Saving lives: building a total nationwide multimodal suicide cohort to improve precision in prediction and prevention of suicide
Approximately 800,000 people die by suicide globally every year, accounting for 1.5% of all deaths. Suicide is the leading cause of death among 15-24-year-olds in the world. The ultimate purpose of this research project is to decrease suicide rates by improving our ability to predict this outcome.
The causes of suicide are complex, with a wide range of predisposing factors and precipitating events. Prediction and prevention of suicide remains a major public health challenge. Overall, this project aims to lay the groundwork to increase our ability to prevent suicide.
- What environmental variables are associated with suicide deaths?
- Which genetic variants are associated with suicide deaths?
- Can a combination of register-based and genetic risk factors improve suicide prediction?
- Can machine learning using the multimodal dataset improve suicide prediction?
The principal investigator of the project is Christian Rück, psychiatrist and Professor at the Department of Clinical Neuroscience, KI. He has expertise in leading large clinical and multimodal projects to completion and implementation. James Crowley, Associate Professor in Genetics at the University of North Carolina at Chapel Hill and affiliated to KI. He is the lead PI of the two large genetics projects, the Danish OCD and Tourette Study (DOTS) and the Nordic OCD & Related Disorders Consortium (NORDiC). Role: expertise in genetics. Patrick F Sullivan is Professor of psychiatric genetics at KI and Professor at the University of North Carolina at Chapel Hill. Prof Sullivan is a founder and the lead principal investigator of the Psychiatric Genomics Consortium (PGC), the largest consortium in the history of psychiatry. Professors Christina Dalman, Håkan Karlsson, and Renee Gardner, KI, have vast experience in working with all aspects of PKU based data acquisition and both biological and register analyses for other phenotypes such as schizophrenia and autism and are organizing the data acquisition in this project. Professor Seena Fazel, Oxford University and Professor Bo Runeson, KI, provide the team with expertise in suicidology. Professor Fazel also has studied risk prediction tools for suicide and other behaviors. John Wallert, assistant professor at KI, Matthew Halvorsen, PhD at University of North Carolina at Chapel Hill and KI and Magnus Boman, Professor in Intelligent Software Systems and a computational epidemiologist at the Royal Institute of Technology are our computational backbone with expertise in genetical analysis and Machine Learning. Boman’s group tackles all levels of the Machine Learning stack, from knowledge representation to the smallest detail of data storage and recall. David Mataix-Cols, Professor at KI, the most cited European researcher (ISI Web of Science) in the field of anxiety, obsessive-compulsive, and related disorders. Lorena Fernández de la Cruz is a senior researcher at KI with expertise in register-based research including suicide. Julia Boberg is a clinical psychologist and PhD student. Roles: study design, data analysis, and interpretation. Associate Professor Niklas Juth, KI, is a philosopher and medical ethicist with expertise in the ethical issues involved in prediction and genetics.
Group members involved in the project