以全基因组关联分析大数据为基础的孟德尔随机化方法探索出生体重与儿童肥胖的关联

doi:10.3969/j.issn.1673-5501.2019.02.011

摘要/Abstract

摘要： 目的利用全基因组关联分析(GWAS)大数据,通过孟德尔随机化(MR)方法,探讨出生体重与儿童肥胖之间的关联。方法本研究采用MR研究方法,以基因工具变量探讨出生体重与儿童肥胖的因果关联。以早期生长遗传学联盟(EGG)公开发表的基因数据为参考依据(数据获取时间为2018年10月20日),借助MR-base平台,筛选出与出生体重关联有统计学意义的SNP作为工具变量(筛选参数为P＜5×10^-8、连锁不平衡r²＜0.1),通过逆方差加权分析法(IVW)、加权中值法和MR-Egger法分别判断出生体重与儿童肥胖(儿童肥胖定义:0~18岁按不同性别年龄别BMI≥P₉₅)的因果关联。绘制SNP相关的出生体重与儿童肥胖风险的森林图及散点图。结果共筛选到33个与出生体重相关的SNP。共纳入5 530例肥胖儿童和8 318名正常儿童。IVW分析:OR=1.79,95％CI:1.29~2.47,P=4.24×10^-4;加权中值法:OR=1.30,95％CI:0.81~2.08,P=0.27;MR-Egger法:OR=1.73,95％CI:0.58~5.20,P=0.36。森林图IVW结果显示,儿童肥胖的遗传易感性与出生体重水平有关,rs7964361、rs11765649、rs3780573和rs1351394的分析均表明出生体重与儿童肥胖的关联差异有统计学意义。与出生体重相关的SNP及其儿童肥胖风险的散点图显示,IVW法、MR-Egger法和加权中值法的因果关联估计相近。结论 IVW法分析显示出生体重与儿童肥胖具有较强的相关性,但其他两种统计方法分析均差异无统计学意义,故二者的关联尚待进一步的证据支撑。

关键词: 出生体重, 儿童肥胖, 孟德尔随机化

Abstract: Objective To explore the causal association between birth weight and childhood obesity by using the GWAS data and the Mendelian randomization (MR) method.Methods Based on the genetic data published by the Early Growth Genetics Consortium (EGG) (data acquisition time is October 20, 2018), the SNP with statistically significant association with birth weight was screened by MR-base platform. As instrumental variables (screening parameters P<5×10^-8, linkage disequilibrium r²<0.1), birth weight and childhood obesity were determined by inverse variance weighted analysis (IVW), weighted median method and MR-Egger method, respectively (definition of childhood obesity: BMI≥95%). Forest maps and scatter plots were also applied.Results A total of 33 SNPs related to birth weight were screened. A total of 5,530 obese children and 8,318 normal children were included. IVW analysis: OR=1.79, 95% CI: 1.29~2.47, P=4.24×10^-4; weighted median method: OR=1.30, 95% CI: 0.81~2.08, P=0.27; MR-Egger method: OR=1.73, 95% CI: 0.58~5.20, P=0.36. The result of IVW in the forest map showed that the genetic susceptibility of childhood obesity was related to the birth weight level. rs7964361, rs11765649, rs3780573 and rs1351394 showed that birth weight and childhood obesity were statistically significant. The scatter plot showed that the causal correlation estimates for the IVW method, the MR-Egger method, and the weighted median method were similar.Conclusion IVW analysis showed that there was a strong correlation between birth weight and childhood obesity, but the other two statistical methods found that the difference was not statistically significant, so the causal association remained to be supported by further evidence.

Key words: Birth weight, Childhood obesity, Mendeline randomization

梁颖娜, 黄宇婷, 李立新. 以全基因组关联分析大数据为基础的孟德尔随机化方法探索出生体重与儿童肥胖的关联[J]. 中国循证儿科杂志, 2019, 14(2): 134-138.

LIANG Ying-na, HUANG Yu-ting, LI Li-xin. Mendelian randomization based on GWAS big data to explore birth weight and childhood obesity[J]. Chinese Journal of Evidence -Based Pediatric, 2019, 14(2): 134-138.

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