Abstract The National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) initiative is a dimensional framework to study psychopathology in terms of deviations from normal processes, rather than starting with a categorical syndrome and then seeking biological and behavioral mechanisms that correspond to that syndrome. RDoC was introduced in 2009 to fill a gap in the status quo approaches for psychopathology research design to advance the understanding of mental disorders. The emphasis is on connecting measurements in biological and behavioral activity as assessed by a wide variety of data types. This chapter describes the various aspects of dimensionality that embody a central principle of RDoC research. Normal-to-abnormal dimensions represent transitions to and from clinical pathology across time and periods of development, where heterogeneity can be captured by different kinds of observations (e.g., neural systems, behavior, and symptom reports). Looking forward, an integration of the multiple measures of functions relevant to psychopathology can contribute to an empirically based understanding of mental disorders to inform efforts toward clinical diagnostic precision and create avenues for novel treatment development. The RDoC initiative also supports the development of reliable and valid tasks, fast becoming a norm for assessing psychopathological dimensions, as well as providing a platform to integrate computational methods and machine learning with psychopathology research.

Abstract The Research Domain Criteria (RDoC) project is an experimental framework for translational research on mental illness. The project was initiated in response to the increasing concern that contemporary scientific data in genetics, neurobiology, and behavior do not align with current diagnostic categories, thus constraining cutting-edge research. RDoC encourages new ways of studying psychopathology in terms of dysregulation in basic functions (e.g., working memory or reward valuation), with an emphasis on neurodevelopment and environmental effects that are recognized as key drivers of disorder risk. This chapter reviews ways in which RDoC has integrated multiple measures of dimensional functions to promote mechanistic studies that have already resulted in multiple proof-of-concept clinical trials. This transdiagnostic research has fostered a wide variety of computational methods that are shifting perspectives on mental illness toward a precision approach to psychiatry.

Background Diagnosis in psychiatry faces familiar challenges. Validity and utility remain elusive, and confusion regarding the fluid and arbitrary border between mental health and illness is increasing. The mainstream strategy has been conservative and iterative, retaining current nosology until something better emerges. However, this has led to stagnation. New conceptual frameworks are urgently required to catalyze a genuine paradigm shift.Methods We outline candidate strategies that could pave the way for such a paradigm shift. These include the Research Domain Criteria (RDoC), the Hierarchical Taxonomy of Psychopathology (HiTOP), and Clinical Staging, which all promote a blend of dimensional and categorical approaches.Results These alternative still heuristic transdiagnostic models provide varying levels of clinical and research utility. RDoC was intended to provide a framework to reorient research beyond the constraints of DSM. HiTOP began as a nosology derived from statistical methods and is now pursuing clinical utility. Clinical Staging aims to both expand the scope and refine the utility of diagnosis by the inclusion of the dimension of timing. None is yet fit for purpose. Yet they are relatively complementary, and it may be possible for them to operate as an ecosystem. Time will tell whether they have the capacity singly or jointly to deliver a paradigm shift.Conclusions Several heuristic models have been developed that separately or synergistically build infrastructure to enable new transdiagnostic research to define the structure, development, and mechanisms of mental disorders, to guide treatment and better meet the needs of patients, policymakers, and society.

Despite tremendous advancements in neuroscience, there has been limited impact on patient care. Current psychiatric treatments are largely non-specific, and drug development is hindered by outdated, overinclusive diagnostic categories and a "one-size-fits-all" approach. Additionally, mechanisms underlying psychiatric illnesses and their treatments with conventional medications remain poorly understood. Precision psychiatry is a strategy that holds great promise for novel therapies targeting specific pathophysiologic mechanisms in selected patients, ultimately contributing to more effective, personalized treatments. Immunopsychiatry, which focuses on the immune system's role in psychiatric disorders, exemplifies the challenges and potential solutions for precision psychiatry. Despite understanding how inflammation contributes to psychiatric illness, results of clinical trials with anti-inflammatory drugs have been inconsistent and underwhelming. Shortcomings of these trials include a lack of focus on subgroups of patients with increased inflammation, the use of non-specific outcome variables (e.g., not specific to inflammation's impact on the brain and behavior), and failure to establish target engagement of the inflammatory response. To advance anti-inflammatory treatments, clinical trials should: 1) enrich for patients using predictive biomarkers; 2) use clinical outcome assessments that align with inflammation's effects on the brain; 3) consider novel diagnostic constructs linked to inflammation; and 4) verify target engagement. Moreover, greater attention should be paid to efforts to repurpose available anti-inflammatory drugs while awaiting development of novel treatments targeting more specific immune pathways. Taken together, a collaborative approach involving academia, industry, funding agencies, patients, payors, and policymakers is required to advance Immunopsychiatry and ultimately provide a roadmap for successful implementation of precision psychiatry.

Current nosology claims to separate mental disorders into distinct categories that do not overlap with each other. This nosological separation is not based on underlying pathophysiology but on convention-based clustering of qualitative symptoms of disorders which are typically measured subjectively. Yet, clinical heterogeneity and diagnostic overlap in disease symptoms and dimensions within and across different diagnostic categories of mental disorders is huge. While diagnostic categories provide the basis for general clinical management, they do not describe the underlying neurobiology that gives rise to individual symptomatic presentations. The ability to incorporate neurobiology into the diagnostic framework and to stratify patients accordingly will be a critical step forward for the development of new treatments for mental disorders. Furthermore, it will also allow physicians to provide patients with a better understanding of their illness's complexities and management. To realize this ambition, a paradigm shift is needed to build an understanding of how neuropsychiatric conditions can be defined more precisely using quantitative (multimodal) biological processes and markers and thus to significantly improve treatment success. The ECNP New Frontiers Meeting 2024 set out to develop a consensus roadmap for building a new diagnostic framework for mental disorders by discussing its rationale, outlook, and consequences with all stakeholders involved. This framework would instantiate a set of principles and procedures by which research could continuously improve precision diagnostics while moving away from traditional nosology. In this meeting report, the speakers’ summaries from their presentations are combined to address three key elements for generating such a roadmap, namely, the application of innovative technologies, understanding the biology of mental illness, and translating biological understanding into new approaches. In general, the meeting indicated a crucial need for a biology-informed framework to establish more precise diagnosis and treatment for mental disorders to facilitate bringing the right treatment to the right patient at the right time.

22q11DS is a robust genetic predictor of schizophrenia (SCZ) and other psychiatric illnesses: nearly 30% of individuals develop SCZ. Understanding the relationship of cognition and psychophysiological variables could lead to a greater understanding of circuit-based abnormal functioning in 22q11DS and SCZ.

22q11.2 deletion syndrome (22q11DS) is a very robust genetic predictor of the development of psychosis and other psychiatric illnesses. We examined performance on a battery of cognitive tests and psychophysiological biomarkers known to be associated with psychosis-risk in 22q11DS and compared them to clinical symptoms.

OBJECTIVES/GOALS: 22q.11 deletion syndrome (22q11DS) is a genomic syndrome that elevates risk for psychosis >20-fold. We used a battery of cognitive and psychophysiological psychosis-risk biomarkers in 22q11DS patients and healthy subjects in order to identify biomarkers of psychosis in 22q11DS that could be used as translational targets in intervention studies. METHODS/STUDY POPULATION: We recruited 15 22q11DS individuals (Mean age=30, M/F=9/6) and 19 healthy controls (HCs; Mean age=34, M/F=5/14). Each individual completed the MATRICS Consensus Cognitive Battery (MCCB), the Wechsler Abbreviated Scale of Intelligence, Second edition (WASI-II) Verbal IQ subtests, and the computerized Wisconsin Card Sorting Task (WCST). To examine auditory EEG responses, each participant completed the 'Double-Deviant' target detection paradigm, which presents a pseudorandom sequence of frequent standard tones and infrequent deviant tones. Mismatch negativity (MMN) metrics were generated from this assessment. Welch's t-tests were completed for neurocognitive variables. One-Way ANOVAs were completed to examine EEG results, with sex entered as a separate factor and age entered as a covariate. RESULTS/ANTICIPATED RESULTS: Significant group differences were found in 8 of the 9 neurocognitive measurements (FDR-adjusted p's< 0.02, average Cohen's d=1.62, average observed power= 0.91) indicating widespread cognitive deficits in 22q11DS subjects across multiple domains. The Double-Deviant MMN ERP response was significantly smaller in absolute magnitude in the 22q11DS group (FDR-adjusted p=0.048, Cohen’s d= -0.864, observed power= 0.58). The MMN ERPs for the frequency and duration deviants were not significantly different (FDR-adjusted p's> 0.33). No group by sex interactions were observed in any of the measures. Neurocognitive variables were associated with psychosis positive, negative, general, and disorganized symptom scales. DISCUSSION/SIGNIFICANCE: Our results identify potential psychosis-risk biomarkers in 22q11DS. If replicated, these biomarkers could provide important translational targets for future clinical trials for individuals with 22q11DS and other individuals at-risk for psychosis syndromes.

Abstract This chapter provides an introduction to the Research Domain Criteria (RDoC) project. RDoC is a framework for psychopathology research created in 2009 by the US National Institute of Mental Health in order to foster innovative research that transcends the reliance on current disorder categories in studying mental illness. RDoC takes a translational approach that considers psychopathology in terms of deviations in normal dimensions of functioning (such as cognitive processes or motivational systems) that often reflect transdiagnostic effects across multiple disorder classes. The framework calls for studies that integrate multiple data types (e.g., behavioral, physiological, and self-report measures) and emphasizes developmental trajectories and the impact of various environmental influences. Fundamental issues regarding relevant philosophy of science issues are discussed, and selected recent studies are reviewed that illustrate exemplars of research designs. The conclusion briefly summarizes RDoC’s current status and potential future directions.

The integration of developmental processes is essential for a full understanding of psychopathology. The National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) provide a scaffold on which to organize the components and processes of psychopathology and to detail behavioral and biological disruptions in developmental processes gone awry. This special section on Integrating Developmental Psychopathology With the RDoC Framework provides the opportunity to comment on five extraordinary developmental psychopathology articles that report results and theory integral to RDoC. An introductory overview provides context for RDoC's approach to developmental issues. This is followed by brief summaries of each article and points regarding its particularly salient aspects, and concludes with broader comments about the import of the articles as a set. Collectively, the work by these eminent translational scholars illustrates how to conduct significant research on developmental psychopathology using RDoC, and simultaneously raises important questions and future directions to integrate development and environment in RDoC-framed research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The National Institute of Mental Health (NIMH) addressed in its 2008 Strategic Plan an emerging concern that the current diagnostic system was hampering translational research, as accumulating data suggested that the system’s disorder categories constituted heterogeneous syndromes rather than specific diseases. However, established practices in peer review placed high priority on that system’s disorders in evaluating grant applications for mental illness. To provide guidelines for alternative study designs, NIMH set a goal to develop new ways of studying psychopathology based on dimensions of measurable behavior and related neurobiological measures. The Research Domain Criteria (RDoC) project is the result, intended to build a literature that informs new conceptions of mental illness and future revisions to diagnostic manuals. The framework calls for the study of empirically derived fundamental dimensions characterized by related behavioral/psychological and neurobiological data (e.g., reward valuation, working memory). RDoC also emphasizes approaches including neurodevelopment, environmental effects, and the full range of dimensions of interest (from typical to increasingly abnormal), as well as research designs that integrate data across behavioral, biological, and self-report measures. This article provides an overview of the project’s first decade and its potential future directions. RDoC remains grounded in experimental psychopathology perspectives, and its progress is strongly linked to psychological measurement and integrative approaches to brain-behavior relationships.

BACKGROUND:In 2013, a few years after the launch of the National Institute of Mental Health's Research Domain Criteria (RDoC) initiative, Cuthbert and Insel published a paper titled "Toward the future of psychiatric diagnosis: the seven pillars of RDoC." The RDoC project is a translational research effort to encourage new ways of studying psychopathology through a focus on disruptions in normal functions (such as reward learning or attention) that are defined jointly by observable behavior and neurobiological measures. The paper outlined the principles of the RDoC research framework, including emphases on research that acquires data from multiple measurement classes to foster integrative analyses, adopts dimensional approaches, and employs novel methods for ascertaining participants and identifying valid subgroups.DISCUSSION:To mark the first decade of the RDoC initiative, we revisit the seven pillars and highlight new research findings and updates to the framework that are related to each. This reappraisal emphasizes the flexible nature of the RDoC framework and its application in diverse areas of research, new findings related to the importance of developmental trajectories within and across neurobehavioral domains, and the value of computational approaches for clarifying complex multivariate relations among behavioral and neurobiological systems.CONCLUSION:The seven pillars of RDoC have provided a foundation that has helped to guide a surge of new studies that have examined neurobehavioral domains related to mental disorders, in the service of informing future psychiatric nosology. Building on this footing, future areas of emphasis for the RDoC project will include studying central-peripheral interactions, developing novel approaches to phenotyping for genomic studies, and identifying new targets for clinical trial research to facilitate progress in precision psychiatry.