Association of single nucleotide polymorphism Rs2236518 in PRDM16 gene with BMI in Chinese males

PRD1-BF-1-RlZl homologous domain containing protein-16 （PRDM16） is a cell-autonomous transcriptional component that stimulates the development of brown fat cells. The aim of this study was to investigate the contribution of genetic variants of PRDM16 to obesity-related phenotype variations in Chines...

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Bibliographic Details
Published in:Acta pharmacologica Sinica 2013-05, Vol.34 (5), p.710-716
Main Authors: Yue, Hua, He, Jin-wei, Ke, Yao-hua, Zhang, Hao, Wang, Chun, Hu, Wei-wei, Gu, Jie-mei, Fu, Wen-zhen, Hu, Yun-qiu, Li, Miao, Liu, Yu-juan, Zhang, Zhen-lin
Format: Article
Language:English
Subjects:
Adult
Age Factors
Aged
Aged, 80 and over
Asian Continental Ancestry Group - genetics
Biomedical and Life Sciences
Biomedicine
BMI
Body Mass Index
Cohort Studies
DNA-Binding Proteins - genetics
Female
Haplotypes
Humans
Immunology
Internal Medicine
Male
Medical Microbiology
Middle Aged
Obesity - genetics
Original
original-article
Pharmacology/Toxicology
Phenotype
Polymorphism, Single Nucleotide
Transcription Factors - genetics
Vaccine
中国
协会
单因素方差分析
单核苷酸多态性
基因变异
实时定量PCR
男性
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Summary:PRD1-BF-1-RlZl homologous domain containing protein-16 （PRDM16） is a cell-autonomous transcriptional component that stimulates the development of brown fat cells. The aim of this study was to investigate the contribution of genetic variants of PRDM16 to obesity-related phenotype variations in Chinese. Methods： A total of 3204 subjects （consisting of 400 male-offspring nuclear families, 401 female-offspring nuclear families, and 729 unrelated older males） were recruited. Ten tag single nucleotide polymorphisms （SNPs） within the PRDM16 gene were genotyped using multiplex quantitative real-time PCR by Taqman assay. Body compositions were measured by dual-energy X-ray absorptiometry （DXA）. The associations of the SNPs with the obesity-related phenotypes were analyzed using the quantitative transmission disequilib- rium test （QTDT）, GLM-ANOVA and PLINK statistical methods. Results： Rs2236518 was the only SNP that was associated with BMI in young （aged 20-40 years） males （P=0.011） using QTDT, and in the older men （aged 50-80 years） （P=O.O03） using GLM-ANOVA. No significant associations were detected in the females. Nor was a relationship found between any haplotype and obesity-related phenotypes. When PLINK was used, no significant relationship was detected between 10 SNPs and obesity-related phenotypes in any of the studied cohorts. Conclusion： Rs2236518 is associated with BMI in the young males （using QTDT）, and the older males （using GLM-ANOVA）. However, the result is not confirmed using PLINK. The discrepancy needs to be further addressed.
ISSN:1671-4083
1745-7254
DOI:10.1038/aps.2012.201