[HTML][HTML] Meta-analysis of the Gly482Ser variant in PPARGC1A in type 2 diabetes and related phenotypes

I Barroso, J Luan, MS Sandhu, PW Franks, V Crowley… - Diabetologia, 2006 - Springer
I Barroso, J Luan, MS Sandhu, PW Franks, V Crowley, AJ Schafer, S O'rahilly, NJ Wareham
Diabetologia, 2006Springer
Aims/hypothesis Peroxisome proliferator-activated receptor-γ co-activator-1α (PPARGC1A)
is a transcriptional co-activator with a central role in energy expenditure and glucose
metabolism. Several studies have suggested that the common PPARGC1A polymorphism
Gly482Ser may be associated with risk of type 2 diabetes, with conflicting results. To clarify
the role of Gly482Ser in type 2 diabetes and related human metabolic phenotypes we
genotyped this polymorphism in a case-control study and performed a meta-analysis of …
Aims/hypothesis
Peroxisome proliferator-activated receptor-γ co-activator-1α (PPARGC1A) is a transcriptional co-activator with a central role in energy expenditure and glucose metabolism. Several studies have suggested that the common PPARGC1A polymorphism Gly482Ser may be associated with risk of type 2 diabetes, with conflicting results. To clarify the role of Gly482Ser in type 2 diabetes and related human metabolic phenotypes we genotyped this polymorphism in a case-control study and performed a meta-analysis of relevant published data.
Materials and methods
Gly482Ser was genotyped in a type 2 diabetes case-control study (N=1,096) using MassArray technology. A literature search revealed publications that examined Gly482Ser for association with type 2 diabetes and related metabolic phenotypes. Meta-analysis of the current study and relevant published data was undertaken.
Results
In the pooled meta-analysis, including data from this study and seven published reports (3,718 cases, 4,818 controls), there was evidence of between-study heterogeneity (p<0.1). In the fixed-effects meta-analysis, the pooled odds ratio for risk of type 2 diabetes per Ser482 allele was 1.07 (95% CI 1.00–1.15, p=0.044). Elimination of one of the studies from the meta-analysis gave a summary odds ratio of 1.11 (95% CI 1.04–1.20, p=0.004), with no between-study heterogeneity (p=0.475). For quantitative metabolic traits in normoglycaemic subjects, we also found significant between-study heterogeneity. However, no significant association was observed between Gly482Ser and BMI, fasting glucose or fasting insulin.
Conclusions/interpretation
This meta-analysis of data from the current and published studies supports a modest role for the Gly482Ser PPARGC1A variant in type 2 diabetes risk.
Springer