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Sickness Behaviour and Depression: An Updated Model of Peripheral-Central Immunity Interactions
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Submitted:
01 March 2022
Posted:
03 March 2022
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Abstract
Current lines of research into mood disorders indicate that immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain functions, even when these mediators are produced in peripheral tissues. Elevated levels of circulating immune molecules have been consistently associated with depressive symptoms in a number of clinical populations and experimental models, to the extent that major depressive disorder (MDD) is now seen, at least in part, as a disorder of immunity. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy with the hope to improve treatment efficacy, particularly in those cohorts that do not respond well to standard medication. Such new practice requires the availability of biomarkers to tailor these new therapies to those most likely to benefit but also clear mechanisms of action describing the interaction between peripheral immunity and brain function. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease through peripherally induced sickness behaviour as the model for immune-induced MDD. After an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we propose a modified model of periphery-brain interaction that goes beyond the currently established view of interaction between peripheral cytokines and microglia cells as the driver of depression. Instead, we suggest that brain barriers are primary actors in the communication between body and brain and, as a consequence, in the pathophysiology of the disease. This model suggests novel biomarkers, novel targets for therapies as well as a novel mechanism for resistance to standard treatments.
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Subject: Medicine and Pharmacology - Psychiatry and Mental Health
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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