Journal
City Healthcare
Record source
OpenAlex Research Library
Abstract / Description
Background. Posttraumatic stress disorder (PTSD) is one of the most prevalent and socially significant consequences of exposure to extreme stress. Its pathogenesis involves impairments in neuroplasticity, in which brain-derived neurotrophic factor (BDNF) plays a key role. In recent decades, the potential of using BDNF system components as biomarkers for objective diagnosis, disease prognosis, and personalized therapy in PTSD has been actively investigated; however, the data remain contradictory and require systematization. The goal was to systematize and summarize current evidence on the role of BDNF in the pathogenesis of PTSD, to examine the molecular, genetic, and epigenetic aspects of its dysfunction, and to evaluate the diagnostic and prognostic potential of BDNF system components as possible biomarkers. Materials and methods. A systematic literature search was conducted in PubMed, Scopus, Web of Science, eLibrary, and Google Scholar databases for the period 2000-2025 in accordance with PRISMA guidelines, using keywords reflecting the relationship between BDNF and PTSD. Original clinical and experimental studies, meta-analyses, and systematic reviews in English and Russian were included. Results. A multi-layered nature of BDNF system dysfunction in PTSD was shown, ranging from region-specific changes in protein expression to genetic and epigenetic alterations. Controversies in peripheral BDNF levels were identified, attributable to differences in biomaterial type, protein form, and sample heterogeneity. Assessment of mature BDNF, the proBDNF/mBDNF ratio, BDNF gene promoter methylation, and regulatory microRNAs (miR-182-5p, miR-9-5p, miR-204-5p) demonstrated prognostic value, being associated with symptom severity, chronicity, and treatment response. The use of total BDNF as an independent diagnostic marker for PTSD is currently not justified. The most promising approach involves integrating a panel of BDNF-related measures (genotype, epigenetic marks, mature protein level, microRNAs) into multifactorial models for disease prognosis and personalized therapy.