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Strategy 1.2

Identify the genetic and environmental factors associated with mental disorders.

NIMH invites research focused on model systems, domains of function (e.g. emotion regulation, executive function, impulsivity, social communication, and memory), and/or patient populations. Investigators are encouraged to integrate their research across levels of analysis; utilize neurodevelopmental approaches; and study sex/gender differences. NIMH also encourages genomic studies in diverse, global populations, including African Americans and Hispanics, as well as population isolates. NIMH has large existing efforts in genome wide association studies (GWAS) and encourages applications that leverage insights from these types of studies to pursue innovative approaches in phenotyping, epigenomics, and next generation sequencing.

Applicants are highly encouraged to generate and broadly share data and biospecimens through the appropriate databases and repositories, such as the NIMH Human Genetics Initiative , the NIH database of Genotypes and Phenotypes , or the National Database for Autism Research . For guidance on consent and data sharing templates, please contact Dr. Yin Yao .

Research Priorities

  1. Define genomic variations associated with mental disorders.

    Priority areas include:

    1. Identifying pathogenic genomic variation in large datasets and across disorders.
    2. Targeting collection of DNA samples from both patients and first-degree relatives for disorders that are under-represented in the portfolio (e.g., autism spectrum disorder, attention deficit/hyperactivity disorder, eating disorders, obsessive compulsive disorder, and Tourette Syndrome).
  2. Determine the biological consequences of genomic variation associated with mental disorders.

    Priority areas include:

    1. Discovering the functional molecular elements in pathways and circuits associated with mental disorders or component phenotypes (with a special emphasis on systems biology and gene regulation).
    2. Determining and validating patterns of gene expression across tissues (e.g. peripheral blood, fibroblasts, lymphocyte cell lines, induced pluripotent stem cells) to identify biomarkers associated with mental disorders.
    3. Developing comprehensive molecular models across trajectories of normative and clinical phenotypes (and component phenotypes) that are related to domains of brain functions.
    4. Using paradigms of comparative and evolutionary biology to identify homologous critical genomic elements in humans and other species to understand brain function across development in health and disease states.
  3. Promote discovery of the role of novel risk/susceptibility genes.

    Priority areas include:

    1. Studying gene and protein networks in cells and circuits that regulate NIMH-relevant domains of function.
    2. Determining whether alternate mRNA isoforms or changes in the levels, timing, and/or location of gene expression in the brain contribute to pathophysiological outcomes.
    3. Understanding how environmental and experiential influences interact with susceptibility genes to compound risk for dysfunction and/or psychopathology.
    4. Demonstrating how changes in gene expression in development and across the lifespan are influenced by and interact with environmental conditions leading to functional and behavioral outcomes of interest to NIMH.
  4. Define the molecular mechanisms responsible for sensitive periods in development when experience can have enduring effects on gene expression, brain function, or behavior. Variables to consider can include, but are not limited to, parent of origin effects, paternal age, drug exposures, immune activation, stress, and social factors impacting risk for mental disorders.

    Priority areas include:

    1. Identifying genetic factors that alter experience-dependent gene expression, brain function, or cognition.
    2. Developing, validating, and using appropriate model systems to examine suspected environmental contributors.
    3. Using genome-wide analyses followed by in-depth functional studies to investigate epigenomic alterations associated with developmental transitions and/or environmental conditions.
  5. Develop informatics tools and statistical methods for data integration and analysis.

    Priority areas include:

    1. Developing novel tools and approaches in bioinformatics and related areas to integrate large diverse datasets across phenotypes.
    2. Developing novel statistical methods to analyze increasingly large datasets across molecular hierarchies (e.g., sequence, expression, regulation, deep phenotyping, etc).
    3. Developing statistical methods for relating genetic information to brain structure, function, and connectivity, especially methods for correcting for multiple comparisons of large numbers of candidate gene variants or for interactions of gene variants.

Back to Strategic Objective 1 Overview