Integrative Neurobiological Approaches to Assessment

The clinical management of mental illness based on categorical diagnoses alone is limited. A move toward precision medicine in psychiatry requires better understanding of individual mechanisms of risk and resilience. For this, integrative approaches to clinical and biological characterization are needed, in order to advance the ongoing diagnostic re-conceptualization of mental illness toward a dimensional, transdiagnostic, and mechanism-informed disease understanding. This will go hand-in-hand with the identification of biological markers that can aid in diagnosis, therapy selection, prognosis, and the identification of at-risk individuals. This chapter aims to present neurobiological approaches that may assist in the future assessment of mental illness, in the context of the mutual relationship between diagnostic re-conceptualization and mechanistic exploration. The chapter explores different areas of research in biological psychiatry that hold particular promise for future clinical applications, and describes the challenges frequently encountered during the discovery, and the clinical translation of biological illness hallmarks. The focus is particularly on machine learning approaches that can do justice to the complexity of mental health and illness. They have already started to transform other areas of medicine and are being increasingly applied in psychiatry. Finally, this chapter will give a perspective on future developments in biomarker research and the clinical translation of research findings.