An Assessment of the Individual and Collective Effects of Variants on Height Using Twins and a Developmentally Informative Study Design

In a sample of 3,187 twins and 3,294 of their parents, we sought to investigate association of both individual variants and a genotype-based height score involving 176 of the 180 common genetic variants with adult height identified recently by the GIANT consortium. First, longitudinal observations on height spanning pre-adolescence through adulthood in the twin sample allowed us to investigate the separate effects of the previously identified SNPs on pre-pubertal height and pubertal growth spurt. We show that the effect of SNPs identified by the GIANT consortium is primarily on prepubertal height. Only one SNP, rs7759938 in LIN28B, approached a significant association with pubertal growth. Second, we show how using the twin data to control statistically for environmental variance can provide insight into the ultimate magnitude of SNP effects and consequently the genetic architecture of a phenotype. Specifically, we computed a genetic score by weighting SNPs according to their effects as assessed via meta-analysis. This weighted score accounted for 9.2% of the phenotypic variance in height, but 14.3% of the corresponding genetic variance. Longitudinal samples will be needed to understand the developmental context of common genetic variants identified through GWAS, while genetically informative designs will be helpful in accurately characterizing the extent to which these variants account for genetic, and not just phenotypic, variance.

本研究纳入3187名双生子及其3294名父母作为研究样本，旨在探究单个遗传变异以及基于基因型的身高评分（纳入了GIANT联盟近期鉴定出的与成人身高相关的180个常见遗传变异中的176个）与成人身高的关联。首先，双生子样本中涵盖了从青春前期到成年的身高纵向观测数据，这使得我们能够探究此前鉴定出的单核苷酸多态性（Single Nucleotide Polymorphisms, SNPs）对青春前期身高及青春期生长突增的独立影响。本研究发现，GIANT联盟鉴定出的SNPs主要影响青春前期身高；仅LIN28B基因内的rs7759938这一个SNP，与青春期生长存在接近显著水平的关联。其次，本研究展示了如何利用双生子数据对环境方差进行统计控制，从而帮助我们理解SNP效应的最终强度，进而解析某一表型的遗传架构。具体而言，我们依据荟萃分析所评估的SNP效应值对其进行加权，构建了遗传评分。该加权评分可解释身高表型方差的9.2%，但可解释对应遗传方差的14.3%。若要理解通过全基因组关联研究（Genome-Wide Association Study, GWAS）鉴定出的常见遗传变异的发育背景，需要借助纵向样本；而利用具备遗传信息的实验设计，则有助于准确表征这些变异所能解释的遗传方差（而非仅表型方差）的占比范围。