Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

Area of Science:

• Genetics
• Psychiatry
• Metabolic Disorders

Background:

• Growing evidence indicates a complex relationship between psychiatric disorders and metabolic dysregulations.
• Previous research focused on specific disorder pairs, limiting understanding of the broader psycho-metabolic nexus.

Purpose of the Study:

• To investigate the shared genetic underpinnings between psychiatric disorders and metabolic dysregulations.
• To identify novel genetic variants and genes contributing to the comorbidity of these conditions.
• To develop improved risk prediction models for clinical applications.

Main Methods:

• Utilized large-scale UK Biobank data and genome-wide association study (GWAS) summary statistics for 8 psychiatric disorders and 43 metabolic traits.
• Employed a comprehensive strategy to identify genetic correlations, local pleiotropy, and pleiotropic genes.
• Developed polygenic risk score (PRS) models integrating genetic information.

Main Results:

• Identified significant bidirectional clinical risks and 104 robust genetic correlation pairs between psychiatric and metabolic traits.
• Uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants, including 45 novel SNVs for psychiatric disorders and 75 for metabolic traits.
• Highlighted RBM6 as a key pleiotropic gene and demonstrated enhanced predictive power of PRS models with integrated genetic data.

Conclusions:

• The study confirms intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations.
• Emphasizes the necessity of integrated diagnostic and treatment approaches for these comorbidities.
• Identified novel genetic targets for understanding and managing psycho-metabolic conditions.