Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

最小表型分析是指依赖少量自我报告项目来识别疾病病例，越来越多地用于全基因组关联研究（GWAS）。在这里，我们报告了由最小表型定义的抑郁症和严格定义的重度抑郁症（MDD）之间遗传结构的差异：前者具有较低的基因型衍生遗传力，这不能通过纳入较轻的病例和较高比例的基因组来解释。除了严格定义的 MDD 之外，这种疾病与其他疾病都有共同的遗传倾向。基于最小表型定义的 GWAS 优先识别非 MDD 特异性的位点，尽管它产生高度预测性的多基因风险评分，但预测能力可以完全通过大样本量而不是 MDD 的特异性来解释。我们的结果表明，对最小表型分析结果的依赖可能会对 MDD 的遗传结构产生偏见，并妨碍识别 MDD 特异性途径的能力。