title: Uncoupling protein 2 gene polymorphisms are associated with obesity.
abstract: BACKGROUND
  Uncoupling protein 2 (UCP2) gene polymorphisms have been reported as genetic risk factors for obesity and type 2 diabetes mellitus (T2DM). We examined the association of commonly observed UCP2 G(-866)A (rs659366) and Ala55Val (C > T) (rs660339) single nucleotide polymorphisms (SNPs) with obesity, high fasting plasma glucose, and serum lipids in a Balinese population.
  
  
  METHODS
  A total of 603 participants (278 urban and 325 rural subjects) were recruited from Bali Island, Indonesia. Fasting plasma glucose (FPG), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) were measured. Obesity was determined based on WHO classifications for adult Asians. Participants were genotyped for G(-866)A and Ala55Val polymorphisms of the UCP2 gene.
  
  
  RESULTS
  Obesity prevalence was higher in urban subjects (51%) as compared to rural subjects (23%). The genotype, minor allele (MAF), and heterozygosity frequencies were similar between urban and rural subjects for both SNPs. All genotype frequencies were in Hardy-Weinberg equilibrium. A combined analysis of genotypes and environment revealed that the urban subjects carrying the A/A genotype of the G(-866)A SNP have higher BMI than the rural subjects with the same genotype. Since the two SNPs showed strong linkage disequilibrium (D' = 0.946, r2 = 0.657), a haplotype analysis was performed. We found that the AT haplotype was associated with high BMI only when the urban environment was taken into account.
  
  
  CONCLUSIONS
  We have demonstrated the importance of environmental settings in studying the influence of the common UCP2 gene polymorphisms in the development of obesity in a Balinese population.
authors.affiliation: Eijkman Institute for Molecular Biology, Jl, Diponegoro 69, Jakarta, Indonesia.
authors.forename: Sukma
authors.initials: S
authors.lastname: Oktavianthi
authors.forename: Hidayat
authors.initials: H
authors.lastname: Trimarsanto
authors.forename: Clarissa A
authors.initials: CA
authors.lastname: Febinia
authors.forename: Ketut
authors.initials: K
authors.lastname: Suastika
authors.forename: Made R
authors.initials: MR
authors.lastname: Saraswati
authors.forename: Pande
authors.initials: P
authors.lastname: Dwipayana
authors.forename: Wibowo
authors.initials: W
authors.lastname: Arindrarto
authors.forename: Herawati
authors.initials: H
authors.lastname: Sudoyo
authors.forename: Safarina G
authors.initials: SG
authors.lastname: Malik
mesh_terms: D000328:Adult; D000368:Aged; D044466:Asian People / Q000235:genetics; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D003430:Cross-Sectional Studies; D005260:Female; D005787:Gene Frequency; D059647:Gene-Environment Interaction; D020022:Genetic Predisposition to Disease; D006579:Heterozygote; D006801:Humans; D007214:Indonesia / Q000453:epidemiology; D007473:Ion Channels / Q000235:genetics*; D015810:Linkage Disequilibrium; D008055:Lipids / Q000097:blood; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D024101:Mitochondrial Proteins / Q000235:genetics*; D009765:Obesity / Q000097:blood / Q000208:ethnology / Q000235:genetics*; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D012423:Rural Health / Q000208:ethnology; D000071246:Uncoupling Protein 2; D014504:Urban Health / Q000208:ethnology
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D007473:Ion Channels; D008055:Lipids; D024101:Mitochondrial Proteins; C000604389:UCP2 protein, human; D000071246:Uncoupling Protein 2