[Neurobiology of early life traumatic stress and trauma: Prolonged neuroendocrine dysregulation as a neurodevelopmental risk factor].

Early life stressors display a high universal prevalence and constitute a major public health problem with two thirds of youth being exposed to potentially traumatic experiences by the age of 17. Traumatic stress exposure during critical periods of development may have essential and long-lasting effects on the physical and mental health of individuals and represents a developmental risk factor mediating risk for disease. Early-life stress (ELS) and childhood trauma (CT) can both have an impact on sensitive neuronal brain networks involved in stress reactions, and could exert a programming effect on glucocorticoid signaling leading to chronic hyper- or hypo-activation of the stress system. In addition, alterations in emotional and autonomic reactivity, circadian rhythm disruption, functional and structural changes in the brain, as well as immune and metabolic dysregulation have been lately identified as important risk factors for a chronically impaired homeostatic balance after ELS/CT. Furthermore, human genetic background and epigenetic modifications through stress-related gene expression could interact with these alterations and explain inter-individual variation in vulnerability or resilience to stress. This narrative review presents relevant evidence from mainly human research on the most acknowledged neurobiological allostatic pathways exerting enduring adverse effects of ELS/CT even decades later. Future studies should prospectively investigate potential confounders, their temporal sequence and combined effects at the biological level, while considering the potentially delayed time-frame for the expression of their effects. Finally, screening strategies for ELS/CT and trauma need to be improved. Information about ELS/CT history and the number of adverse experiences could help to better identify the individual risk for disease development, predict individual treatment response and design prevention strategies to reduce the negative effects of ELS/CT.

Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response.

Major depressive disorder is a leading cause of disability worldwide and a major contributor to the overall global burden of disease. While there are several options for antidepressant treatment, only about 40-60% of patients respond to initial monotherapy, while 30-40% of patients may even show resistance to treatment. This article offers a narrative review of those studies evaluating the predictive properties of various blood-based baseline biomarkers regarding treatment responses to the pharmacological, stimulation, or behavioral treatment of patients with treatment-resistant depression (TRD). Our results show that overall, there is only a very limited number of studies assessing baseline peripheral biomarkers regarding treatment response in TRD. Although there is some evidence for the predictive significance of particular biomarkers (e.g., IL-6, CRP, BDNF), the majority of the results are either single-study reports or studies with conflicting results. This may contribute to the wide variety of treatment protocols and different TRD definition criteria, the small number of patients included, and the existence of different biological phenotypes of the disorder used within the various studies. Taken together, there does not yet appear to be any specific baseline peripheral biomarker with sufficient discriminative predictive validity that can be used in the routine clinical practice of TRD. The discovery of new biomarkers and the better clinical characterization of known biomarkers could support the better classification and staging of TRD, the development of personalized treatment algorithms with higher rates of remission and fewer side effects, and the development of new precision drugs for specific subgroups of patients.

[Peripheral prognostic biomarkers of response in treatment-resistant depression].

Major depressive disorder is a serious mental health disorder of high prevalence and the leading cause of disability worldwide. While there are several classes of therapeutic agents with proven antidepressant efficacy, only about 40-60% of patients respond to initial antidepressant monotherapy, and 30-40% of patients may even show resistance to treatment even under optimal antidepressant pharmacotherapy. Despite the existence of international guidelines, there are still no clear and widely accepted treatment algorithms, no established predictive biomarkers of response to treatment, while the management treatment- resistant depression is usually based on clinical experience. The present article offers a brief narrative review of studies published so far on the predictive quality of various blood-based peripheral biomarkers with respect to response to pharmacological, stimulation or behavioral treatment in patients with treatment-resistant depression. To summarize the results, there does not yet appear to be any specific biomarker that has sufficient discriminative predictive validity and can be used in the routine clinical practice of treating resistant depression. Many factors are likely to account for the above-mentioned research findings, including the wide variety of treatment protocols and the non-uniformly accepted definition of resistant depression used by the various studies, the small number of patients with treatment-resistant depression included, and the existence of different pathophysiological phenotypes of the disorder. The ineffective treatment of major depressive disorder requires an immediate improvement of our therapeutic approach by establishing clinically useful and easily accessible predictive biomarkers of response with high accuracy. The discovery of new and better clinical characterization of known biomarkers in the treatment of treatment-resistant depression could support a better staging and classification of the disorder, the development of personalized treatment algorithms for specific patient subgroups, the achievement of higher rates of stable remission, and the development of new precision drugs with minimal side effects.