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During the past two decades, there has been increasing interest in understanding and characterizing the role of inflammation in major depressive disorder. Several evidences linked inflammation to major depression, including the presence of elevated levels of pro-inflammatory cytokines, together with other mediators of inflammation both in the blood and in the brain of depressed patients.However, whether depression itself acts in an immunomodulatory fashion or whether other factors related to depression result in these immunological effects remains an open question. Regardless, major depression is often the result of the exposure to stressful events early in life, which may also act through the modulation of inflammatory responses. Indeed, subjects with a history of childhood trauma show high levels of pro-inflammatory cytokines and an increased risk to develop psychopathologies later in life. Moreover, depressed patients with a history of childhood trauma are also less responsive to antidepressant therapies, suggesting that increased inflammation or altered activation of the immune system may also be relevant for the response to antidepressant therapies. This review will provide an overview on the potential role of the inflammatory/immune system and stress related biomarkers to aid diagnosis, predict treatment response, enhance treatment matching, and prevent the onset or relapse of major depression. We will also discuss the role of early life adverse events in increasing the vulnerability to depression development by acting on the inflammatory and stress-related system. Finally, we will discuss the putative biological mechanisms underlying the transmission, from one generation to the next, of the stress signatures and thus, of the increased vulnerability for psychopathologies induced by childhood trauma events.

An enhanced understanding of the pathophysiology of depression would facilitate the discovery of new efficacious medications. To this end, we examined hippocampal transcriptional changes in rat models of disease and in humans to identify common disease signatures by using a new algorithm for signature-based clustering of expression profiles. The tool identified a transcriptomic signature comprising 70 probesets able to discriminate depression models from controls in both Flinders Sensitive Line and Learned Helplessness animals. To identify disease-relevant pathways, we constructed an expanded protein network based on signature gene products and performed functional annotation analysis. We applied the same workflow to transcriptomic profiles of depressed patients. Remarkably, a 171-probesets transcriptional signature which discriminated depressed from healthy subjects was identified. Rat and human signatures shared the SCARA5 gene, while the respective networks derived from protein-based significant interactions with signature genes contained 25 overlapping genes. The comparison between the most enriched pathways in the rat and human signature networks identified a highly significant overlap (p-value: 3.85 × 10(–6)) of 67 terms including ErbB, neurotrophin, FGF, IGF, and VEGF signaling, immune responses and insulin and leptin signaling. In conclusion, this study allowed the identification of a hippocampal transcriptional signature of resilient or susceptible responses in rat MDD models which overlapped with gene expression alterations observed in depressed patients. These findings are consistent with a loss of hippocampal neural plasticity mediated by altered levels of growth factors and increased inflammatory responses causing metabolic impairments as crucial factors in the pathophysiology of MDD.