Machine learning-based personalized inflammation phenotyping and molecular mechanisms of treatment resistance in major depression

Focus topic:	Life Science Technologies
Type of funding:	Individual funding programmes
Programme:	CZS Nexus
Funded institution:	Universität Ulm

Dr. Alexander Behnke researches the biological mechanisms of mental illness. He studied psychology at the TU Dresden, obtained his doctorate at the University of Ulm and most recently worked as a postdoctoral researcher at the University of Ulm and Columbia University.

Goals

Depression is a growing challenge for healthcare worldwide. Chronic, mild inflammatory processes are considered an important risk factor for treatment resistance. However, the causes and sources of this inflammation are still poorly understood.

Dr. Behnke's project aims to trace the inflammation in depression back to the activity of specific immune cell types. Artificial intelligence will be used to identify biomarkers that predict the individual response of patients to their treatment. Gene expression data and in vitro experiments will be used to identify cell-specific molecular mechanisms of inflammatory activity in depression. From this, concrete targets for pharmacological innovations that reduce inflammation will be derived. The project will provide valuable foundations for necessary advances in personalized diagnostics and treatment prognosis of patients with depression and lead to a deeper understanding of inflammatory activity in depression.