Novel variants in the putative peroxisome proliferator-activated receptor {gamma} promoter and relationships with obesity in men

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Thomas M Larsen, Lesli H Larsen, Signe K Torekov, Jakob Ek, Eva Black, Søren Toubro, Arne Astrup, Thorkild I A Sørensen, Torben Hansen, Oluf Pedersen

Yet unidentified variants within the peroxisome proliferator-activated receptor gamma (PPARgamma) 2 promoter may explain the inconsistent reports on associations between variants in the coding region and obesity or diabetes. Thus, we examined the putative PPARgamma2 promoter (-3371 to +43 bp) for variants in 83 subjects with obesity or type 2 diabetes. We identified eight variants, seven of which were novel, including -792A>G, -816C>T, -882T>C, -1505G>A, -1881C>T, -1884T>A, -2604T>C, and -2953A>G. The variants -816C>T, -1505G>A, -1881C>T, and -2604T>C were in total linkage disequilibrium, and there was a high degree of linkage disequilibrium between several of the novel variants and Pro12Ala. The novel variants were, together with Pro12Ala and 1431C>T, examined for relationships with obesity among 234 men with early-onset obesity with a BMI at age approximately 20 years of 33.2+/-2.5 kg/m2 and 323 nonobese men with a BMI of 21.7+/-2.5 kg/m2, who were also reexamined after approximately 29 years. The prevalence of the identified variants was not significantly different between the two groups, and the variants did not affect changes in BMI over time. In conclusion, the identified novel variants in the PPARgamma2 promoter region do not explain the reported discrepancies in the association of previously identified variants with obesity and type 2 diabetes.
Original languageEnglish
JournalObesity Research
Issue number6
Pages (from-to)953-8
Number of pages6
Publication statusPublished - 2005

    Research areas

  • Body Mass Index, Chromosome Mapping, Cohort Studies, DNA, Diabetes Mellitus, Type 2, Follow-Up Studies, Genetic Variation, Genotype, Humans, Linkage Disequilibrium, Male, Middle Aged, Obesity, PPAR gamma, Promoter Regions, Genetic, Sequence Analysis, DNA, Statistics, Nonparametric

ID: 38455854