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Randau M, Bach B, Reinholt N, Pernet C, Oranje B, Rasmussen BS, Arnfred S. Transdiagnostic psychopathology in the light of robust single-trial event-related potentials. Psychophysiology 2024; 61:e14562. [PMID: 38459627 DOI: 10.1111/psyp.14562] [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: 09/25/2023] [Revised: 01/25/2024] [Accepted: 02/24/2024] [Indexed: 03/10/2024]
Abstract
Recent evidence indicates that event-related potentials (ERPs) as measured on the electroencephalogram (EEG) are more closely related to transdiagnostic, dimensional measures of psychopathology (TDP) than to diagnostic categories. A comprehensive examination of correlations between well-studied ERPs and measures of TDP is called for. In this study, we recruited 50 patients with emotional disorders undergoing 14 weeks of transdiagnostic group psychotherapy as well as 37 healthy comparison subjects (HC) matched in age and sex. HCs were assessed once and patients three times throughout treatment (N = 172 data sets) with a battery of well-studied ERPs and psychopathology measures consistent with the TDP framework The Hierarchical Taxonomy of Psychopathology (HiTOP). ERPs were quantified using robust single-trial analysis (RSTA) methods and TDP correlations with linear regression models as implemented in the EEGLAB toolbox LIMO EEG. We found correlations at several levels of the HiTOP hierarchy. Among these, a reduced P3b was associated with the general p-factor. A reduced error-related negativity correlated strongly with worse symptomatology across the Internalizing spectrum. Increases in the correct-related negativity correlated with symptoms loading unto the Distress subfactor in the HiTOP. The Flanker N2 was related to specific symptoms of Intrusive Cognitions and Traumatic Re-experiencing and the mismatch negativity to maladaptive personality traits at the lowest levels of the HiTOP hierarchy. Our study highlights the advantages of RSTA methods and of using validated TDP constructs within a consistent framework. Future studies could utilize machine learning methods to predict TDP from a set of ERP features at the subject level.
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Affiliation(s)
- Martin Randau
- Research Unit for Psychotherapy & Psychopathology, Mental Health Service West, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Bo Bach
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Nina Reinholt
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Cyril Pernet
- Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
| | - Bob Oranje
- Center for Neuropsychiatric Schizophrenia Research (CNSR), Copenhagen University Hospital, Copenhagen, Denmark
| | - Belinda S Rasmussen
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Sidse Arnfred
- Research Unit for Psychotherapy & Psychopathology, Mental Health Service West, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
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Mihaljevic M, Chang YH, Witmer AM, Coughlin JM, Schretlen DJ, Barker PB, Yang K, Sawa A. Reduction of N-acetyl aspartate (NAA) in association with relapse in early-stage psychosis: a 7-Tesla MRS study. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:29. [PMID: 38429320 PMCID: PMC10907360 DOI: 10.1038/s41537-024-00451-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 02/15/2024] [Indexed: 03/03/2024]
Abstract
Understanding the biological underpinning of relapse could improve the outcomes of patients with psychosis. Relapse is elicited by multiple reasons/triggers, but the consequence frequently accompanies deteriorations of brain function, leading to poor prognosis. Structural brain imaging studies have recently been pioneered to address this question, but a lack of molecular investigations is a knowledge gap. Following a criterion used for recent publications by others, we defined the experiences of relapse by hospitalization(s) due to psychotic exacerbation. We hypothesized that relapse-associated molecules might be underscored from the neurometabolites whose levels have been different between overall patients with early-stage psychosis and healthy subjects in our previous report. In the present study, we observed a significant decrease in the levels of N-acetyl aspartate in the anterior cingulate cortex and thalamus in patients who experienced relapse compared to patients who did not. Altogether, decreased N-acetyl aspartate levels may indicate relapse-associated deterioration of neuronal networks in patients.
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Affiliation(s)
- Marina Mihaljevic
- Departments of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yu-Ho Chang
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ashley M Witmer
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jennifer M Coughlin
- Departments of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David J Schretlen
- Departments of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter B Barker
- Departments of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kun Yang
- Departments of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Akira Sawa
- Departments of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Departments of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Departments of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Departments of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Departments of Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Parker D, Trotti R, McDowell J, Keedy S, Keshavan M, Pearlson G, Gershon E, Ivleva E, Huang LY, Sauer K, Hill S, Sweeny J, Tamminga C, Clementz B. Differentiating Biomarker Features and Familial Characteristics of B-SNIP Psychosis Biotypes. RESEARCH SQUARE 2024:rs.3.rs-3702638. [PMID: 38260530 PMCID: PMC10802686 DOI: 10.21203/rs.3.rs-3702638/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Idiopathic psychosis shows considerable biological heterogeneity across cases. B-SNIP used psychosis-relevant biomarkers to identity psychosis Biotypes, which will aid etiological and targeted treatment investigations. Psychosis probands from the B-SNIP consortium (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognition, saccades, and auditory EEG measurements. ERP quantifications were substantially modified from previous iterations of this approach. Multivariate integration reduced multiple biomarker outcomes to 11 "bio-factors". Twenty-four different approaches indicated bio-factor data among probands were best distributed as three subgroups. Numerical taxonomy with k-means constructed psychosis Biotypes, and rand indices evaluated consistency of Biotype assignments. Psychosis subgroups, their non-psychotic first-degree relatives, and healthy individuals were compared across bio-factors. The three psychosis Biotypes differed significantly on all 11 bio-factors, especially prominent for general cognition, antisaccades, ERP magnitude, and intrinsic neural activity. Rand indices showed excellent consistency of clustering membership when samples included at least 1100 subjects. Canonical discriminant analysis described composite bio-factors that simplified group comparisons and captured neural dysregulation, neural vigor, and stimulus salience variates. Neural dysregulation captured Biotype-2, low neural vigor captured Biotype-1, and deviations of stimulus salience captured Biotype-3. First-degree relatives showed similar patterns as their Biotyped proband relatives on general cognition, antisaccades, ERP magnitudes, and intrinsic brain activity. Results extend previous efforts by the B-SNIP consortium to characterize biologically distinct psychosis Biotypes. They also show that at least 1100 observations are necessary to achieve consistent outcomes. First-degree relative data implicate specific bio-factor deviations to the subtype of their proband and may inform studies of genetic risk.
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Huang LY, Parker DA, Ethridge LE, Hamm JP, Keedy SS, Tamminga CA, Pearlson GD, Keshavan MS, Hill SK, Sweeney JA, McDowell JE, Clementz BA. Double dissociation between P300 components and task switch error type in healthy but not psychosis participants. Schizophr Res 2023; 261:161-169. [PMID: 37776647 PMCID: PMC11015813 DOI: 10.1016/j.schres.2023.09.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/02/2023] [Accepted: 09/13/2023] [Indexed: 10/02/2023]
Abstract
Event-related potentials (ERPs) during oddball tasks and the behavioral performance on the Penn Conditional Exclusion Task (PCET) measure context-appropriate responding: P300 ERPs to oddball targets reflect detection of input changes and context updating in working memory, and PCET performance indexes detection, adherence, and maintenance of mental set changes. More specifically, PCET variables quantify cognitive functions including inductive reasoning (set 1 completion), mental flexibility (perseverative errors), and working memory maintenance (regressive errors). Past research showed that both P300 ERPs and PCET performance are disrupted in psychosis. This study probed the possible neural correlates of 3 PCET abnormalities that occur in participants with psychosis via the overlapping cognitive demands of the two study paradigms. In a two-tiered analysis, psychosis (n = 492) and healthy participants (n = 244) were first divided based on completion of set 1 - which measures subjects' ability to use inductive reasoning to arrive at the correct set. Results showed that participants who failed set 1 produced lower parietal P300, independent of clinical status. In the second tier of analysis, a double dissociation was found among healthy set 1 completers: frontal P300 amplitudes were negatively associated with perseverative errors, and parietal P300 was negatively associated with regressive errors. In contrast, psychosis participants showed global P300 reductions regardless of PCET performance. From this we conclude that in psychosis, overall activations evoked by the oddball task are reduced while the cognitive functions required by PCET are still somewhat supported, showing some level of independence or compensatory physiology in psychosis between neural activities underlying the two tasks.
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Affiliation(s)
- Ling-Yu Huang
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David A Parker
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - Lauren E Ethridge
- Department of Psychology and Pediatrics, University of Oklahoma, Norman, OK, USA
| | - Jordan P Hamm
- Department of Neuroscience, Georgia State University, Atlanta, GA, USA
| | - Sarah S Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | | | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jennifer E McDowell
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - Brett A Clementz
- Departments of Psychology & Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA.
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Clementz BA, Chattopadhyay I, Trotti RL, Parker DA, Gershon ES, Hill SK, Ivleva EI, Keedy SK, Keshavan MS, McDowell JE, Pearlson GD, Tamminga CA, Gibbons RD. Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1. Schizophr Res 2023; 260:143-151. [PMID: 37657281 PMCID: PMC10712427 DOI: 10.1016/j.schres.2023.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 09/03/2023]
Abstract
Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.
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Affiliation(s)
- Brett A Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA 30602, United States of America.
| | - Ishanu Chattopadhyay
- Department of Medicine, Section of Hospital Medicine, University of Chicago, Chicago, IL, United States of America
| | - Rebekah L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - David A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta VA Medical Center, Atlanta, GA, United States of America
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States of America
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Jennifer E McDowell
- Department of Psychology, Owens Institute for Behavioral Research, University of Georgia, Athens, GA 30602, United States of America
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University, School of Medicine, New Haven, CT, United States of America; Olin NeuroPsychiatry Research Center, Institute of Living, Hartford, CT, United States of America
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Robert D Gibbons
- Center for Health Statistics, Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL, United States of America
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Li F, Wang G, Jiang L, Yao D, Xu P, Ma X, Dong D, He B. Disease-specific resting-state EEG network variations in schizophrenia revealed by the contrastive machine learning. Brain Res Bull 2023; 202:110744. [PMID: 37591404 DOI: 10.1016/j.brainresbull.2023.110744] [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: 06/27/2023] [Revised: 08/03/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023]
Abstract
Given a multitude of genetic and environmental factors, when investigating the variability in schizophrenia (SCZ) and the first-degree relatives (R-SCZ), latent disease-specific variation is usually hidden. To reliably investigate the mechanism underlying the brain deficits from the aspect of functional networks, we newly iterated a framework of contrastive variational autoencoders (cVAEs) applied in the contrasts among three groups, to disentangle the latent resting-state network patterns specified for the SCZ and R-SCZ. We demonstrated that the comparison in reconstructed resting-state networks among SCZ, R-SCZ, and healthy controls (HC) revealed network distortions of the inner-frontal hypoconnectivity and frontal-occipital hyperconnectivity, while the original ones illustrated no differences. And only the classification by adopting the reconstructed network metrics achieved satisfying performances, as the highest accuracy of 96.80% ± 2.87%, along with the precision of 95.05% ± 4.28%, recall of 98.18% ± 3.83%, and F1-score of 96.51% ± 2.83%, was obtained. These findings consistently verified the validity of the newly proposed framework for the contrasts among the three groups and provided related resting-state network evidence for illustrating the pathological mechanism underlying the brain deficits in SCZ, as well as facilitating the diagnosis of SCZ.
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Affiliation(s)
- Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, China
| | - Guangying Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, China; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, China; Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610041, China; Rehabilitation Center, Qilu Hospital of Shandong University, Jinan 250012, China.
| | - Xuntai Ma
- Clinical Medical College of Chengdu Medical College, Chengdu 610500, China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, China.
| | - Debo Dong
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Institute of Neuroscience and Medicine, Brain and Behavior (INM-7), Research Center Jülich, Jülich, Germany.
| | - Baoming He
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China; Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, China.
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Goena J, Alústiza I, Vidal-Adroher C, Garcés MS, Fernández M, Molero P, García-Eulate R, Fernández-Seara M, Ortuño F. Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study. Front Psychol 2023; 14:1110972. [PMID: 37529319 PMCID: PMC10390230 DOI: 10.3389/fpsyg.2023.1110972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 06/05/2023] [Indexed: 08/03/2023] Open
Abstract
Introduction Over the past few years, several studies have described the brain activation pattern related to both time discrimination (TD) and change detection processes. We hypothesize that both processes share a common brain network which may play a significant role in more complex cognitive processes. The main goal of this proof-of-concept study is to describe the pattern of brain activity involved in TD and oddball detection (OD) paradigms, and in processes requiring higher cognitive effort. Methods We designed an experimental task, including an auditory test tool to assess TD and OD paradigms, which was conducted under functional magnetic resonance imaging (fMRI) in 14 healthy participants. We added a cognitive control component into both paradigms in our test tool. We used the general linear model (GLM) to analyze the individual fMRI data images and the random effects model for group inference. Results We defined the areas of brain activation related to TD and OD paradigms. We performed a conjunction analysis of contrast TD (task > control) and OD (task > control) patterns, finding both similarities and significant differences between them. Discussion We conclude that change detection and other cognitive processes requiring an increase in cognitive effort require participation of overlapping functional and neuroanatomical components, suggesting the presence of a common time and change detection network. This is of particular relevance for future research on normal cognitive functioning in the healthy population, as well as for the study of cognitive impairment and clinical manifestations associated with various neuropsychiatric conditions such as schizophrenia.
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Affiliation(s)
- Javier Goena
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
- Department of Psychiatry, Basurto University Hospital, Bilbao, Spain
| | - Irene Alústiza
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Cristina Vidal-Adroher
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - María Sol Garcés
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Colegio de Ciencias Sociales y Humanidades, Universidad San Francisco de Quito, Quito, Ecuador
- Instituto de Neurociencias, Universidad San Francisco de Quito, Quito, Ecuador
| | - Miguel Fernández
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Patricio Molero
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Reyes García-Eulate
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - María Fernández-Seara
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Felipe Ortuño
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
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Parker DA, Cubells JF, Imes SL, Ruban GA, Henshey BT, Massa NM, Walker EF, Duncan EJ, Ousley OY. Deep psychophysiological phenotyping of adolescents and adults with 22q11.2 deletion syndrome: a multilevel approach to defining core disease processes. BMC Psychiatry 2023; 23:425. [PMID: 37312091 PMCID: PMC10262114 DOI: 10.1186/s12888-023-04888-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/18/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND 22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal interstitial-deletion disorder, occurring in approximately 1 in 2000 to 6000 live births. Affected individuals exhibit variable clinical phenotypes that can include velopharyngeal anomalies, heart defects, T-cell-related immune deficits, dysmorphic facial features, neurodevelopmental disorders, including autism, early cognitive decline, schizophrenia, and other psychiatric disorders. Developing comprehensive treatments for 22q11.2DS requires an understanding of both the psychophysiological and neural mechanisms driving clinical outcomes. Our project probes the core psychophysiological abnormalities of 22q11.2DS in parallel with molecular studies of stem cell-derived neurons to unravel the basic mechanisms and pathophysiology of 22q11.2-related psychiatric disorders, with a primary focus on psychotic disorders. Our study is guided by the central hypothesis that abnormal neural processing associates with psychophysiological processing and underlies clinical diagnosis and symptomatology. Here, we present the scientific background and justification for our study, sharing details of our study design and human data collection protocol. METHODS Our study is recruiting individuals with 22q11.2DS and healthy comparison subjects between the ages of 16 and 60 years. We are employing an extensive psychophysiological assessment battery (e.g., EEG, evoked potential measures, and acoustic startle) to assess fundamental sensory detection, attention, and reactivity. To complement these unbiased measures of cognitive processing, we will develop stem-cell derived neurons and examine neuronal phenotypes relevant to neurotransmission. Clinical characterization of our 22q11.2DS and control participants relies on diagnostic and research domain criteria assessments, including standard Axis-I diagnostic and neurocognitive measures, following from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) and the North American Prodrome Longitudinal Study (NAPLS) batteries. We are also collecting measures of autism spectrum (ASD) and attention deficit/hyperactivity disorder (ADHD)-related symptoms. DISCUSSION Studying 22q11.2DS in adolescence and adulthood via deep phenotyping across multiple clinical and biological domains may significantly increase our knowledge of its core disease processes. Our manuscript describes our ongoing study's protocol in detail. These paradigms could be adapted by clinical researchers studying 22q11.2DS, other CNV/single gene disorders, or idiopathic psychiatric syndromes, as well as by basic researchers who plan to incorporate biobehavioral outcome measures into their studies of 22q11.2DS.
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Affiliation(s)
- David A Parker
- Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA.
| | - Joseph F Cubells
- Department of Human Genetics; Emory Autism Center; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 1551 Shoup Court, Decatur, GA, 30033, USA
| | - Sid L Imes
- Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA
| | - Gabrielle A Ruban
- Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA
| | - Brett T Henshey
- Emory University, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA
| | - Nicholas M Massa
- Atlanta Veterans Administration Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Psychology and Interdisciplinary Sciences Building Suite 487, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Erica J Duncan
- Atlanta Veterans Administration Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Brain Health Center, 12 Executive Park Dr, Atlanta, GA, 30329, USA
| | - Opal Y Ousley
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 1551 Shoup Court, Decatur, GA, USA
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9
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Trotti RL, Parker DA, Sabatinelli D, Keshavan MS, Keedy SK, Gershon ES, Pearlson GD, Hill SK, Tamminga CA, McDowell JE, Clementz BA. Emotional scene processing in biotypes of psychosis. Psychiatry Res 2023; 324:115227. [PMID: 37121219 PMCID: PMC10175237 DOI: 10.1016/j.psychres.2023.115227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/14/2023] [Accepted: 04/23/2023] [Indexed: 05/02/2023]
Abstract
Social-emotional deficits in psychosis may be indexed by deviations in emotional scene processing, but event-related potential (ERP) studies indicate such deviations may not map cleanly to diagnostic categories. Neurobiologically defined psychosis subgroups offer an alternative that may better capture neurophysiological correlates of social-emotional deficits. The current study investigates emotional scene-elicited ERPs in Biotypes of psychosis in a large (N = 622), well-characterized sample. Electroencephalography was recorded in healthy persons (N = 129), Biotype-1 (N = 195), Biotype-2 (N = 131), and Biotype-3 (N = 167) psychosis cases. ERPs were measured from posterior and centroparietal scalp locations. Neural responses to emotional scenes were compared between healthy and psychosis groups. Multivariate group discrimination analyses resulted in two composite variates that differentiated groups. The first variate displayed large differences between low-cognition (Biotype-1, Biotype-2) and intact-cognition groups (Biotype-3, healthy persons). The second indicated a small-to-moderate distinction of Biotypes-2 and -3 from Biotype-1 and healthy persons. Two multivariate correlations were identified indicating associations between 1) self-reported emotional experience and generalized cognition and 2) socio-occupational functioning and late-stage emotional processing. Psychosis Biotypes displayed emotional processing deficits not apparent in DSM psychosis subgroups. Future translational research may benefit from exploring emotional scene processing in such neurobiologically-defined psychosis groups.
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Affiliation(s)
- R L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - D A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - D Sabatinelli
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - M S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - S K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - E S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - G D Pearlson
- Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - S K Hill
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, USA
| | - C A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J E McDowell
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - B A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
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10
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Clementz BA, Parker DA, Trotti RL, McDowell JE, Keedy SK, Keshavan MS, Pearlson GD, Gershon ES, Ivleva EI, Huang LY, Hill SK, Sweeney JA, Thomas O, Hudgens-Haney M, Gibbons RD, Tamminga CA. Psychosis Biotypes: Replication and Validation from the B-SNIP Consortium. Schizophr Bull 2022; 48:56-68. [PMID: 34409449 PMCID: PMC8781330 DOI: 10.1093/schbul/sbab090] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Current clinical phenomenological diagnosis in psychiatry neither captures biologically homologous disease entities nor allows for individualized treatment prescriptions based on neurobiology. In this report, we studied two large samples of cases with schizophrenia, schizoaffective, and bipolar I disorder with psychosis, presentations with clinical features of hallucinations, delusions, thought disorder, affective, or negative symptoms. A biomarker approach to subtyping psychosis cases (called psychosis Biotypes) captured neurobiological homology that was missed by conventional clinical diagnoses. Two samples (called "B-SNIP1" with 711 psychosis and 274 healthy persons, and the "replication sample" with 717 psychosis and 198 healthy persons) showed that 44 individual biomarkers, drawn from general cognition (BACS), motor inhibitory (stop signal), saccadic system (pro- and anti-saccades), and auditory EEG/ERP (paired-stimuli and oddball) tasks of psychosis-relevant brain functions were replicable (r's from .96-.99) and temporally stable (r's from .76-.95). Using numerical taxonomy (k-means clustering) with nine groups of integrated biomarker characteristics (called bio-factors) yielded three Biotypes that were virtually identical between the two samples and showed highly similar case assignments to subgroups based on cross-validations (88.5%-89%). Biotypes-1 and -2 shared poor cognition. Biotype-1 was further characterized by low neural response magnitudes, while Biotype-2 was further characterized by overactive neural responses and poor sensory motor inhibition. Biotype-3 was nearly normal on all bio-factors. Construct validation of Biotype EEG/ERP neurophysiology using measures of intrinsic neural activity and auditory steady state stimulation highlighted the robustness of these outcomes. Psychosis Biotypes may yield meaningful neurobiological targets for treatments and etiological investigations.
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Affiliation(s)
- Brett A Clementz
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - David A Parker
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Rebekah L Trotti
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Institute of Living, Hartford Healthcare Corp, Hartford, CT, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ling-Yu Huang
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Olivia Thomas
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | | | - Robert D Gibbons
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
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11
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Qiu Y, Wang J, Zhang Y, Wu T, Li B, Yu X. The Personality Traits and P300 of Offspring of Parents With Alcohol Dependence Differ Depending on Current Risky Drinking: A Preliminary Case-Control Study. Front Psychiatry 2022; 13:918965. [PMID: 35757213 PMCID: PMC9226557 DOI: 10.3389/fpsyt.2022.918965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
AIMS The aim of this study was to investigate the personality traits, and P300 component in the offspring of parents with alcohol dependence (OPAD) currently engaged in risky drinking and those not engaged in risky drinking, and to further explore the correlates of problematic alcohol use. METHODS A case-control study was conducted according to the cutoff of the Alcohol Use Disorder Identification Test (AUDIT). The frequency of the TaqIA polymorphism of the dopamine receptor D2 gene associated with alcohol dependence was compared between the two OPAD groups. Tridimensional Personality Questionnaire (TPQ), The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST), and the MINI-International Neuropsychiatric Interview (M.I.N.I.) were measured or interviewed in OPAD not engaged in risky drinking (resilient; n = 35) and those currently engaged in risky drinking (vulnerable; n = 20). P300 was measured to test the possible electrophysiological differences. The correlates of alcohol use were analyzed. RESULTS Vulnerable OPAD showed higher novelty seeking subscale scores (NS4; 4.45 ± 2.012 vs. 3.31 ± 1.728, P < 0.05) and harm avoidance subscale scores (HA4; 5.3 ± 2.319 vs. 3.66 ± 2.461, P < 0.05) than resilient OPAD, while the total scores of each dimension showed no significant difference. OPAD engaged in risky drinking showed more tobacco use than OPAD resistant to risky drinking. OPAD with risky drinking showed a shorter P300 latency than resilient OPAD on Fz electrodes. AUDIT scores of OPAD were correlated with P300 latency. CONCLUSIONS P300 differed between OPAD with and without risky drinking and alcohol use was associated with P300 latency, indicating that P300 may be used in the early detection of vulnerable OPAD and early intervention in the future.
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Affiliation(s)
- Yujia Qiu
- Clinical Research Department, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
| | - Jing Wang
- Clinical Research Department, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
| | - Ying Zhang
- Clinical Research Department, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
| | - Tingfang Wu
- Ward Ten, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Bing Li
- Clinical Research Department, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
| | - Xin Yu
- Clinical Research Department, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
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12
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Affiliation(s)
- Ned H Kalin
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
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13
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Abo Hamza EG, Kéri S, Csigó K, Bedewy D, Moustafa AA. Pareidolia in Schizophrenia and Bipolar Disorder. Front Psychiatry 2021; 12:746734. [PMID: 34955913 PMCID: PMC8702957 DOI: 10.3389/fpsyt.2021.746734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
While there are many studies on pareidolia in healthy individuals and patients with schizophrenia, to our knowledge, there are no prior studies on pareidolia in patients with bipolar disorder. Accordingly, in this study, we, for the first time, measured pareidolia in patients with bipolar disorder (N = 50), and compared that to patients with schizophrenia (N = 50) and healthy controls (N = 50). We have used (a) the scene test, which consists of 10 blurred images of natural scenes that was previously found to produce illusory face responses and (b) the noise test which had 32 black and white images consisting of visual noise and 8 images depicting human faces; participants indicated whether a face was present on these images and to point to the location where they saw the face. Illusory responses were defined as answers when observers falsely identified objects that were not on the images in the scene task (maximum illusory score: 10), and the number of noise images in which they reported the presence of a face (maximum illusory score: 32). Further, we also calculated the total pareidolia score for each task (the sum number of images with illusory responses in the scene and noise tests). The responses were scored by two independent raters with an excellent congruence (kappa > 0.9). Our results show that schizophrenia patients scored higher on pareidolia measures than both healthy controls and patients with bipolar disorder. Our findings are agreement with prior findings on more impaired cognitive processes in schizophrenia than in bipolar patients.
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Affiliation(s)
- Eid G Abo Hamza
- Psychology Department, College of Humanities and Sciences, Ajman University, Ajman, United Arab Emirates.,College of Education, Tanta University, Tanta, Egypt
| | - Szabolcs Kéri
- National Institute of Psychiatry and Addictions, Budapest, Hungary.,Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary.,Department of Physiology, University of Szeged, Szeged, Hungary
| | - Katalin Csigó
- National Institute of Psychiatry and Addictions, Budapest, Hungary
| | - Dalia Bedewy
- Psychology Department, College of Humanities and Sciences, Ajman University, Ajman, United Arab Emirates.,College of Education, Tanta University, Tanta, Egypt
| | - Ahmed A Moustafa
- Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.,School of Psychology & Marcs Institute for Brain and Behaviour, Western Sydney University, Sydney, NSW, Australia
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