Project Grant R01MH137676

Award Date 9/6/24
Completion Date 5/31/29
Dollars Obligated $1.4M
Federal Grant Program
93.242
Assistance Type
Project Grant
Place of Performance
New York, NY 10013, USA
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This Project Grant award from the National Institute of Mental Health (NIMH), under the Mental Health Research Grants program (CFDA 93.242), is focused on leveraging electronic health records (EHRs) and genetic data to develop predictive models and identify subtypes of psychosis-related disorders. The key products and services to be delivered under this $1,424,534 award include:

  1. Building machine learning-based prediction models to forecast clinical outcomes such as treatment response, illness severity, medical comorbidities, and diagnostic transitions for individuals with psychosis-related disorders, using longitudinal EHR data from two large databases.

  2. Performing cohort-level analyses to discover novel psychosis-related diagnosis and prognosis subtypes.

  3. Enhancing the predictive models by incorporating dimensional phenotyping data (cognition, exposome, social determinants) and whole genome sequencing on a cohort of 10,000 patients with schizophrenia.

  4. Exploring the psychosocial and ethical implications of implementing these psychiatric clinical predictors, including patient and clinician attitudes and experiences.

The award was granted to the New York Genome Center, Inc., a non-profit research institution, on September 6, 2024, with a project period ending on May 31, 2029.

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