Single nucleotide polymorphisms of the peroxisome proliferator-activated receptor-alpha gene (PPARA) influence the conversion from impaired glucose tolerance to type 2 diabetes: the STOP-NIDDM trial.
ABSTRACT Peroxisome proliferator-activated receptor (PPAR) alpha, a transcription factor of the nuclear receptor superfamily, regulates fatty acid oxidation. We evaluated the association of single nucleotide polymorphisms (SNPs) of the PPAR-alpha gene (PPARA) with the conversion from impaired glucose tolerance to type 2 diabetes in 767 subjects of the STOP-NIDDM trial in order to investigate the effect of acarbose in comparison with placebo on the prevention of diabetes. In the placebo group, the G (162V) allele of rs1800206 increased the risk for diabetes by 1.9-fold (95% CI 1.05-3.58) and was associated with elevated levels of plasma glucose and insulin. The effect of this allele on the risk of diabetes in the placebo group was enhanced by the simultaneous presence of the risk alleles of the PPAR-gamma2, PPAR-gamma coactivator 1alpha, and hepatic nuclear factor 4alpha genes (odds ratios 2.2, 2.5, and 3.4, respectively). In the acarbose group, subjects carrying the minor G allele of rs4253776 and the CC genotype of rs4253778 of PPARA had a 1.7- and 2.7-fold increased risk for diabetes. Our data indicate that SNPs of PPARA increase the risk of type 2 diabetes alone and in combination with the SNPs of other genes acting closely with PPAR-alpha.
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ABSTRACT: Permutation tests are widely used in genomic research as a straightforward way to obtain reliable statistical inference without making strong distributional assumptions. However, in this paper we show that in genetic association studies it is not typically possible to construct exact permutation tests of gene-gene or gene-environment interaction hypotheses. We describe an alternative to the permutation approach in testing for interaction, a parametric bootstrap approach. Using simulations, we compare the finite-sample properties of a few often-used permutation tests and the parametric bootstrap. We consider interactions of an exposure with single and multiple polymorphisms. Finally, we address when permutation tests of interaction will be approximately valid in large samples for specific test statistics.Annals of Human Genetics 04/2010; 75(1):36-45. · 2.22 Impact Factor
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ABSTRACT: The greatest clinical challenge in type 2 diabetes mellitus is the prevention of its long-term complications, many of which are of a cardiovascular nature. Despite the progress in cardiovascular risk management of diabetes patients using lipid-lowering and antihypertensive drugs, a substantial residual risk persists. Indeed, treated diabetes patients have a similar risk as untreated nondiabetic individuals. Although glycemic control through the use of antihyperglycemic agents improves microvascular complications, macrovascular disease risk is not reduced. These observations point to the need for additional therapeutic approaches in order to better control global cardiovascular risk. The peroxisome proliferator-activated receptor (PPAR) family members play major roles in the regulation of lipid and glucose metabolism and immune-inflammatory processes, making these transcription factors ideal targets for such therapeutic strategies. This review discusses our current knowledge of the effectiveness of PPAR-based therapeutics, focusing exclusively on cardiovascular disease in type 2 diabetes mellitus and the future prospects for novel generation of PPAR agonists.Current Atherosclerosis Reports 08/2009; 11(4):281-8. · 2.92 Impact Factor
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ABSTRACT: To study the association of polymorphisms in the genes encoding peroxisome proliferator-activated receptors (PPARs) with the polycystic ovary syndrome (PCOS). Case-control study and meta-analysis of published evidence. One hundred and sixty-one polycystic ovary syndrome patients and 113 non-hyperandrogenic women. Genotyping for PPAR-gamma coactivator-1 gene (PPARGC1A) Gly482Ser, PPAR-alpha Leu162Val, PPAR-delta rs2267668A/G, PPAR-delta-87T/C, PPAR-gamma2 Pro12Ala and PPAR-gamma2 -681C/G variants and systematic review of the literature using the Entrez-PubMed search engine, followed by meta-analysis whenever possible. Polycystic ovary syndrome patients carried the Gly482Ser variant in PPARGC1A more frequently than controls (72%vs. 58%, chi(2 )=( )5.54 P = 0.019), whereas carriers of the PPAR-alpha Leu162Val, PPAR-delta rs2267668A/G, PPAR-delta-87T/C, PPAR-gamma2 Pro12Ala and PPAR-gamma2 -681C/G variants were distributed similarly among both groups. The interaction between the PPARGC1A Gly482Ser and PPAR-delta-87T/C variants was also associated with PCOS (OR = 1.24, 95% CI 1.05-1.50, P = 0.008). The systematic review identified 31 studies addressing associations between PPARs variants and PCOS; meta-analysis was possible for nine studies focusing on the PPAR-gamma2 Pro12Ala variant. Although the individual studies did not reveal any statistically significant association, meta-analysis uncovered that carrying the PPAR-gamma2 Pro12Ala variant was associated with a reduced probability of having PCOS (OR = 0.77, 95% CI 0.61-0.96, P = 0.025), and that this association may be mediated by an effect on insulin sensitivity. Common polymorphisms in the PPARGC1A, PPAR-delta and PPAR-gamma2 loci are associated with PCOS.Clinical Endocrinology 09/2009; 72(3):383-92. · 3.40 Impact Factor