Forgetful, sad and old: Do vascular cognitive impairment and depression share a common pre-disease network and how is it impacted by ageing?

Vascular cognitive impairment (VCI) and depression frequently coexist in geriatric populations and reciprocally increase disease risks. We assert that a shared pre-disease state of the psycho-immune-neuroendocrine (PINE) network model mechanistically explains bidirectional associations between VCI and depression. Five pathophysiological sub-networks are identified that are shared by VCI and depression: neuroinflammation, kynurenine pathway imbalance, hypothalamic-pituitary-adrenal (HPA) axis overactivity, impaired neurotrophic support and cerebrovascular dysfunction. These do not act independently, and their complex interactions necessitate a systems biology approach to better define disease pathogenesis. The PINE network is already established in the context of non-communicable diseases (NCDs) such as depression, hypertension, atherosclerosis, coronary heart disease and type 2 diabetes mellitus. We build on previous literature to specifically explore mechanistic links between MDD and VCI in the context of PINE pathways and discuss key mechanistic commonalities linking these comorbid conditions and identify a common pre-disease state which precedes transition to VCI and MDD. We expand the model to incorporate bidirectional interactions with biological ageing. Diathesis factors for both VCI and depression feed into this network and the culmination of shared mechanisms (on an ageing substrate) lead to a critical network transition to one or both disease states. A common pre-disease state underlying VCI and depression can provide clinicians a unique opportunity for early risk assessment and intervention in disease development. Establishing the mechanistic elements and systems biology of this network can reveal early warning or predictive biomarkers together with novel therapeutic targets. Integrative studies are recommended to elucidate the dynamic networked biology of VCI and depression over time.

Environmental Stressors and the PINE Network: Can Physical Environmental Stressors Drive Long-Term Physical and Mental Health Risks?

Both psychosocial and physical environmental stressors have been linked to chronic mental health and chronic medical conditions. The psycho-immune-neuroendocrine (PINE) network details metabolomic pathways which are responsive to varied stressors and link chronic medical conditions with mental disorders, such as major depressive disorder via a network of pathophysiological pathways. The primary objective of this review is to explore evidence of relationships between airborne particulate matter (PM, as a concrete example of a physical environmental stressor), the PINE network and chronic non-communicable diseases (NCDs), including mental health sequelae, with a view to supporting the assertion that physical environmental stressors (not only psychosocial stressors) disrupt the PINE network, leading to NCDs. Biological links have been established between PM exposure, key sub-networks of the PINE model and mental health sequelae, suggesting that in theory, long-term mental health impacts of PM exposure may exist, driven by the disruption of these biological networks. This disruption could trans-generationally influence health; however, long-term studies and information on chronic outcomes following acute exposure event are still lacking, limiting what is currently known beyond the acute exposure and all-cause mortality. More empirical evidence is needed, especially to link long-term mental health sequelae to PM exposure, arising from PINE pathophysiology. Relationships between physical and psychosocial stressors, and especially the concept of such stressors acting together to impact on PINE network function, leading to linked NCDs, evokes the concept of syndemics, and these are discussed in the context of the PINE network.

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

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.