Here, we present a systematic approach to assess the comparability of down-sampled summary statistics with their full data counterparts and examine their suitability for typical follow-up analyses. We used externalizing, a latent factor representing a cross-cutting liability to behaviors and disorders characterized by problems with self-regulation, as our model phenotype. A previous multivariate GWAS by the Externalizing Consortium identified several hundred genomic loci associated with an externalizing (EXT) factor, reflecting shared genetic liability among seven indicator phenotypes (Karlsson Linnér et al. 2021): (1) attention-deficit/hyperactivity disorder (ADHD; Demontis et al. 2019), (2) problematic alcohol use (ALCP; Sanchez-Roige et al. 2019), (3) lifetime cannabis use (CANN; Pasman et al. 2018), (4) reverse-coded age at first sexual intercourse (FSEX; Karlsson Linnér et al. 2019), (5) number of sexual partners (NSEX; Karlsson Linnér et al. 2019), (6) general risk tolerance (RISK; Karlsson Linnér et al. 2019), and (7) lifetime smoking initiation (SMOK; Liu et al. 2019). However, the univariate GWASs on two of the seven phenotypes, SMOK and CANN, contain restricted data, which limits public sharing of the summary statistics from this multivariate GWAS (hereafter, the original study on externalizing).
