Veller Carl, Przeworski Molly, Coop Graham
Department of Ecology and Evolution, University of Chicago.
Department of Biological Sciences, Columbia University.
bioRxiv. 2023 Nov 16:2023.11.13.566950. doi: 10.1101/2023.11.13.566950.
Family-based genome-wide association studies (GWAS) have emerged as a gold standard for assessing causal effects of alleles and polygenic scores. Notably, family studies are often claimed to provide an unbiased estimate of the average causal effect (or average treatment effect; ATE) of an allele, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. Here, we show that this interpretation does not hold in general. Because Mendelian segregation only randomizes alleles among children of heterozygotes, the effects of alleles in the children of homozygotes are not observable. Consequently, if an allele has different average effects in the children of homozygotes and heterozygotes, as can arise in the presence of gene-by-environment interactions, gene-by-gene interactions, or differences in LD patterns, family studies provide a biased estimate of the average effect in the sample. At a single locus, family-based association studies can be thought of as providing an unbiased estimate of the average effect in the children of heterozygotes (i.e., a local average treatment effect; LATE). This interpretation does not extend to polygenic scores, however, because different sets of SNPs are heterozygous in each family. Therefore, other than under specific conditions, the within-family regression slope of a PGS cannot be assumed to provide an unbiased estimate for any subset or weighted average of families. Instead, family-based studies can be reinterpreted as enabling an unbiased estimate of the extent to which Mendelian segregation at loci in the PGS contributes to the population-level variance in the trait. Because this estimate does not include the between-family variance, however, this interpretation applies to only (roughly) half of the sample PGS variance. In practice, the potential biases of a family-based GWAS are likely smaller than those arising from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, the causal interpretation of family-based GWAS estimates is less straightforward than has been widely appreciated.
基于家系的全基因组关联研究（GWAS）已成为评估等位基因和多基因分数因果效应的金标准。值得注意的是，家系研究通常被认为能够基于等位基因从父母向子女的随机传递与随机对照试验之间的类比，提供等位基因平均因果效应（或平均治疗效应；ATE）的无偏估计。在此，我们表明这种解释通常并不成立。由于孟德尔分离仅在杂合子的子女中等位基因进行随机化，纯合子子女中等位基因的效应无法观察到。因此，如果一个等位基因在纯合子和杂合子的子女中具有不同的平均效应，例如在基因 - 环境相互作用、基因 - 基因相互作用或连锁不平衡（LD）模式差异存在时可能出现这种情况，那么家系研究将提供样本中平均效应的有偏估计。在单个位点，基于家系的关联研究可被视为提供杂合子子女中平均效应的无偏估计（即局部平均治疗效应；LATE）。然而，这种解释并不适用于多基因分数，因为每个家庭中不同的单核苷酸多态性（SNP）集合是杂合的。因此，除了在特定条件下，不能假定多基因分数的家系内回归斜率能为任何家庭子集或加权平均值提供无偏估计。相反，基于家系的研究可以重新解释为能够无偏估计多基因分数中位点的孟德尔分离对性状群体水平方差的贡献程度。然而，由于这个估计不包括家庭间方差，所以这种解释仅适用于（大致）样本多基因分数方差的一半。在实际中，基于家系的GWAS的潜在偏差可能小于标准的基于人群的GWAS中因混杂因素产生的偏差，因此家系研究对于剖析遗传对表型变异的贡献仍然很重要。尽管如此，基于家系的GWAS估计的因果解释比广泛认为的要复杂。
