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Kotov R, Jonas KG, Carpenter WT, Dretsch MN, Eaton NR, Forbes MK, Forbush KT, Hobbs K, Reininghaus U, Slade T, South SC, Sunderland M, Waszczuk MA, Widiger TA, Wright AGC, Zald DH, Krueger RF, Watson D. Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum. World Psychiatry 2020; 19:151-172. [PMID: 32394571 PMCID: PMC7214958 DOI: 10.1002/wps.20730] [Citation(s) in RCA: 139] [Impact Index Per Article: 34.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.
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Affiliation(s)
- Roman Kotov
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | | | - Michael N Dretsch
- Walter Reed Army Institute of Research, US Army Medical Research Directorate - West, Silver Spring, MD, USA
| | - Nicholas R Eaton
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA
| | - Miriam K Forbes
- Department of Psychology, Macquarie University, Sydney, Australia
| | - Kelsie T Forbush
- Department of Psychology, University of Kansas, Lawrence, KS, USA
| | - Kelsey Hobbs
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Ulrich Reininghaus
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
- ESRC Centre for Society and Mental Health, King's College London, London, UK
- Centre for Epidemiology and Public Health, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Tim Slade
- Matilda Centre for Research in Mental Health and Substance Abuse, University of Sydney, Sydney, NSW, Australia
| | - Susan C South
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
| | - Matthew Sunderland
- Matilda Centre for Research in Mental Health and Substance Abuse, University of Sydney, Sydney, NSW, Australia
| | - Monika A Waszczuk
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Thomas A Widiger
- Department of Psychology, University of Kentucky, Lexington, KY, USA
| | - Aidan G C Wright
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - David H Zald
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - David Watson
- Department of Psychology, University of Notre Dame, South Bend, IN, USA
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Harvey PD. An Array of Studies Addressing Cognition and Cognitively Defined Neuropsychiatric Conditions: Many More Connections Than You Might Think. Am J Psychiatry 2020; 177:491-496. [PMID: 32475142 DOI: 10.1176/appi.ajp.2020.20040407] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Six articles in the June 2020 issue of the American Journal of Psychiatry address the overall construct of cognition. These articles have a broad connection to cognition, which is itself a broad concept. From the experimental psychology perspective, cognition is the set of processes associated with attending, learning, knowing, and remembering. From the clinical perspective, a number of neuropsychiatric conditions are defined by the presence of cognitive impairment, with onset ranging from childhood, such as attention deficit hyperactivity disorder and intellectual disability, to later life, such as dementia. Other conditions have notable cognitive impairments even if specific cognitive impairments are not an explicit part of their formal diagnostic criteria, including autism spectrum disorder and schizophrenia. Thus, the array of articles in this issue are related to each other and also may make important points about the role of cognition in everyday functioning and the connections between cognitive impairments in neuropsychiatric conditions and in the human population in general. Further, these articles address the neurobiological substrates that have an impact on cognition, with important implications in other domains, such as genomics. Finally, through sophisticated research methods, they clarify the results of previous studies that were affected by a variety of methodological challenges.
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Affiliation(s)
- Philip D Harvey
- University of Miami Miller School of Medicine, Miami; and Bruce W. Carter Miami VA Medical Center, Miami
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Zhang Y, Yang Y, Zhu L, Zhu Q, Jia Y, Zhang L, Peng Q, Wang J, Liu J, Fan W, Wang J. Volumetric Deficit Within the Fronto-Limbic-Striatal Circuit in First-Episode Drug Naïve Patients With Major Depression Disorder. Front Psychiatry 2020; 11:600583. [PMID: 33551870 PMCID: PMC7854541 DOI: 10.3389/fpsyt.2020.600583] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 12/21/2020] [Indexed: 12/21/2022] Open
Abstract
Background: Depression is a major psychiatric disorder and the leading cause of disability worldwide. Previous evidence suggested certain pattern of structural alterations were induced by major depression disorder (MDD) with heterogeneity due to patients' clinical characteristics and proposed that early impairment of fronto-limbic-striatal circuit was involved. Yet the hypothesis couldn't be replicated fully. Accordingly, this study aimed to validate this hypothesis in a new set of first-episode, drug naïve MDD patients and further explore the neuroimaging biomarker of illness severity using whole-brain voxel-based morphometry (VBM). Materials and Methods: A total of 93 participants, 30 patients with first-episode medication-naïve MDD, and 63 healthy controls were enrolled in the study. VBM was applied to analyze differences in the gray matter volume (GMV) between these two groups. The correlation between the GMV of the identified brain regions and the severity of clinical symptoms quantified by the Hamilton Depression Scale (HAMD) was further conducted in the post-hoc analysis to confirm the role of GMV structural alteration in clinical symptoms. Results: Our results revealed that the brain gray matter volume of the prefrontal lobe, limbic system, striatum, cerebellum, temporal lobe, and bilateral lingual gyri were significantly decreased in MDD patients compared with healthy controls. Besides, the HAMD scores were negatively correlated with GMV of the right insula and positively correlated with that of the right lingual gyrus. Conclusions: Our findings provide robust evidence that gray matter structural abnormalities within the prefronto-limbic-striatal circuit are implicated in the pathophysiology of MDD at an early stage without confounding influence of medication status. Besides, our data suggest that the cerebellum, lingual gyrus, and fusiform gyrus should also be integrated into the brain alterations in MDD. Future synthesis of individual neuroimaging studies and more advanced statistical analysis comparing subfields of the aforementioned regions are warranted to further shed light on the neurobiology of the disease and assist in the diagnosis of this burdensome disorder.
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Affiliation(s)
- Yiran Zhang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Yun Yang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Licheng Zhu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Qing Zhu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuxi Jia
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Lan Zhang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Qinmu Peng
- School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China
| | - Jiazheng Wang
- Clinical and Technical Solutions, Philips Healthcare, Beijing, China
| | - Jia Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Wenliang Fan
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Jing Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
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