Exposure treatment in anxiety disorders: proof of principle of an a priori response prediction approach
While knowledge on the neurobiological signatures of fear and anxiety disorders and, in particular, their association with treatment outcome is accumulating, clinical translation still awaits empirical proof of evidence. Exposure-based cognitive-behavioural therapy (CBT) is a first-line treatment, but clinically significant change is only seen in approx. 50-65% of patients. Patient stratification is a powerful option to increase treatment response; however, developing prognostic markers suitable for single-patient predictions still is in its infancy and crucially requires external cross-validation embedded within an a priori prediction approach - a procedure yet largely missing in the field of biomarker research. Employing a bicentric strategy, we will test the hypothesis that a priori prediction of treatment outcome based on neurobiological measures is possible in a second, independent sample. We will build upon findings from previous mechanistic studies of the CRC and incorporate them into the development of a predictive pattern comprising fear-relevant genotypes and molecules targeting neuropeptides (NPSR1, MAOA, SCL6A4/5-HT, CRHR1, BDNF Val66Met, OXTR), related epigenetic signatures as well as neurofunctional activation patterns associated with fear circuitry functions, and clinical data. Pre-treatment neurobiological signatures will be tested for their potential as a predictive response marker towards behavioural exposure in a model disorder of fear circuitry dysfunctions (spider phobia). Multivariate pattern analyses employing a machine learning framework will be used to generate predictions on the individual patient level and to cross-validate markers in a second, independent sample. We expect this project to further bridge the translational gap between basic and clinical research and to bring stratified medicine approaches into reach as one of the long-term goals of this CRC.