AIMS/HYPOTHESIS: PPARGC1A and PPARGCB encode transcriptional coactivators that regulate numerous metabolic processes. We tested associations and treatment (i.e. metformin or lifestyle modification) interactions with metabolic traits in the Diabetes Prevention Program, a randomised controlled trial in persons at high risk of type 2 diabetes. METHODS: We used Tagger software to select 75 PPARGCA1 and 94 PPARGC1B tag single-nucleotide polymorphisms (SNPs) for analysis. These SNPs were tested for associations with relevant cardiometabolic quantitative traits using generalised linear models. Aggregate genetic effects were tested using the sequence kernel association test. RESULTS: In aggregate, PPARGC1A variation was strongly associated with baseline triacylglycerol concentrations (p = 2.9 × 10(-30)), BMI (p = 2.0 × 10(-5)) and visceral adiposity (p = 1.9 × 10(-4)), as well as with changes in triacylglycerol concentrations (p = 1.7 × 10(-5)) and BMI (p = 9.9 × 10(-5)) from baseline to 1 year. PPARGC1B variation was only associated with baseline subcutaneous adiposity (p = 0.01). In individual SNP analyses, Gly482Ser (rs8192678, PPARGC1A) was associated with accumulation of subcutaneous adiposity and worsening insulin resistance at 1 year (both p < 0.05), while rs2970852 (PPARGC1A) modified the effects of metformin on triacylglycerol levels (p(interaction) = 0.04). CONCLUSIONS/ INTERPRETATION: These findings provide several novel and other confirmatory insights into the role of PPARGC1A variation with respect to diabetes-related metabolic traits. TRIAL REGISTRATION: ClinicalTrials.gov NCT00004992.
RCT Entities:
AIMS/HYPOTHESIS: PPARGC1A and PPARGCB encode transcriptional coactivators that regulate numerous metabolic processes. We tested associations and treatment (i.e. metformin or lifestyle modification) interactions with metabolic traits in the Diabetes Prevention Program, a randomised controlled trial in persons at high risk of type 2 diabetes. METHODS: We used Tagger software to select 75 PPARGCA1 and 94 PPARGC1B tag single-nucleotide polymorphisms (SNPs) for analysis. These SNPs were tested for associations with relevant cardiometabolic quantitative traits using generalised linear models. Aggregate genetic effects were tested using the sequence kernel association test. RESULTS: In aggregate, PPARGC1A variation was strongly associated with baseline triacylglycerol concentrations (p = 2.9 × 10(-30)), BMI (p = 2.0 × 10(-5)) and visceral adiposity (p = 1.9 × 10(-4)), as well as with changes in triacylglycerol concentrations (p = 1.7 × 10(-5)) and BMI (p = 9.9 × 10(-5)) from baseline to 1 year. PPARGC1B variation was only associated with baseline subcutaneous adiposity (p = 0.01). In individual SNP analyses, Gly482Ser (rs8192678, PPARGC1A) was associated with accumulation of subcutaneous adiposity and worsening insulin resistance at 1 year (both p < 0.05), while rs2970852 (PPARGC1A) modified the effects of metformin on triacylglycerol levels (p(interaction) = 0.04). CONCLUSIONS/ INTERPRETATION: These findings provide several novel and other confirmatory insights into the role of PPARGC1A variation with respect to diabetes-related metabolic traits. TRIAL REGISTRATION: ClinicalTrials.gov NCT00004992.
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