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Metrics details. Current diagnostic systems for mental disorders rely upon presenting signs and symptoms, with the result that current definitions do not adequately reflect relevant neurobiological and behavioral systems - impeding not only research on etiology and pathophysiology but also the development of new treatments.

The National Institute of Mental Health began the Research Domain Criteria RDoC project in to develop a research classification system for mental disorders based upon dimensions of neurobiology and observable behavior.

RDoC supports research to explicate fundamental biobehavioral dimensions that cut across current heterogeneous disorder categories. We summarize the rationale, status and long-term goals of RDoC, outline challenges in developing a research classification system such as construct validity and a suitable process for updating the framework and discuss seven distinct differences in conception and emphasis from current psychiatric nosologies.

Future diagnostic systems cannot reflect ongoing advances in genetics, neuroscience and cognitive science until a literature organized around these disciplines is available to inform the revision efforts.

The goal of the RDoC project is to provide a framework for research to transform the approach to the nosology of mental disorders. Peer Review reports. As of this writing, there are three versions of diagnostic systems for psychiatry in development. This attention is not surprising given the prominence of the DSM for clinical diagnosis both in the US and internationally, its simultaneous role in research, and the number of controversial issues that have been involved in the revision process - such as the debates over autism spectrum disorder [ 1 ], bereavement and depression [ 2 ], and personality disorders [ 3 , 4 ], to name just a few.

The DSM revisions have also prompted an extensive re-visiting of important issues regarding the nature of mental disorders, and how they should be considered scientifically. An excellent summary and analysis of these topics is represented by the series of papers that appeared recently in Philosophy, Ethics, and Humanities in Medicine and BMC Medicine [ 5 — 7 ]; see also [ 8 ].

This revision effort is being accomplished by an international group of experts, including some intentional overlap with members from the DSM committees. It is worth noting that the ICD represents the official diagnostic standard in the US as in the rest of the world. The latter is intended largely for use by highly trained mental health professionals though it is employed by many professional groups. By contrast, the ICD is necessarily designed for health settings around the world, to be used not only by practitioners with widely divergent levels of expertise but also in cultural settings where assumptions about the etiology and nature of disorders may be highly dissimilar from the Western milieu of the DSM.

Accordingly, the ICD places stronger emphasis on public health applications than the DSM, and one reflection of this emphasis is the use of definitions that emphasize short text descriptions of each disorder rather than the polythetic symptom lists of the DSM. Given its status as a research classification system rather than one intended for routine clinical use, this initiative diverges markedly from the others in multiple respects.

The seven major differences between RDoC and the established systems are delineated in the sections that follow, as its share of this forum. One caveat is in order at the outset to provide an appropriate context for the remarks that follow. However, discussions among the framers of the DSM-5, the ICD revisions and the NIMH RDoC have from their inception been cordial, and marked by general agreement about the relative emphasis of each respective system and also about their shared interests.

A diagnostic system can have many purposes. For instance, a major reason for the creation of the ICD was to establish a comprehensive manual for determining causes of mortality, thus enhancing efforts at improving public health.

Any discussion about the ramifications of these various considerations in actually making a difference on how we treat our patients, however, has been conspicuously lacking. This lack is likely due in no small part to the current nature of treatments for mental disorders. On the one hand, effective treatments exist.

Treatments for major classes of disorders such as depression, anxiety disorders, schizophrenia and bipolar disorders are available, and effective for large numbers of patients. Further, a number of effective treatment modalities - pharmaceutical interventions, psychosocial or behavioral treatments, medical devices - have been established. On the other hand, treatments are not particularly precise, and tend to affect broad classes of disorders.

Anti-depressant medications, such as selective serotonin reuptake inhibitors, are used to treat not only depression but a wide variety of anxiety, mood and other disorders. Anti-psychotic agents are used not only with schizophrenia but in bipolar disorder and sometimes for personality and other severe disorders. Anxiolytics such as valium are prescribed widely across the anxiety and mood spectrum. A similar situation prevails for behavioral treatments; for instance, the use of cognitive-behavioral therapy, albeit with many variants, has expanded beyond the internalizing disorders spectrum for which it was originally developed to the treatment of virtually all mental disorders for example, see [ 10 ].

Although decent treatments for mental disorders are thus plentiful, it is instructive to contrast the changes in disease burden for other diseases over the past several decades with that for mental disorders. For instance, the impact of research - both clinically and in public health arenas - has been dramatic for heart disease. Death due to heart disease climbed steadily from through , at a rate that projected almost 1.

Instead, because of the rapid progress of research, the actual mortality due to heart disease was only about one quarter of that number; approximately 1. By contrast, mortality has not decreased for any mental illness, prevalence rates are similarly unchanged [ 13 ], there are no clinical tests for diagnosis, detection of disorders is delayed well beyond generally accepted onset of pathology, and there are no well-developed preventive interventions.

There are many reasons for this lack of progress in mental disorders. The brain is the most complex organ in the body, and it is well-accepted that mental illnesses involve highly complex interactions of genetic factors and experience.

The brain cannot be studied directly with the facility we have for more accessible organs, limiting progress based on pathology. However, the diagnostic system for psychiatry has also been increasingly noted as an impediment to progress. The problems have been extensively documented for example, [ 14 — 18 ] and do not need to be elaborated here, but include excessive co-morbidity of disorders, marked heterogeneity of mechanisms and reification of disorders.

In particular, the underlying validity of the disease entities has been questioned, in that the DSM and ICD categories do not map well onto emerging findings from genetics, systems neuroscience and behavioral science for example, [ 19 , 20 ] ; as a result, it becomes very difficult to translate research from basic studies, either in animal models or in humans, to a systematic understanding of pathology or to systematic treatments directed at mechanisms. Nevertheless, the DSM and ICD system the two nosologies are largely overlapping in terms of the actual listing of disorders has become the standard to obtain research grants regarding etiology and pathophysiology, to conduct drug trials at all phases, and to obtain regulatory approvals for pharmaceutical treatments.

In behavioral research as well, the need to establish evidence-based treatments has led researchers to copy the lead of drug trials and conduct trials in terms of DSM and ICD diagnoses. Thus, issues with the current nosology markedly affect the treatment development arena. One reason for this low response rate is the artificial grouping of heterogeneous syndromes with different pathophysiological mechanisms into one disorder … by increasing the mechanistic understanding of disease and matching the right treatments to the right patients, one could move from one-size-fits-all to targeted therapy and increase the benefit-risk ratio for patients.

This problem is no doubt a not insignificant reason why so many pharmaceutical companies have withdrawn from active development research in mental disorders [ 22 , 23 ]. And the reliance on biologically heterogeneous categories as the gold standard for diagnosis has clearly precluded the identification or validation of biomarkers.

Although one could imagine revising the diagnostic categories to align with biological discoveries, our field has essentially excluded biological findings that do not map on to the current heterogeneous categories of symptom clusters. In other areas of medicine, trends have increasingly moved in the direction of ever more precise specification of the genetic, molecular and cellular aspects of disease.

In specialty after specialty, there has been a realization that disease entities that appear to be a single disorder actually have distinct genetic precursors and pathophysiology.

In another domain, perhaps the most striking example of this trend involves a new drug, Ivacaftor Kalydeco , approved by the Food and Drug Administration after an expedited review. The drug is effective in treating patients with cystic fibrosis who have a form of the syndrome with a specific mutation of the cystic fibrosis transmembrane regulator gene. In November , the US National Academy of Sciences published a major report on precision medicine outlining the significance of this development and calling for new knowledge networks that can harness the power of promising technologies to identify and correct specific pathophysiologies that result from genetic and environmental causes [ 26 ].

As yet, the field of mental disorders research lags badly behind the rest of medicine in moving toward precision medicine; yet, knowledge of the central nervous system has exploded over the last two decades, and new technologies are rapidly eclipsing such well-known methods as positron emission tomography scans and magnetic resonance imaging.

How can these rapid developments in basic science be harnessed in the service of precision medicine for mental disorders? As a national health ministry, NIMH is committed to reducing the burden of suffering due to mental illness through research. Decades of research have increasingly revealed that neural circuits and systems are a critical factor in how the brain is organized and functions, and how genetics and epigenetics exert their influence.

However, this knowledge cannot be implemented in clinical studies as readily as might be hoped. Any one mechanism, such as fear circuits or working memory, is implicated in multiple disorders as currently defined; it is difficult to know which diagnostic category to select first to explore any promising leads, and a positive result immediately raises the question of whether the demonstration of efficacy must be extended to all similar disorders a time-consuming and expensive proposition.

RDoC represents a real paradigm shift, by considering mental disorders from a translational point of view. RDoC does not take as a starting point the traditional view of disorders as symptom complexes based largely on clinical descriptions.

Rather, the approach proceeds in two steps. The first step is to inventory the fundamental, primary behavioral functions that the brain has evolved to carry out, and to specify the neural systems that are primarily responsible for implementing these functions.

For instance, much is now known about circuits for fear and defense [ 28 ], for various aspects of appetitive behavior such as learning to predict reward and moving toward reward [ 29 ], and cognitive functions such as working memory [ 30 ]. The second step then involves a consideration of psychopathology in terms of dysfunction of various kinds and degrees in particular systems, as studied from an integrative, multi-systems point of view. The project began with deliberations among members of an internal NIMH working group, which served to define the overall shape of the effort as well as the specific process to be followed.

The project moved forward rapidly once this organizational matrix was established. The five major domains, conceived on empirical grounds from such diverse research areas as temperament, behavior genetics and structural models of mental disorders, also served as a convenient way to organize the workshops in that one workshop was conducted for each of the five domains.

Approximately 30 to 40 experts convened for each workshop. An important consideration is that the dimensions, as behavioral entities tied to neural systems, are always dependent upon the march of research to continually refine and evolve a scientific understanding of their function and of their implementing circuits. First, the approach incorporates a strong translational research perspective.

Rather than starting with symptom-based definitions of disorders and working toward their pathophysiology, RDoC inverts this process. Basic science - in genetics, other areas of neuroscience and behavioral science -serves as the starting point, and disorders are considered in terms of disruptions of the normal-range operation of these systems, with an emphasis on the mechanisms that serve to result in dysfunctions of varying degrees.

Second, RDoC incorporates an explicitly dimensional approach to psychopathology, as called for in many recent analyses of psychopathology [ 32 , 33 ]. The third distinction follows directly from the second. In particular, zones of very mild or transient psychopathology, with their potential for understanding proximate etiology and for indicated prevention, receive short shrift.

Thus, scale development represents a high priority for RDoC research applications. In fact, well-validated and psychometrically optimized measures based upon cognitive neuroscience research are beginning to appear [ 34 ].

Consistent with contemporary measurement science, new scales would and should almost invariably incorporate interval or ratio scaling to improve quantification of the phenomena of interest.

As such assessments muster, it becomes feasible to determine cut-points along the distribution for varying types of interventions, essentially similar to practices in other areas of medicine where continuous measures are available, such as hypertension or hypercholesterolemia. A further advantage of this approach is that ongoing research studies about relative risk at various points along the dimension can inform decisions about changing the cut-points at which interventions are indicated - as has happened repeatedly, such as in hypertension research [ 35 ].

The fourth distinction concerns the types of designs and sampling strategies that RDoC studies must necessarily follow. In the traditional clinical study, the independent variable is almost always one or more usually one DSM or ICD groups, often versus controls. It is relatively straightforward to diagnose the patients according to the symptom-based criteria, excluding those who fail to meet criteria for the diagnosis under study.

The resultant groups form the independent grouping variable. RDoC, by contrast, involves a two-step procedure. In some cases, this might simply comprise all patients presenting at a certain type of clinic, such as for anxiety disorders or serious mental illness. Then, the second step is to specify the independent variable in the study.

To permit investigators freedom in pursuing their hypotheses, the independent variable may be chosen from any unit of analysis.

Thus, performance on a working memory task might be the independent variable for a study of working memory in serious mental illness; dependent variables might comprise neuroimaging of specified brain areas, relevant assessments of real-world dysfunction and an exploration of relevant candidate genes.

For a study of anxiety disorders, fear-potentiated startle might be the independent variable, stratified by a relevant genetic polymorphism, and the dependent variables could be overall symptom severity and distress plus performance on a behavioral fear-avoidance test.

Thus, while more interesting research designs can be created, the investigator will need to be more thoughtful about crafting the design of the study to answer the particular experimental question. Fifth, and critically important, the system is intended to provide a structure that places equal weight on behavioral functions and upon neural circuits and their constituent elements - that is, to be an integrative model rather than one based primarily on either behavior or neuroscience.

This integrative approach can be seen in the way in which goal 1. The criterion for including a construct in the matrix during the workshops reflects this same priority. Following from this consideration, a sixth distinction is that the RDoC project is intended at its inception, in particular to concentrate on constructs for which there is solid evidence to serve as a platform for ongoing research.

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