An Integrative Approach for Subtyping Mental Disorders Using Multimodal Data

TL;DR

This paper introduces MINDS, a Bayesian model that integrates clinical, cognitive, and neuroimaging data to identify meaningful subtypes of mental disorders, improving diagnosis and treatment strategies.

Contribution

The paper presents MINDS, a novel Bayesian hierarchical model for multimodal data integration, enabling simultaneous dimension reduction and clustering for psychiatric subtyping.

Findings

Identified clinically interpretable ADHD and OCD subtypes.

Demonstrated improved stability and accuracy over existing methods.

Revealed distinct cognitive and neurodevelopmental profiles for subtypes.

Abstract

Understanding the biological and behavioral heterogeneity underlying psychiatric disorders is critical for advancing precision diagnosis, treatment, and prevention. This paper addresses the scientific question of how multimodal data, spanning clinical, cognitive, and neuroimaging measures, can be integrated to identify biologically meaningful subtypes of mental disorders. We introduce Mixed INtegrative Data Subtyping (MINDS), a Bayesian hierarchical model designed to jointly analyze mixed-type data for simultaneous dimension reduction and clustering. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, MINDS integrates clinical symptoms, cognitive performance, and brain structure measures to subtype Attention-Deficit/Hyperactivity Disorder (ADHD) and Obsessive-Compulsive Disorder (OCD). Our method leverages Polya-Gamma augmentation for computational efficiency and robust inference. Simulations demonstrate improved stability and accuracy compared to existing clustering approaches. Application to the ABCD data reveals clinically interpretable subtypes of ADHD and OCD with distinct cognitive and neurodevelopmental profiles. These findings show how integrative multimodal modeling can enhance the reproducibility and clinical relevance of psychiatric subtyping, supporting data-driven policies for early identification and targeted interventions in mental health.