U01MH136497

Impact-MH: Clinical and behavioral fingerprints of psychopathology - Summary

Psychiatric symptoms are a leading cause of suffering and disability worldwide.

Decades of research have focused on understanding their etiology and underpinnings, typically using a diagnosis-based approach in which individuals with a given condition are compared to a matched ‘control’ group.

Less work has focused on characterizing the longitudinal course of symptoms at the individual level in relation to underlying cognitive, affective, and behavioral mechanisms.

Recognizing that most (if not all) psychiatric disorders are defined by their longitudinal course, this application moves beyond the limitations of traditional diagnosis-centered and ‘case-control’ designs to collect longitudinal data over two years from a large sample (N=2400), highly enriched for psychopathology across a wide range of traditional diagnoses, to identify predictive markers of symptom change using assessments that can be easily implemented in real-world settings.

Specifically, we will collect:

(I) Data embedded in electronic health records (EHR), including social determinants of health;

(II) Traditional clinical measures typically used in diagnosis-based approaches (e.g., clinical interviews, well-validated clinical scales);

(III) Recently developed computational behavioral tasks with demonstrated sensitivity to latent constructs and to within-person change;

(IV) Short gamified behavioral measures of mood and reward-relevant constructs, measured repeatedly;

(V) Spoken narrative responses to uniform prompts for natural language processing (NLP) analyses; and

(VI) Patient-derived and NIH Toolbox continuous measures of key transdiagnostic outcomes.

These data will be analyzed using advanced statistical and machine learning approaches (e.g., latent growth curve modeling, neural network transformer modeling), consistent with the recommendations set forth in the Impact-MH RFA.

In Aim 1, we will use this rich dataset to test the predictive value of ‘traditional’ (EHR, other clinical) vs computational and NLP data in predicting outcomes.

We will further test the differential predictive value of combinations of measures, including sparse and dense behavioral sampling, seeking to identify a minimum set of measures with maximum added clinical value.

In Aim 2, we will examine longitudinal clinical trajectories using data-driven trajectory analysis of multidimensional clinical and computational fingerprints; this approach may ultimately be used to generate normative models to track and forecast clinical course in patients.

Finally, in Aim 3, we will seek to identify subgroups, based on computational fingerprint similarities at baseline, that predict differences in outcomes at 2-year follow-up, and to test whether optimal predictive models differ among such subgroups.

This rich dataset will have enormous value beyond these three aims.

We are recruiting from established diagnosis- and population-specific research programs; combination of the longitudinal data collected here with additional data collected by these programs, including neuroimaging and genetics, will create rich opportunities for secondary and exploratory analyses in subgroups.

Finally, these data will be made available to the community, in deidentified form in collaboration with the Impact-MH Data Coordinating Center, for exploratory and confirmatory analysis by others.

Yale Univ

THE MISSION OF THE NATIONAL INSTITUTE OF MENTAL HEALTH (NIMH) IS TO TRANSFORM THE UNDERSTANDING AND TREATMENT OF MENTAL ILLNESSES THROUGH BASIC AND CLINICAL RESEARCH, PAVING THE WAY FOR PREVENTION, RECOVERY, AND CURE. IN MAY 2020, NIMH RELEASED ITS NEW STRATEGIC PLAN FOR RESEARCH. THE NEW STRATEGIC PLAN BUILDS ON THE SUCCESSES OF PREVIOUS NIMH STRATEGIC PLANS BY PROVIDING A FRAMEWORK FOR SCIENTIFIC RESEARCH AND EXPLORATION, AND ADDRESSING NEW CHALLENGES IN MENTAL HEALTH. THE NEW STRATEGIC PLAN OUTLINES FOUR HIGH-LEVEL GOALS: GOAL 1: DEFINE THE BRAIN MECHANISMS UNDERLYING COMPLEX BEHAVIORS GOAL 2: EXAMINE MENTAL ILLNESS TRAJECTORIES ACROSS THE LIFESPAN GOAL 3: STRIVE FOR PREVENTION AND CURES GOAL 4: STRENGTHEN THE PUBLIC HEALTH IMPACT OF NIMH-SUPPORTED RESEARCH THESE FOUR GOALS FORM A BROAD ROADMAP FOR THE INSTITUTE'S RESEARCH PRIORITIES OVER THE NEXT FIVE YEARS, BEGINNING WITH THE FUNDAMENTAL SCIENCE OF THE BRAIN AND BEHAVIOR, AND EXTENDING THROUGH EVIDENCE-BASED SERVICES THAT IMPROVE PUBLIC HEALTH OUTCOMES. THE INSTITUTE'S OVERALL FUNDING STRATEGY IS TO SUPPORT A BROAD SPECTRUM OF INVESTIGATOR-INITIATED RESEARCH IN FUNDAMENTAL SCIENCE, WITH INCREASING USE OF INSTITUTE-SOLICITED INITIATIVES FOR APPLIED RESEARCH WHERE PUBLIC HEALTH IMPACT IS A SHORT-TERM MEASURE OF SUCCESS. THE NEW STRATEGIC PLAN ALSO ADDRESSES A NUMBER OF CROSS-CUTTING THEMES THAT ARE RELEVANT TO ALL RESEARCH SUPPORTED BY NIMH, THESE THEMES HIGHLIGHT AREAS WHERE NIMH-FUNDED SCIENCE MAY HAVE THE GREATEST IMPACT, BRIDGE GAPS, AND OFFER NOVEL APPROACHES TO ACCELERATE ADVANCES IN MENTAL HEALTH RESEARCH. FOR EXAMPLE, NIMH VALUES A COMPREHENSIVE RESEARCH AGENDA THAT TAKES AN INCLUSIVE APPROACH THAT ENSURES RESEARCH INTERESTS ARE VARIED, MAINTAIN DIVERSE PARTICIPATION AND PARTNERSHIPS, AND ACHIEVE RESEARCH GOALS ACROSS MULTIPLE TIMEFRAMES. THIS INCLUDES DIVERSE METHODOLOGIES, TOOLS, AND MODELS, RESEARCH ADDRESSING COMPLEX BASIC, TRANSLATIONAL, AND APPLIED QUESTIONS, RESEARCH INCLUDING BOTH SEXES AND, AS APPROPRIATE, GENETIC BACKGROUND, AND, PARTICIPANTS FROM DIVERSE RACIAL AND ETHNIC BACKGROUNDS, AND ACROSS GENDER IDENTITIES, GEOGRAPHICAL CONTEXT, SOCIOECONOMIC STATUS, NEUROTYPE, AND AGE OFFERING THE BEST POSSIBLE REPRESENTATION, FOR THE BROADEST NUMBER OF INDIVIDUALS WHO MAY ULTIMATELY BENEFIT FROM THESE SCIENTIFIC ADVANCES. TO ACCOMPLISH THE GOALS OUTLINED IN THE NEW STRATEGIC PLAN, NIMH WILL SUPPORT RESEARCH THAT AIMS: TO CHARACTERIZE THE GENOMIC, MOLECULAR, CELLULAR, AND CIRCUIT COMPONENTS CONTRIBUTING TO BRAIN ORGANIZATION AND FUNCTION, TO IDENTIFY THE DEVELOPMENTAL, FUNCTIONAL, AND REGULATORY MECHANISMS RELEVANT TO COGNITIVE, AFFECTIVE, AND SOCIAL DOMAINS, ACROSS UNITS OF ANALYSIS, AND, TO GENERATE AND VALIDATE NOVEL TOOLS, TECHNIQUES, AND MEASURES TO QUANTIFY CHANGES IN THE ACTIVITY OF MOLECULES, CELLS, CIRCUITS, AND CONNECTOMES. TO DISCOVER GENE VARIANTS AND OTHER GENOMIC ELEMENTS THAT CONTRIBUTE TO THE DEVELOPMENT OF MENTAL ILLNESSES IN DIVERSE POPULATIONS, TO ADVANCE OUR UNDERSTANDING OF THE COMPLEX ETIOLOGY OF MENTAL ILLNESSES USING MOLECULAR EPIDEMIOLOGIC APPROACHES THAT INCORPORATE INDIVIDUAL GENETIC INFORMATION IN LARGE COHORTS, TO ELUCIDATE HOW HUMAN GENETIC VARIATION AFFECTS THE COORDINATION OF MOLECULAR, CELLULAR, AND PHYSIOLOGICAL NETWORKS SUPPORTING HIGHER-ORDER FUNCTIONS AND EMERGENT PROPERTIES OF NEUROBIOLOGICAL SYSTEMS, AND, TO DEVELOP NOVEL TOOLS AND TECHNIQUES FOR THE ANALYSIS OF LARGE-SCALE GENETIC, MULTI-OMIC DATA AS IT APPLIES TO MENTAL HEALTH. TO UTILIZE CONNECTOMIC APPROACHES TO IDENTIFY BRAIN NETWORKS AND CIRCUIT COMPONENTS THAT CONTRIBUTE TO VARIOUS ASPECTS OF MENTAL FUNCTION AND DYSFUNCTION, TO DETERMINE THROUGH BRAIN-WIDE ANALYSIS HOW CHANGES IN THE PHYSIOLOGICAL PROPERTIES OF MOLECULES, CELLS, AND CIRCUITS CONTRIBUTE TO MENTAL ILLNESSES, TO DEVELOP MOLECULAR, CELLULAR, AND CIRCUIT-LEVEL BIOMARKERS OF IMPAIRED NEURAL FUNCTION IN HUMANS, AND, TO DEVELOP INNOVATIVE TECHNOLOGIES, INCLUDING NEW IMAGING, COMPUTATIONAL, PHARMACOLOGICAL, AND GENETIC TOOLS TO INTERROGATE AND MODULATE CIRCUIT ACTIVITY AND STRUCTURE ALTERED IN MENTAL ILLNESSES. TO ELUCIDATE THE MECHANISMS CONTRIBUTING TO THE TRAJECTORIES OF BRAIN DEVELOPMENT AND BEHAVIOR, AND, TO CHARACTERIZE THE EMERGENCE AND PROGRESSION OF MENTAL ILLNESSES, AND IDENTIFYING SENSITIVE PERIODS FOR OPTIMAL INTERVENTION. TO DETERMINE EARLY RISK AND PROTECTIVE FACTORS, AND RELATED MECHANISMS, TO SERVE AS NOVEL INTERVENTION GROUPS, AND, TO DEVELOP RELIABLE AND ROBUST BIOMARKERS AND ASSESSMENT TOOLS TO PREDICT ILLNESS ONSET, COURSE, AND ACROSS DIVERSE POPULATIONS. TO DEVELOP NOVEL INTERVENTIONS USING A MECHANISM-INFORMED, EXPERIMENTAL THERAPEUTICS APPROACH, AND, TO DEVELOP AND IMPLEMENT MEASUREMENT STRATEGIES TO FACILITATE MECHANISM-BASED INTERVENTION DEVELOPMENT AND TESTING. TO INVESTIGATE PERSONALIZED INTERVENTION STRATEGIES ACROSS DISEASE PROGRESSION AND DEVELOPMENT, AND, TO DEVELOP AND REFINE COMPUTATIONAL APPROACHES AND RESEARCH DESIGNS THAT CAN BE USED TO INFORM AND TEST PERSONALIZED INTERVENTIONS. TO DEVELOP AND TEST APPROACHES FOR ADAPTING, COMBINING, AND SEQUENCING INTERVENTIONS TO ACHIEVE THE GREATEST IMPACT ON THE LIVES AND FUNCTIONING OF PERSONS SEEKING CARE, TO CONDUCT EFFICIENT PRAGMATIC TRIALS THAT EMPLOY NEW TOOLS TO RAPIDLY IDENTIFY, ENGAGE, ASSESS, AND FOLLOW PARTICIPANTS IN THE CONTEXT OF ROUTINE CARE, AND, TO ENHANCE THE PRACTICAL RELEVANCE OF EFFECTIVENESS RESEARCH VIA DEPLOYMENT-FOCUSED, HYBRID, EFFECTIVENESS-IMPLEMENTATION STUDIES. TO EMPLOY ASSESSMENT PLATFORMS WITHIN HEALTHCARE SYSTEMS TO ACCURATELY ASSESS THE DISTRIBUTION AND DETERMINANTS OF MENTAL ILLNESSES AND TO INFORM STRATEGIES FOR IMPROVED SERVICES, TO OPTIMIZE REAL-WORLD DATA COLLECTION SYSTEMS TO IDENTIFY STRATEGIES FOR IMPROVING ACCESS, QUALITY, EFFECTIVENESS, AND CONTINUITY OF MENTAL HEALTH SERVICES, AND, TO COMPARE ALTERNATIVE FINANCING MODELS TO PROMOTE EFFECTIVE AND EFFICIENT CARE FOR INDIVIDUALS WITH SERIOUS EMOTIONAL DISTURBANCES AND SERIOUS MENTAL ILLNESSES. TO STRENGTHEN PARTNERSHIPS WITH KEY STAKEHOLDERS TO DEVELOP AND VALIDATE STRATEGIES FOR IMPLEMENTING, SUSTAINING, AND CONTINUOUSLY IMPROVE EVIDENCE-BASED PRACTICES, TO BUILD MODELS TO SCALE-UP EVIDENCE-BASED PRACTICES FOR USE IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE AND OTHER SETTINGS, AND, TO DEVELOP DECISION-SUPPORT TOOLS AND TECHNOLOGIES THAT INCREASE THE EFFECTIVENESS AND CONTINUOUS IMPROVEMENT OF MENTAL HEALTH INTERVENTIONS IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE, AND OTHER SETTINGS. TO ADAPT, VALIDATE, AND SCALE-UP PROGRAMS CURRENTLY IN USE THAT IMPROVE MENTAL HEALTH SERVICES FOR UNDERSERVED POPULATIONS, TO DEVELOP AND VALIDATE SERVICE DELIVERY MODELS THAT PROVIDE EVIDENCE-BASED CARE FOR INDIVIDUALS THROUGHOUT THE COURSE OF MENTAL ILLNESS, TO DEVELOP AND VALIDATE SYSTEMS-LEVEL STRATEGIES USING TECHNOLOGY AND OTHER APPROACHES, TO IDENTIFY, SUPPORT, AND MONITOR THE EFFECTIVENESS OF EVIDENCE-BASED CARE THROUGHOUT THE COURSE OF ILLNESS, AND, TO DEVELOP AND VALIDATE DECISION-MAKING MODELS THAT BRIDGE MENTAL HEALTH, MEDICAL, AND OTHER CARE SETTINGS TO INTEGRATE THE APPROPRIATE CARE FOR PEOPLE WITH SERIOUS MENTAL ILLNESSES AND COMORBID MEDICAL CONDITIONS.

93.242 - Mental Health Research Grants

National Institute of Mental Health (NIMH) [HHS - NIH]

New Haven, Connecticut 065102715 United States

Single Zip Code

Individually Measured Phenotypes to Advance Computational Translation in Mental Health (IMPACT-MH) (U01 Clinical Trial Optional) (RFA-MH-23-105)

Amendment Since initial award the total obligations have increased 100% from $4,159,108 to $8,309,045.