Dynamic risk prediction (DRP) model for post trauma psychopathology

Hippocrates, the father of medicine, put forth the importance of prognosis over diagnosis stating that; “there is no such thing as a disease; there are individuals who fall ill”. Modern medicine, however, has made diagnosis the venerable element of medical practice. Mental disorders lack indefinite anatomical and or pathogenic indicators, and therefore could benefit from an evidence-based prognostic approach. Such models built on neurobiological and psychological measurements will allow reliably predicting the risk of future illness, likelihood of remission vs chronicity as well as treatment response in an individual patient (i.e. personalized manner). Our work aims to develop a prediction model for developing psychopathology after an exposure to a traumatic stressor. 

Stress is ever-present in our lives, significantly impacting the onset and aggravation of mental and physical health and resulting in an economic cost of ~ 300€ billion annually. Critically, even a single life-threatening stressful event can trigger an onset of a debilitating mental disorder like Post-Traumatic Stress Disorder (PTSD), the most common trauma-related psychopathology. However, the trajectories of response to a potentially traumatic event vary immensely between individuals, ranging from full remission to lifelong debilitating disorder. We assume that the trajectory of traumatic stress response could be depicted by repeated measurements at multi–domains, enabling us to capture the nature and dynamics of the response which might result in post-traumatic psychopathology. It is well established that knowing the clinical trajectory early on is essential for efficient prevention and/or treatment of PTSD as well as for unveiling the underlying mechanisms of the disorder.

The main goal of this project is to apply advanced statistical and machine learning methods for developing Dynamic Risk Prediction (DRP) models for individual post-traumatic psychopathology. We believe that such a model could serve for precise and personalized monitoring, prevention and treatment of PTSD. The computation of the DRP model will be based on three unique independent datasets recently obtained at PI Hendler’s lab, covering post-traumatic psychopathology development from one-month post-trauma and up to many years later on (i.e., acute and chronic PTSD populations).