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Rubin LH, Cho K, Bolzenius J, Mannarino J, Easter RE, Dastgheyb RM, Anok A, Tomusange S, Saylor D, Wawer MJ, Nakasujja N, Nakigozi G, Paul R. Mental health phenotypes of well-controlled HIV in Uganda. Front Public Health 2025; 12:1407413. [PMID: 39935743 PMCID: PMC11810918 DOI: 10.3389/fpubh.2024.1407413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 12/16/2024] [Indexed: 02/13/2025] Open
Abstract
Introduction The phenotypic expression of mental health (MH) conditions among people with HIV (PWH) in Uganda and worldwide are heterogeneous. Accordingly, there has been a shift toward identifying MH phenotypes using data-driven methods capable of identifying novel insights into mechanisms of divergent MH phenotypes among PWH. We leverage the analytic strengths of machine learning combined with inferential methods to identify novel MH phenotypes among PWH and the underlying explanatory features. Methods A total of 277 PWH (46% female, median age = 44; 93% virally suppressed [<50copies/mL]) were included in the analyses. Participants completed the Patient Health Questionnaire (PHQ-9), Beck Anxiety Inventory (BAI), and the PTSD Checklist-Civilian (PCL-C). A clustering pipeline consisting of dimension reduction with UMAP followed by HBDScan was used to identify MH subtypes using total symptom scores. Inferential statistics compared select demographic (age, sex, education), viral load, and early life adversity between clusters. Results We identified four MH phenotypes. Cluster 1 (n = 76; PTSD phenotype) endorsed clinically significant PTSD symptoms (average PCL-C total score > 33). Clusters 2 (n = 32; anxiety phenotype) and 3 (n = 130; mixed anxiety/depression phenotype) reported minimal PTSD symptoms, with modest BAI (Cluster 2) and PHQ-9 (Cluster 3) elevations. Cluster 4 (n = 39; minimal symptom phenotype) reported no clinical MH symptom elevations. Comparisons revealed higher rates of sexual abuse during childhood among the PTSD phenotype vs. the minimal symptom phenotype (p = 0.03). Discussion We identified unique MH phenotypes among PWH and confirmed the importance of early life adversity as an early risk determinant for unfavorable MH among PWH in adulthood.
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Affiliation(s)
- Leah H. Rubin
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Molecular and Comparative Pathobiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Kyu Cho
- Missouri Institute of Mental Health, University of Missouri - St. Louis, St. Louis, MO, United States
| | - Jacob Bolzenius
- Missouri Institute of Mental Health, University of Missouri - St. Louis, St. Louis, MO, United States
| | - Julie Mannarino
- Missouri Institute of Mental Health, University of Missouri - St. Louis, St. Louis, MO, United States
| | - Rebecca E. Easter
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Raha M. Dastgheyb
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Aggrey Anok
- Rakai Health Sciences Program, Kalisizo, Uganda
| | | | - Deanna Saylor
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Maria J. Wawer
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | | | | | - Robert Paul
- Missouri Institute of Mental Health, University of Missouri - St. Louis, St. Louis, MO, United States
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Sennerstam V, Hedman-Lagerlöf E, Nilsonne G, Lekander M, Rück C, Wallert J, Axelsson E, Lindsäter E. Exhaustion Disorder in Primary Care: A Comparison With Major Depressive Disorder and Adjustment Disorder. Scand J Psychol 2024. [PMID: 39648299 DOI: 10.1111/sjop.13087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2024] [Revised: 11/22/2024] [Accepted: 11/26/2024] [Indexed: 12/10/2024]
Abstract
Exhaustion disorder (ED) was introduced to the Swedish version of the International Classification of Diseases, 10th edition (ICD-10) 2005. Primarily characterized by general fatigue and cognitive deficits, ED has become one of the most common mental health diagnoses in Sweden. Little is still known regarding the discriminative validity of the ED diagnosis and how it relates to other diagnostic constructs. The study aimed to investigate the discriminative validity of ED compared with two similar diagnoses, major depressive disorder (MDD) and adjustment disorder (AD). Using data from a sample of patients with a principal diagnosis of either ED (n = 352), MDD (n = 99), or AD (n = 302), we compared demographic and clinical variables and scores on self-report symptom scales. Results showed that ED patients were of a higher age and had a higher frequency of sickness absence than MDD and AD patients. There was a substantial overlap of symptoms between ED and MDD, only differing on two of nine self-report symptom scales, with ED patients rating lower work ability d = -0.37 and alcohol consumption d = -0.57. Compared with AD patients, ED patients reported more severe symptoms in every symptom domain. Given the prevalent use of ED diagnosis, its diagnostic validity and clinical usefulness merit further attention.
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Affiliation(s)
- Victoria Sennerstam
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Gustavsberg University Primary Care Centre, Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden
- Osher Center for Integrative Health, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Erik Hedman-Lagerlöf
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Gustavsberg University Primary Care Centre, Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden
- Osher Center for Integrative Health, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Gustav Nilsonne
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stress Research Institute, Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Mats Lekander
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Osher Center for Integrative Health, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stress Research Institute, Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Sweden
| | - John Wallert
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Erland Axelsson
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Liljeholmen University Primary Health Care Centre, Academic Primary Health Care Centre, Stockholm, Sweden
| | - Elin Lindsäter
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Gustavsberg University Primary Care Centre, Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden
- Osher Center for Integrative Health, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Sweden
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Park SC. Culture and Psychiatric Diagnosis. Psychiatr Ann 2024; 54. [DOI: 10.3928/00485713-20241210-01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2025]
Abstract
This article examines the impact of cultural factors on psychiatric diagnosis, with particular attention to the
Diagnostic and Statistical Manual of Mental Disorders (DSM)
. Since the release of
DSM-III
in 1980, the operational, symptom-based criteria have sought to establish universal standards for diagnosing mental disorders. However, this approach faces challenges such as diagnostic ambiguity and cultural misalignment. The concept of the “Procrustean bed” underscores the limitations of applying DSM criteria without considering cultural variations, particularly in diagnosing major depression. For instance, in Western cultural contexts heavily influenced by Christianity, guilt is often emphasized as a symptom of depression, although this may be less prevalent in non-Western societies. Comparative studies show that Western patients frequently report guilt and a depressed mood, whereas patients in Asian societies often present with symptoms such as suicidal behavior or illness-related anxiety. This article also explores “culture-bound syndromes,” which are mental health conditions shaped by specific cultural contexts, such as
hwa-byung
(anger syndrome) in Korea and
hikikomori
(social withdrawal syndrome) in Japan. These syndromes underscore the necessity for culturally adapted diagnostic approaches. For example,
hwa-byung
, characterized by repressed anger within a patriarchal society, overlaps with DSM-defined depressive and anxiety disorders but maintains a unique cultural expression. Similarly,
hikikomori
, reflecting extreme social withdrawal exacerbated by the pandemic, is associated with depression and social anxiety. This study advocates for the integration of cultural
phronesis
or practical wisdom into psychiatry, emphasizing the importance of nuanced and culturally sensitive diagnosis methods. Recognizing alternative symptom expressions, such as anger or shame, in non-Western patients is critical for improving diagnostic accuracy and treatment outcomes.
[
Psychiatr Ann
. 2024;54(12):e330–e334.]
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Misiak B, Rejek M, Bielawski T, Błoch M, Samochowiec J, Bąba-Kubiś A, Gawęda Ł, Maciaszek J. The same but different too: Depression profiles in young adults without a history of psychiatric treatment identified using Bayesian and partial correlation networks. J Psychiatr Res 2024; 179:83-91. [PMID: 39260112 DOI: 10.1016/j.jpsychires.2024.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 07/29/2024] [Accepted: 09/03/2024] [Indexed: 09/13/2024]
Abstract
Depression is a heterogenous diagnostic construct; however, dynamic interactions between specific depressive symptoms across their qualitatively different profiles remain largely unknown. The study aimed to recognize the most prevalent profiles of depressive symptoms and assess their dynamics in young adults without a history of psychiatric treatment. Depressive symptoms were recorded using the Patient Health Questionnaire-9 (PHQ-9). The data were assessed for all theoretical and empirical combinations of depressive symptoms in participants with a positive screening for depression. The profiles identified in the majority of participants were analyzed using partial correlation and Bayesian networks. Data from 3583 individuals with a positive screening for depression were analyzed. Out of 382 theoretical profiles, 150 profiles (39.3%) were present in this dataset. The majority of participants (56.8%) showed 4 profiles of depressive symptoms including the profile with all depressive symptoms present, the profile without suicidal ideation, the profile without psychomotor impairment, and the profile without both psychomotor impairment and suicidal ideation. The profiles differed largely in terms of their dynamics and symptoms that are necessary to activate the whole network. The network characteristics within specific profiles did not differ significantly across the level of difficulties attributable to depressive symptoms. Our findings indicate that depression emerging in young adults shows a limited number of symptom profiles. However, dynamics of depressive symptoms differs largely between specific profiles regardless of functional impairment indicating the need to personalize therapeutic approaches. Future studies should further disentangle the heterogeneity of depressive symptoms, e.g., by dissecting the symptoms that are combined together by single PHQ-9 items (i.e., hypersomnia and insomnia; psychomotor agitation and retardation).
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Affiliation(s)
- Błażej Misiak
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland.
| | - Maksymilian Rejek
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - Tomasz Bielawski
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - Marta Błoch
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland
| | - Agata Bąba-Kubiś
- Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland
| | - Łukasz Gawęda
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Julian Maciaszek
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
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Spiller TR, Duek O, Helmer M, Murray JD, Fielstein E, Pietrzak RH, von Känel R, Harpaz-Rotem I. Unveiling the Structure in Mental Disorder Presentations. JAMA Psychiatry 2024; 81:1101-1107. [PMID: 39110437 PMCID: PMC11307158 DOI: 10.1001/jamapsychiatry.2024.2047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 05/21/2024] [Indexed: 08/10/2024]
Abstract
Importance DSM criteria are polythetic, allowing for heterogeneity of symptoms among individuals with the same disorder. In empirical research, most combinations were not found or only rarely found, prompting criticism of this heterogeneity. Objective To elaborate how symptom-based definitions and assessments contribute to a distinct probability pattern for the occurrence of symptom combinations. Design, Setting, and Participants This cross-sectional study involved a theoretical argument, simulation, and secondary data analysis of 4 preexisting datasets, each consisting of symptoms from 1 of the following syndromes: posttraumatic stress disorder, depression, schizophrenia, and anxiety. Data were obtained from various sources, including the National Institute of Mental Health Data Archive and Department of Veteran Affairs. A total of 155 474 participants were included (individual studies were 3930 to 63 742 individuals in size). Data were analyzed between July 2021 and January 2024. Exposure For each participant, the presence or absence of each assessed symptom and their combination was determined. The number of all combinations and their individual frequencies were assessed. Main Outcome and Measure Probability or frequency of unique symptom combinations and their distribution. Results Among the 155 474 participants, the mean (SD) age was 47.5 (14.8) years; 33 933 (21.8%) self-identified as female and 121 541 (78.2%) as male. Because of the interrelation between symptoms, some symptom combinations were significantly more likely than others. The distribution of the combinations' probability was heavily skewed with most combinations having a very low probability. Across all 4 empirical samples, the 1% most common combinations were prevalent in a total of 33.1% to 78.6% of the corresponding sample. At the same time, many combinations (ranging from 41.7% to 99.8%) were reported by less than 1% of the sample. Conclusions and Relevance This study found that within-disorder symptom heterogeneity followed a specific pattern consisting of few prevalent, prototypical combinations and numerous combinations with a very low probability of occurrence. Future discussions about the revision of diagnostic criteria should take this specific pattern into account by focusing not only on the absolute number of symptom combinations but also on their individual and cumulative probabilities. Findings from clinical populations using common diagnostic criteria may have limited generalizability to the large group of individuals with a low-probability symptom combination.
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Affiliation(s)
- Tobias R. Spiller
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- National Center for PTSD, VA Connecticut Healthcare System, West Haven
- Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich (USZ), Zurich, Switzerland
- University of Zurich (UZH), Zurich, Switzerland
| | - Or Duek
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- National Center for PTSD, VA Connecticut Healthcare System, West Haven
- Department of Epidemiology, Biostatistics and Community Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Markus Helmer
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - John D. Murray
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- Wu Tsai Institute, Yale University, New Haven, Connecticut
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire
| | - Elliot Fielstein
- Mental Health Informatics Section, Office of Mental Health and Suicide Prevention, Department of Veterans Affairs, Washington, DC
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Robert H. Pietrzak
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- National Center for PTSD, VA Connecticut Healthcare System, West Haven
- Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, Connecticut
| | - Roland von Känel
- Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich (USZ), Zurich, Switzerland
- University of Zurich (UZH), Zurich, Switzerland
| | - Ilan Harpaz-Rotem
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- National Center for PTSD, VA Connecticut Healthcare System, West Haven
- Wu Tsai Institute, Yale University, New Haven, Connecticut
- Department of Psychology, Yale University, New Haven, Connecticut
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Rothman B, Slomkowski M, Speier A, Rush AJ, Trivedi MH, Lawson E, Fahmy M, Carpenter D, Chen D, Forbes A. Evaluating the Efficacy of a Digital Therapeutic (CT-152) as an Adjunct to Antidepressant Treatment in Adults With Major Depressive Disorder: Protocol for the MIRAI Remote Study. JMIR Res Protoc 2024; 13:e56960. [PMID: 39163592 PMCID: PMC11372332 DOI: 10.2196/56960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 05/31/2024] [Accepted: 06/17/2024] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is common worldwide and can be highly disabling. People with MDD face many barriers to treatment and may not experience full symptom relief even when treated. Therefore, new treatment modalities are needed for MDD. Digital therapeutics (DTx) may provide people with MDD an additional treatment option. OBJECTIVE This study aimed to describe a phase 3 remote, multicenter, randomized, masked, sham-controlled trial evaluating the efficacy of a smartphone app-based DTx (CT-152) in adult participants diagnosed with MDD, used as an adjunct to antidepressant therapy (ADT). METHODS Participants aged 22-64 years with a current primary diagnosis of MDD and an inadequate response to ADT were included. Participants were randomized 1:1 to CT-152 or a sham DTx. CT-152 is a smartphone app-based DTx that delivers a cognitive-emotional and behavioral therapeutic intervention. The core components of CT-152 are the Emotional Faces Memory Task exercises, brief lessons to learn and apply key therapeutic skills, and SMS text messaging to reinforce lessons and encourage engagement with the app. The sham DTx is a digital working memory exercise with emotionally neutral stimuli designed to match CT-152 for time and attention. Participants took part in the trial for up to 13 weeks. The trial included a screening period of up to 3 weeks, a treatment period of 6 weeks, and an extension period of 4 weeks to assess the durability of the effect. Sites and participants had the option of an in-person or remote screening visit; the remaining trial visits were remote. Efficacy was evaluated using the Montgomery-Åsberg Depression Rating Scale, the Generalized Anxiety Disorder-7, Clinical Global Impression-Severity scale, the Patient Health Questionnaire-9, and the World Health Organization Disability Assessment Schedule 2.0. The durability of the effect was evaluated with the Montgomery-Åsberg Depression Rating Scale and Generalized Anxiety Disorder-7 scale. Adverse events were also assessed. Satisfaction, measured by the Participant and Healthcare Professional Satisfaction Scales, and health status, measured by the EQ-5D-5L, were summarized using descriptive statistics. RESULTS This study was initiated in February 2021 and had a primary completion date in October 2022. CONCLUSIONS This represents the methodological design for the first evaluation of CT-152 as an adjunct to ADT. This study protocol is methodologically robust and incorporates many aspects of conventional pivotal pharmaceutical phase 3 trial design, such as randomization and safety end points. Novel considerations included the use of a sham comparator, masking considerations for visible app content, and outcome measures relevant to DTx. The rigor of this methodology will provide a more comprehensive understanding of the effectiveness of CT-152. TRIAL REGISTRATION ClinicalTrials.gov NCT04770285; https://clinicaltrials.gov/study/NCT04770285. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR1-10.2196/56960.
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Affiliation(s)
- Brian Rothman
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Mary Slomkowski
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Austin Speier
- Click Therapeutics, Inc, New York, NY, United States
| | - A John Rush
- School of Medicine, Duke University, Durham, NC, United States
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
- O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Erica Lawson
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Michael Fahmy
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | | | - Dalei Chen
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Ainslie Forbes
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
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Verdejo-Garcia A, Rossi G, Albein-Urios N, Lozano OM, Diaz-Batanero C. Identifying internalizing transdiagnostic profiles through motivational and cognitive control systems: Relations with symptoms, functionality, and quality of life. Compr Psychiatry 2024; 133:152498. [PMID: 38788615 DOI: 10.1016/j.comppsych.2024.152498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 05/01/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND The diversity of patients' symptomatology among people seeking treatment on community-based mental health services poses significant challenges to traditional models of care. Recent approaches favor identifying transdiagnostic factors that allow a better understanding of patient heterogeneity and designing more effective and quality interventions. This study examines the heterogeneity of patients with internalizing symptoms based on profiles identified with cognitive and motivational control variables. Differences between these profiles on dimensional measures of psychopathology and quality of life are examined. METHODS 263 patients were selected by non-probabilistic sampling procedures on mental health services in the province of Huelva (Spain). A latent class analysis on the standardized scale scores of The Behavioral Inhibition/Behavioral Activation System Scales and the Effortful Control Scale of the Adult Temperament Questionnaire Short-Form was conducted. Profiles were compared on the scores of the Inventory of Depression and Anxiety Symptoms-II, the WHO Disability Assessment Schedule II, and the Health Assessment Questionnaire SF-36. RESULTS The four latent profile solution is the one that showed the best fit indicators and substantive interpretability, with a kappa of 0.94 in the cross-validation procedure with 75% of the sample. No sex differences were found between the profiles (χ32 5.17, p = .160). Profiles #1 and #3, both characterized by an imbalance between low activation and high inhibition, had lower well-being, lower functionality, and quality of life. When comparing profile #2 (featuring the highest inhibitory control) lower scores on most internalizing scales are observed, specially claustrophobia, social anxiety, panic mania. Profile #4 (low control, high activation, and high inhibition) showed greater scores on both mania and euphoria and lower scores on emotional role. CONCLUSIONS We identified four distinctive profiles that had overly increased behavioral inhibition (as expected in internalizing disorders) and differed in the degree of imbalance between inhibition and activation systems, and between motivational systems and top-down cognitive control. The profile characterized by high activation and reduced cognitive (inhibitory) control was the one showing greater mood-related symptoms and lower levels of quality of life. These profiles could be generated by treatment providers to guide clinical management in an evidence-based manner.
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Affiliation(s)
- A Verdejo-Garcia
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - G Rossi
- Personality and Psychopathology research group (PEPS), Department of Psychology (PE), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - N Albein-Urios
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - O M Lozano
- University of Huelva, Department of Clinical and Experimental Psychology, Huelva, Spain; University of Huelva, Research Center for Natural Resources, Health and the Environment, Huelva, Spain
| | - C Diaz-Batanero
- University of Huelva, Department of Clinical and Experimental Psychology, Huelva, Spain; University of Huelva, Research Center for Natural Resources, Health and the Environment, Huelva, Spain.
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8
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Borgogna NC, Owen T, Aita SL. The absurdity of the latent disease model in mental health: 10,130,814 ways to have a DSM-5-TR psychological disorder. J Ment Health 2024; 33:451-459. [PMID: 37947129 DOI: 10.1080/09638237.2023.2278107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/21/2023] [Accepted: 10/11/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Latent disease classification is currently the accepted approach to mental illness diagnosis. In the United States, this takes the form of the Diagnostic and Statistical Manual of Mental Disorders-5-Text Revision (DSM-5-TR). Latent disease classification has been criticized for reliability and validity problems, particularly regarding diagnostic heterogeneity. No authors have calculated the scope of the heterogeneity problem of the entire DSM-5-TR. AIMS We addressed this issue by calculating the unique diagnostic profiles that exist for every DSM-5-TR diagnosis. METHODS We did this by applying formulas previously used in smaller heterogeneity analyses to all diagnoses within the DSM-5-TR. RESULTS We found that there are 10,130,814 ways to be diagnosed with a mental illness using DSM-5-TR criteria. When specifiers are considered, this number balloons to over 161 septillion unique diagnostic presentations (driven mainly by bipolar II disorder). Additionally, there are 1,951,065 ways to present with psychiatric symptoms, yet not meet diagnostic criteria. CONCLUSIONS Latent disease classification leads to considerable heterogeneity in possible presentations. We provide examples of how latent disease classification harms research and treatment programs. We echo recommendations for the dismissal of latent disease classification as a mental illness diagnostic program.
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Affiliation(s)
- Nicholas C Borgogna
- Department of Psychological Sciences, Texas Tech University, Lubbock, TX, USA
| | - Tyler Owen
- Department of Psychological Sciences, Texas Tech University, Lubbock, TX, USA
| | - Stephen L Aita
- Department of Psychology, University of Maine, Orono, ME, USA
- Department of Mental Health, VA Maine Healthcare System, Augusta, ME, USA
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9
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Villarreal-Zegarra D, Otazú-Alfaro S, Segovia-Bacilio P, García-Serna J, Reategui-Rivera CM, Melendez-Torres GJ. Profiles of depressive symptoms in Peru: An 8-year analysis in population-based surveys. J Affect Disord 2023; 333:384-391. [PMID: 37086796 DOI: 10.1016/j.jad.2023.04.078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 04/13/2023] [Accepted: 04/17/2023] [Indexed: 04/24/2023]
Abstract
Background Profiles of depressive symptoms have been described due to heterogeneity in symptomatology and presentation. In our study, we estimate depressive symptom profiles and relate these symptom profiles to risk factors in the Peruvian population. Methods We carried out an observational study based on the Peruvian Demographic and Health Survey (2014-2022). Men and women aged 15 years and older living in urban and rural areas in all regions of Peru were included. The Patient Health Questionnaire-9 was used to define depressive symptom profiles. We estimated latent class models to define the profiles and performed a Poisson regression analysis to determine the associated factors. Results A total of 259,655 participants were included. The three-class model was found to be the most appropriate, and the classes were defined according to the severity of depressive symptoms (moderate-severe symptoms, mild symptoms, and without depressive symptoms). Also, it was found that the three classes identified have not changed during the years of evaluations, presenting very similar prevalence over the years. In addition, women are more likely than men to belong to a class with more severe depressive symptoms; and the older the age, the higher the probability of belonging to a class with greater severity of depressive symptoms. Conclusions Our study found that at the population level in Peru, depressive symptoms are grouped into three classes according to the intensity of the symptomatology present (no symptoms, mild symptoms and moderate-severe symptoms).
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Affiliation(s)
- David Villarreal-Zegarra
- Escuela de Medicina, Universidad César Vallejo, Trujillo, Peru; Instituto Peruano de Orientación Psicológica, Lima, Peru.
| | | | | | | | - C Mahony Reategui-Rivera
- Instituto Peruano de Orientación Psicológica, Lima, Peru; Unidad de Telesalud, Facultad de Medicina, Universidad Nacional Mayor de San Marcos, Lima, Peru.
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10
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Shen H, Ge L, Cao B, Wei GX, Zhang X. The contribution of the cingulate cortex: treating depressive symptoms in first-episode drug naïve schizophrenia. Int J Clin Health Psychol 2023; 23:100372. [PMID: 36793339 PMCID: PMC9922813 DOI: 10.1016/j.ijchp.2023.100372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/17/2023] [Indexed: 01/29/2023] Open
Abstract
Background Our previous study has shown the cingulate cortex abnormalities in first-episode drug naïve (FEDN) schizophrenia patients with comorbid depressive symptoms. However, it remains largely unknown whether antipsychotics may induce morphometric change in cingulate cortex and its relationship with depressive symptoms. The purpose of this study was to further clarify the important role of cingulate cortex in the treatment on depressive symptoms in FEDN schizophrenia patients. Method In this study, 42 FEDN schizophrenia patients were assigned into depressed patients group (DP, n = 24) and non-depressed patients group (NDP, n = 18) measured by the 24-item Hamilton Depression Rating Scale (HAMD). Clinical assessments and anatomical images were obtained from all patients before and after 12-week treatment with risperidone. Results Although risperidone alleviated psychotic symptoms in all patients, depressive symptoms were decreased only in DP. Significant group by time interaction effects were found in the right rostral anterior cingulate cortex (rACC) and other subcortical regions in the left hemisphere. After risperidone treatment, the right rACC were increased in DP. Further, the increasing volume of right rACC was negatively associated with improvement in depressive symptoms. Conclusion These findings suggested that the abnormality of the rACC is the typical characteristics in schizophrenia with depressive symptoms. It's likely key region contributing to the neural mechanisms underlying the effects of risperidone treatment on depressive symptoms in schizophrenia.
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Affiliation(s)
- Haoran Shen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Likun Ge
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Alberta, Canada
| | - Gao-Xia Wei
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Xiangyang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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11
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Hicks EM, Seah C, Cote A, Marchese S, Brennand KJ, Nestler EJ, Girgenti MJ, Huckins LM. Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings. Transl Psychiatry 2023; 13:129. [PMID: 37076454 PMCID: PMC10115809 DOI: 10.1038/s41398-023-02412-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 03/17/2023] [Accepted: 03/24/2023] [Indexed: 04/21/2023] Open
Abstract
Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.
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Affiliation(s)
- Emily M Hicks
- Pamela Sklar Division of Psychiatric Genomics, Departments of Psychiatry and of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
| | - Carina Seah
- Pamela Sklar Division of Psychiatric Genomics, Departments of Psychiatry and of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
| | - Alanna Cote
- Pamela Sklar Division of Psychiatric Genomics, Departments of Psychiatry and of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
| | - Shelby Marchese
- Pamela Sklar Division of Psychiatric Genomics, Departments of Psychiatry and of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
| | - Kristen J Brennand
- Pamela Sklar Division of Psychiatric Genomics, Departments of Psychiatry and of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, 06511, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511, USA
| | - Eric J Nestler
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511, USA.
| | - Laura M Huckins
- Pamela Sklar Division of Psychiatric Genomics, Departments of Psychiatry and of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA.
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511, USA.
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12
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P50 sensory gating, cognitive deficits and depressive symptoms in first-episode antipsychotics-naïve schizophrenia. J Affect Disord 2023; 324:153-161. [PMID: 36587903 DOI: 10.1016/j.jad.2022.12.143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 12/21/2022] [Accepted: 12/25/2022] [Indexed: 12/31/2022]
Abstract
OBJECTIVE Sensory gating P50 (SG-P50) may be involved in the pathophysiological mechanisms of impaired cognition in schizophrenia (SCZ). Comorbid depressive symptoms are common in SCZ patients and are also found to be associated with their cognitive impairment. However, it is unclear whether SG-P50 is abnormal in first episode antipsychotics naïve (FEAN) SCZ patients with depressive symptoms. Our aimed to investigate the relationships between SG-P50, depressive symptoms and neurocognition in FEAN-SCZ patients. METHODS We recruited 103 FEAN-SCZ patients (depression: n = 63; non-depression: n = 40) and 55 healthy controls. SG-P50 was measured using the standard auditory dual-click (S1&S2) paradigm. Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale-17 (HDRS-17). Cognitive performance was evaluated using the MATRICS Consensus Cognitive Battery (MCCB). RESULTS Compared with non-depressive patients, depressive patients had a significantly larger S2 amplitude (p = 0.005) and a higher S2/S1 ratio at trend level (p = 0.075) after corrected. There were significant differences in the scores of CPT-IP and Mazes (NAB) between depressive and non-depressive FEAN-SCZ patients (both p values < 0.05). For all patients, the SG-P50 S2/S1 ratio was significantly correlated with HDRS-17 score (r = 0.23, p = 0.020) and MCCB-Symbol coding (r = -0.16, p = 0.043). For depressive FEAN-SCZ patients, S2 amplitude was an independent predictor of the MCCB-Mazes (NAB) (β = -0.31, t = -2.52, p = 0.015). CONCLUSIONS SG-P50 deficit may be an informational biomarker for depressive symptoms and neurocognitive impairments in FEAN-SCZ patients.
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13
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Chen J, Patil KR, Yeo BTT, Eickhoff SB. Leveraging Machine Learning for Gaining Neurobiological and Nosological Insights in Psychiatric Research. Biol Psychiatry 2023; 93:18-28. [PMID: 36307328 DOI: 10.1016/j.biopsych.2022.07.025] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 07/06/2022] [Accepted: 07/28/2022] [Indexed: 11/18/2022]
Abstract
Much attention is currently devoted to developing diagnostic classifiers for mental disorders. Complementing these efforts, we highlight the potential of machine learning to gain biological insights into the psychopathology and nosology of mental disorders. Studies to this end have mainly used brain imaging data, which can be obtained noninvasively from large cohorts and have repeatedly been argued to reveal potentially intermediate phenotypes. This may become particularly relevant in light of recent efforts to identify magnetic resonance imaging-derived biomarkers that yield insight into pathophysiological processes as well as to refine the taxonomy of mental illness. In particular, the accuracy of machine learning models may be used as dependent variables to identify features relevant to pathophysiology. Moreover, such approaches may help disentangle the dimensional (within diagnosis) and often overlapping (across diagnoses) symptomatology of psychiatric illness. We also point out a multiview perspective that combines data from different sources, bridging molecular and system-level information. Finally, we summarize recent efforts toward a data-driven definition of subtypes or disease entities through unsupervised and semisupervised approaches. The latter, blending unsupervised and supervised concepts, may represent a particularly promising avenue toward dissecting heterogeneous categories. Finally, we raise several technical and conceptual aspects related to the reviewed approaches. In particular, we discuss common pitfalls pertaining to flawed input data or analytic procedures that would likely lead to unreliable outputs.
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Affiliation(s)
- Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China; Department of Psychiatry, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-universität Düsseldorf, Düsseldorf, Germany
| | - B T Thomas Yeo
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; Integrative Sciences & Engineering Programme, National University of Singapore, Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-universität Düsseldorf, Düsseldorf, Germany
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14
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Moller CI, Davey CG, Badcock PB, Wrobel AL, Cao A, Murrihy S, Sharmin S, Cotton SM. Correlates of suicidality in young people with depressive disorders: A systematic review. Aust N Z J Psychiatry 2022; 56:910-948. [PMID: 35362327 DOI: 10.1177/00048674221086498] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Depression is one of the most prevalent and disabling mental health conditions among young people worldwide. The health and economic burdens associated with depressive illness are substantial. Suicide and depression are closely intertwined, yet a diagnosis of depression itself lacks predictive specificity for suicidal behaviour. To better inform suicide prevention and early intervention strategies for young people, improved identification of modifiable intervention targets is needed. The objective of this review was to identify clinical, psychosocial and biological correlates of suicidality in young people diagnosed with a broad range of unipolar and bipolar depressive disorders. METHOD Systematic searches were conducted across MEDLINE, Embase and PsycINFO to identify studies of young people aged 15-25 years diagnosed with unipolar or bipolar depressive disorders. An assessment of suicidality was required for inclusion. Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 and Synthesis Without Meta-analysis guidelines. RESULTS We integrated findings from 71 studies including approximately 24,670 young people with clinically diagnosed depression. We identified 26 clinical, psychosocial and biological correlates of suicidality. Depression characteristics (type and severity), psychiatric comorbidity (particularly anxiety and substance use disorders) and neurological characteristics emerged as having the most evidence for being associated with suicidal outcomes. Our ability to pool data and conduct meaningful quantitative synthesis was hampered by substantial heterogeneity across studies and incomplete reporting; thus, meta-analysis was not possible. CONCLUSION Findings of this review reinforce the notion that suicidality is a complex phenomenon arising from the interplay of multiple contributing factors. Our findings question the utility of considering a diagnosis of depression as a specific risk factor for suicidality in young people. Suicidality itself is transdiagnostic; adoption of a transdiagnostic approach to investigating its aetiology and treatment is perhaps warranted. Future research investigating specific symptoms, or symptom networks, might help to further our understanding of suicidality among young people experiencing mental illness.
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Affiliation(s)
- Carl I Moller
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The University of Melbourne, Parkville, VIC, Australia
| | - Christopher G Davey
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The University of Melbourne, Parkville, VIC, Australia
- Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
| | - Paul B Badcock
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The University of Melbourne, Parkville, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Anna L Wrobel
- Orygen, The University of Melbourne, Parkville, VIC, Australia
- IMPACT - The Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Alice Cao
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Sean Murrihy
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The University of Melbourne, Parkville, VIC, Australia
| | - Sonia Sharmin
- Department of Occupational Therapy, Social Work and Social Policy, La Trobe University, Bundoora, VIC, Australia
- Research and Evaluation, Take Two, Berry Street, Eaglemont, VIC, Australia
- Department of Public Health, Torrens University Australia, Melbourne, VIC, Australia
| | - Sue M Cotton
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The University of Melbourne, Parkville, VIC, Australia
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15
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Brydges CR, Bhattacharyya S, Dehkordi SM, Milaneschi Y, Penninx B, Jansen R, Kristal BS, Han X, Arnold M, Kastenmüller G, Bekhbat M, Mayberg HS, Craighead WE, Rush AJ, Fiehn O, Dunlop BW, Kaddurah-Daouk R. Metabolomic and inflammatory signatures of symptom dimensions in major depression. Brain Behav Immun 2022; 102:42-52. [PMID: 35131442 PMCID: PMC9241382 DOI: 10.1016/j.bbi.2022.02.003] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 01/25/2022] [Accepted: 02/01/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions. METHODS Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism. RESULTS The IMD clinical dimension and the inflammatory index were positively correlated (r = 0.19, p = 0.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids. CONCLUSION The IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.
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Affiliation(s)
| | - Sudeepa Bhattacharyya
- Arkansas Biosciences Institute, Department of Biological Sciences, Arkansas State University, AR, USA
| | | | - Yuri Milaneschi
- Amsterdam UMC / GGZ inGeest Research & Innovation, Amsterdam, Netherlands
| | - Brenda Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Department of Amsterdam Public Health Research Institute and Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Bruce S Kristal
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xianlin Han
- University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Mandakh Bekhbat
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Helen S Mayberg
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - W Edward Craighead
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA; Department of Psychology, Emory University, Atlanta, GA, USA
| | - A John Rush
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Department of Psychiatry, Health Sciences Center, Texas Tech University, Permian Basin, TX, USA; Duke-National University of Singapore, Singapore
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, USA
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Department of Medicine, Duke University, Durham, NC, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC, USA.
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16
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Kamath J, Leon Barriera R, Jain N, Keisari E, Wang B. Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives. World J Psychiatry 2022; 12:393-409. [PMID: 35433319 PMCID: PMC8968499 DOI: 10.5498/wjp.v12.i3.393] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/23/2021] [Accepted: 02/13/2022] [Indexed: 02/06/2023] Open
Abstract
Depression is a serious medical condition and is a leading cause of disability worldwide. Current depression diagnostics and assessment has significant limitations due to heterogeneity of clinical presentations, lack of objective assessments, and assessments that rely on patients' perceptions, memory, and recall. Digital phenotyping (DP), especially assessments conducted using mobile health technologies, has the potential to greatly improve accuracy of depression diagnostics by generating objectively measurable endophenotypes. DP includes two primary sources of digital data generated using ecological momentary assessments (EMA), assessments conducted in real-time, in subjects' natural environment. This includes active EMA, data that require active input by the subject, and passive EMA or passive sensing, data passively and automatically collected from subjects' personal digital devices. The raw data is then analyzed using machine learning algorithms to identify behavioral patterns that correlate with patients' clinical status. Preliminary investigations have also shown that linguistic and behavioral clues from social media data and data extracted from the electronic medical records can be used to predict depression status. These other sources of data and recent advances in telepsychiatry can further enhance DP of the depressed patients. Success of DP endeavors depends on critical contributions from both psychiatric and engineering disciplines. The current review integrates important perspectives from both disciplines and discusses parameters for successful interdisciplinary collaborations. A clinically-relevant model for incorporating DP in clinical setting is presented. This model, based on investigations conducted by our group, delineates development of a depression prediction system and its integration in clinical setting to enhance depression diagnostics and inform the clinical decision making process. Benefits, challenges, and opportunities pertaining to clinical integration of DP of depression diagnostics are discussed from interdisciplinary perspectives.
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Affiliation(s)
- Jayesh Kamath
- Department of Psychiatry and Immunology, University of Connecticut School of Medicine, University of Connecticut Health Center, Farmington, CT 06030, United States
- Department of Psychiatry, University of Connecticut School of Medicine, University of Connecticut Health Center, Farmington, CT 06032, United States
| | - Roberto Leon Barriera
- Department of Psychiatry, University of Connecticut School of Medicine, University of Connecticut Health Center, Farmington, CT 06032, United States
| | - Neha Jain
- Department of Psychiatry, University of Connecticut School of Medicine, University of Connecticut Health Center, Farmington, CT 06032, United States
| | - Efraim Keisari
- Department of Psychiatry, University of Connecticut School of Medicine, University of Connecticut Health Center, Farmington, CT 06032, United States
| | - Bing Wang
- Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, United States
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Kim IB, Park SC. Machine Learning-Based Definition of Symptom Clusters and Selection of Antidepressants for Depressive Syndrome. Diagnostics (Basel) 2021; 11:1631. [PMID: 34573974 PMCID: PMC8468112 DOI: 10.3390/diagnostics11091631] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/03/2021] [Accepted: 09/03/2021] [Indexed: 12/30/2022] Open
Abstract
The current polythetic and operational criteria for major depression inevitably contribute to the heterogeneity of depressive syndromes. The heterogeneity of depressive syndrome has been criticized using the concept of language game in Wittgensteinian philosophy. Moreover, "a symptom- or endophenotype-based approach, rather than a diagnosis-based approach, has been proposed" as the "next-generation treatment for mental disorders" by Thomas Insel. Understanding the heterogeneity renders promise for personalized medicine to treat cases of depressive syndrome, in terms of both defining symptom clusters and selecting antidepressants. Machine learning algorithms have emerged as a tool for personalized medicine by handling clinical big data that can be used as predictors for subtype classification and treatment outcome prediction. The large clinical cohort data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D), Combining Medications to Enhance Depression Outcome (CO-MED), and the German Research Network on Depression (GRND) have recently began to be acknowledged as useful sources for machine learning-based depression research with regard to cost effectiveness and generalizability. In addition, noninvasive biological tools such as functional and resting state magnetic resonance imaging techniques are widely combined with machine learning methods to detect intrinsic endophenotypes of depression. This review highlights recent studies that have used clinical cohort or brain imaging data and have addressed machine learning-based approaches to defining symptom clusters and selecting antidepressants. Potentially applicable suggestions to realize machine learning-based personalized medicine for depressive syndrome are also provided herein.
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Affiliation(s)
- Il Bin Kim
- Department of Psychiatry, Hanyang University Guri Hospital, Guri 11923, Korea;
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Seon-Cheol Park
- Department of Psychiatry, Hanyang University Guri Hospital, Guri 11923, Korea;
- Department of Psychiatry, Hanyang University College of Medicine, Seoul 04763, Korea
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18
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Psychopathology and Neurocognition in the Era of the p-Factor: The Current Landscape and the Road Forward. PSYCHIATRY INTERNATIONAL 2021. [DOI: 10.3390/psychiatryint2030018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Neurocognitive abilities have frequently been claimed to be involved in the aetiology of psychopathology. Neurocognitive deficits have been reported across many disorders, and theoretical perspectives associate these deficits to the onset and maintenance of the symptomology. Recently, the heterogeneity of symptoms, and comorbidity of disorders, have motivated the development of structural models of psychopathology. Structural models indicate that factors such as internalising, externalising, thought disorder and the p-factor account for a wide variety of symptomology. It is unclear how neurocognitive abilities are best examined within these structures to advance our understanding of psychopathology. In this paper, we use Caspi et al.’s seminal writings as a framework to describe how neurocognitive abilities have been previously associated with categorical disorders and recently associated, and claimed to drive, the factors of psychopathology. We discuss the implications of the p-factor as a substantive construct or statistical artefact, and how this impacts the exploration of neurocognitive abilities and psychopathology. Further, we provide the case for alternative structural approaches, describe an innovative hypothesis of neurocognitive functioning, the multidimensional hypothesis, and explain how this may further our understanding of the heterogeneity of neurocognitive performance and psychopathology at the individual level. Finally, we provide a road forward for the future examination of neurocognitive abilities in psychopathology.
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19
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Fang X, Zhang R, Bao C, Zhou M, Yan W, Lu S, Xie S, Zhang X. Abnormal regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF) in first-episode drug-naïve schizophrenia patients comorbid with depression. Brain Imaging Behav 2021; 15:2627-2636. [PMID: 33788124 DOI: 10.1007/s11682-021-00465-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/25/2021] [Indexed: 01/21/2023]
Abstract
The current study aimed to characterize the regional homogeneity (ReHo) or fractional amplitude of low frequency fluctuations (fALFF) alterations in first-episode drug-naïve schizophrenia comorbid with depression. Sixty-nine first-episode drug-naïve schizophrenia patients and 34 healthy controls (HC) were included in the final analysis. Schizophrenia patients were divided into depressive patients (DP) and non-depressive patients (NDP), with 35 and 34 patients respectively, using the Hamilton Rating Scale for Depression -17(HRSD-17). All participants underwent resting-state fMRI (rs-fMRI), the fALFF (slow-4 and slow-5 bands) and ReHo were used to process the data. The results revealed eleven brain regions with altered slow-5 fALFF, eleven brain regions with altered slow-4 fALFF and ten brain regions with altered ReHo among DP, NDP and HC groups. Compared to NDP, the DP group had increased slow-5 fALFF in the Right Inferior Temporal Gyrus, increased ReHo in the Right Superior and Inferior Frontal Gyrus. The altered slow-5 fALFF in the Right Inferior Temporal Gyrus, altered ReHo in the Right Inferior Frontal Gyrus and Superior Frontal Gyrus were all positively correlated with the depressive symptoms in patients. However, there were no significant differences in slow-4 fALFF between DP and NDP groups. Our results indicate that the increased slow-5 fALFF in the Right Inferior Temporal Gyrus, increased ReHo in the Right Superior and Inferior Frontal Gyrus were associated with depressive symptoms in schizophrenia, which may provide preliminary evidence in better understanding the neural mechanisms underlying depressive symptoms in schizophrenia.
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Affiliation(s)
- Xinyu Fang
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Rongrong Zhang
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Chenxi Bao
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Min Zhou
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Wei Yan
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Shuiping Lu
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Shiping Xie
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
| | - Xiangrong Zhang
- Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
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Kim YK, Park SC. An alternative approach to future diagnostic standards for major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2021; 105:110133. [PMID: 33049324 DOI: 10.1016/j.pnpbp.2020.110133] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/06/2020] [Indexed: 12/17/2022]
Abstract
During the period extending from 1780 to 1880, the conceptualization of melancholia changed from an intellectual to a mood model. The modern view of depression, based on Kraepelinian dualism, has reflected changes in opinion on psychiatric taxonomy of individual melancholia. From the point of view of an "operational revolution," the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition (DSM-III) were based on a neoKraepelinian approach rooted in disease essentialism. In the revision process from the DSM-IV to the DSM-5, a combined dimensional and categorial approach was used. In the DSM-5, the diagnostic criteria for major depressive disorder are polythetic and operational in approach reflecting the heterogeneity of major depressive disorder. Although 227 different symptom combinations fulfilling the diagnostic criteria for major depressive disorder can be theoretically calculated, certain symptom combinations are more prevalent than others in real clinical situations. The heterogeneity of these operational criteria for major depressive disorder have been criticized in a manner informed by the Wittgensteinian analogy of the language game. Herein, our network analysis proposes a novel perspective on the psychopathology of major depressive disorder. The novel approach suggested here may lay the foundation for a redefinition of the traditional taxonomy of depression.
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Affiliation(s)
- Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Republic of Korea.
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21
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Park SC, Kim YK. Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:103-116. [PMID: 33834397 DOI: 10.1007/978-981-33-6044-0_7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, College of Medicine, Ansan, Republic of Korea.
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Park SC, Kim Y, Kim K, Woo YS, Kim JB, Jang EY, Lee HY, Yim HW, Ham BJ, Kim JM, Park YC. Network Analysis of the Symptoms of Depressive Disorders Over the Course of Therapy: Changes in Centrality Measures. Psychiatry Investig 2021; 18:48-58. [PMID: 33460534 PMCID: PMC7897865 DOI: 10.30773/pi.2020.0367] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/07/2020] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE Network analysis can be used in terms of a novel psychopathological approach for depressive syndrome. We aimed to estimate the successive network structures of depressive symptoms in patients with depressive disorder using data from the Clinical Research Center for Depression study. METHODS We enrolled 1,152 South Korean adult patients with depressive disorders who were beginning treatment for first-onset or recurrent depressive episodes. We examined the network structure of the severities of the items on the Hamilton Depression Rating Scale (HAMD) at baseline and at weeks 2, 12, 25, and 52. The node strength centrality of all the HAMD items at baseline and at week 2, 12, 25, and 52 in terms of network analysis. RESULTS In the severity networks, the anxiety (psychic) item was the most centrally situated in the initial period (baseline and week 2), while loss of weight was the most centrally situated item in the later period (weeks 25 and 52). In addition, the number of strong edges (i.e., edges representing strong correlations) increased in the late period compared to the initial period. CONCLUSION Our findings support a period-specific and symptom-focused therapeutic approach that can provide complementary information to the unidimensional total HAMD score.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Republic of Korea
| | - Yaeseul Kim
- Department of Psychiatry, Hanyang University School of Medicine, Seoul, Republic of Korea
| | - Kiwon Kim
- Department of Psychiatry, Veteran Health Service Medical Center, Seoul, Republic of Korea
| | - Young Sup Woo
- Department of Psychiatry, The Catholic University of Korea, Yeouido St. Mary's Hospital, Seoul, Republic of Korea
| | - Jung-Bum Kim
- Department of Psychiatry, Keimyung University School of Medicine, Daegu, Republic of Korea
| | - Eun Young Jang
- Department of Counselling Psychology, Honam Unviersity College of Humanities and Social Sciences, Gwangju, Republic of Korea
| | - Hwa-Young Lee
- Department of Psychiatry, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea
| | - Hyeon-Woo Yim
- Department of Preventive Medicine, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Seoul, Republic of Korea
| | - Jae-Min Kim
- Department of Psychiatry, Chonnam National University School of Medicine, Gwangju, Republic of Korea
| | - Yong Chon Park
- Department of Neuropsychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea
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Wang M, Ju Y, Lu X, Sun J, Dong Q, Liu J, Zhang L, Zhang Y, Zhang S, Wang Z, Liu B, Li L. Longitudinal changes of amplitude of low-frequency fluctuations in MDD patients: A 6-month follow-up resting-state functional magnetic resonance imaging study. J Affect Disord 2020; 276:411-417. [PMID: 32871671 DOI: 10.1016/j.jad.2020.07.067] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 05/19/2020] [Accepted: 07/05/2020] [Indexed: 11/16/2022]
Abstract
OBJECTIVE The aim of this study includes: (1) using resting-state functional magnetic resonance imaging (rsfMRI) to explore the aberrant brain regional spontaneous brain activities in acute major depressive disorder (MDD) patients; (2) to determine whether the abnormalities could be restored after 6 months of antidepressant treatment; (3) to investigate whether the differences in regional spontaneous brain activities are associated with clinical variables in MDD. METHOD RsfMRI scanning was performed in 149 MDD patients and 122 healthy control (HC) subjects at baseline. After 6 months of antidepressant treatment, rsfMRI scanning was reperformed in remitted MDD patients (MDD-R) (n=63). The characteristics of the amplitude of low-frequency fluctuations (ALFF), and the relationship between the fMRI representatives and clinical variables in the MDD group were analyzed. RESULTS (1) Compared to healthy controls, significantly decreased ALFF in the right precuneus/posterior cingulate cortex (PCUN/PCC) was detected in MDD. (2) The ALFF value of precuneus in MDD-R group did not change significantly after a 6-month antidepressant treatment and was still lower than the HC group when remission was achieved (P = 0.002). (3) No correlations were found between ALFF in the right PCUN/PCC and Hamilton Depression Rating Scale(HAMD) total score, illness duration, age of onset, and the number of episodes in the baseline MDD group. The ALFF change was not correlated with depressive symptom improvement in MDD-R group. CONCLUSIONS The reduction of ALFF in the precuneus persisted in MDD who achieved clinical remission, suggesting that the decreased ALFF in PCUN/PCC may be a trait marker of MDD.
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Affiliation(s)
- Mi Wang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Yumeng Ju
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Xiaowen Lu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Jinrong Sun
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Qiangli Dong
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Jin Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Liang Zhang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Yan Zhang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Shuai Zhang
- Zhumadian Psychiatric Hospital, Zhumaidan, Henan 463000, China
| | - Zengguang Wang
- Zhumadian Psychiatric Hospital, Zhumaidan, Henan 463000, China
| | - Bangshan Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China.
| | - Lingjiang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University, China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China.
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Nunes A, Trappenberg T, Alda M. The definition and measurement of heterogeneity. Transl Psychiatry 2020; 10:299. [PMID: 32839448 PMCID: PMC7445182 DOI: 10.1038/s41398-020-00986-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 07/21/2020] [Accepted: 08/10/2020] [Indexed: 12/31/2022] Open
Abstract
Heterogeneity is an important concept in psychiatric research and science more broadly. It negatively impacts effect size estimates under case-control paradigms, and it exposes important flaws in our existing categorical nosology. Yet, our field has no precise definition of heterogeneity proper. We tend to quantify heterogeneity by measuring associated correlates such as entropy or variance: practices which are akin to accepting the radius of a sphere as a measure of its volume. Under a definition of heterogeneity as the degree to which a system deviates from perfect conformity, this paper argues that its proper measure roughly corresponds to the size of a system's event/sample space, and has units known as numbers equivalent. We arrive at this conclusion through focused review of more than 100 years of (re)discoveries of indices by ecologists, economists, statistical physicists, and others. In parallel, we review psychiatric approaches for quantifying heterogeneity, including but not limited to studies of symptom heterogeneity, microbiome biodiversity, cluster-counting, and time-series analyses. We argue that using numbers equivalent heterogeneity measures could improve the interpretability and synthesis of psychiatric research on heterogeneity. However, significant limitations must be overcome for these measures-largely developed for economic and ecological research-to be useful in modern translational psychiatric science.
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Affiliation(s)
- Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Thomas Trappenberg
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.
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Park SC, Kim D. The Centrality of Depression and Anxiety Symptoms in Major Depressive Disorder Determined Using a Network Analysis. J Affect Disord 2020; 271:19-26. [PMID: 32312693 DOI: 10.1016/j.jad.2020.03.078] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 01/21/2020] [Accepted: 03/24/2020] [Indexed: 01/27/2023]
Abstract
BACKGROUND Comorbid anxiety symptoms are highly prevalent and closely linked with poorer treatment outcomes, chronicity, and hospitalization in major depressive disorder (MDD). Our study aimed to estimate the network of depression and anxiety symptoms that was developed based on a sample of MDD patients. METHODS We constructed a network of the 21 Beck Depression Inventory (BDI) symptoms and 21 Beck Anxiety Inventory (BAI) symptoms in 223 patients with MDD who were beginning psychiatric treatment. In addition, each of the depression and anxiety symptoms was considered to be an ordered categorical variable ranging in value from 0 to 3. RESULTS The three depression symptoms including loss of energy, loss of interest, and worthlessness and the seven anxiety symptoms including faintness or lightheadedness, feeling of choking, feeling scared, fear of the worst happening, nervousness, inability to relax, and feeling shaky were identified as the ten most central nodes within a network of depression and anxiety symptoms. The inter-connection between irritability and nervousness was a strong trans-diagnostic edge within the network of depression and anxiety symptoms. LIMITATIONS Because our study was designed in a cross-sectional manner, the networks were estimated undirectionally. CONCLUSIONS Our findings show that depression symptoms are not more central than anxiety symptoms within an estimated network structure of symptoms in patients with MDD. Moreover, the inter-connection between irritability and nervousness may suggests a probable trans-diagnostic association in MDD symptomatology.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Republic of Korea.
| | - Daeho Kim
- Department of Psychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea.
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26
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Park SC, Jang EY, Xiang YT, Kanba S, Kato TA, Chong MY, Lin SK, Yang SY, Avasthi A, Grover S, Kallivayalil RA, Udomratn P, Chee KY, Tanra AJ, Tan CH, Sim K, Sartorius N, Park YC, Shinfuku N. Network analysis of the depressive symptom profiles in Asian patients with depressive disorders: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD). Psychiatry Clin Neurosci 2020; 74:344-353. [PMID: 32048773 PMCID: PMC7318233 DOI: 10.1111/pcn.12989] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 01/21/2020] [Accepted: 02/04/2020] [Indexed: 12/13/2022]
Abstract
AIM We aimed to estimate the network structures of depressive symptoms using network analysis and evaluated the geographic regional differences in theses network structures among Asian patients with depressive disorders. METHODS Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD), the network of the ICD-10 diagnostic criteria for depressive episode was estimated from 1174 Asian patients with depressive disorders. The node strength centrality of all ICD-10 diagnostic criteria for a depressive episode was estimated using a community-detection algorithm. In addition, networks of depressive symptoms were estimated separately among East Asian patients and South or Southeast Asian patients. Moreover, networks were estimated separately among Asian patients from high-income countries and those from middle-income countries. RESULTS Persistent sadness, fatigue, and loss of interest were the most centrally situated within the network of depressive symptoms in Asian patients with depressive disorders overall. A community-detection algorithm estimated that when excluding psychomotor disturbance as an outlier, the other nine symptoms formed the largest clinically meaningful cluster. Geographic and economic variations in networks of depressive symptoms were evaluated. CONCLUSION Our findings demonstrated that the typical symptoms of the ICD-10 diagnostic criteria for depressive episode are the most centrally situated within the network of depressive symptoms. Furthermore, our findings suggested that cultural influences related to geographic and economic distributions of participants could influence the estimated depressive symptom network in Asian patients with depressive disorders.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Republic of Korea
| | - Eun Young Jang
- Department of Counseling Psychology, Honam University College of Humanities and Social Sciences, Gwangju, Republic of Korea
| | - Yu-Tao Xiang
- Faculty of Health Sciences, University of Macau, Macau, China
| | - Shigenobu Kanba
- Department of Neuropsychiatry, Graduate School of Medicine, Kyushu University, Fukuoka, Japan
| | - Takahiro A Kato
- Department of Neuropsychiatry, Graduate School of Medicine, Kyushu University, Fukuoka, Japan
| | - Mian-Yoon Chong
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung & Chang Gung University School of Medicine, Linkou, Taiwan
| | - Shih-Ku Lin
- Psychiatry Center, Tapei City Hospital, Taipei, Taiwan
| | - Shu-Yu Yang
- Department of Pharmacy, Taipei City Hospital and Fu Jen University, Taipei, Taiwan
| | - Ajit Avasthi
- Department of Psychiatry, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Sandeep Grover
- Department of Psychiatry, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | | | - Pichet Udomratn
- Department of Psychiatry, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| | - Kok Yoon Chee
- Tunku Abdul Rahman Institute of Neurosciences, Kuala Lumpur, Malaysia
| | - Andi J Tanra
- Faculty of Medicine, Department of Psychiatry, Hasanuddin University, Makassar, Indonesia
| | - Chay-Hoon Tan
- Department of Pharmacology, National University Hospital, Singapore
| | - Kang Sim
- Institute of Mental Health, Buangkok Green Medical Park, Singapore
| | - Norman Sartorius
- Association for the Improvement of Mental Health Programmes, Geneva, Switzerland
| | - Yong Chon Park
- Department of Neuropsychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea
| | - Naotaka Shinfuku
- Department of Social Welfare, School of Human Sciences, Seinan Gakuin University, Fukuoka, Japan
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Park SC. Symptom-based selection of antidepressants. JOURNAL OF THE KOREAN MEDICAL ASSOCIATION 2020; 63:216-226. [DOI: 10.5124/jkma.2020.63.4.216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Accepted: 03/11/2020] [Indexed: 10/17/2024] Open
Abstract
Most evidence-based pharmacological guidelines recommend selective serotonin reuptake inhibitors, serotoninnorepinephrine reuptake inhibitors, norepinephrine-dopamine reuptake inhibitors or norepinephrine and specific serotonin antidepressants as the first-line treatment for major depression. Since the clinical factors associated with treating patients with depression are relatively complex, it can be challenging to apply the recommendations of evidence-based medicine verbatim. Furthermore, the diagnostic criteria of major depressive disorders, which are defined in a polythetic and operational manner, inevitably result in their heterogeneity. Studies have inferred that depressive syndrome may be connected with “family resemblance” rather than being shared with a neurobiological essence. Therefore, the symptom-based selection of antidepressants can be supported by a network analysis that provides a novel perspective on the symptom structure of major depression. The symptom-based treatment algorithm suggests treatment options that can be applied to the symptoms that are included in and excluded from the diagnosis criteria of major depressive disorder. The symptom-based selection of antidepressants and other psychotropic agents involves matching the deconstructed symptoms of depression to the specific neuroanatomical regions and neurotransmitters. This ensures timely and optimized treatment options for patients with depression.
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Nunes A, Trappenberg T, Alda M. We need an operational framework for heterogeneity in psychiatric research. J Psychiatry Neurosci 2020; 45:3-6. [PMID: 31845771 PMCID: PMC6919921 DOI: 10.1503/jpn.190198] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
- Abraham Nunes
- From the Department of Psychiatry (Nunes, Alda) and the Faculty of Computer Science (Trappenberg, Nunes), Dalhousie University, Halifax, NS, Canada
| | - Thomas Trappenberg
- From the Department of Psychiatry (Nunes, Alda) and the Faculty of Computer Science (Trappenberg, Nunes), Dalhousie University, Halifax, NS, Canada
| | - Martin Alda
- From the Department of Psychiatry (Nunes, Alda) and the Faculty of Computer Science (Trappenberg, Nunes), Dalhousie University, Halifax, NS, Canada
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29
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Fang X, Chen L, Wang D, Yu L, Wang Y, Chen Y, Ren J, Tang W, Zhang C. Metabolic profiling identifies TC and LDL as potential serum biomarkers for depressive symptoms in schizophrenia. Psychiatry Res 2019; 281:112522. [PMID: 31521045 DOI: 10.1016/j.psychres.2019.112522] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 08/15/2019] [Accepted: 08/16/2019] [Indexed: 01/25/2023]
Abstract
This study aimed to explore the relationship between serum levels of cardiometabolic biomarkers and depressive symptoms in schizophrenia patients treated with atypical antipsychotics. A total of 210 patients with schizophrenia and 70 healthy controls were recruited in our present study. All patients were rated on the 17-item Hamilton Depression Rating Scale (HAMD-17) to measure depressive symptoms and the Positive and Negative Syndrome Scale (PANSS) for psychopathology. Serum cardiometabolic biomarkers (HDL, LDL, TC, TG, GLU) in all participants were measured. Our results showed that schizophrenia patients had higher levels of serum GLU, TG, TC, LDL and BMI, but lower levels of HDL than controls (all P < 0.05). Compared to patients without depressive symptoms, those with depressive symptoms showed higher PANSS total, general psychopathology, positive and negative symptom scores (all p < 0.05), as well as higher serum levels of LDL (p < 0.001) and TC (p = 0.011). In addition, our correlation analysis showed that serum LDL (P < 0.001) and TC (P = 0.045) levels were positively associated with HAMD total scores in schizophrenia patients after age, sex and education levels were controlled. Our results suggest the appearance of depression in schizophrenia patients may be associated with high levels of metabolic parameters, especially TC and LDL.
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Affiliation(s)
- Xinyu Fang
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Lixian Chen
- The Second People's Hospital of Yuhuan, Zhejiang, China
| | - Dandan Wang
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Lingfang Yu
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Yewei Wang
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Yan Chen
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Juanjuan Ren
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Wei Tang
- Wenzhou Kangning Hospital, Wenzhou Medical University, Zhejiang, China
| | - Chen Zhang
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
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Park SC, Kim YK. Diagnostic Issues of Depressive Disorders from Kraepelinian Dualism to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Psychiatry Investig 2019; 16:636-644. [PMID: 31550874 PMCID: PMC6761797 DOI: 10.30773/pi.2019.09.07] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 09/06/2019] [Indexed: 02/07/2023] Open
Abstract
Because the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) was mainly influenced by the neo-Kraepelinian approach, its categorical approach to defining mental disorders has been criticized from the viewpoint of etiological neutrality. In the context of bridging the gap between "presumed etiologies-based symptomatology" and "identifiable pathophysiological etiologies," the content in 5th edition, the DSM-5, has been revised to incorporate a combination of categorical and dimensional approaches. The most remarkable change of note regarding the diagnostic classification of depressive disorders in the DSM-5 is the splitting of mood disorders into bipolar disorders and depressive disorders, which is in accordance with the deconstruction of the Kraepelinian dualism for psychoses. The transdiagnostic specifiers "with mixed features," "with psychotic features," and "with anxious distress" are introduced to describe the relationships of depressive disorders with bipolar disorders, schizophrenia, and generalized anxiety disorder, respectively, in a dimensional manner. The lowering of the diagnostic threshold for major depressive disorder (MDD) may be caused by the addition of "hopelessness" to the subjective descriptors of depressive mood and the elimination of "bereavement exclusion" from the definition of MDD. Since the heterogeneity of MDD is equivalent to the Wittgensteinian "games" analogy, the different types of MDD are related not by a single essential feature but rather by "family resemblance." Network analyses of MDD symptoms may therefore need further review to elucidate the connections among interrelated symptoms and other clinical elements.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Republic of Korea
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, Republic of Korea
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Park SC. Understanding the Relationship between Low Muscle Mass and Depressed Mood in Korean Girls. J Korean Med Sci 2019; 34:e51. [PMID: 30804727 PMCID: PMC6384435 DOI: 10.3346/jkms.2019.34.e51] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 01/02/2019] [Indexed: 12/03/2022] Open
Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Korea
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Kim YK, Park SC. Classification of Psychiatric Disorders. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1192:17-25. [PMID: 31705488 DOI: 10.1007/978-981-32-9721-0_2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Because of the poor link between psychiatric diagnosis and neurobiological findings, it is difficult to classify mental disorders. The changes made to psychiatric diagnostic systems over the years can be understood in terms of "practical conservatism." The Diagnostic and Statistical Manual of Mental Disorders (DSM)-I and DSM-II were theoretically supported by the psychoanalytic and psychodynamic approach. Subsequently, psychiatric diagnoses of this kind were opposed by the anti-psychiatry movement, as well as by the findings of the Rosenhan experiment. Thus, the DSM-III revolution contained more empiricism, aligning psychiatry with biomedicine. Psychiatric diagnoses are classified and defined in terms of Kraepelinian dualism, using a categorical approach. The empirical trend was continued in the DSM-IV. To overcome the limitations of current psychiatric diagnostic systems and integrate fundamental genetic, neurobiological, behavioral, environmental, and experimental components into psychiatry, the Research Domain Criteria (RDoC) were established. To overcome the limitations of the categorical approach, psychiatrists have considered adopting a dimensional approach. However, their efforts were frustrated in the DSM-5 revision process. Thus, the DSM-5 is characterized by the rearrangement of psychiatric diagnoses, the partial adoption of a dimensional approach, the introduction of new diagnoses, and harmonization with the International Classification of Diseases.
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Affiliation(s)
- Yong-Ku Kim
- Department of Psychiatry, College of Medicine, Korea University Ansan Hospital, 516, Gojan-dong, 425-707, Ansan, Gyeonggi Province, Republic of Korea
| | - Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, 875, Haeun-daero, Haeundae-gu, 48108, Busan, Republic of Korea.
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Valkonen-Korhonen M, Leinola H, Könönen M, Niskanen E, Purhonen M, Pakarinen M, Ruusunen A, Lehto SM, Mervaala E, Honkalampi K, Koivumaa-Honkanen H, Viinamäki H. Bifrontal active and sham rTMS in treatment-resistant unipolar major depression. Nord J Psychiatry 2018; 72:586-592. [PMID: 30348049 DOI: 10.1080/08039488.2018.1500640] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND AND AIM Prevention of the recurrence of major depression and its residual symptoms requires effective treatment. Our aim was to study the effects of bifrontal active rTMS controlled by sham rTMS in treatment-resistant unipolar major depressive disorder (MDD). METHODS Thirty-seven patients with treatment-resistant MDD were randomized into two groups. One group received a total of 30 sessions of active bifrontal rTMS (10 Hz rTMS on left dorsolateral prefrontal cortex (DLPFC) and 1 Hz rTMS on right DLPFC) and the other group received bilateral sham rTMS on five days a week for six weeks. RESULTS Depressive symptoms significantly improved in both the groups, but without a significant group difference. Furthermore, patients with psychotic depression improved similarly to those with moderate or severe depression. CONCLUSIONS The results of present study indicate a large sham effect of stimulation treatment. The intensive structured treatment protocol may explain the positive outcome in both the groups. It is important to recognize, appreciate, and utilize placebo effects as a significant means of rehabilitation in psychiatric care.
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Affiliation(s)
- Minna Valkonen-Korhonen
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland
| | - Hanna Leinola
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland
| | - Mervi Könönen
- b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland.,c Department of Clinical Neurophysiology , Kuopio University Hospital , Kuopio , Finland
| | - Eini Niskanen
- d Department of Applied Physics , University of Eastern Finland , Kuopio , Finland
| | - Maija Purhonen
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland
| | - Maarit Pakarinen
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland
| | - Anu Ruusunen
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland.,e Food and Mood Centre/IMPACT SRC School of Medicine , Deakin University , Geelong , Australia
| | - Soili M Lehto
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland.,f Department of Psychology and Logopedics Faculty of Medicine , University of Helsinki , Helsinki , Finland
| | - Esa Mervaala
- b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland.,c Department of Clinical Neurophysiology , Kuopio University Hospital , Kuopio , Finland.,g Institute of Clinical Medicine/Clinical Neurophysiology , University of Eastern Finland , Kuopio , Finland
| | - Kirsi Honkalampi
- h School of Educational Sciences and Psychology , University of Eastern Finland , Joensuu , Finland
| | - Heli Koivumaa-Honkanen
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland.,i Departments of Psychiatry: North Karelia Central Hospital , Joensuu , Finland.,j SOTE , Iisalmi , Finland.,k South-Savonia Hospital District , Mikkeli , Finland.,l Lapland Hospital District , Rovaniemi , Finland
| | - Heimo Viinamäki
- a Department of Psychiatry , Kuopio University Hospital , Kuopio , Finland.,b Institute of Clinical Medicine/Psychiatry , University of Eastern Finland , Kuopio , Finland
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Svensson AF, Khaldi M, Engström I, Matusevich K, Nordenskjöld A. Remission rate of transcranial magnetic stimulation compared with electroconvulsive therapy: a case-control study. Nord J Psychiatry 2018; 72:471-476. [PMID: 30359165 DOI: 10.1080/08039488.2018.1481998] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
PURPOSE To compare the rate of remission, rate of response, change in depressive symptoms, and adverse effects between repetitive transcranial magnetic stimulation (rTMS) and electroconvulsive therapy (ECT). MATERIALS AND METHODS In this retrospective case-control study, 35 patients treated for depression with rTMS (left dorsolateral prefrontal cortex, 90% observed motor threshold, 10 Hz, 2000 pulses/session, 15 sessions) at Örebro University Hospital, Sweden (cases), were compared with a matched group of 35 patients treated for depression with ECT (controls). Data on controls were obtained from the Swedish National Quality Register for ECT (Q-ECT). Severity of depression was evaluated using the Montgomery-Åsberg Depression rating scale (MADRS). RESULTS Remission rate was 26% for cases and 43% for controls (p = .3). Response rate was 40% for cases and 51% for controls (p = .63). The median decrease in MADRS was 11 (IQR 3-19) vs. 17 (IQR 6-27; p = .10) for rTMS and ECT, respectively. There was no statistically significant difference in any measure of treatment effect between rTMS and ECT. More than half of the patients of the rTMS group experienced scalp discomfort and 11% of the ECT group had memory disturbances. CONCLUSIONS All measures of therapeutic efficacy were numerically inferior in the rTMS group compared to the ECT group. The differences were not statistically significant, probably because the sample size was small. More studies are required to find the optimal place for rTMS within the Swedish health care system. Such studies could be facilitated by inclusion of rTMS in the Q-ECT.
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Affiliation(s)
| | - Maher Khaldi
- a School of Medical Sciences , Örebro University , Örebro , Sweden
| | - Ingemar Engström
- b School of Medical Sciences , University Health Care Research Center, Örebro University , Sweden
| | | | - Axel Nordenskjöld
- b School of Medical Sciences , University Health Care Research Center, Örebro University , Sweden
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Qiu H, Liu Y, He H, Wu Y, He W, Huang G, He J. The association between mean platelet volume levels and poststroke depression. Brain Behav 2018; 8:e01114. [PMID: 30178628 PMCID: PMC6192406 DOI: 10.1002/brb3.1114] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 07/24/2018] [Accepted: 07/28/2018] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE High levels of mean platelet volume (MPV) had been found in depression subjects. We sought to examine the relationship between MPV and poststroke depression (PSD). METHODS One hundred and eighty-five patients with acute ischemic stroke were enrolled in our study. Peripheral venous blood samples were drawn at admission and MPV levels were measured by the automated hematology analyzer. Patients with a HAMD-17 score >7 were diagnosed as having PSD. RESULTS We found that 60 patients (32.4%) developed PSD, the MPV levels in PSD patients were significantly higher (9.3 ± 1.8 fl) compared to non-PSD patients (8.5 ± 1.6 fl). High MPV levels (≥9.1 fl) were independently correlated with PSD (OR 2.762, 95% CI 1.138-6.702, p = 0.025). CONCLUSIONS Patients with higher levels of MPV at admission were correlated with the development of PSD at 1 month after stroke and might be a predictor of its presence.
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Affiliation(s)
- Huihua Qiu
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yuntao Liu
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Hongfei He
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yuemin Wu
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Weilei He
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Guiqian Huang
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jincai He
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Greco A, Messerotti Benvenuti S, Gentili C, Palomba D, Scilingo EP, Valenza G. Assessment of linear and nonlinear/complex heartbeat dynamics in subclinical depression (dysphoria). Physiol Meas 2018; 39:034004. [DOI: 10.1088/1361-6579/aaaeac] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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