LBPS 01-07 STUDY OF 6 BMI-ASSOCIATED LOCI IDENTIFIED IN GWAS FOR INTERACTIVE ASSOCIATIONS WITH CENTRAL OBESITY IN THE CHINESE CHILDREN

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Abstract

Objective:

Recent genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with body mass index (BMI)/generalized obesity. In this study, we aimed to evaluate the interactive associations of identified SNPs with risk of central obesity in a child population from China.

Design and Method:

We genotyped 6 SNPs (FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, CSK rs1378942) in the Chinese children (N = 3502, age range 6–18 years) from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS). Based on the age- and sex- specific waist circumference (WC) standards generated in the BCAMS study, 1196 central obese cases and 2306 controls were identified. We analyzed gene-gene interactions among 6 polymorphic loci using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then used logistic regression models to confirm the best combination of loci identified in the GMDR.

Results:

GMDR analysis showed a significant gene-gene interaction between the rs17782313 polymorphism in the MC4R gene and the rs6265 polymorphism in the gene BDNF. The best two-locus combination scored 10 for cross-validation consistency and 10 for sign test (P = 0.0010). This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the combination of the MC4R rs17782313 and the BDNF rs6265 was associated with a significantly increased risk of central obesity (OR = 1.48, 95% CI:1.25–1.74; P = 3.70 × 10–6) after adjustment for sex, age, pubertal stage, physical activity and family history of obesity.

Conclusions:

Our study showed the statistically interactive association between the MC4R rs17782313 and the BDNF rs6265 with risk of central obesity in the Chinese children, revealing that these genes affect obesity more likely through a complex interaction pattern than single gene effect.

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