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. 2025 Sep;15(9):e70742.
doi: 10.1002/brb3.70742.

Shared Genetic Architecture Among Severe Mental Disorders: A System Biology Approach Based on Protein-Protein Interaction

Hernan F Guillen-Burgos  1   2   3 , Valentina Vanegas  3 , Isabella Gonzalez  1   4 , Ana M Caicedo  3 , Valentina Arango  5 , Juan F Galvez-Florez  2 , Juan-Manuel Anaya  6 , Roger S McIntyre  7 , Wilson Terán  8
Affiliations

Shared Genetic Architecture Among Severe Mental Disorders: A System Biology Approach Based on Protein-Protein Interaction

Hernan F Guillen-Burgos et al. Brain Behav. 2025 Sep.

Abstract

Introduction: The study explores shared genetic architecture among major psychiatric disorders-major depressive disorder, bipolar disorder, schizophrenia, and post-traumatic stress disorder-emphasizing their overlapping molecular pathways. Using public datasets, we identified shared genes and examined their functional implications through protein-protein interaction (PPI) networks and gene set enrichment analysis (GSEA).

Methods: Genes associated with each disorder were identified through the NCBI Gene database. Intersection analyses of gene sets were conducted using R to identify overlaps among the four disorders. STRING was used to predict PPI and conduct clustering analyses. Gene set enrichment analysis was performed to explore biological pathways, molecular functions, and cellular components.

Results: We identified 31 intersected genes across all four disorders. PPI analyses demonstrated significant network enrichment, revealing interconnected pathways related to inflammation, neurotransmission, and synaptic plasticity. Functional enrichment highlighted pathways such as cytokines signaling, dopaminergic transmission, and synaptic vesicle cycling. Tissue expression analysis indicated significant involvement of brain regions, including the anterior cingulate cortex and mesolimbic system.

Conclusion: This study underscores the shared genetic underpinnings of severe psychiatric disorders, highlighting common biological processes, such as pro-inflammatory markers and synaptic signaling. These findings offer a transdiagnostic perspective, potentially informing novel therapeutic strategies for overlapping psychiatric conditions.

Keywords: neuroinflammation; protein–protein interaction; severe mental disorders; shared genetic architecture; synaptic plasticity.

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Conflict of interest statement

H.F.G.B. has received research grant support from the Ministry of Science, Technology, and Innovation (MinCiencias) in Colombia, UKRI in the United Kingdom; and speaker fees from Abbott, GSK, Roche, Pfizer, Synergy R&D. V.V., A.C., I.G., V.A., J.F.G.F., J.M.A., and W.T. declare no conflicts of interest to report. R.S.M. has received research grant support from CIHR/GACD/National Natural Science Foundation of China (NSFC) and the Milken Institute; speaker/consultation fees from Lundbeck, Janssen, Alkermes, Neumora Therapeutics, Boehringer Ingelheim, Sage, Biogen, Mitsubishi Tanabe, Purdue, Pfizer, Otsuka, Takeda, Neurocrine, Sunovion, Bausch Health, Axsome, Novo Nordisk, Kris, Sanofi, Eisai, Intra‐Cellular, NewBridge Pharmaceuticals, Viatris, Abbvie, and Atai Life Sciences. He also is the CEO of Braxia Scientific Corp.

Figures

FIGURE 1
FIGURE 1
Protein–protein interaction network of MDD versus BD versus SZ versus PTSD (A). Venn diagram of MDD versus BD versus SZ versus PTSD (B). Protein–protein interaction network of MDD versus BD versus SZ versus PTSD (C). PPI network MDD versus BD versus SZ versus PTSD (including only database, co‐expression, experiments) (D). MCL algorithm graph from 31 genes intersected.
FIGURE 3
FIGURE 3
(A) Coexpression scores based on RNA expression patterns of 31 genes selected from STRING database and ProteomeHD and (B) tissue expression of the 31 genes selected in brain tissues.
FIGURE 2
FIGURE 2
Functional enrichment analysis of the 31 genes selected by MDD versus BD versus SZ versus PTSD (A). Biological pathways (B). Molecular functions (C). Cellular component (D). KEGG pathways (E). Genes grouped by categories.
See this image and copyright information in PMC

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