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Strategy 2.1

Define the developmental trajectories of mental disorders.

Existing knowledge of brain and behavioral development is insufficient to permit identification of specific time points at which normal and psychopathological trajectories diverge. NIMH seeks novel research approaches to identify such time points that will guide the development of preventive or preemptive interventions. Ultimately, NIMH envisions that findings from targeted basic and clinical research stimulated by this objective would form the basis for a comprehensive “map” of trajectories (i.e., growth curves) of mental illness risk and resilience across the lifespan. Human longitudinal research would characterize intermediate phenotypes and biomarkers that link neurodevelopmental processes with the development of psychiatric disorders. Analogous basic research in non-human animals would include mapping functional gene expression across development, identifying mechanisms regulating cellular, circuit and behavioral maturation, and longitudinal tracking of typical and atypical trajectories of brain development and function.

The current portfolio includes few studies of mental disorder prodromes or precursors of onset. The intent of this strategic objective is to support research that fundamentally breaks new ground in understanding the development of psychopathology, rather than research that incrementally refines well-studied topics.

Research Priorities

  1. Identify points of divergence in typical and atypical developmental trajectories, with a focus on specificity and predictive value.

    Priority areas include:

    1. Incorporating and integrating multiple methods (e.g., epidemiologic, neuroimaging, behavioral, molecular and genetic approaches) to identify and track risk and resilience trajectories for mental disorders. Seek to identify biomarkers with predictive value for diagnosis and treatment.
    2. Conducting longitudinal studies that track changes in behavior with brain structure, connectivity, and function, in order to characterize the progression from primary changes to subsequent clinical presentation, and to identify predictors of divergence from the typical trajectory.
    3. Examining the heterogeneity in individual biologic, behavioral, and social factors across development that affects diagnostic presentation.
    4. Identifying the mechanisms that underlie behavioral changes across development, including epistasis, gene x environment, or gene x development interactions.
  2. Identify the mechanistic basis for aberrant developmental trajectories, emphasizing cellular and circuit dysfunction with predictive value for psychopathology.

    Priority areas include:

    1. Determining the neurobiological and behavioral consequences of genetic variants that have shown empirical associations with mental illness. Use multiple tools in such studies (e.g., imaging, transgenic animals, optogenetics, designer receptors, and behavioral tasks).
    2. Examining the developmental trajectory of epigenomic, transcriptomic, metabolomic, and proteomic changes underlying pathophysiology.
    3. Using patient-specific stem cells to model aberrant proliferation, differentiation, and maturation relevant to mental illnesses, to identify novel targets relevant to mental illness, or to screen candidate therapeutics.
    4. Examining sex differences that emphasize functional consequences for development of aberrant circuitry and behavior underlying models of mental illness.
  3. Determine environmental modifiers of developmental trajectories, emphasizing periods of greatest sensitivity to perturbation and/or intervention.

    Priority areas include:

    1. Identifying potential disease trajectory modifiers, such as early, acute, or chronic immune activation, stress, trauma, or social/cultural factors.
    2. Investigating sensitive periods (i.e., discrete time periods during which the impact of experience is particularly strong) in the development of psychopathology, and identify the optimal periods for intervention to prevent, pre-empt, and/or effectively treat mental illness.
    3. Studying mechanisms by which therapeutically relevant exposures of psychotropic medications affect brain development and behavior. This can include effects of maternal medication on in utero development, or developmental effects of juvenile/adolescent treatment. Priority will be given to studies of mechanisms responsible for changes in the effectiveness of therapeutics across postnatal development.
    4. Studying behaviorally induced neural plasticity, including testing whether cognitive training can lead to long-term changes in behavioral and neural activation, examining the neural specificity and mechanisms of training effects, and identifying sensitive periods and task parameters to optimize behavioral interventions.
  4. Advance research methods and technologies, by improving measurement precision and facilitating the integration and sharing of data characterizing typical and atypical developmental trajectories in humans and non-human animals (relevant to Objectives 2.1, 2.2, and/or 2.3).

    Priority areas include:

    1. Mapping developmental trajectories: develop capabilities for creating a digital informatics “map” that includes extant knowledge about developmental trajectories of mental disorders. The map would integrate findings across species, disorders and modes of discovery. It would include continually updated information (e.g., via PubMed) and could be annotated by the research community.
    2. Measuring and manipulating development: developing novel techniques to compare brain and behavioral function and dysfunction across different ages and species. This could involve integrating longitudinal structural, connectivity, and functional neuroimaging measures; manipulating development and plasticity of cells and circuits in model organisms; high throughput analysis of differentiation in specific brain regions or cell types and consequences of such differentiation on behavior; and identifying axonal projections and connectivity in post-mortem human brain tissue.
    3. Integrating and analyzing diverse data: developing novel analytic techniques to integrate existing data from disparate longitudinal studies and across multiple modalities (e.g., neuroimaging, behavioral, clinical, and epidemiologic), and to cross-calibrate and standardize measures across different developmental periods and species.

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