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    Developing novel theory and methods for understanding the genetic architecture of complex human traits (R21 Clinical Trial Not Allowed)

    Developing methods to understand complex human traits by integrating genetic and non-genetic factors across different scales and disciplines.

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    Funder: National Institutes of Health

    Due Dates: June 16, 2025 (New) | July 16, 2025 (Renewal/Resubmission/Revision) | October 16, 2025 (New) | November 16, 2025 (Renewal/Resubmission/Revision) | February 16, 2026 (New) | March 16, 2026 (Renewal/Resubmission/Revision) | June 16, 2026 (New) | July 16, 2026 (Renewal/Resubmission/Revision) | October 16, 2026 (New) | November 16, 2026 (Renewal/Resubmission/Revision)

    Funding Amounts: Up to $275,000 direct costs over 2 years; no more than $200,000 in any single year; project period max 2 years.

    Summary: Supports interdisciplinary development of novel theory and methods to understand how genetic and non-genetic factors contribute to complex human trait variation.

    Key Information: Clinical trials are not allowed; data generation costs must not exceed 20% of direct costs; methods must be generalizable and use publicly available data.


    Description

    This NIH funding opportunity supports exploratory/developmental (R21) research projects that develop novel theory and methods to better understand the genetic architecture of complex human traits. The focus is on integrating genetic and non-genetic factors—such as environmental, social, and ecological influences—across individuals, families, and populations. Projects should be interdisciplinary, drawing from both natural and social sciences, and should leverage formal theory, simulations, and validation using large-scale, publicly available datasets.

    The program encourages approaches that move beyond traditional frameworks, aiming for comprehensive models that account for direct and indirect, additive and non-additive, and interaction effects. The ultimate goal is to advance holistic, generalizable methods for understanding human trait variation relevant to health and disease.


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