Investigating biological traces of traumatic stress in changing societies: challenges and directions from the ESTSS Task Force on Neurobiology

Traumatic stress can have severe consequences for both mental and physical health. Furthermore, both psychological and biological traces of trauma increase as a function of accumulating traumatic experiences. Neurobiological research may aid in limiting the impact of traumatic stress, by leading to advances in preventive and treatment interventions. To promote the possibility for clinical implementation of novel research findings, this brief review describes timely conceptual and methodological challenges and directions in neurobiological trauma research on behalf of the Task Force “Neurobiology of Traumatic Stress” of the European Society for Traumatic Stress Studies (ESTSS). The most important conceptual challenges are the heterogeneity of disorders and existence of subtypes across diagnostic categories: differential latent profiles and trajectories regarding symptom expression and neural correlates are being unraveled; however, similar latent classes’ approaches for treatment response and neurobiological data remain scarce thus far. The key to improving the efficacy of currently available preventive interventions and treatments for trauma-related disorders lies in a better understanding and characterization of individual differences in response to trauma and interventions. This could lead to personalized treatment strategies for trauma-related disorders, based on objective information indicating whether individuals are expected to benefit from them. The most important methodological challenge identified here is the need for large consortia and meta-analyses or, rather, mega-analyses on existent data as a first step. In addition, large multicenter studies, combining novel methods for repeated sampling with more advanced statistical modeling techniques, such as machine learning, should aim to translate identified disease mechanisms into molecular blood-based biomarker combinations to predict disorder vulnerability and treatment responses