title: Combined effects of 19 common variations on type 2 diabetes in Chinese: results from two community-based studies.
abstract: BACKGROUND
  Many susceptible loci for type 2 diabetes mellitus (T2DM) have recently been identified from Caucasians through genome wide association studies (GWAS). We aimed to determine the association of 11 known loci with T2DM and impaired glucose regulation (IGR), individually and in combination, in Chinese.
  
  
  RESULTS
  Subjects were enrolled in: (1) a case-control study including 1825 subjects with T2DM, 1487 with IGR and 2200 with normal glucose regulation; and (2) a prospective cohort with 734 non-diabetic subjects at baseline. The latter was followed up for 3.5 years, in which 67 subjects developed T2DM. Nineteen single nucleotide polymorphisms (SNPs) were selected to replicate in both studies. We found that CDKAL1 (rs7756992), SLC30A8 (rs13266634, rs2466293), CDKN2A/2B (rs10811661) and KCNQ1 (rs2237892) were associated with T2DM with odds ratio from 1.21 to 1.35. In the prospective study, the fourth quartile of risk scores based on the combined effects of the risk alleles had 3.05 folds (95% CI, 1.31-7.12) higher risk for incident T2DM as compared with the first quartile, after adjustment for age, gender, body mass index and diabetes family history. This combined effect was confirmed in the case-control study after the same adjustments. The addition of the risk scores to the model of clinical risk factors modestly improved discrimination for T2DM by 1.6% in the case-control study and 2.9% in the prospective study.
  
  
  CONCLUSIONS
  Our study provided further evidence for these GWAS derived SNPs as the genetic susceptible loci for T2DM in Chinese and extended this association to IGR.
authors.affiliation: State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Min
authors.initials: M
authors.lastname: Xu
authors.forename: Yufang
authors.initials: Y
authors.lastname: Bi
authors.forename: Yu
authors.initials: Y
authors.lastname: Xu
authors.forename: Bing
authors.initials: B
authors.lastname: Yu
authors.forename: Yun
authors.initials: Y
authors.lastname: Huang
authors.forename: Lina
authors.initials: L
authors.lastname: Gu
authors.forename: Yaohua
authors.initials: Y
authors.lastname: Wu
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Zhu
authors.forename: Mian
authors.initials: M
authors.lastname: Li
authors.forename: Tiange
authors.initials: T
authors.lastname: Wang
authors.forename: Aiyun
authors.initials: A
authors.lastname: Song
authors.forename: Jianing
authors.initials: J
authors.lastname: Hou
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Li
authors.forename: Guang
authors.initials: G
authors.lastname: Ning
mesh_terms: D000368:Aged; D044466:Asian People / Q000235:genetics*; D001786:Blood Glucose / Q000378:metabolism; D016022:Case-Control Studies; D002681:China; D055812:Community-Based Participatory Research / Q000379:methods; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000208:ethnology / Q000235:genetics*; D005215:Fasting / Q000097:blood; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000379:methods; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors
chemical_list: D001786:Blood Glucose