Association of both peroxisome proliferator-activated receptor, gene-gene interactions and the body mass index / 中华流行病学杂志
Chinese Journal of Epidemiology
;
(12): 740-745, 2012.
Article
in Chinese
| WPRIM
| ID: wpr-288066
ABSTRACT
Objective To investigate the association of ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptor ( α,δ,γ) with obesity and the additional role of a gene-gene interaction among 10 SNPs.Methods Participants were recruited within the framework of the PMMJS (Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu Province)-cohort-population-survey in the urban community of Jiangsu province,China.820 subjects (513 non obese subjects,307 obese subjects ) were randomly selected and no individuals were related to each other.Tea SNPs (rs135539,rs4253778,rs1800206,rs2016520,rs9794,rs10865710,rs1805192,rs709158,rs3856806,rs4684847) were selected from the HapMap database,which covered PPARα,PPARδ and PPARγ.Logistic regression model was used to examine the association between ten SNPs in the PPARs and obesity.Odds ratios (OR) and 95% confident interval (95%CI) were calculated.Interactions were explored by using the Generalized Multifactor Dimensionality Reduction (GMDR).Results A group of 820 participants (mean age was 50.05 ± 9.41) was involved.The frequency of the mutant alleles of rs2016520 in obese populations was less than that in non-obese populations (26% vs.33%,P< 0.0 1 ).The frequency of the mutant alleles of rs 10865710 in obese populations was more than that in non-obese populations (37% vs.31%,P=0.01 ).C allele carriers had a significantly lower obesity occurrence than TT homozygotes [OR (95% CI)0.63 (0.47-0.84) ] for rs2016520 but no significant association was observed between other SNP and incident obesity.GMDR analysis showed a significant gene-gene interaction among rs2016520,rs9794 and rs10865710 for the three-dimension models (P=0.0010),in which prediction accuracy was 0.5834 and cross-validation consistency was 9/10.It also showed a significant gene-gene interactions between rs2016520 and rs10865710 in all the two-dimensional models (P=0.0010),in which predictive accuracy was 0.5746 and cross-validation consistency was 9/10.Conclusion Our data showed that rs2016520 was associated with lower obesity risk,as well as interactions among rs2016520,rs9794 and rs 10865710 on incident obesity.
Full text:
Available
Index:
WPRIM (Western Pacific)
Type of study:
Prognostic study
Language:
Chinese
Journal:
Chinese Journal of Epidemiology
Year:
2012
Type:
Article
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