Multi‐polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives

Abstract

The dense co‐occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder‐specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention‐deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject‐specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross‐disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e‐4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e‐4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

Combining Transdiagnostic and Disorder-Level GWAS Enhances Precision of Psychiatric Genetic Risk Profiles in a Multi-Ancestry Sample

“…For example, depression PGS show little specificity, accounting for a similar amount of variance in mood disorders, anxiety disorders, ADHD, and SUDs. 91 Similarly, an evaluation of 16 PGS for psychiatric phenotypes found that most were associated with general psychopathology rather than the specific domain for which they purported to measure risk. 92 Although PGS have shown clinical utility in predicting some non-psychiatric disorders, 93,94 prediction performance for psychiatric phenotypes remains limited.…”