EPIGENETIC SIGNATURES OF ANXIETY DISORDERS AND OCD: FROM MOLECULAR INSIGHTS TO CLINICAL TRANSLATION

Overall Abstract Anxiety disorders, such as generalized anxiety disorder, panic disorder, and phobias, as well as obsessive compulsive disorder (OCD) are highly prevalent mental disorders that impose significant socioeconomic and personal burdens. Epigenetic mechanisms, particularly DNA methylation, are of interest as a correlate of anxiety disorders because of their role in adapting to the environment throughout the life course and their potential as predictors of treatment response. At the same time, several aspects need to be considered in epigenome-wide association studies of anxiety disorders, including disentangling anxiety and depression signatures, epigenetic signatures across the life span, sample size, and the translational potential of the results. This symposium will present recent findings from members of the PGC Anxiety Epigenetics Working Groups and discuss current topics in the epigenetics of anxiety disorders and OCD. In the first presentation, Daniel Levey will examine epigenetic signatures of anxiety and depression in the Million Veteran Program. The second talk by Colter Mitchell will focus on structured life-course EWAS of internalizing behaviors and anxiety from early childhood into young adulthood. In the third presentation, Lea Zillich will present the latest results of the groups’ cross-anxiety meta-analysis, identifying DNA methylation signatures across nine clinical cohorts and more than 3,000 participants. The fourth talk from Kira Höffler will focus on DNA methylation as a therapeutic marker in OCD. Finally, Thalia Eley will serve as discussant, synthesizing the key findings of the presentations and providing perspectives on potential clinical applications of epigenetic research in anxiety disorders and OCD. Together, these presentations will provide an overview of the current advances in psychiatric epigenetics of anxiety disorders and OCD and discuss future directions to better understand disease mechanisms and improve prediction and prevention strategies.