EXT2基因多态性与南方人2型糖尿病的相关性研究
发表时间：2010-07-06 浏览次数：518次
作者：马聪, 盛宏光, 罗嘉俊 作者单位：江苏大学医学院，江苏 镇江212001; 上海市徐汇区中心医院内分泌科，上海 200031;上海市普陀区人民医院内科，上海 200060
【摘要】目的： 探讨EXT2基因多态性与2型糖尿病及其代谢指标的相关性。方法： 研究对象均来自于上海地区，其中糖尿病患者共286例，正常人300例。RFLP法检测基因位点rs3740878, rs11037909 和 rs1113132的多态性。HardyWeinberg平衡法检测基因型的频率，同时对糖尿病组和正常组的代谢指标进行比较。结果： 对于rs3740878 位点：2型糖尿病组A等位基因和AA基因型的频率分别为71%,53.5%，显著高于正常组(65.3%, 47.3%,P<0.01或P<0.05)，A等位基因携带者患2型糖尿病的风险是G等位基因携带者的1.30倍(OR=1.30, 95% CI：1.017-1.665,P=0.036)，AA基因型患糖尿病的风险是GG基因型的1.68倍(OR=1.68, 95% CI：1.022-2.773, χ2=4.233,P=0.04);同样对于位点rs11037909：2型糖尿病组TT基因型的频率为56.70%显著高于正常组46.3%(χ2=18.262, P<0.000 1)，2型糖尿病组T基因的频率74.7%显著高于正常组65.7%(χ2=20.467, P<0.000 1)。杂合体CT基因型和纯合体TT基因型患2型糖尿病的风险分别是CC基因型的1.9倍(OR=1.9, 95%CI：1.063-3.405, χ2=4.776, P=0.029)和 2.497倍(OR=2.497, 95%CI：1.419-4.369, χ2=10.482, P=0.001)。但是并没有发现这两个基因位点多态性与代谢指标之间有相关性，同样对于rs1113132位点来说，基因型与等位基因的分布在正常组和糖尿病组并没有显著的统计学差异。结论: 基因EXT2两个多态性位点(rs3740878) 和(rs11037909)中的等位基因A和T与中国南方人的2型糖尿病有显著的相关性，而位点rs1113132的多态性可能与中国南方人的2型糖尿病无关。
【关键词】 2型糖尿病; 单核苷酸多态性; EXT2基因
Association studies of polymorphisms in EXT2(exostoses 2) gene with type 2 diabetes in southern Chinese population
MA Cong， SHENG Hongguang， LUO Jiajun
(School of Medicine， Jiangsu University, Zhenjiang Jiangsu 212001;Department of Endocrinology, Xuhui District Central Hospital, Shanghai 200031; Department of Internal Medicine,People′s Hospital of Putuo District,Shanghai 200060,China)
[Abstract]Objective: To investigate the association of EXT2 gene polymorphisms(rs3740878, rs11037909, rs1113132 )with type 2 diabetes mellitus and the relevant metabolic parameters. Methods： A total of 286 cases with type 2 diabetes mellitus(type 2 diabetes group) and 300 normal group(NC group) from Shanghai area were used in the study. Polymorphisms of rs3740878, rs11037909 and rs1113132 were determined by polymerase chain reactionrestriction fragment length polymorphism(PCRRFLP) assay with the genomic DNA. The genotype frequency was analyzed by HardyWeinberg disequilibrium. Meanwhile the metabolic parameters were compared between the two groups. Results: The frequencies of A allele and AA genotype of rs3740878 in type 2 diabetes group were 71% and 53.5%, and were significantly higher than those in NC group(65.3% and 47.3%, P<0.01 or P<0.05). The risk of type 2 diabetes for those carrying A allele was 1.30 times higher than those carrying G allele(OR=1.30, 95% CI:1.017-1.665,P=0.036). As compared with the people with GG genotype, those with AA genotype showed 1.68 times increased risk of type 2 diabetes(OR=1.68, 95% CI:1.022-2.773,χ2=4.233, P=0.04). Similarly,as for rs11037909 the TT(56.7%) genotype in type 2 diabetes was significantly higher than normal(46.3%) group(χ2=18.262, P<0.000 1),the allele of T(74.7%) in type 2 diabetes was also higher than the normal(65.7%) group(χ2=20.467, P<0.000 1). Compared with homozygotes(CC) the heterozygotes(CT) increases susceptibility to type 2 diabetes 1.9(OR=1.9, 95% CI:1.063-3.405, χ2=4.776, P=0.029) times and compared with homozygotes(CC) the homoozygotes(TT) increases susceptibility to type 2 diabetes 2.497(OR=2.497, 95% CI:1.419-4.369, χ2=10.482, P=0.001) times. However we found no association between the two SNPs and metabolic parameters. In addition, there were no significant differences in the frequency of rs1113132 polymorphism between type 2 diabetes and normal groups. Conclusion: The A allele(rs3740878) and the T allele(rs11037909) of EXT2 polymorphism were positively associated with T2DM in South Chinese population in Shanghai area.While the site rs1113132 may have nothing to do with type 2 diabetes mellitus in South of China.
[Key words]type 2 diabetes; single nucleotide polymorphism; EXT2 gene
It is reported that the total number of people with type 2 diabetes in China is estimated to increase from 20.8 million in 2000 to 42.3 million in 2030[1]. Besides the important contribution of environmental factors, including changes in dietary patterns and lifestyle, genetic determinants also play a major role in type 2 diabetes susceptibility. Over the past decade, serious efforts have been put into the search for type 2 diabetes susceptibility genes, but progress is slower than anticipated[2,3].Up to date, only a few genetic variants leading to type 2 diabetes have been clearly identified[4]. The recent availability of highdensity genotyping arrays has presented the opportunity for genomewide association studies. First such a study has identified several novel risk loci for type 2 diabetes, in particular, a nonsynonymous single nucleotide polymorphism(SNP) in the gene for exostoses 2(EXT2; rs3740878, rsll037909 and rs 1113132)[5]. For future application of these risk alleles in the assessment of the overall diabetes risk, it is important to validate whether these variants have the same effect in Chinese population, who have different genetic background and lower diabetes prevalence compared with European populations[6-8].
1 Subjects and Methods
1.1 Study subjects
All type 2 diabetes patients were selected from the outpatient or inpatient at the Endocrinology Department in Xuhui District Central Hospital and Putuo People′s Hospital in Shanghai according to the diagnosis criteria recommended by WHO in 1999. There were a total of 286 type 2 diabetes cases including 135 females and 151 males with mean age at(76.0±10.3)years. Following conditions were excluded: other types of diabetes mellitus, abnormalities in liver or renal functions, creatinine being over 1.2 times of normal upper limit, ALT being more than twice the normal upper limit, and islet cell antibodies being positive. In addition, a total of 300 control cases were included with 158 females and 142 males having a mean age at(77.1±9.9)years. All control cases were healthy without family history of type 2 diabetes within three generations. OGTT test was used to rule out type 2 diabetes in the controls. The whole study were approved by the ethnic committee of the hospital and informed consents were obtained from all participants.
1.2 Methods
The subjects were fasted at least 10 hours and 1 ml elbow vein blood was obtained in the morning. The blood sample was treated with sodium citrate for anticoagulation and preserved at -80℃ for genomic DNA extraction. OGTT test with 75 g glucose was performed for all subjects. Blood glucose was detected with glucose oxidase method(detected by the central laboratory in Xuhui District Central Hospital). And insulin was detected with radioimmunoassay(detected by the central laboratory in Xuhui District Central Hospital).
1.3 SNP analysis
Genomic DNA was isolated by a kit from Shanghai Tiangen Biotech Co., Ltd. Polymerase chain reaction(PCR) was used to amplify the genomic sequences containing rs3740878, rs11037909 and rs1113132 with following primers: 5′GAGGCTCACTTACCTCTCCAC3′and 5′TGAGCCAGACAGAGTTGAATG3′for rs3740878: 5′CCTTGTGATTAATCTTATGAGAGAA3′and 5′GCAATATCTTCACAGTTCATATG3′for rs11037909:5′GGAAGCCTAAAGGATAGAACAG3′and 5′AGAAGGTACTGGAAGTTCCTC 3′for rs1113132.To determine the polymorphism of rs3740878, rs11037909 and rs1113132 the PCR fragments were digested with TaqⅠ,Alu and PuvⅡ respectively,then followed by electrophoresis in agarose gel. As for rs3740878 the AA genotype gave rise to a single 264 bp fragment. The AG genotype gave rise to a mixed 264 bp,137 bp and 127 bp fragments. The GG genotype was represented by a mixed 137 bp, 127 bp fragments. Then the polymorphism of rs11037909 gave rise to CC,CT,TT three genotypes.The CC genotype was represented by a single 203 bp fragment, the CT genotype gave rise to mixed fragments with 203 bp,133 bp,70 bp.The TT genotype was represented by 133 bp and 70 bp fragments;while the rs1113132 was also divided into GG(196 bp),CC(154 bp,42 bp) and CG(196 bp,154 bp,42 bp) three genotypes.
1.4 Statistical analysis
Data were processed with SPSS13.0 software. HardyWeinberg disequilibrium was used to test the population representatives of each genomic frequency. All data were tested for normality. Date with normal distribution were expressed mean±s and the data with nonnormal distribution(FINS, and age) were logtransformed to normal distribution for analysis. Quantitative data were compared with χ2 test. Multigroup comparison was performed with variance and covariance analysis. Logistic regression analysis was used to analyze the association of genotype with disease.
2 Results
2.1 Metabolic parameters in the two groups
The clinical and laboratory data of total 286 cases with type 2 diabetes and 300 normal controls(NC) from Shanghai area were used in the study(Tab 1). After adjustment for age and gender, the body mass index(BMI),waist circumstance(WC),HbA1c,FPG, 2hPG, HDLC,SBP and DBP of the type 2 diabetes group were significantly higher than NC group(P<0.01 or P<0.05). After adjustment for age, gender, WC and BMI, other parameters including FPG, 2hPG, HbA1c,HDLC and blood pressure were all significantly higher in the type 2 diabetes group than the NC group. There were no significant differences in LDLC between the two groups. Tab 1 Comparison of clinical and laboratory data between two groups(略)
2.2 The distribution of genotype and allele of rs3740878 in two groups
As regard with the rs3740878 polymorphism(Tab 2 and Fig 1), the distributions of AA, AG and GG in both groups were in consistent with HardyWeinberg equilibrium(P>0.05). AA genotype frequencies of the type 2 diabetes and normal groups were 53.5% and 47.3% respectively, and the frequency of AA genotype in the type 2 diabetes group was significantly higher than NC group(χ2=7.561, P<0.05). The frequencies of A allele was 71% and 65.3% in type 2 diabetes and NC groups, and the former was significantly higher than the latter(χ2=8.302, P<0.01). Based on these data, it was calculated that the risk of type 2 diabetes for those carrying A allele was 1.30 fold higher than those carrying G allele(OR=1.30, 95% CI: 1.017-1.665,χ2=4.379, P=0.036). After adjustment of age, gender, WC and BMI, nonconditional logistic regression analysis revealed that those with AA genotype had 1.68 fold increased risks of type 2 diabetes as compared with those carrying GG genotype(OR=1.68, 95% CI:1.022-2.773, χ2=4.233, P=0.04), while the AG genotype didn′t increase the risk as compared with the GG genotype.When metabolic parameters were considered, there were no significant differences between the three genotypes.Tab 2 The distribution of genotype and allele of rs3740878 in two groups(略)
2.3 The distribution of genotype and allele of rs11037909 in two groups
As the locus for rs11037909(Fig 2 and Tab 3), the distributions of CC, CT and TT in both groups were in consistent with HardyWeinberg equilibrium(P>0.05). TT genotype frequencies of the type 2 diabetes and normal groups were 56.7% and 46.3% respectively, and the frequency of TT genotype in the type 2 diabetes group was significantly higher than NC group(χ2=18.262, P<0.000 1). The frequencies of T allele was 74.7% in T2DM and 65.7% in normal groups. And the frequency of T allele in the type 2 diabetes group was significantly higher than NC group(χ2=20.467, P<0.000 1). Based on these data, it was calculated that the risk of type 2 diabetes for those carrying T allele was 1.54 fold higher than those carrying C allele(OR=1.54, 95% CI:1.196-1.982, χ2=11.265, P=0.001). After adjustment of age, gender, WC and BMI, nonconditional logistic regression analysis revealed that rs11037909 increases susceptibility to type 2 diabetes 1.9(OR=1.9, 95%CI:1.063-3.405, χ2=4.776, P=0.029) times for heterozygotes(CT) compared with homozygotes(CC) and 2.497(OR=2.497, 95%CI:1.419-4.369, χ2=10.482, P=0.001) times for homozygotes(TT) compared with homozygotes(CC),and also the metabolic parameters in different genotypes made no sense.Tab 3 The distribution of genotype and allele of rs11037909 in two groups(略)
2.4 The distribution of genotype and allele of rs1113132 in two groups
As for the polymorphism of rs1113132(Tab 4 and Fig 3), the distribution of the CC, CG and GG genotypes in each group were in consistent with HardyWeinberg equilibrium(type 2 diabetes group: χ2=2.527, P=0.283;normal group: χ2=1.183, P=0.554). The genotype frequencies of CC,GG and CG in type 2 diabetes and normal groups were 47.2%, 12.9%, 39.9% and 45.0%, 16.0%, 39.0%, respectively. There was no significant difference(χ2=5.523, P=0.063); While the frequencies of C allele was 67.1% and 64.5% in type 2 diabetes and andnormal groups, and the frequency of C allele in the type 2 diabetes group was significantly higher than NC group(χ2=6.157, P=0.013).Tab 4 The distribution of genotype and allele of rs1113132 in two groups(略)
3 Discussion
In this study of southern Chinese Han people,we replicated associations with several diabetes susceptibility variants recently identified in White Europeans[9-12]. Through the studies of 586 cases of Chinese subpopulation in Shanghai region, this study indicated that rs3740878 and rs11037909 of EXT2 gene was associated with type 2 diabetes in the Chinese subpopulation in Shanghai area. With respect to the genotypes of the two sites on EXT2 gene, the distributions were significantly different between normal and type 2 diabetes groups(P<0.05, 0.01), which is consistent with the results from the original study[9]. But they were largely negative in the subsequent four GWASs and other replication studies in samples from U.K.[10,12], Finnish[13,14], Swedish[13], Icelandic[11],German[15], Japanese[16] populations and another study in Shanghai area[17].Maybe this study had a smaller sample size.The frequencies of G allele(rs3740878) and C allele(rs11037909) in the normal groups were 34.7% and 34.3%[consistent with the frequency of 37.5%(rs3740878) and 34.4%(rs11037909) in Chinese population reported in SNP of NCBI]. The frequency of A and T alleles were significantly different between the normal and the type 2 diabetes groups, suggesting that the A allele of rs3740878 and the T allele of rs11037909 were positively associated with T2DM in the Chinese subpopulation in Shanghai area. However, our results suggested that there were no significant differences between type 2 diabetes and normal groups for rs1113132, it was not consistent with a GWA study of French Caucasians[18].
During the pathogenesis of type 2 diabetes,insulin resistance of peripheral tissues(liver,skeletal muscle,and adipose tissue) provokes compensatory increments in insulin secretion by pancreatic βcells.When insulin resistance is no longer compensated and βcells exhaust, hyperglycemia arises[19]. The present study demonstrated that the blood glucose, blood pressure and blood lipid of the T2DM group were higher than the control group after adjustment of age and BMI, consistent with the clinical manifestations and pathophysiological features of metabolic disturbances in type 2 diabetes.
EXT2 gene is located on 11p12-p11.In a baseline quantitative traits[20], for a crude analysis,they noted apparent associations of genotype at EXT2 rs3740878 with baseline βcell function, as measured by the insulinogenic index.The EXT2 rs3740878 risk T allele was nominally associated with reduced insulin secretion in carriers of the highrisk genotype compared with those with lowrisk genotype(P=0.001): this difference may have been driven in part by a compensatory response to the borderline higher insulin resistance of CC homozygotes. When adjusted for selfreported ethnicity, however, the above associations at EXT2 was abolished. In this study we also found no association between the genotypes and metabolic parameters. However, another research indicated that[21]: Two SNPs in EXT2(rs3740878 and rs1113132) among nondiabetic Pima Indians were associated with several measures of insulin resistance, including a lower insulinstimulated glucose disposal rate in response to a hyperinsulinemiceuglycemic clamp(P=0.03, adjusted for age, sex, and percent body fat), and elevated glucose and insulin levels during an OGTT(P=0.04, 0.03, and 0.008 for 1-h glucose, 1-h insulin, and 2-h insulin levels, respectively, adjusted for age, sex, and percent body fat), despite no difference in percentage of body fat(P=0.32, adjusted for age and sex).But what is the real function EXT2 ? Does it have relations with βcells or insulin resistance ? A further study is needed !
These study indicates that the two of the SNPs(rs3740878, rs11037909) in EXT2 gene are major type 2 diabetes locus in southern Chinese population.At the moment we still cannot say whether its effect is depend on insulin sensitivity or secretion ? We have not observed a significant association between the rs1113132 and diabetes risk.
Such discrepancy is probably due to small sample size of the present study or due to the differences of regions and ethnic groups. So the relationship of rs1113132 and type 2 diabetes needs to be confirmed by additional studies.Further studies are required to understand better the differences in insulin dynamics that result from variants at this and other diabetes associated genes identified to date.
(Acknowledgement: Sincere gratitude should be extended to the academician Wang Enduo and Chen Yan and their colleagues from Chinese Academy of Sciences, for their great support. Particularly, we are grateful for the earnest instruction of experimental techniques by Pro. Wang Enduo.)
【参考文献】
[1]Boutayeb A, Boutayeb S. The burden of non communicable diseases in developing countries[J].Int J Equity Health, 2005,4(1):2.
[2]Das SK, Elbein SC.The genetic basis of type 2 diabetes[J]. Cell Sci,2006, 2(4):100-131.
[3]Owen KR, McCarthy MI.Genetics of type 2 diabetes[J]. Curr Opin Genet Dev,2007,17(3):239-244.
[4]O′Rahilly S, Barroso I,Wareham NJ. Genetic factors in type 2 diabetes: the end of the beginning?[J].Science,2005,307(5708):370-373.
[5]Sladek R, Rocheleau G, Rung J, et al.A genomewide association study identifies novel risk loci for type 2 diabetes[J].Nature,2007,445(7130):881-885.
[6]International HapMap Consortium.A haplotype map of the human genome[J]. Nature,2005,437(7063):1299-1320.
[7]International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs[J]. Nature,2007,449(7164):851-861.
[8]Wild S, Roglic G, Green A, et al. Global prevalence of diabetes:estimates for the year 2000 and projections for 2030[J]. Diabetes Care,2004,27(5):1047-1053.
[9]Sladek R, Rocheleau G, Rung J.A genomewide association study identifies novel risk loci for type 2 diabetes[J]. Nature,2007,445(7130):881-885.
[10]Wellcome Trust Case Control Consortium. Genomewide association study of 14000 cases of seven common diseases and 3000 shared controls[J].Nature, 2007,447(7145):661-678.
[11]Steinthorsdottir V, Thorleifsson G, Reynisdottir I.A variant in CDKAL1 influences insulin response and risk of type 2 diabetes[J]. Nat Genet, 2007,39(6):770-775.
[12]Zeggini E, Weedon MN, Lindgren CM. Replication of genomewide association signals in UK samples reveals risk loci for type 2 diabetes[J]. Science, 2007,316(5829):1336-1341.
[13]Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, and Novartis Institutes of BioMedical Research.Genomewide association analysis identifies loci for type 2 diabetes and triglyceride levels[J].Science,2007,316(5829):1331-1336.
[14]Scott LJ, Mohlke KL, Bonnycastle LL.A genomewide association study of type 2 diabetes in Finns detects multiple susceptibility variants[J]. Science, 2007,316(5829):1341-1345.
[15]Schulze MB, AlHasani H, Boeing H. Variation in the HHEXIDE gene region predisposes to type 2 diabetes in the prospective, populationbased EPICPotsdam cohort[J]. Diabetologia,2007,50(11):2405-2407.
[16]Horikoshi M, Hara K, Ito C.Variations in the HHEX gene are associated with increased risk of type 2 diabetes in the Japanese population[J].Diabetologia,2007,50(12):2461-2466.
[17]Wu Y, Li H, Loos RJ, et al.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[J].Diabetes, 2008,57(10):2834-2842.
[18]Sladek R, Rocheleau G, Rung J, et al. A genomewide association study identifies novel risk loci for type 2 diabetes[J]. Nature, 2007,445(7130):881-885.
[19]Weyer C,Bogards C, Mott DM. The natural history of insulin secretory dysfunction and insulin resistance in the pathogenesis of type 2 diabetes mellitus[J].J Clin Invest, 1999,104(6):787-794.
[20]Moore AF, Jablonski KA,McAteer JB. Extension of type 2 diabetes genomewide association scan results in the diabetes prevention program[J].Diabetes, 2008,57(9):2503-2510.
[21]Rong R, Hanson RL, Ortiz D, et al. 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[J]. Diabetes,2009,58(2): 478-488.
