We computed rgs between AGGoverall and a set of preselected outcomes (N = 46; collectively referred to as “external phenotypes”; Supplementary Table 14). Phenotypes were selected based on established hypotheses with AGG and the availability of sufficiently powered GWAS summary statistics. We restricted rgs to phenotypes for which the Z-scores of the LDSC-based \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h_{SNP}^2$$\end{document}hSNP2 ≥ 4 [29]. Next, we estimated rgs for all rater-specific assessments of AGG (except for father-reported AGG). Genomic Structural Equation Modelling (Genomic SEM) [37] was applied to test if rgs were significantly different across raters. Specifically, for every phenotype, we tested whether (1) all three rgs between the external phenotype and rater-specific assessment of AGG, i.e., mother, teacher, or self-ratings, could be constrained at zero, and (2) whether rgs could be constrained to be equal across raters. A \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\chi ^2$$\end{document}χ2 difference test was applied to assess whether imposing the constraints resulted in a significant worse model fit compared to a model where the rgs between the phenotype and
