| Diabetes is a metabolic disorder caused by a variety of causes, which ischaracterized by chronic hyperglycemia, accompanied by lack of insulin secretionand insulin resistance, leading to metabolic disorders of carbohydrates, fats, proteins,resulting in chronic injury to multiple organs and dysfunction failure. Type2diabetesis the most common type of diabetes, accounting for more than90%of all diabetescases. According to the International Diabetes Federation （IDF） estimates that in2011global diabetes prevalence rate of8.3%is expected to9.9%in2030, of which80%ofpatients are from low and middle income countries. In China, it was estimated thatapproximately92.4million adults were suffering from type2diabetes per year during2007-2008and there was an increased prevalence in young and middle-agedpopulation. Type2diabetes can cause a variety of complications, such ascardiovascular disease, nephropathy, retinopathy and diabetic foot, and bringenormous economic and social burden to families and society.Although environmental factors have clearly contributed to the rise in prevalenceof type2diabetes, genetic factors have an important impact on type2diabetessusceptibility. Differences between genetic backgrounds are mainly in the generalpopulation for differences in genome sequences, including single nucleotidepolymorphisms （SNPs）. Based on candidate genes strategy, the researchers foundsome candidate genes really associated with type2diabetes, such as PPARG-γ（peroxisome proliferator-activated receptor-γ）, KCNJ11（ATP-sensitive potassium channel subunit）, TCF7L2（transcription factor7-2）, and CAPN10（calpain10）. Butthese genes can only explain a small part of the genetic etiology of diabetic patients,indicating that a large amount of low-penetrance susceptibility genes are to bediscovered.Over the last several years, as a powerful method to investigate the geneticdeterminants of complex diseases, genome-wide association studies （GWAS） havesuccessfully identified thousands of genetic markers that are related to thesusceptibility of diseases. For example, four Caucasian GWAS had consistentlyidentified CDKAL1（6p22.3） as a novel type2diabetes susceptible gene in2007.Intronic variants （rs10946398, rs7756992, rs7754840and rs9465871） in CDKAL1had significant associations with the risk of type2diabetes. Subsequently, four newSNPs （rs4712524, rs4712523, rs6931514and rs10440833） in CDKAL1were alsoreported to increase the risk of type2diabetes in GWAS of Japanese and Caucasianpopulation. Simultaneously, Zaggini et al detected another two new type2diabetessusceptible signals at6p21.1（the maker SNP: rs9472138and rs9369425） neighboringto VEGFA in a Caucasian type2diabetes GWAS and a meta-analysis of type2diabetes GWAS. However, the two SNPs were failed to replicate in the finalvalidations: further studies will be required to establish the associations with theincreased type2diabetes risk.Up to now, most of the GWAS were conducted among populations ofnon-Chinese ancestry and the contributions of these variants to the type2diabetesrisk in Han Chinese are poorly characterized. Nevertheless, some most significantSNPs （rs10946398and rs7756992） on chromosome6have been successfullyreplicated in many case-control studies of Chinese population, but no study hassystematically conducted to include all the SNPs identified by GWAS onchromosome6associated with type2diabetes risk. For instance, the association ofSNP rs9472138neighboring to VEGFA with the risk of type2diabetes has not beenconfirmed in Chinese after GWAS exploration and the minor allele frequency （MAF）of this variant is lower in Chinese （0.116）, Japanese （0.081） and Africans （0.137） thanin Caucasians （0.239）, suggesting that there may be a heterogeneity of the associations with type2diabetes among different populations. Here, we performed acase-control study including2925type2diabetes cases and3281controls in a HanChinese population to further determine the associations between these SNPs onchromosome6p21.1and6p22.3and type2diabetes risk.Based on the recent GWA studies of type2diabetes, we identified8SNPs inCDKAL1（6p22.3） showing associations with the risk of type2diabetes, includingrs4712523, rs10946398, rs7754840, rs7756992, rs9465871, rs10440833, rs4712524and rs6931514. The MAF of these8SNPs were all higher than0.05in Chinese Hanpopulation （CHB）. Based on HapMap database （phase II, Nov08, on NCBI B36assembly, dbSNP b126）, we selected2representative SNPs （rs4712523andrs7756992） with r2<0.8among first6SNPs in CHB （Figure1）. The last2SNPs（rs4712524and rs6931514） which had no linkage disequilibrium （LD） information inHapMap were also selected for genotyping. In addition, SNPs rs9472138andrs9369425close to VEGFA （6p21.1） significantly associated with type2diabetes riskwere also in complete LD （r2=1.0） and we selected rs9472138in the validation for itsstronger reported association than rs9369425. Finally,5SNPs （rs4712523, rs7756992,rs4712524, rs6931514and rs9472138） were included in the present study. TaqManOpenArray Genotyping System and iPLEX Sequenom MassARRAY platform wereused to genotype the samples.The results show that:1) After adjusting for age, sex, and BMI, multivariatelogistic regression analysis showed that all the five SNPs were significantlyassociated with type2diabetes risk with overall effects （odds ratio, OR） from1.19to1.29in the additive genetic model (rs6931514: OR=1.29,95%CI=1.19-1.39,P=5.6×10-10; rs7756992: OR=1.23,95%CI=1.15-1.32, P=1.2×10-8; rs4712523:OR=1.25,95%CI=1.15-1.35, P=3.8×10-8; rs4712524: OR=1.24,95%CI=1.15-1.35,P=6.8×10-8; rs9472138: OR=1.19,95%CI=1.05-1.34, P=0.006).2) Conditionalanalysis identified two independent signals （rs6931514at6p22.3and rs9472138at6p21.1） that were significantly associated with type2diabetes.3) Compared with thewild homozygote of rs6931514and rs9472138, subjects with variant alleles of thetwo SNPs had increased risk for type2diabetes susceptibility in a dose-response manner (Ptrend=7.4×10-12). Stratification analysis by age, sex, BMI showed that therisk effect of rs9472138was more evident in the younger, female, overweight orobesity, smokers and drinkers. But no significant heterogeneity in every two stratumswas detected.4) Compared with the most common haplotype AAAA at6p22.3, theGGGG haplotype which was consisted of risk alleles of4SNPs was associated with a33%elevated risk of type2diabetes (adjusted OR=1.33,95%CI=1.22-1.45,P=1.5×10-10). Meanwhile, haplotype GGAA was also significantly associated with a1.17-fold increased type2diabetes risk （adjusted OR=1.17,95%CI=1.03-1.33,P=0.015）.5) Type2diabetes-related quantitative phenotypes association analysisshowed that only rs6931514was associated with fasting glucose levels, with aregression coefficient as0.03（95%CI=0.00-0.05, P=0.042）.In conclusion, our findings indicated that genetic variants of CDKAL1andVEGFA on chromosome6may contribute to type2diabetes risk in Chinesepopulation, especially for rs9472138at6p21.1identified for the first time tosignificantly increase the type2diabetes risk in Chinese individuals, indicating thatthese regions may have more important roles in the development of type2diabetes. |
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