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Katherine Musliner

Associate professor, Department of Affective Disorders, Aarhus University and Aarhus University Hospital-Psychiatry, Aarhus Denmark

Katherine Musliner is an associate professor in the Department of Affective Disorders at Aarhus University Hospital-Psychiatry and the Department of Clinical Medicine at Aarhus University. Her research focuses on the interplay between genetic and non-genetic characteristics as risk factors for onset and outcomes in psychiatric disorders. In particular, she is interested in bringing epidemiological approaches, particularly genetic epidemiology, to bear on research questions that are relevant for clinical practice.

Polygenic risk and clinical outcomes in patients with severe mental illness

Polygenic risk scores are of great interest to the medical community due to their potential for inclusion in clinical practice. However, the utility of these scores as diagnostic or decision aids in psychiatric clinical settings has yet to be established. There are also potential risks associated with the use of polygenic risk scores in clinical settings which need to be balanced against the potential benefits. This presentation will discuss the potential for polygenic risk scores to help predict clinical course in patients with mood disorders. We examined the associations between polygenic risk scores and clinical outcomes such as recurrence, increased severity, progression to a different psychiatric diagnosis, latent trajectories of hospital contacts and future medication use in the iPSYCH2015 case cohort sample. This sample was drawn from the base population of all individuals born in Denmark from 1981 to 2008 and includes all individuals who received a diagnosis of major depressive disorder, bipolar disorder, schizophrenia, attention deficit hyperactivity disorder, autism, or anorexia nervosa in Danish psychiatric hospitals from 1995 to 2015. Our results suggest that polygenic risk scores are better at predicting progression from one psychiatric diagnosis to another than they are at predicting the course of any given diagnosis within a hospital treatment setting.