The impact of lipid-metabolizing genetic polymorphisms on body mass index and their interactions with soybean food intake: a study in a Chinese population.
OBJECTIVE
To evaluate the association of known polymorphisms in the lipid metabolic pathway with body mass index (BMI), and estimate their interactions with soybean food intake.


METHODS
A community-based cross-sectional survey was conducted in a Chinese Han population. BMI, soybean food intake, and single nucleotide polymorphisms of rs599839, rs3846662, rs3846663, rs12916, rs174547, rs174570, rs4938303, and rs1558861 were measured in 944 subjects. A multivariate logistic regression was used to analyze the association of the studied polymorphisms with BMIs. The expectation-maximization algorithm was employed to evaluate the extent of linkage disequilibrium between pairwise polymorphisms. The gene-environment interaction was assessed in the general multifactor dimensionality reduction model.


RESULTS
The polymorphisms of rs3846662 and rs3846663 were associated with 10% highest BMIs when comparing to the 10% lowest values both in individuals and haplotype-based association tests. Although no statistically significant gene-environment interactions were found, people with the haplotype composed of C allele in rs3846662 and T allele in rs3846663 and low frequency of soybean intake had significantly higher risk to overweight and obesity as compared with those with the haplotype consisting of T allele in rs3846662 and C allele in rs3846663 and highly frequent soybean food intake, with an odds ratio of 1.64 (95% confidence interval: 1.15-2.34, P<0.01) after adjusting for the common confounders.


CONCLUSIONS
Our study has suggested that rs3846662 and rs3846663 may be the potential candidate polymorphisms for obesity, and their effect on the pathogenesis could be mediated by the frequency of soybean food intake.
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Jin Wei
JW
Wang
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Xun
X
Tang
Fangshan District Bureau of Health, Beijing 102401, China.
Na
N
Li
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Yi Qun
YQ
Wu
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Shuai
S
Li
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Jin
J
Li
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Xue Ying
XY
Qin
The First Hospital of Fangshan District, Beijing 102400, China.
Zong Xin
ZX
Zhang
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Yong Hua
YH
Hu
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Da Fang
DF
Chen
D000328:Adult; D053283:Apolipoprotein B-48 / Q000235:genetics; D044466:Asian People / Q000235:genetics; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D004032:Diet; D050171:Dyslipidemias / Q000235:genetics; D004435:Eating; D005260:Female; D059647:Gene-Environment Interaction; D020022:Genetic Predisposition to Disease; D006239:Haplotypes; D006801:Humans; D006903:Hydroxymethylglutaryl CoA Reductases / Q000235:genetics; D050356:Lipid Metabolism / Q000235:genetics*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D050177:Overweight / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D012097:Repressor Proteins / Q000235:genetics; D013025:Glycine max
D053283:Apolipoprotein B-48; C486398:BCL6B protein, human; D012097:Repressor Proteins; C553220:HMGCR protein, human; D006903:Hydroxymethylglutaryl CoA Reductases
Body mass index; Gene-environment interaction; Genetic epidemiology; Haplotypes; Lipid metabolism