Mapping the Genetic Landscape Across 14 Psychiatric Disorders: Clinical Implications for Underlying Genetic Factors

The traditional psychiatric diagnostic framework confers discrete categories that researchers continue to challenge. This webinar will review the methods and findings reported in the paper, Mapping the Genetic Landscape Across 14 Psychiatric Disorders published in Nature (December 2025). Future implications for clinical care in psychiatry will be discussed.

Center for Practice Transformation – University of Minnesota has been approved by NBCC as an Approved Continuing Education Provider, ACEP No. 7404. Programs that do not qualify for NBCC credit are clearly identified. Center for Practice Transformation – University of Minnesota is solely responsible for all aspects of the programs. This applies to the live webinar event.

Center for Practice Transformation is a pre-approved CE Provider by the Minnesota Board of Social Work (#CEP-204).

For participants needing clinical clock hours (CCH), this workshop meets the requirements, as defined by the Board of Social Work: 

  • Differential diagnosis and biopsychosocial assessment, including narrative development and psychopathology across the life span: 1 CCH
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Format

Virtual

Number of CEUs

1 CEU(s)

Type

Webinar
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About the Presenter

Peter P. Zandi, PhD, MPH, MHS

Peter P. Zandi is the Arlene and Robert Kogod Professor of Mood Disorders and Vice Chair of Precision Medicine in the Department of Psychiatry and Behavioral Sciences at the Johns Hopkins University School of Medicine.  He is Co-Director of the Precision Medicine Center of Excellence in Mood Disorders, and he is Research Champion for the National Network of Depression Centers.  He earned his degrees in psychiatric epidemiology at Johns Hopkins and has expertise in genetic epidemiology, pharmacoepidemiology, pharmacogenetics, and mental health informatics.  His group uses statistical genetics and bioinformatics methods to study the genetic causes mood disorders. He also has experience leading observational and randomized studies to evaluate pharmacological and neuromodulation treatments for mood disorders, as well as pharmacogenetics studies of responses to these treatments. More recently, he has been working to develop new approaches that leverage health informatics technologies, including electronic medical records and mobile technology, to establish learning health systems for mood disorders that can support the next generation of large-scale research on mood disorders.  The goal of his work is to advance our understanding of the causes of mood disorders and develop precision-guided strategies for treating and preventing them.  

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