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    NIDA Animal Genomics Program (U01 Clinical Trial Not Allowed)

    The NIDA Animal Genomics Program aims to identify genetic variants influencing addictive behaviors, SUD stages, associated behaviors, and comorbidities through genomics approaches.

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    Funder: National Institutes of Health

    Due Dates: July 23, 2025 (New/Renewal/Resubmission/Revision) | February 11, 2026 (New/Renewal/Resubmission/Revision) | July 23, 2026 (New/Renewal/Resubmission/Revision) | February 11, 2027 (New/Renewal/Resubmission/Revision)

    Funding Amounts: No budget cap; budgets must reflect actual project needs. Maximum project period: 5 years. Cooperative agreement (U01).

    Summary: Supports research to identify genetic, genomic, and molecular (epi)genetic variants underlying addiction-related phenotypes, substance use disorder (SUD) stages, associated behaviors, and comorbidities using animal models and multi-omics approaches.

    Key Information: Clinical trials are not allowed. Foreign and domestic organizations are eligible. Data management and sharing plans are required.


    Description

    This opportunity, offered by the National Institute on Drug Abuse (NIDA) at NIH, funds research to uncover the genetic, genomic, and molecular (including epigenetic) variants that underlie neural and behavioral processes relevant to substance use disorder (SUD) risk, progression, and comorbidities. The program aims to link genetic and molecular mechanisms to neural circuit function and behavior, using animal models and advanced genomics, multi-omics, and data science approaches.

    Research may focus on:

    • Phenotypes associated with addictive behaviors and vulnerability to different SUD stages (e.g., initial use, escalation, tolerance, dependence, relapse, recovery).
    • Behaviors genetically associated with SUD (e.g., impulsivity, novelty seeking).
    • Comorbidities with genetic correlations to SUD (e.g., anxiety, stress, social defeat).

    NIDA encourages projects that integrate multi-level omics data, delineate gene networks, and/or use artificial intelligence or machine learning. Studies may include variant identification at the neural circuit level and the application of neuroscience to genomics in tissues and cells. The ultimate goal is to reveal novel mechanisms and inform future therapeutic strategies for addiction.


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