Genomic SEM applied to explore etiological divergences in bipolar subtypes

Area of Science:

• Genetics
• Psychiatry
• Computational Biology

Background:

• Bipolar disorder (BD) encompasses BD I (manic episodes) and BD II (hypomanic and depressive episodes).
• BD II is often considered less severe than BD I, but evidence is inconsistent.

Purpose of the Study:

• Investigate divergent genetic pathways between BD I and BD II using genomic structural equation modeling (Genomic SEM).
• Examine genetic correlations with external traits and the influence of major depression and schizophrenia.
• Identify neuronal gene expression patterns associated with BD subtypes via transcriptome-wide SEM (T-SEM).

Main Methods:

• Genomic SEM applied to PGC GWAS summary statistics.
• Analysis of genetic correlations across 98 external traits.
• Follow-up modeling for major depression and schizophrenia components.
• T-SEM for gene expression analysis.

Main Results:

• BD II exhibited significant genetic overlap with non-psychiatric medical and internalizing traits (e.g., heart disease, neuroticism, insomnia).
• BD I showed no comparable stronger associations.
• Follow-up models indicated a substantial major depression component for BD II.
• T-SEM identified 35 unique genes linked to shared risk across BD subtypes.

Conclusions:

• Divergent genetic trait relationships support the distinction between BD subtypes.
• Findings challenge the notion of BD II as a less severe condition due to its genetic links with various clinical traits.