IGF2PB2 (rs4402960) and T2DM, as a consequence of the insufficient statistical power in the present sample size or the different impacts of various IGF2BP2 genetic variants. Further studies are required to elucidate the association of other IGF2BP2 variants with the risk of T2DM.
Considering that lifestyle changes can modify the risk of T2DM, the likely effect of metabolic quantitative traits on T2DM susceptibility needs to be addressed, as well as their interaction with various gene variants. Here, MLR models were developed to demonstrate that obesity (BMI ≥28.0 kg/m2) remained an independently risk factor for T2DM after potential confounder adjustment (P < 0.05, data not shown). Although it had been known for decades that both T2DM and obesity have a genetic basis , the mechanism by which obesity relates to T2DM in humans is still unclear. Since some genetic variants are known to affect the risk of T2DM through obesity, a hypothesis comes up that IGF2BP2 may have a relationship with obesity. However, no significant difference in IGF2BP2 expression in obese patients carrying different rs4402960 genotypes has been found .
Our study is the first analysis of the interaction of obesity and IGF2BP2 variant on T2DM susceptibility. It is noteworthy that the risk imparted by the minor A allele was higher than that by the C allele in obese subjects (P = 0.008 for allele analysis and P < 0.001 for genotype analysis), thus prompting the speculation of a possible interaction between IGF2BP2 (rs4402960) and obesity in determining overall T2DM risk. However, the underlying mechanism has been still unknown. The associations between variants of IGF2BP2 and abdominal/visceral total fat were evidenced in Canadian Caucasians  and Mexican Americans , suggesting a possible role of IGF2BP2 in insulin resistance. This finding implies that IGF2BP2 (rs4402960) may disturb T2DM susceptibility through its contribution to insulin resistance, which is experienced mainly by obese individuals.
Several limitations of the study deserve comment. Firstly, the subjects who participated in the study were recruited from Shanghai, so they may not have been representative of China as a whole. Secondly, it is important to mention that our study was performed on Chinese individuals, and our findings may not be relevant to people of other ethnicities.
The present study did not replicate the association of IGF2BP2 (rs4402960) and T2DM. Interestingly, it provided data suggesting that the wild C allele of IGF2BP2 (rs4402960) had a protective effect against T2DM in obese subjects of Chinese Han population. Further studies and a larger sample size are required to elucidate the relevant mechanisms, as well as the likely contribution of other IGF2BP2 variants to the risk of T2DM.
The study was supported by a grant from The National Nature Science Foundation of China (No. 81270903).
- Rong R, Hanson RL, Ortiz D, Wiedrich C, Kobes S, Knowler WC, Bogardus C, Baier LJ: Association analysis of variation in/near FTO, CDKAL1, SLC30A8, HHEX, EXT2, IGF2BP2, LOC387761, and CDKN2B with type 2 diabetes and related quantitative traits in Pima Indians. Diabetes 2009, 58(2):478–488.PubMedPubMed CentralView ArticleGoogle Scholar
- 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.PubMedPubMed CentralView ArticleGoogle Scholar
- Stancakova A, Kuulasmaa T, Paananen J, Jackson AU, Bonnycastle LL, Collins FS, Boehnke M, Kuusisto J, Laakso M: Association of 18 confirmed susceptibility loci for type 2 diabetes with indices of insulin release, proinsulin conversion, and insulin sensitivity in 5,327 nondiabetic Finnish men. Diabetes 2009, 58(9):2129–2136. 10.2337/db09-0117PubMedPubMed CentralView ArticleGoogle Scholar
- Ruchat SM, Elks CE, Loos RJ, Vohl MC, Weisnagel SJ, Rankinen T, Bouchard C, Pérusse L: Association between insulin secretion, insulin sensitivity and type 2 diabetes susceptibility variants identified in genome-wide association studies. Acta Diabetol 2009, 46(3):217–226. 10.1007/s00592-008-0080-5PubMedView ArticleGoogle Scholar
- Lee YH, Kang ES, Kim SH, Han SJ, Kim CH, Kim HJ, Ahn CW, Cha BS, Nam M, Nam CM, Lee HC: 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(11–12):991–998.PubMedView ArticleGoogle Scholar
- Kim WY, Kim JE, Choi YJ, Huh KB: Nutritional risk and metabolic syndrome in Korean type 2 diabetes mellitus. Asia Pac J Clin Nutr 2008, 17(Suppl 1):47–51.PubMedGoogle Scholar
- Xin Z, Liu C, Niu WY, Feng JP, Zhao L, Ma YH, Hua L, Yang JK: Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population. BMC Public Health 2012, 12: 732. 10.1186/1471-2458-12-732PubMedPubMed CentralView ArticleGoogle Scholar
- Wang X, Ding X, Su S, Spector TD, Mangino M, Iliadou A, Snieder H: Heritability of insulin sensitivity and lipid profile depend on BMI: evidence for gene-obesity interaction. Diabetologia 2009, 52(12):2578–2584. 10.1007/s00125-009-1524-3PubMedPubMed CentralView ArticleGoogle Scholar
- Lamina C, Forer L, Schönherr S, Kollerits B, Ried JS, Gieger C, Peters A, Wichmann HE, Kronenberg F: Evaluation of gene-obesity interaction effects on cholesterol levels: a genetic predisposition score on HDL-cholesterol is modified by obesity. Atherosclerosis 2012, 225(2):363–369. 10.1016/j.atherosclerosis.2012.09.016PubMedView ArticleGoogle Scholar
- Lasram K, Ben Halim N, Benrahma H, Mediene-Benchekor S, Arfa I, Hsouna S, Kefi R, Jamoussi H, Ben Ammar S, Bahri S, Abid A, Benhamamouch S, Barakat A, Abdelhak S: Contribution of CDKAL1 rs7756992 and IGF2BP2 rs4402960 polymorphisms in type 2 diabetes, diabetic complications, obesity risk and hypertension in the Tunisian population. J Diabetes 2014. doi:10.1111/1753–0407.12147Google Scholar
- Ng MC, Park KS, Oh B, Tam CH, Cho YM, Shin HD, Lam VK, Ma RC, So WY, Cho YS, Kim HL, Lee HK, Chan JC, Cho NH: Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 2008, 57(8):2226–2233. 10.2337/db07-1583PubMedPubMed CentralView ArticleGoogle Scholar
- Li X, Allayee H, Xiang AH, Trigo E, Hartiala J, Lawrence JM, Buchanan TA, Watanabe RM: Variation in IGF2BP2 interacts with adiposity to alter insulin sensitivity in Mexican Americans. Obesity (Silver Spring) 2009, 17(4):729–736. 10.1038/oby.2008.593PubMed CentralView ArticleGoogle Scholar
- Bei-Fan Z: Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults: study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Asia Pac J Clin Nutr 2002, 11(Suppl 8):S685-S693.View ArticleGoogle Scholar
- Alberti KG, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998, 15(7):539–553. 10.1002/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-SPubMedView ArticleGoogle Scholar
- Chauhan G, Spurgeon CJ, Tabassum R, Bhaskar S, Kulkarni SR, Mahajan A, Chavali S, Kumar MV, Prakash S, Dwivedi OP, Ghosh S, Yajnik CS, Tandon N, Bharadwaj D, Chandak GR: Impact of common variants of PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 on the risk of type 2 diabetes in 5,164 Indians. Diabetes 2010, 59(8):2068–2074. 10.2337/db09-1386PubMedPubMed CentralView ArticleGoogle Scholar
- Gu T, Horová E, Möllsten A, Seman NA, Falhammar H, Prázný M, Brismar K, Gu HF: IGF2BP2 and IGF2 genetic effects in diabetes and diabetic nephropathy. J Diabetes Complications 2012, 26(5):393–398. 10.1016/j.jdiacomp.2012.05.012PubMedView ArticleGoogle Scholar
- Wu J, Wu J, Zhou Y, Zou H, Guo S, Liu J, Lu L, Xu H: Quantitative assessment of the variation in IGF2BP2 gene and type 2 diabetes risk. Acta Diabetol 2012, 49(Suppl 1):S87-S97.PubMedView ArticleGoogle Scholar
- Zhang SM, Xiao JZ, Ren Q, Han XY, Tang Y, Yang WY, Ji LN: Replication of association study between type 2 diabetes mellitus and IGF2BP2 in Han Chinese population. Chin Med J (Engl) 2013, 126(21):4013–4018.Google Scholar
- 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(7):1992–1996. 10.2337/db07-1789PubMedPubMed CentralView ArticleGoogle Scholar
- Chistiakov DA, Nikitin AG, Smetanina SA, Bel'chikova LN, Suplotova LA, Shestakova MV, Nosikov VV: The rs11705701 G > A polymorphism of IGF2BP2 is associated with IGF2BP2 mRNA and protein levels in the visceral adipose tissue—a link to type 2 diabetes susceptibility. Rev Diabet Stud 2012, 9(2–3):112–122.PubMedPubMed CentralView ArticleGoogle Scholar
- Moore AF, Jablonski KA, McAteer JB, Saxena R, Pollin TI, Franks PW, Hanson RL, Shuldiner AR, Knowler WC, Altshuler D, Florez JC, Diabetes Prevention Program Research Group: Extension of type 2 diabetes genome-wide association scan results in the diabetes prevention program. Diabetes 2008, 57(9):2503–2510. 10.2337/db08-0284PubMedPubMed CentralView ArticleGoogle Scholar
- Louveau I, Gondret F: Regulation of development and metabolism of adipose tissue by growth hormone and the insulin-like growth factor system. Domest Anim Endocrinol 2004, 27(3):241–255. 10.1016/j.domaniend.2004.06.004PubMedView ArticleGoogle Scholar
- Miralles F, Portha B: Early development of beta-cells is impaired in the GK rat model of type 2 diabetes. Diabetes 2001, 50(Suppl 1):S84-S88.PubMedView ArticleGoogle Scholar
- Parikh H, Lyssenko V, Groop LC: Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus. BMC Med Genomics 2009, 2: 72. 10.1186/1755-8794-2-72PubMedPubMed CentralView ArticleGoogle Scholar
- Baier LJ, Hanson RL: Genetic studies of the etiology of type 2 diabetes in Pima Indians: hunting for pieces to a complicated puzzle. Diabetes 2004, 53(5):1181–1186. 10.2337/diabetes.53.5.1181PubMedView ArticleGoogle Scholar
- Ruchat SM, Elks CE, Loos RJ, Vohl MC, Weisnagel SJ, Rankinen T, Bouchard C, Pérusse L: Evidence of interaction between type 2 diabetes susceptibility genes and dietary fat intake for adiposity and glucose homeostasis-related phenotypes. J Nutrigenet Nutrigenomics 2009, 2(4–5):225–234.PubMedView ArticleGoogle Scholar
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