General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study

Abstract

Background: Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology.

Methods: The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS.

Results: Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040-0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062).

Conclusions: PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.

Keywords: Child Behavior Checklist; childhood psychopathology; general factor; genetic; polygenic.

Fig. 1.

(a) Graphical representation of the 1- and 5-factor structure of the CBCL scales in the ABCD Sample; (b) Proportion of total associations between PRSs and CBCL psychopathology due to the factors. Notes: (a) is a graphical representation of the CBCL structure from Michelini et al. (2019). The intermediate 2-, 3-, and 4-factor solutions reported in the original paper are not the focus of the current study and are omitted from the figure. The factor loadings come from a confirmatory factor analysis in the analytic subsample used in the current study. The model fit was appropriate in the current subsample: root mean square error of approximation (RMSEA) = 0.031 (95% CI 0.030–0.031), standardized root mean square residual (SRMR) = 0.09, Comparative Fit Index (CFI) = 0.90, Tucker–Lewis Index (TLI) = 0.90. In (b), only the 15 PRSs that showed significant associations with CBCL psychopathology factors in regression models are depicted. The total R² reflects associations between PRSs and CBCL 1- and 5- factors, exclusive of 10 PCs.