Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation

Genome-wide association studies have successfully identified thousands of loci for a range of human complex traits and diseases. The proportion of phenotypic variance explained by significant associations is, however, limited. Given the same dense SNP panels, mixed model analyses capture a greater proportion of phenotypic variance than single SNP analyses but the total is generally still less than the genetic variance estimated from pedigree studies. Combining information from pedigree relationships and SNPs, we examined 16 complex anthropometric and cardiometabolic traits in a Scottish family-based cohort comprising up to 20,000 individuals genotyped for ~520,000 common autosomal SNPs. The inclusion of related individuals provides the opportunity to also estimate the genetic variance associated with pedigree as well as the effects of common family environment. Trait variation was partitioned into SNP-associated and pedigree-associated genetic variation, shared nuclear family environment, shared couple (partner) environment and shared full-sibling environment. Results demonstrate that trait heritabilities vary widely but, on average across traits, SNP-associated and pedigree-associated genetic effects each explain around half the genetic variance. For most traits the recently-shared environment of couples is also significant, accounting for ~11% of the phenotypic variance on average. On the other hand, the environment shared largely in the past by members of a nuclear family or by full-siblings, has a more limited impact. Our findings point to appropriate models to use in future studies as pedigree-associated genetic effects and couple environmental effects have seldom been taken into account in genotype-based analyses. Appropriate description of the trait variation could help understand causes of intra-individual variation and in the detection of contributing loci and environmental factors.

全基因组关联研究（Genome-wide association studies）已成功鉴定出与一系列人类复杂性状及疾病相关的数千个基因座。然而，已发现的显著关联所解释的表型方差比例仍较为有限。即便使用相同的高密度SNP分型面板（SNP panels），混合模型分析（mixed model analyses）所能解释的表型方差比例也高于单SNP分析（single SNP analyses），但总体仍普遍低于家系研究（pedigree studies）估算的遗传方差。本研究整合家系亲缘关系与SNP信息，对一个包含至多20000名个体的苏格兰家系队列展开分析，该队列的所有研究对象均完成了约52万个常见常染色体SNP的分型检测。纳入相关个体的研究设计，使得我们不仅能够估算与家系相关的遗传方差，还可评估常见家庭环境的效应。我们将性状变异划分为SNP关联遗传变异、家系关联遗传变异、共享核心家庭环境（nuclear family environment）、共享伴侣（配偶）环境以及共享全同胞环境（full-sibling environment）五类。研究结果显示，性状遗传力（heritabilities）存在显著差异，但在所有性状的平均水平上，SNP关联与家系关联的遗传效应各自解释了约一半的遗传方差。对于多数性状而言，近期形成的伴侣共享环境同样具有显著影响，平均可解释约11%的表型方差。与之相对，核心家庭或全同胞既往共享的环境，其对性状变异的影响则较为有限。本研究结果提示，未来的相关研究应采用合适的分析模型——鉴于基于基因型的分析中，极少纳入家系关联遗传效应与伴侣环境效应。对性状变异的合理阐释，有助于理解个体内变异（intra-individual variation）的成因，同时也能助力于鉴定潜在的致病基因座与环境影响因素。