This paper reviews that cell-mediated-immune (CMI) activation and inflammation contribute to depressive symptoms, including anhedonia; anxiety-like behaviors; fatigue and somatic symptoms, e.g. illness behavior or malaise; and mild cognitive impairment (MCI). These effects are in part mediated by increased levels of pro-inflammatory cytokines (PICs), e.g. interleukin-1 (IL-1), IL-6 and tumor necrosis factor (TNF)α, and Th-1-derived cytokines, such as IL-2 and interferon (IFN)γ. Moreover, new pathways, i.e. concomitants and sequels of CMI activation and inflammation, were detected in depression: (1) Induction of indoleamine 2,3-dioxygenase (IDO) by IFNγ and some PICs is associated with depleted plasma tryptophan, which may interfere with brain 5-HT synthesis, and increased production of anxiogenic and depressogenic tryptophan catabolites. (2) Increased bacterial translocation may cause depression-like behaviors by activating the cytokine network, oxidative and nitrosative stress (O&NS) pathways and IDO. (3) Induction of O&NS causes damage to membrane ω3 PUFAs, functional proteins, DNA and mitochondria, and autoimmune responses directed against intracellular molecules that may cause dysfunctions in intracellular signaling. (4) Decreased levels of ω3 PUFAs and antioxidants, such as coenzyme Q10, glutathione peroxidase or zinc, are associated with an increased inflammatory potential; more oxidative damage; the onset of specific symptoms; and changes in the expression or functions of brain 5-HT and N-methyl-d-aspartate receptors. (5) All abovementioned factors cause neuroprogression, that is a combination of neurodegeneration, neuronal apoptosis, and lowered neurogenesis and neuroplasticity. It is concluded that depression may be the consequence of a complex interplay between CMI activation and inflammation and their sequels/concomitants which all together cause neuroprogression that further shapes the depression phenotype. Future research should employ high throughput technologies to collect genetic and gene expression and protein data from patients with depression and analyze these data by means of systems biology methods to define the dynamic interactions between the different cell signaling networks and O&NS pathways that cause depression.
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