一种多分析方法，用于评估北印度成年人中28个基因的55个单核苷酸多态性与肥胖风险的关联。

A multianalytical approach to evaluate the association of 55 SNPs in 28 genes with obesity risk in North Indian adults.

作者信息

Srivastava Apurva, Mittal Balraj, Prakash Jai, Srivastava Pranjal, Srivastava Nimisha, Srivastava Neena

机构信息

Department of Medical Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh, 226014, India.

Department of Physiology, King George's Medical University, Chowk, Lucknow, Uttar Pradesh, 226003, India.

出版信息

Am J Hum Biol. 2017 Mar;29(2). doi: 10.1002/ajhb.22923. Epub 2016 Sep 21.

DOI:10.1002/ajhb.22923

PMID:27650258

Abstract

OBJECTIVES

The aim of the study was to investigate the association of 55 SNPs in 28 genes with obesity risk in a North Indian population using a multianalytical approach.

METHODS

Overall, 480 subjects from the North Indian population were studied using strict inclusion/exclusion criteria. SNP Genotyping was carried out by Sequenom Mass ARRAY platform (Sequenom, San Diego, CA) and validated Taqman allelic discrimination (Applied Biosystems ). Statistical analyses were performed using SPSS software version 19.0, SNPStats, GMDR software (version 6) and GENEMANIA.

RESULTS

Logistic regression analysis of 55 SNPs revealed significant associations (P < .05) of 49 SNPs with BMI linked obesity risk whereas the remaining 6 SNPs revealed no association (P > .05). The pathway-wise G-score revealed the significant role (P = .0001) of food intake-energy expenditure pathway genes. In CART analysis, the combined genotypes of FTO rs9939609 and TCF7L2 rs7903146 revealed the highest risk for BMI linked obesity. The analysis of the FTO-IRX3 locus revealed high LD and high order gene-gene interactions for BMI linked obesity. The interaction network of all of the associated genes in the present study generated by GENEMANIA revealed direct and indirect connections. In addition, the analysis with centralized obesity revealed that none of the SNPs except for FTO rs17818902 were significantly associated (P < .05).

CONCLUSIONS

In this multi-analytical approach, FTO rs9939609 and IRX3 rs3751723, along with TCF7L2 rs7903146 and TMEM18 rs6548238, emerged as the major SNPs contributing to BMI linked obesity risk in the North Indian population.

摘要

目的

本研究旨在采用多分析方法，调查28个基因中的55个单核苷酸多态性（SNP）与北印度人群肥胖风险之间的关联。

方法

总体而言，采用严格的纳入/排除标准，对480名北印度人群的受试者进行了研究。通过Sequenom Mass ARRAY平台（Sequenom，圣地亚哥，加利福尼亚州）进行SNP基因分型，并采用经过验证的Taqman等位基因鉴别法（应用生物系统公司）。使用SPSS软件19.0版、SNPStats、GMDR软件（6版）和GENEMANIA进行统计分析。

结果

对55个SNP的逻辑回归分析显示，49个SNP与体重指数（BMI）相关的肥胖风险存在显著关联（P < 0.05），而其余6个SNP未显示出关联（P > 0.05）。按通路计算的G评分显示食物摄入-能量消耗通路基因具有显著作用（P = 0.0001）。在分类回归树（CART）分析中，FTO基因的rs9939609和TCF7L2基因的rs7903146的组合基因型显示出与BMI相关的肥胖风险最高。对FTO-IRX3基因座的分析显示，BMI相关肥胖存在高度连锁不平衡（LD）和高阶基因-基因相互作用。GENEMANIA生成的本研究中所有相关基因的相互作用网络显示出直接和间接的联系。此外，对全身性肥胖的分析显示，除FTO基因的rs17818902外，没有其他SNP存在显著关联（P < 0.05）。