The pathophysiology of major depressive disorder through the lens of systems biology: Network analysis of the psycho-immune-neuroendocrine physiome

Nicolas J C Stapelberg, Tuan A Bui, Verena Mansour, Susannah Johnson, Grace Branjerdporn*, Sam Adhikary, Kevin Ashton, Nevin Taylor, John P Headrick

*Corresponding author for this work

Research output: Contribution to journalReview articleResearchpeer-review

1 Citation (Scopus)

Abstract

BACKGROUND/AIMS: The psycho-immune-neuroendocrine (PINE) network is a predominantly physiological (metabolomic) model constructed from the literature, inter-linking multiple biological processes associated with major depressive disorder (MDD), thereby integrating putative mechanistic pathways for MDD into a single network.

MATERIAL AND METHODS: Previously published metabolomic pathways for the PINE network based on literature searches conducted in 1991-2021 were used to construct an edge table summarizing all physiological pathways in pairs of origin nodes and target nodes. The Gephi software program was used to calculate network metrics from the edge table, including total degree and centrality measures, to ascertain key network nodes and construct a directed network graph.

RESULTS: An edge table and directional network graph of physiological relationships in the PINE network is presented. The network has properties consistent with complex biological systems, with analysis yielding key network nodes comprising pro-inflammatory cytokines (TNF- α, IL6 and IL1), glucocorticoids and corticotropin releasing hormone (CRH). These may represent central structural and regulatory elements in the context of MDD.

CONCLUSION: The identified hubs have a high degree of connection and are known to play roles in the progression from health to MDD. These nodes represent strategic targets for therapeutic intervention or prevention. Future work is required to build a weighted and dynamic simulation of the network PINE.

Original languageEnglish
Article number577959
JournalJournal of Neuroimmunology
Volume372
Early online date3 Sep 2022
DOIs
Publication statusPublished - 15 Nov 2022

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