Population Specific Impact of Genetic Variants in KCNJ11 Gene to Type 2 Diabetes: A Case-Control and Meta-Analysis Study

Background and Objectives

Potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene have a key role in insulin secretion and is of substantial interest as a candidate gene for type 2 diabetes (T2D). The current work was performed to delineate the genetic influence of KCNJ11 polymorphisms on risk of T2D in South Indian population through case-control association study along with systematic review and meta-analysis.

Methods

A case-control study of 400 T2D cases and controls of South Indian origin were performed to analyze the association of KCNJ11 polymorphisms (rs5219, rs5215, rs41282930, rs1800467) and copy number variations (CNV) on the risk of T2D. In addition a systematic review and meta-analysis for KCNJ11 rs5219 was conducted in 3,831 cases and 3,543 controls from 5 published reports from South-Asian population by searching various databases. Odds ratio with 95% confidence interval (CI) was used to assess the association strength. Cochran''s Q, I² statistics were used to study heterogeneity between the eligible studies.

Results

KCNJ11 rs5215, C-G-C-C haplotype and two loci analysis (rs5219 vs rs1800467) showed a significant association with T2D but CNV analysis did not show significant variation between T2D cases and control subjects. Lower age of disease onset (P = 0.04) and higher body mass index (BMI) (P = 0.04) were associated with rs5219 TT genotype in T2D patients. The meta-analysis of KCNJ11 rs5219 on South Asian population showed no association on susceptibility to T2D with an overall pooled OR = 0.98, 95% CI = 0.83–1.16. Stratification analysis showed East Asian population and global population were associated with T2D when compared to South Asians.

Conclusion

KCNJ11 rs5219 is not independently associated with T2D in South-Indian population and our meta-analysis suggests that KCNJ11 polymorphism (rs5219) is associated with risk of T2D in East Asian population and global population but this outcome could not be replicated in South Asian sub groups.     

Identification of New Genetic Risk Variants for Type 2 Diabetes

Although more than 20 genetic susceptibility loci have been reported for type 2 diabetes (T2D), most reported variants have small to moderate effects and account for only a small proportion of the heritability of T2D, suggesting that the majority of inter-person genetic variation in this disease remains to be determined. We conducted a multistage, genome-wide association study (GWAS) within the Asian Consortium of Diabetes to search for T2D susceptibility markers. From 590,887 SNPs genotyped in 1,019 T2D cases and 1,710 controls selected from Chinese women in Shanghai, we selected the top 2,100 SNPs that were not in linkage disequilibrium (r²<0.2) with known T2D loci for in silico replication in three T2D GWAS conducted among European Americans, Koreans, and Singapore Chinese. The 5 most promising SNPs were genotyped in an independent set of 1,645 cases and 1,649 controls from Shanghai, and 4 of them were further genotyped in 1,487 cases and 3,316 controls from 2 additional Chinese studies. Consistent associations across all studies were found for rs1359790 (13q31.1), rs10906115 (10p13), and rs1436955 (15q22.2) with P-values (per allele OR, 95%CI) of 6.49×10⁻⁹ (1.15, 1.10–1.20), 1.45×10⁻⁸ (1.13, 1.08–1.18), and 7.14×10⁻⁷ (1.13, 1.08–1.19), respectively, in combined analyses of 9,794 cases and 14,615 controls. Our study provides strong evidence for a novel T2D susceptibility locus at 13q31.1 and the presence of new independent risk variants near regions (10p13 and 15q22.2) reported by previous GWAS.     

Meta-Analysis of the Relationship between Common Type 2 Diabetes Risk Gene Variants with Gestational Diabetes Mellitus

Background

A number of case-control studies were conducted to investigate the association of common type 2 diabetes (T2D) risk gene polymorphisms with gestational diabetes mellitus (GDM). However, these studies have yielded contradictory results. We therefore performed a meta-analysis to derive a more precise estimation of the association between these polymorphisms and GDM, hence achieve a better understanding to the relationship between T2D and GDM.

Methods

PubMed, EMBASE, ISI web of science and the Chinese National Knowledge Infrastructure databases were systematically searched to identify relevant studies. Data were abstracted independently by two reviewers. A meta-analysis was performed to examine the association between 9 polymorphisms from 8 genes and susceptibility to GDM. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Heterogeneity among articles and their publication bias were also tested.

Results

We identified 22 eligible studies including a total of 10,336 GDM cases and 17,445 controls. We found 8 genetic polymorphisms were significantly associated with GDM in a random-effects meta-analysis. These polymorphisms were in or near the following genes: TCF7L2 (rs7903146), MTNR1B (rs10830963), IGF2BP2 (rs4402960), KCNJ11 (rs5219), CDKAL1 (rs7754840), KCNQ1 (rs2237892 and rs2237895) and GCK (rs4607517); while no association was found for PPARG with GDM risk. Similar results were also observed under dominant genetic model for these polymorphisms.

Conclusions

This meta-analysis found 8 genetic variants associated with GDM. The relative contribution and relevance of the identified genes in the pathogenesis of GDM should be the focus of future studies.     

Genetic Variants of TPCN2 Associated with Type 2 Diabetes Risk in the Chinese Population

Objective

The aim of this study was to determine whether TPCN2 genetic variants are associated with type 2 diabetes and to elucidate which variants in TPCN2 confer diabetes susceptibility in the Chinese population.

Research Design and Methods

The sample population included 384 patients with type 2 diabetes and 1468 controls. Anthropometric parameters, glycemic and lipid profiles and insulin resistance were measured. We selected 6 TPCN2 tag single nucleotide polymorphisms (rs35264875, rs267603153, rs267603154, rs3829241, rs1551305, and rs3750965). Genotypes were determined using a Sequenom MassARRAY SNP genotyping system.

Results

Ultimately, we genotyped 3 single nucleotide polymorphisms (rs3750965, rs3829241, and rs1551305) in all individuals. There was a 5.1% higher prevalence of the rs1551305 variant allele in type 2 diabetes individuals (A) compared with wild-type homozygous individuals (G). The AA genotype of rs1551305 was associated with a higher diabetes risk (p<0.05). The distributions of rs3829241 and rs3750965 polymorphisms were not significantly different between the two groups. HOMA-%B of subjects harboring the AA genotype of rs1551305 decreased by 14.87% relative to the GG genotype.

Conclusions

TPCN2 plays a role in metabolic regulation, and the rs1551305 single nucleotide polymorphism is associated with type 2 diabetes risk. Future work will begin to unravel the underlying mechanisms.     

Genetic Variants Associated with Lipid Profiles in Chinese Patients with Type 2 Diabetes

Dyslipidemia is a strong risk factor for cardiovascular disease among patients with type 2 diabetes (T2D). The aim of this study was to identify lipid-related genetic variants in T2D patients of Han Chinese ancestry. Among 4,908 Chinese T2D patients who were not taking lipid-lowering medications, single nucleotide polymorphisms (SNPs) in seven genes previously found to be associated with lipid traits in genome-wide association studies conducted in populations of European ancestry (ABCA1, GCKR, BAZ1B, TOMM40, DOCK7, HNF1A, and HNF4A) were genotyped. After adjusting for multiple covariates, SNPs in ABCA1, GCKR, BAZ1B, TOMM40, and HNF1A were identified as significantly associated with triglyceride levels in T2D patients (P < 0.05). The associations between the SNPs in ABCA1 (rs3890182), GCKR (rs780094), and BAZ1B (rs2240466) remained significant even after correction for multiple testing (P = 8.85×10⁻³, 7.88×10⁻⁷, and 2.03×10⁻⁶, respectively). BAZ1B (rs2240466) also was associated with the total cholesterol level (P = 4.75×10⁻²). In addition, SNP rs157580 in TOMM40 was associated with the low-density lipoprotein cholesterol level (P = 6.94×10⁻³). Our findings confirm that lipid-related genetic loci are associated with lipid profiles in Chinese patients with type 2 diabetes.     

Effect of Common Genetic Variants of Growth Arrest-Specific 6 Gene on Insulin Resistance,Obesity and Type 2 Diabetes in an Asian Population

Objectives

Growth arrest-specific 6 (Gas6), a vitamin K-dependent protein, has been implicated in systemic inflammation, obesity, and insulin resistance (IR). Data from recent studies suggest that polymorphisms in the Gas6 gene are associated with cardiovascular disorders and type 2 diabetes (T2D). However, the association of Gas6 gene variants with obesity, IR, and T2D development has not been explored.

Materials and Methods

Four common single nucleotide polymorphisms (SNPs) in the Gas6 gene were genotyped in 984 participants from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family cohort. An insulin suppression test was performed to determine IR based on steady-state plasma glucose (SSPG). Associations between IR indices and obesity, and SNP genotypes, based on previously-reported data for this cohort (Phase I), were analyzed. In the present follow-up study (Phase II), the effects of gene variants of Gas6 on the progression to T2D were explored in individuals who were free of T2D in Phase I. The mean follow-up period for Phase II was 5.7 years.

Results

The mean age of the study population in Phase I was 49.5 years and 16.7% of individuals developed T2D during follow-up. After adjusting for covariates, three SNPs (rs8191973, rs8197974, and rs7323932) were found to be associated with SSPG levels (p = 0.007, p = 0.03, and p = 0.011, respectively). This association remained significant after multiple testing and showed a significant interaction with physical activity for SNP rs8191973. However, no other significant correlations were observed between Gas6 polymorphisms and other indices of IR or obesity. A specific haplotype, AACG (from rs8191974, rs7323932, rs7331124, and rs8191973), was positively associated with SSPG levels (p = 0.0098). None of the polymorphisms were associated with an increased risk of T2D development.

Conclusions

Our results suggest that Gas6 gene variants are associated with IR, although their effects on subsequent progression to T2D were minimal in this prospective Asian cohort.     

Association of Type 2 Diabetes Genetic Variants with Breast Cancer Survival among Chinese Women

ObjectiveTo evaluate whether the genetic susceptibility of T2D was associated with overall survival (OS) and disease-free survival (DFS) outcomes for breast cancer (BC).MethodsIncluded in the study were 6346 BC patients who participated in three population-based epidemiological studies of BC and were genotyped with either GWAS or Exome-chip. We constructed a genetic risk score (GRS) for diabetes using risk variants identified from the GWAS catalog (http://genome.gov/gwastudies) that were associated with T2D risk at a minimum significance level of P ≤ 5.0E-8 among Asian population and evaluated its associations with BC outcomes with Cox proportional hazards models.ResultsDuring a median follow-up of 8.08 years (range, 0.01–16.95 years), 1208 deaths were documented in 6346 BC patients. Overall, the diabetes GRS was not associated with OS and DFS. Analyses stratified by estrogen receptor status (ER) showed that the diabetes GRS was inversely associated with OS among women with ER- but not in women with ER+ breast cancer; the multivariable adjusted HR was 1.38 (95% CI: 1.05–1.82) when comparing the highest to the lowest GRS quartiles. The association of diabetes GRS with OS varied by diabetes status (P for interaction <0.01). In women with history of diabetes, higher diabetes GRS was significantly associated with worse OS, with HR of 2.22 (95% CI: 1.28–3.88) for the highest vs. lowest quartile, particularly among women with an ER- breast cancer, with corresponding HR being 4.59 (95% CI: 1.04–20.28). No significant association between the diabetes GRS and OS was observed across different BMI and PR groups.ConclusionsOur study suggested that genetic susceptibility of T2D was positively associated with total mortality among women with ER- breast cancer, particularly among subjects with a history of diabetes. Additional studies are warranted to verify the associations and elucidate the underlying biological mechanism.     

Common Genetic Variants of Surfactant Protein-D (SP-D) Are Associated with Type 2 Diabetes

Context

Surfactant protein-D (SP-D) is a primordial component of the innate immune system intrinsically linked to metabolic pathways. We aimed to study the association of single nucleotide polymorphisms (SNPs) affecting SP-D with insulin resistance and type 2 diabetes (T2D).

Research Design and Methods

We evaluated a common genetic variant located in the SP-D coding region (rs721917, Met³¹Thr) in a sample of T2D patients and non-diabetic controls (n = 2,711). In a subset of subjects (n = 1,062), this SNP was analyzed in association with circulating SP-D concentrations, insulin resistance, and T2D. This SNP and others were also screened in the publicly available Genome Wide Association (GWA) database of the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC).

Results

We found the significant association of rs721917 with circulating SP-D, parameters of insulin resistance and T2D. Indeed, G carriers showed decreased circulating SP-D (p = 0.004), decreased fasting glucose (p = 0.0002), glycated hemoglobin (p = 0.0005), and 33% (p = 0.002) lower prevalence of T2D, estimated under a dominant model, especially among women. Interestingly, these differences remained significant after controlling for origin, age, gender, and circulating SP-D. Moreover, this SNP and others within the SP-D genomic region (i.e. rs10887344) were significantly associated with quantitative measures of glucose homeostasis, insulin sensitivity, and T2D, according to GWAS datasets from MAGIC.

Conclusions

SP-D gene polymorphisms are associated with insulin resistance and T2D. These associations are independent of circulating SP-D concentrations.     

Cumulative Effect and Predictive Value of Genetic Variants Associated with Type 2 Diabetes in Han Chinese: A Case-Control Study

Background

Genome-wide association studies (GWAS) have identified dozens of single nucleotide polymorphisms (SNPs) associated with type 2 diabetes risk. We have previously confirmed the associations of genetic variants in HHEX, CDKAL1, VEGFA and FTO with type 2 diabetes in Han Chinese. However, the cumulative effect and predictive value of these GWAS identified SNPs on the risk of type 2 diabetes in Han Chinese are largely unknown.

Methodology/Principal Findings

We conducted a two-stage case-control study consisting of 2,925 cases and 3,281controls to examine the association of 30 SNPs identified by GWAS with type 2 diabetes in Han Chinese. Significant associations were found for proxy SNPs at KCNQ1 [odds ratio (OR) = 1.41, P = 9.91 × 10–16 for rs2237897], CDKN2A/CDKN2B (OR = 1.30, P = 1.34 × 10–10 for rs10811661), CENTD2 (OR = 1.28, P = 9.88 × 10-4 for rs1552224) and SLC30A8 (OR = 1.19, P = 1.43 × 10-5 for rs13266634). We further evaluated the cumulative effect on type 2 diabetes of these 4 SNPs, in combination with 5 SNPs at HHEX, CDKAL1, VEGFA and FTO reported previously. Individuals carrying 12 or more risk alleles had a nearly 4-fold increased risk for developing type 2 diabetes compared with those carrying less than 6 risk alleles [adjusted OR = 3.68, 95% confidence interval (CI): 2.76–4.91]. Adding the genetic factors to clinical factors slightly improved the prediction of type 2 diabetes, with the area under the receiver operating characteristic curve increasing from 0.76 to 0.78. However, the difference was statistically significant (P < 0.0001).

Conclusions/Significance

We confirmed associations of SNPs in KCNQ1, CDKN2A/CDKN2B, CENTD2 and SLC30A8 with type 2 diabetes in Han Chinese. The utilization of genetic information may improve the accuracy of risk prediction in combination with clinical characteristics for type 2 diabetes.     

GWAS在2型糖尿病相关基因研究中的应用

2型糖尿病(type 2 diabetes,T2D)是一种常见的复杂疾病,其发病受到遗传和环境因素的共同作用.全基因组关联研究(genome-wide association study,GWAS)是一种可在全基因组范围筛查疾病相关的序列变异的新型群体关联研究方法.近年来,采用GWAS以及在此基础上展开的meta分析,已分别在TCF7L2、HHEX-IDE、SLC30A8、CDKAL1、CDKN2A-CDKN2B、IGF2BP2、NOTCH2、CDC123-CAMK1D、ADAMTS9、THADA、TSPAN8-LGR5、JAZF1等12个基因区域鉴定出多个T2D相关的多态位点.已有的研究提示,上述多个基因可能在胰岛β细胞发育和功能维持方面扮演着重要角色.本文集中介绍了GWAS的原理及其在T2D研究中的优势;回顾了GWAS在T2D研究中的主要发现;并对运用GWAS在T2D研究中尚需解决的问题进行了总结和展望.     

Oxidative Stress-Related Genes in Type 2 Diabetes: Association Analysis and Their Clinical Impact

Worldwide prevalence of diabetes mellitus motivates a number of association studies to be conducted throughout the world. Eleven polymorphisms from nine candidate genes in oxidative stress pathway have been analyzed in eastern Indian type 2 diabetic patients (n = 145) and healthy controls (n = 100). Different biochemical parameters were also analyzed for their association with the disease. Significant associations were observed for rs2070424 A>G SOD1 (OR 3.91, 95% CI 2.265–8.142, P < 0.001), rs854573 A>G PON1 (OR 3.415, 95% CI 2.116–5.512, P < 0.001), rs6954345 G>C PON2 (OR 3.208, 95% CI 2.071–4.969, P < 0.001), RAGE rs1800624 ?374 T>A (OR 3.58, 95% CI 2.218–5.766, P < 0.001), and NOS3 ?786 T>C (OR 3.75, 95% CI 2.225–6.666, P < 0.001). Haplotype containing two risk alleles of PON1 and PON2 genes was significantly associated with disease (OR 8.34, 95% CI 1.554–44.804, P < 0.002). Our results suggest that carriers of major and efficient alleles of oxidative stress genes are more likely to survive the comorbid complications and single copy of risk allele is sufficient for developing the disease.     

Genetic Variants in PCSK1 Gene Are Associated with the Risk of Coronary Artery Disease in Type 2 Diabetes in a Chinese Han Population: A Case Control Study

Background

Insulin and glucagon-like peptide 1 (GLP-1), converted by proprotein convertase 1 (PC1/3) from proinsulin and proglucagon, are associated with type 2 diabetes (T2DM) and coronary artery disease (CAD). The aim of this study is to investigate the association of PCSK1 gene, which encodes PC1/3, with the risk of CAD in Chinese patients with T2DM.

Methods

We selected and genotyped 5 haplotype-tagging single nucleotide polymorphisms (SNPs) at PCSK1 gene (across 39873bp locus) in a case-control study of Chinese Han population involving 425 diabetic patients (62.1% male, mean age 63.2 years) with CAD as positive cases and 258 diabetic patients (44.2% male, mean age 62.0 years) without CAD as controls.

Results

The allele frequencies at rs3811951 were significantly different between cases and controls (30.7% vs. 37.2%), with the allele G associated with decreased risk for CAD (OR = 0.75, 95% CI = 0.59–0.94, p = 0.013). In recessive inheritance mode, the carriers of GG had a lower risk (OR = 0.50, 95%CI = 0.31–0.82, p = 0.005), even after adjusted for gender, age, BMI and smoking (OR = 0.43, 95%CI = 0.24–0.77, p = 0.004). The carriers of the minor allele A at rs156019 had a higher risk (OR = 1.66, 95%CI = 1.10–2.50, p = 0.016 after adjustment) in dominant inheritance mode. The SNP rs6234 was also significantly associated with CAD risk in women, with the carriers of the minor allele G at rs6234 associated with a reduced CAD risk in recessive inheritance mode (OR = 0.42, 95% CI = 0.18–0.95, p = 0.036 after adjustment).

Conclusions

Our results found that common genetic variants in PCSK1 were associated with CAD in Chinese patients with T2DM.     

磺酰脲类受体基因多态性与2型糖尿病的相关性研究

研 究磺酰脲类受体1（SUR1）基因外显子16-3c/t多态性在中国某南方汉族人群中是否为2型糖尿病的致病基因座。采用聚合酶链反应-限制酶酶切片段长度多态性（PCR-RFLP）方法对南方汉族46个2型糖尿病高发家系成员的SUR1基因外显子16的多态性进行分析。利用Mantel-Haenszel分层分析研究该基因座多态性与2型糖尿病的关系。在高发家系人群中,SUR1基因外显子16-3c/t多态性的基因型频率为：cc型29.3%、ct型507%、tt型20%,c等位基因频率为54.7%;患者组基因型频率为：cc型30.2% 、ct型53.8%、tt型16.0% ,c等位基因频率为57.1% ;未患病亲属组基因型频率为：cc型28.3% 、ct型47.2%、tt型24.5%,c等位基因频率为519%,两组间基因型和等位基因的差异经检验无统计学意义（分别为χ2=3.224,P=0.199;χ2=1.250,P=0264）。在性别、吸烟、饮酒、肥胖、高血压等混杂因素中的频率差异亦无显著性。c等位基因频率低于北方汉族人。在中国某南方汉族2型糖尿病高发家族人群中,未发现SUR1基因外显子16-3c/t多态性与2型糖尿病存在关联,该基因座可能不是该人群的致病基因。 Abstract:To study whether the 3c/t polymorphism of the sulfonylurea receptor 1 (SUR1) gene exon16 increased the risk of type 2 diabetes mellitus in type 2 diabetes mellitus pedigrees in Han population in south area of China.Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was used in 46 type 2 diabetes mellitus pedigrees.The polymorphism in SUR1 was tested and analyzed by Mantel-Haenszel χ2 test.Frequencies of SUR1-3c/t polymorphism had no significant difference between type 2 diabetes mellitus and normal relatives（genotypes χ2=3.224,P=0.199;frequency of allele χ2=1.250,P=0.264）.In all subjects,type 2 diabetes mellitus and normal relatives,SUR1-3c/t genotypes were listed (cc:29.3%,30.2%,28.3%;ct:50.7%,53.8%,47.2%;tt:20%,16.0%,24.5% respectively).The frequencies of c were 54.7%,57.1% and 51.9% respectively.The frequency of c is lower than Han population in northern China.The results show that SUR1 exon16-3c/t polymorphism is not associated with type 2 diabetes mellitus in the population.     

Genetic Variants Contribute to Gene Expression Variability in Humans

Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed.     

Investigation of Variants in UCP2 in Chinese Type 2 Diabetes and Diabetic Retinopathy

Purpose

The aim of this study was to investigate variants in UCP2 genes in type 2 diabetes mellitus (DM) and diabetic retinopathy (DR) in Chinese population.

Materials and Methods

We conducted a single nucleotide polymorphism-based and haplotype-based case-control study between the variants of UCP2 and DM and between the variants of UCP2 and DR in 479 Chinese patients with type 2 DM and 479 control subjects without DM. Two SNPs (rs660339 and rs659366) were selected as genetic markers.

Results

The risk allele C at UCP2 rs660339 was closely associated with DM in Chinese population. There was significant difference in rs660339 between DM and controls (P = 0.0016; OR [95%CI]  = 1.37 (1.14–1.65)). Subjects who were homozygous of the C allele were more likely to develop DM. The frequency of C allele was higher in DM (58%) than in control (51%). But this locus didn''t have a definite effect on the onset of non-proliferative diabetic retinopathy (NPDR) (P = 0.44; OR [95%CI]  = 0.80 (0.56–1.14)) and proliferative diabetic retinopathy (PDR) (P = 1.00; OR [95%CI]  = 0.99 (0.74–1.34)) comparing to subjects with DM without retinopathy (DWR), respectively. Moreover, the UCP2 rs659366 polymorphism showed no significant difference between DM and control (P = 0.66; OR [95%CI]  = 1.10 (0.91–1.32)). However, there was a significant difference between PDR and DWR (P = 0.016; OR [95%CI]  = 0.66 (0.49–0.90)), but there was no difference between NPDR and DWR (P = 1.00; OR [95%CI]  = 0.96 (0.67–1.37)). Participants who carried the G allele at rs659366 were more likely to develop PDR. For the haplotype, C-A was present more frequently in DM than in control (16% vs 7%), indicating that it was risky, and T-A was present less in DM than in control (29% vs 35%). Haplotype frequencies in DR and DWR showed no significant difference (P = 0.068).

Conclusion

It was indicated that UCP2 may be implicated in the pathogenesis of type 2 DM and DR in Chinese population.     

血管紧张素转换酶基因多态性与2型糖尿病发病的相关性研究

目的:探讨血管紧张素转换酶基因(ACE)多态性与其血清水平及2型糖尿病(T2D)发生的相关性.方法:应用聚合酶链反应检测T2D患者287例和正常对照组307例健康人的ACE基因Alu重复序列的插入/缺失(I/D)多态性,采用全自动生化分析仪检测ACE活性及血脂水平,采用SPSS11.0软件包统计分析基因型分布和等位基因频率与其活性、血脂水平及T2D的相关性.结果:ACE I/D多态性在T2D组(DD:13.36%、ID:45.93%、Ⅱ:40.72%)与对照组(DD:13.24%、ID:43.90%、Ⅱ:42.86%)的基因频率无显著性差异(P0.05).T2D组ACE各基因型之间ACE活性有显著性差异(P<0.01).T2D各基因型的血脂水平分析显示Ⅱ型与DD型之间HDL有显著性差异(P<0.05).结论:ACE基因DD型和D等位基因与ACE活性显著相关,但ACE I/D多态性不是T2DM发生的危险因素且无关,DD型与高HDL水平相关.     

Multi-Tissue Computational Modeling Analyzes Pathophysiology of Type 2 Diabetes in MKR Mice

Computational models using metabolic reconstructions for in silico simulation of metabolic disorders such as type 2 diabetes mellitus (T2DM) can provide a better understanding of disease pathophysiology and avoid high experimentation costs. There is a limited amount of computational work, using metabolic reconstructions, performed in this field for the better understanding of T2DM. In this study, a new algorithm for generating tissue-specific metabolic models is presented, along with the resulting multi-confidence level (MCL) multi-tissue model. The effect of T2DM on liver, muscle, and fat in MKR mice was first studied by microarray analysis and subsequently the changes in gene expression of frank T2DM MKR mice versus healthy mice were applied to the multi-tissue model to test the effect. Using the first multi-tissue genome-scale model of all metabolic pathways in T2DM, we found out that branched-chain amino acids'' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice. Microarray data showed low expression of genes in MKR mice versus healthy mice in the degradation of branched-chain amino acids and fatty-acid oxidation pathways. In addition, the flux balance analysis using the MCL multi-tissue model showed that the degradation pathways of branched-chain amino acid and fatty acid oxidation were significantly downregulated in MKR mice versus healthy mice. Validation of the model was performed using data derived from the literature regarding T2DM. Microarray data was used in conjunction with the model to predict fluxes of various other metabolic pathways in the T2DM mouse model and alterations in a number of pathways were detected. The Type 2 Diabetes MCL multi-tissue model may explain the high level of branched-chain amino acids and free fatty acids in plasma of Type 2 Diabetic subjects from a metabolic fluxes perspective.