Transdiagnostic functional connectome signature of anhedonia relates to neurotransmitter and genetic profiles

Anhedonia is a core transdiagnostic symptom across diverse psychiatric disorders, yet its neural mechanisms across multiple biological scales remain unclear. In this study, we aim to explore the neural circuit patterns and molecular genetic foundations of anhedonia by integrating multimodal neuroimaging and transcriptomic data.

We used publicly available resting-state fMRI data from a transdiagnostic cohort (N = 213; comprising healthy controls and patients with diverse affective and psychotic disorders), with anhedonia assessed using the Temporal Experience of Pleasure Scale (TEPS). First, we applied connectome-based predictive modeling (CPM) to derive macroscale functional network patterns predictive of distinct anhedonia dimensions (anticipatory vs. consummatory). Next, the predictive performance and generalizability of these models were evaluated in an independent transdiagnostic cohort (N = 247). Finally, we linked the anhedonia-related connectome pattern (ARCP) to PET-derived neurotransmitter receptor/transporter maps and AHBA gene-expression profiles via spatial correspondence analyses.

CPM robustly predicted anhedonia across diagnostic categories, supporting the "neurobiological continuum" hypothesis of anhedonia. ARCP were distributed across the default mode (DMN), salience (SN), sensorimotor (Som/Mot), and limbic networks. At the edge level, cross-network connections between DMN and Som/Mot constituted the core transdiagnostic feature. Spatial correspondence analyses linked to DRD2 receptor density and gene expression profiles enriched in dopaminergic signaling and autophagy pathways.

We establish a multi-level framework for transdiagnostic anhedonia by linking macroscale connectome aberrations to genetic and receptor-level disruptions. Together, these multi-scale insights advance the transdiagnostic continuum model and offer a promising neurobiological basis for precision psychiatry.