ZHANG Lu, ZHANG Ming, WANG Jin Jin, WANG Chong Jian, REN Yong Cheng, WANG Bing Yuan,, ZHANG Hong Yan, YANG Xiang Yu, ZHAO Yang, HAN Cheng Yi, ZHOU Jun Mei, PANG Chao, YIN Lei, ZHAO Jing Zhi, LUO Xin Ping,#, and HU Dong Sheng,,#

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Association ofandGene Variants with Insulin Secretion, Insulin Resistance, and Obesity in New-onset Diabetes*

ZHANG Lu1,^, ZHANG Ming2,^, WANG Jin Jin3, WANG Chong Jian1, REN Yong Cheng1, WANG Bing Yuan1,2, ZHANG Hong Yan1, YANG Xiang Yu1, ZHAO Yang1, HAN Cheng Yi1, ZHOU Jun Mei2, PANG Chao4, YIN Lei4, ZHAO Jing Zhi4, LUO Xin Ping2,#, and HU Dong Sheng1,2,#

1. Department of Epidemiologyand Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, Henan, China; 2. Department of Preventive Medicine, Shenzhen University; Shenzhen University Health Science Center, Shenzhen 518060, Guangdong, China; 3. Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450016, Henan, China; 4. Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou 450052, Henan, China

This cohort study was designed to evaluate the association of transcription factor 7-like 2 () and proglucagon gene () variants with disordered glucose metabolism and the incidence of type 2 diabetes mellitus (T2DM) in a rural adult Chinese population. A total of 7,751 non-T2DM participants ≥18 years old genotyped at baseline were recruited. The same questionnaire interview and physical and blood biochemical examinations were performed at both baseline and follow-up. During a median 6 years of follow-up, T2DM developed in 227 participants. After adjustment for potential contributory factors, nominally significant associations were seen between TT genotype and the recessive model ofrs7903146 and increased risk of T2DM [hazard ratio ()=4.068, 95% confidence interval (): 1.270-13.026;=4.051, 95%: 1.268-12.946, respectively]. The TT genotype of rs7903146 was also significantly associated with higher fasting plasma insulin level and the homeostasis model assessment of insulin resistance in case of new-onset diabetes. In addition, thers290487 TT genotype was associated with abdominal obesity and thers12104705 CC genotype was associated with both general obesity and abdominal obesity in case of new-onset diabetes

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by hyperglycemia, different degrees of insulin resistance, and pancreatic β-cell dysfunction[1].Genome-wide association studies have confirmed a large number of known genetic variants associated with increased risk of T2DM. Among all identified variants, transcription factor 7-like 2 () had the largest effect on risk for T2DM in people of European origin[2]. The proglucagon gene () located on chromosome 2q24.2 can be activated byin thesignaling pathway, and expresses glucagon-like peptide1 (GLP-1) in the intestine. GLP-1 plays an essential role in regulating blood glucose level by stimulating glucose-dependent insulin secretion[3]. Overweight and obesity are important risk factors for the development of diabetes[4]. T2DM is caused by genetic and especially environmental factors[5]. In this study, we selected the tag single nucleotide polymorphisms (SNPs) rs7903146, rs290487, rs11196218 ofand rs12104705 of, and analyzed the association of these variants with quantitative traits related to the risk for T2DM in a 6-year follow-up study of a rural adult Chinese cohort.

A total of 7,751 participants of Northern Chinese ancestry aged 18 to 74 years old were recruited from July to August 2007 andJuly to August 2008. Reasons for exclusion were fasting plasma glucose (FPG) level≥7.0 mmol/L or self-reported diabetes diagnosis, pregnancy, physical handicap, mental disorder, obesity caused by disease, use of certain drugs, or cancer. During follow-up, 315 individuals died and 1,110 were lost to follow-up. Thus, 6,326 individuals (81.62%) were followed up from July to August 2013 and July to October 2014; of these, 815 had no data on FPG level and unknown history of T2DM. Finally, 5,511 participants were eligible for analysis. T2DM developed in 227. A standard questionnaire was used to assess demographic characteristics, medical history, T2DM family history, smoking and alcohol status, physical activity level, and other risk factors at baseline and follow-up. Anthropometric and laboratory data were obtained at baseline and follow-up. Insulin resistance and β-cell function were calculated from FPG and insulin using the homeostasis model assessment (HOMA) formula[6].

The clinical and biochemical characteristics of subjects (227 with new-onset diabetes and 5,284 non-T2DM participants) at baseline were analyzed (Table 1). The distribution of differences in age, body mass index (BMI), waist circumference, systolic and diastolic blood pressure, fasting plasma glucose, total cholesterol, triglyceride, and HDL-C level between T2DM and non-T2DM subjects was statistically significant (<0.05).

For the 5,511 study participants, the genotype frequencies of all SNPs were in accordance with Hardy-Weinberg equilibrium (>0.05). Genotypic and allelic distributions ofandSNPs are shown in Supplementary Table S1 (in the website of BES, www.besjournal.com). The genotypic but not allelic distributions of rs7903146 differed between T2DM and non-T2DM individuals (=0.02). Supplementary Table S2 (in the website of BES, www.besjournal.com) shows the association ofandSNPs with the incidence of T2DM in different genetic models according to Cox proportional hazards testing. After adjustment for potential risk factors, nominally significant associations were seen for TT genotype and the recessive model ofrs7903146 and increased risk of T2DM [hazard ratio ()=4.068, 95% confidence interval (): 1.270-13.026,=0.0181;=4.051, 95%: 1.268-12.946,=0.0183, respectively].

Among 227 participants in whom T2DM developed during follow-up, 110 received a diagnosis in the hospital and 117 were diagnosed by FPG measurement on outpatient follow-up. No new patients had a history of hypoglycemic agent use. Table 2 shows that the TT genotype of rs7903146 was significantly associated with higher fasting plasma insulin and the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) in those with new-onset diabetes (<0.05). In addition, the rs290487 TT genotype ofwas associated with abdominal obesity and the rs12104705 CC genotype ofwas associated with both general obesity and abdominal obesity in those with new-onset diabetes(<0.05) (Table 3).

Table 1. Anthropometric and Biochemical Characteristics of the Study Population (n=5,511)

*Family history of T2DM in 804 participants was unknown. Data are median (interquartile range) or percentage (%). BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.

Genetic elements are involved in the pathogenesis of T2DM, but lifestyle seems to trigger pathogenic factors. We found no interaction between the-gene and gene environment associated with the risk of T2DM, but our results suggest thatandgenetic variants may be associated withfasting insulin level, insulin resistance, and obesity in new-onset diabetes.

Epidemiological evidence indicates that obesity, and particularly abdominal obesity, is an independent risk factor for T2DM. Visceral fat affects insulin metabolism by releasing free fatty acids, which may reduce hepatic clearance of insulin, leading to insulin resistance and hyperinsulinemia. In addition, fat cells secrete a series of cytokines including leptin, adiponectin, interleukin-6 (IL-6), and tumor necrosis factor (TNF-α), which are related to insulin resistance[7-8].Our results support these findings; moreover, we found that SNP rs290487 inand rs12104705 inwere associated with both general obesity and abdominal obesity in new-onset diabetes.

Furthermore, we found that rs7903146 was associated with fasting insulin level and HOMA-IR in new-onset diabetes. Le Bacquer et al. found that thevariant rs7903146 risk allele is associated with impaired insulin secretion, reduction of total islet number, and quantitative as well as qualitative morphological changes in human islets[9]. Zhou et al. have also identified a-regulated transcriptional network responsible for its effect on insulin secretion in human pancreatic islets. The risk T-allele of rs7903146 was associated with increasedexpression, as well as decreased insulin content and secretion[10]. We found a compensatory increase in fasting insulin levels and HOMA-IR in carriers of risk T-allele in new-onset diabetes. Therefore,not only regulates synthesis of proinsulin, but also processing and possibly clearance of proinsulin and insulin[10]. Although a cohort design was employed in this study, several limitations should be considered when interpreting the findings. First, an oral glucose tolerance test (OGTT) was not consistently performed, which might lead to underestimation of the incidence of T2DM and induce misclassification bias. Second, the number of cases was small, and there was no significant interaction between theandgenes in the incidence of diabetes. Third, a baseline fasting insulin level was not obtained, and dynamic changes in fasting insulin, HOMA-IR, and HOMA-β were not analyzed.

Our study provided important evidence for the association ofandgenetic variants with insulin resistance and obesity in new-onset diabetes.

1. Stumvoll M, Goldstein BJ, van Haeften TW. Type 2 diabetes: principles of pathogenesis and therapy. Lancet, 2005; 9467, 1333-46.

2. Frayling TM. Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat Rev Genet, 2007; 9, 657-62.

3. Yi F, Li D, Ma WZ, et al. GLP-1 biology and GLP-1 based antidiabetic therapy. Journal of Chinese Pharmaceutical Sciences, 2013; 1, 7-27.

4. Abdullah A, Peeters A, de Courten M,et al. The magnitude of association between overweight and obesity and the risk of diabetes: a meta-analysis of prospective cohort studies. Diabetes Res Clin Pract, 2010; 3, 309-19.

5. Hu FB. Globalization of diabetes: the role of diet, lifestyle, and genes.Diabetes Care, 2011; 6, 1249-57.

6. Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabeteologia, 1985; 7, 412-9.

7. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes.Nature, 2006;7121, 840-6.

8. Jazet IM, Pijl H, Meinders AE. Adipose tissue as an endocrine organ: impact on insulin resistance. Neth J Med, 2003; 6, 194-212.

9.Le Bacquer O, Kerr-Conte J, Gargani S, et al. TCF7L2 rs7903146 impairs islet function and morphology in non-diabetic individuals.Diabetologia, 2012; 10, 2677-81.

10.Zhou Y, Park SY, Su J, et al. TCF7L2 is a master regulator of insulin production and processing.Hum Mol Genet, 2014; 24, 6419-31.

Table S1. Genotypic and Allelic Distributions of Single Nucleotide Polymorphisms ofandGene

GeneSNPsGenotype/alleleT2DMNon-T2DMχ2valueP value TCF7L2rs7903146TT3 (1.32)16 (0.30)7.82350.0200 CT24 (10.57)701 (13.27) CC200 (88.11)4567 (86.43) T30 (6.61)733 (6.94)0.00620.9372 C424 (93.39)9835 (93.06) rs290487TT99 (43.61)2231 (42.22)2.16210.3392 CT108 (47.58)2417 (45.74) CC20 (8.81)636 (12.04) T306 (67.40)6879 (65.09)0.42810.5129 C148 (32.60)3689 (34.91) rs11196218*GG128 (57.40)2814 (54.13)1.88060.3905 AG77 (34.53)2024 (38.93) AA18 (8.07)361 (6.94) A113 (25.34)2746 (26.41)0.56420.4526 G333 (74.66)7652 (73.59) GCGrs12104705*TT032 (0.62)2.71050.2579 CT36 (16.14)695 (13.37) CC187 (83.86)4472 (86.02) T36 (8.07)759 (7.30)0.01500.9026 C410 (91.93)9639 (92.70)

. Data were number (%).*The genotypes of 89 participants of SNP rs11196218 and rs12104705 deletion respectively.

Table S2. Association ofandSNPs with Risk of Incident T2DM during Follow-up

SNPGenotypeCrude HR (95% CI)P valueAdjusted HR (95% CI)*P value* rs7903146CCReferenceReference CT0.815 (0.533-1.246)0.34521.028 (0.647-1.633)0.9070 TT3.799 (1.213-11.893)0.02194.068 (1.270-13.026)0.0181 TT+CT vs. CC0.893 (0.597-1.336)0.58291.133 (0.731-1.755)0.5771 TT vs. CT+CC3.893 (1.244-12.175)0.01954.051 (1.268-12.946)0.0183 rs290487TTReferenceReference CT1.027 (0.781-1.351)0.84731.033 (0.745-1.433)0.8466 CC0.792 (0.489-1.281)0.34170.827 (0.478-1.430)0.4958 CC+CT vs. TT0.981 (0.754-1.277)0.88770.991 (0.724-1.356)0.9526 CC vs. CT+TT0.781 (0.493-1.237)0.29190.813 (0.483-1.367)0.4343

Continued

SNPGenotypeCrude HR (95% CI)P valueAdjusted HR (95% CI)*P value* rs11196218AAReferenceReference AG0.676 (0.404-1.129)0.13480.928 (0.486-1.772)0.8206 GG0.818 (0.499-1.343)0.42570.974 (0.517-1.834)0.9351 GG+AG vs. AA0.757 (0.467-1.227)0.25800.954 (0.515-1.770)0.8818 GG vs. AG+AA1.137 (0.870-1.485)0.34641.038 (0.757-1.425)0.8164 rs12104705CCReferenceReference CT1.285 (0.898-1.838)0.16961.236 (0.803-1.903)0.3354 TTNA0.9755NA0.9765 TT+CT vs. CC1.239 (0.866-1.772)0.24071.174 (0.762-1.807)0.4666 TT vs. CT+CCNA0.9754NA0.9763

. The analysis involved 5284 normoglycemic individuals and 227 new-onset diabetes patients during follow-up.*Adjusted for baseline age, sex, family history of T2DM, smoking, alcohol intake, physical activity level, BMI, waist circumference, fasting plasma glucose, total cholesterol, triglyceride, HDL-C and LDL-C. NA not available.

^Zhang Lu and Zhang Ming contributed equally to this manuscript.

#Correspondence should be addressed to HU Dong Sheng, Professor, PhD, Tel: 86-755-86671951, E-mail: hud@szu.edu.cn, and LUO Xin Ping, Professor, PhD, Tel: 86-755-86671951, E-mail: lxp2005@szu.edu.cn

Biographical notes of the first authors: Zhang Lu, female, born in 1977, postgraduate, majoring in epidemiology; Zhang Ming, female, born in 1980, PhD, lecturer, majoring in epidemiology.

Accepted: August 11, 2016

10.3967/bes2016.108

June 7, 2016;

*This study was supported by the National Natural Science Foundation of China (Nos. 81373074 and 81402752); Science and Technology Development Foundation of Shenzhen (No. JCYJ20140418091413562); Natural Science Foundation of Shenzhen University (No. 201404); and High-level Personnel Special Support Project of Zhengzhou University (No. ZDGD13001).