# A transdiagnostic network analysis of psychosocial-clinical-cognitive functioning in young people with bipolar and major depressive disorders

## TL;DR

This study uses network analysis to explore shared patterns in bipolar and major depressive disorders among young people, identifying key factors that could guide treatment.

## Contribution

The study introduces a transdiagnostic network model linking clinical, psychosocial, and cognitive factors in youth mood disorders.

## Key findings

- A two-cluster network structure was identified: symptom-psychosocial and neurocognition clusters.
- Depression and anhedonia were central in the symptom-psychosocial cluster, while processing speed and attention were central in the neurocognition cluster.
- Attention and self-harm were key bridge nodes connecting the two clusters.

## Abstract

High rates of diagnostic conversion and comorbidity between bipolar disorder (BD) and major depressive disorder (MDD) necessitate a transdiagnostic approach to uncover shared mechanisms. Network analysis can model the complex interrelationships among clinical, psychosocial, and cognitive domains, which remain underexplored in an integrated manner.

This study included 1,332 participants aged 10-24 (689 patients with BD-I, BD-II, or MDD, and 643 healthy controls). All underwent comprehensive assessments for clinical symptoms, psychosocial factors, and cognitive performance. We employed exploratory graph analysis to identify network clusters, estimated centrality and bridge centrality to identify key nodes, and used the Network Comparison Test across cognitive subgroups derived from hierarchical clustering.

A transdiagnostic two-cluster structure was identified: a symptom-psychosocial cluster and a neurocognition cluster. Depression and anhedonia were the central nodes within the symptom-psychosocial cluster, while processing speed and attention were central in the neurocognition cluster. Attention and self-harm were the key bridge nodes connecting the two clusters. Cognitive stratification revealed higher nodal strength (visual learning, processing speed) and global strength in the low-cognitive subgroup.

This study delineates a transdiagnostic network architecture in young people’s mood disorders, identifying critical central and bridge nodes as intervention targets. The findings advocate for a dimensional, cognitive-informed approach to understanding and treating BD and MDD.