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关于影响体重指数的常见和罕见基因变异的关联:一项单核苷酸多态性(SNP)与拷贝数变异(CNV)的联合分析

On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis.

作者信息

Peterson Roseann E, Maes Hermine H, Lin Peng, Kramer John R, Hesselbrock Victor M, Bauer Lance O, Nurnberger John I, Edenberg Howard J, Dick Danielle M, Webb Bradley T

机构信息

Virginia Institute for Psychiatric and Behavioral Genetics, Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Biotech I, 800 E, Leigh Street, Richmond, VA 23298-0126, USA.

出版信息

BMC Genomics. 2014 May 14;15(1):368. doi: 10.1186/1471-2164-15-368.

Abstract

BACKGROUND

As the architecture of complex traits incorporates a widening spectrum of genetic variation, analyses integrating common and rare variation are needed. Body mass index (BMI) represents a model trait, since common variation shows robust association but accounts for a fraction of the heritability. A combined analysis of single nucleotide polymorphisms (SNP) and copy number variation (CNV) was performed using 1850 European and 498 African-Americans from the Study of Addiction: Genetics and Environment. Genetic risk sum scores (GRSS) were constructed using 32 BMI-validated SNPs and aggregate-risk methods were compared: count versus weighted and proxy versus imputation.

RESULTS

The weighted SNP-GRSS constructed from imputed probabilities of risk alleles performed best and was highly associated with BMI (p=4.3×10(-16)) accounting for 3% of the phenotypic variance. In addition to BMI-validated SNPs, common and rare BMI/obesity-associated CNVs were identified from the literature. Of the 84 CNVs previously reported, only 21-kilobase deletions on 16p12.3 showed evidence for association with BMI (p=0.003, frequency=16.9%), with two CNVs nominally associated with class II obesity, 1p36.1 duplications (OR=3.1, p=0.009, frequency 1.2%) and 5q13.2 deletions (OR=1.5, p=0.048, frequency 7.7%). All other CNVs, individually and in aggregate, were not associated with BMI or obesity. The combined model, including covariates, SNP-GRSS, and 16p12.3 deletion accounted for 11.5% of phenotypic variance in BMI (3.2% from genetic effects). Models significantly predicted obesity classification with maximum discriminative ability for morbid-obesity (p=3.15×10(-18)).

CONCLUSION

Results show that incorporating validated effect sizes and allelic probabilities improve prediction algorithms. Although rare-CNVs did not account for significant phenotypic variation, results provide a framework for integrated analyses.

摘要

背景

由于复杂性状的结构包含了范围不断扩大的遗传变异,因此需要整合常见变异和罕见变异的分析方法。体重指数(BMI)是一个典型性状,因为常见变异显示出很强的关联性,但只占遗传力的一部分。利用来自成瘾:遗传学与环境研究中的1850名欧洲人和498名非裔美国人,对单核苷酸多态性(SNP)和拷贝数变异(CNV)进行了联合分析。使用32个经BMI验证的SNP构建遗传风险总和评分(GRSS),并比较了汇总风险方法:计数法与加权法、代理法与估算法。

结果

根据风险等位基因的估算概率构建的加权SNP-GRSS表现最佳,与BMI高度相关(p = 4.3×10⁻¹⁶),占表型变异的3%。除了经BMI验证的SNP外,还从文献中鉴定出常见和罕见的BMI/肥胖相关CNV。在先前报道的8种4 CNV中,只有16p12.3上的21千碱基缺失显示出与BMI相关的证据(p = 0.003,频率 = 16.9%),有两种CNV与II类肥胖名义上相关,1p36.1重复(OR = 3.1,p = 0.009,频率1.2%)和5q13.2缺失(OR = 1.5,p = 0.048,频率7.7%)。所有其他CNV,单独或总体上,均与BMI或肥胖无关。包括协变量、SNP-GRSS和16p12.3缺失的联合模型占BMI表型变异的11.5%(遗传效应占3.2%)。模型对肥胖分类具有显著的预测能力,对病态肥胖具有最大的判别能力(p = 3.15×10⁻¹⁸)。

结论

结果表明,纳入经过验证的效应大小和等位基因概率可改善预测算法。虽然罕见CNV并未占显著的表型变异,但结果提供了一个整合分析的框架。

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