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Zheng J, Zong X, Tang L, Guo H, Zhao P, Womer FY, Zhang X, Tang Y, Wang F. Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders. Psychol Med 2024:1-11. [PMID: 38804091 DOI: 10.1017/s0033291724000886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
BACKGROUND Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine. METHODS We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort. RESULTS Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable. CONCLUSIONS Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.
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Affiliation(s)
- Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Xiaofen Zong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Lili Tang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Fay Y Womer
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
- Department of Gerontology, The First Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China
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Meng X, Zhang S, Zhou S, Ma Y, Yu X, Guan L. Putative Risk Biomarkers of Bipolar Disorder in At-risk Youth. Neurosci Bull 2024:10.1007/s12264-024-01219-w. [PMID: 38710851 DOI: 10.1007/s12264-024-01219-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 03/08/2024] [Indexed: 05/08/2024] Open
Abstract
Bipolar disorder is a highly heritable and functionally impairing disease. The recognition and intervention of BD especially that characterized by early onset remains challenging. Risk biomarkers for predicting BD transition among at-risk youth may improve disease prognosis. We reviewed the more recent clinical studies to find possible pre-diagnostic biomarkers in youth at familial or (and) clinical risk of BD. Here we found that putative biomarkers for predicting conversion to BD include findings from multiple sample sources based on different hypotheses. Putative risk biomarkers shown by perspective studies are higher bipolar polygenetic risk scores, epigenetic alterations, elevated immune parameters, front-limbic system deficits, and brain circuit dysfunction associated with emotion and reward processing. Future studies need to enhance machine learning integration, make clinical detection methods more objective, and improve the quality of cohort studies.
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Affiliation(s)
- Xinyu Meng
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Shengmin Zhang
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Shuzhe Zhou
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Yantao Ma
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Xin Yu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Lili Guan
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
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3
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Georgiadis F, Larivière S, Glahn D, Hong LE, Kochunov P, Mowry B, Loughland C, Pantelis C, Henskens FA, Green MJ, Cairns MJ, Michie PT, Rasser PE, Catts S, Tooney P, Scott RJ, Schall U, Carr V, Quidé Y, Krug A, Stein F, Nenadić I, Brosch K, Kircher T, Gur R, Gur R, Satterthwaite TD, Karuk A, Pomarol-Clotet E, Radua J, Fuentes-Claramonte P, Salvador R, Spalletta G, Voineskos A, Sim K, Crespo-Facorro B, Tordesillas Gutiérrez D, Ehrlich S, Crossley N, Grotegerd D, Repple J, Lencer R, Dannlowski U, Calhoun V, Rootes-Murdy K, Demro C, Ramsay IS, Sponheim SR, Schmidt A, Borgwardt S, Tomyshev A, Lebedeva I, Höschl C, Spaniel F, Preda A, Nguyen D, Uhlmann A, Stein DJ, Howells F, Temmingh HS, Diaz Zuluaga AM, López Jaramillo C, Iasevoli F, Ji E, Homan S, Omlor W, Homan P, Kaiser S, Seifritz E, Misic B, Valk SL, Thompson P, van Erp TGM, Turner JA, Bernhardt B, Kirschner M. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study. Mol Psychiatry 2024:10.1038/s41380-024-02442-7. [PMID: 38336840 DOI: 10.1038/s41380-024-02442-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/08/2024] [Accepted: 01/18/2024] [Indexed: 02/12/2024]
Abstract
Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.
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Affiliation(s)
- Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland.
| | - Sara Larivière
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - David Glahn
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, US
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, US
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, Australia
| | - Carmel Loughland
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, USA
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, VIC, Australia
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Melissa J Green
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Murray J Cairns
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Patricia T Michie
- School of Psychological Sciences, University of Newcastle, Newcastle, NSW, Australia
| | - Paul E Rasser
- School of Medicine and Public Health, College of Health, Medicine, and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia
| | - Stanley Catts
- Faculty of Medicine, University of Queensland, St Lucia, QLD, Australia
| | - Paul Tooney
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Rodney J Scott
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Vaughan Carr
- School of Clinical Medicine, Discipline of Psychiatry, UNSW Sydney, Sydney, NSW, Australia
| | - Yann Quidé
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Axel Krug
- University Hospital Bonn, Department of Psychiatry and Psychotherapy, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Frederike Stein
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Igor Nenadić
- Department. of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Raquel Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ruben Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | | | - Aristotle Voineskos
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
| | | | - Diana Tordesillas Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
| | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental Neurosciences, Technischen Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Nicolas Crossley
- Department of Psychiatry, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Vince Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Kelly Rootes-Murdy
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Caroline Demro
- University of Minnesota Department of Psychology, Minneapolis, MN, USA
- Minneapolis VA Health Care System, Minneapolis, MN, USA
| | - Ian S Ramsay
- University of Minnesota Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- University of Minnesota Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA
| | - Andre Schmidt
- University of Basel, Department of Psychiatry, Basel, Switzerland
| | | | | | - Irina Lebedeva
- Mental Health Research Center, Moscow, Russian Federation
| | - Cyril Höschl
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Dana Nguyen
- Department of Pediatric Neurology, University of California Irvine, Irvine, CA, USA
| | - Anne Uhlmann
- Department of child and adolescent psychiatry, TU Dresden, Dresden, Germany
| | - Dan J Stein
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Fleur Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Henk S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Ana M Diaz Zuluaga
- Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia
| | - Carlos López Jaramillo
- Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia
| | - Felice Iasevoli
- University of Naples, Department of Neuroscience, Naples, Italy
| | - Ellen Ji
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Bratislav Misic
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - Sofie L Valk
- Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Paul Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Theo G M van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, the Ohio State University, Columbus, OH, USA
| | - Boris Bernhardt
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland.
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland.
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Preller KH, Scholpp J, Wunder A, Rosenbrock H. Neuroimaging Biomarkers for Drug Discovery and Development in Schizophrenia. Biol Psychiatry 2024:S0006-3223(24)00036-2. [PMID: 38272287 DOI: 10.1016/j.biopsych.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/19/2023] [Accepted: 01/14/2024] [Indexed: 01/27/2024]
Abstract
Schizophrenia is a chronic mental illness that affects up to 1% of the population. While efficacious therapies are available for positive symptoms, effective treatment of cognitive and negative symptoms remains an unmet need after decades of research. New developments in the field of neuroimaging are accelerating our knowledge gain regarding the underlying pathophysiology of symptoms in schizophrenia and psychosis spectrum disorders, inspiring new targets for drug development. However, no validated and qualified biomarkers are currently available to support the development of new therapeutics. This review summarizes the current use of neuroimaging technology in clinical drug development for psychotic disorders. As exemplified by drug development programs that target NMDA receptor hypofunction, neuroimaging results play a critical role in target discovery and establishing target engagement and dose selection. Furthermore, pharmacological neuroimaging may provide response biomarkers that allow for early decision making in proof-of-concept studies that leverage pharmacological challenge models in healthy volunteers. That said, while response and predictive biomarkers are starting to be evaluated in patient populations, they continue to play a limited role. Novel approaches to neuroimaging data acquisition and analysis may aid the establishment of biomarkers that are predictive at the individual level in the future. Nevertheless, various gaps in knowledge need to be addressed and biomarkers need to be validated to establish them as "fit for purpose" in drug development.
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Affiliation(s)
- Katrin H Preller
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany; Boehringer Ingelheim (Schweiz) GmbH, Basel, Switzerland.
| | - Joachim Scholpp
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Andreas Wunder
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Holger Rosenbrock
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
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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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McKenna F, Gupta PK, Sui YV, Bertisch H, Gonen O, Goff DC, Lazar M. Microstructural and Microvascular Alterations in Psychotic Spectrum Disorders: A Three-Compartment Intravoxel Incoherent Imaging and Free Water Model. Schizophr Bull 2023; 49:1542-1553. [PMID: 36921060 PMCID: PMC10686346 DOI: 10.1093/schbul/sbad019] [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] [Indexed: 03/18/2023]
Abstract
BACKGROUND AND HYPOTHESIS Microvascular and inflammatory mechanisms have been hypothesized to be involved in the pathophysiology of psychotic spectrum disorders (PSDs). However, data evaluating these hypotheses remain limited. STUDY DESIGN We applied a three-compartment intravoxel incoherent motion free water imaging (IVIM-FWI) technique that estimates the perfusion fraction (PF), free water fraction (FW), and anisotropic diffusion of tissue (FAt) to examine microvascular and microstructural changes in gray and white matter in 55 young adults with a PSD compared to 37 healthy controls (HCs). STUDY RESULTS We found significantly increased PF, FW, and FAt in gray matter regions, and significantly increased PF, FW, and decreased FAt in white matter regions in the PSD group versus HC. Furthermore, in patients, but not in the HC group, increased PF, FW, and FAt in gray matter and increased PF in white matter were significantly associated with poor performance on several cognitive tests assessing memory and processing speed. We additionally report significant associations between IVIM-FWI metrics and myo-inositol, choline, and N-acetylaspartic acid magnetic resonance spectroscopy imaging metabolites in the posterior cingulate cortex, which further supports the validity of PF, FW, and FAt as microvascular and microstructural biomarkers of PSD. Finally, we found significant relationships between IVIM-FWI metrics and the duration of psychosis in gray and white matter regions. CONCLUSIONS The three-compartment IVIM-FWI model provides metrics that are associated with cognitive deficits and may reflect disease progression.
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Affiliation(s)
- Faye McKenna
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Pradeep Kumar Gupta
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Yu Veronica Sui
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Hilary Bertisch
- Northwell Health, Zucker Hillside Hospital, New York, NY, USA
| | - Oded Gonen
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Donald C Goff
- Department of Psychiatry, New York University School of Medicine, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Mariana Lazar
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
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7
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Mosconi MW, Stevens CJ, Unruh KE, Shafer R, Elison JT. Endophenotype trait domains for advancing gene discovery in autism spectrum disorder. J Neurodev Disord 2023; 15:41. [PMID: 37993779 PMCID: PMC10664534 DOI: 10.1186/s11689-023-09511-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 11/09/2023] [Indexed: 11/24/2023] Open
Abstract
Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.
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Affiliation(s)
- Matthew W Mosconi
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA.
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA.
| | - Cassandra J Stevens
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA
| | - Kathryn E Unruh
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
| | - Robin Shafer
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
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8
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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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9
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Molina V, Fernández-Linsenbarth I, Queipo-de-Llano M, Jiménez-Aparicio MT, Vallecillo-Adame C, Aremy-Gonzaga A, de-Andrés-Lobo C, Recio-Barbero M, Díez Á, Beño-Ruiz-de-la-Sierra RM, Martín-Gómez C, Sanz-Fuentenebro J. Real-life outcomes in biotypes of psychotic disorders based on neurocognitive performance. Eur Arch Psychiatry Clin Neurosci 2023; 273:1379-1386. [PMID: 36416961 PMCID: PMC10449979 DOI: 10.1007/s00406-022-01518-1] [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: 05/05/2022] [Accepted: 10/26/2022] [Indexed: 11/24/2022]
Abstract
Aiming at discerning potential biotypes within the psychotic syndrome, we have recently reported the possible existence of two clusters or biotypes across schizophrenia and bipolar disorder characterized by their cognitive performance using the Brief Assessment of Cognition in Schizophrenia (BACS) instrument and validated with independent biological and clinical indexes (Fernández-Linsenbarth et al. in Schizophr Res 229:102-111, 2021). In this previous work, the group with larger cognitive deficits (N = 93, including 69 chronic schizophrenia, 17 first episodes (FE) of schizophrenia and 7 bipolar disorder patients) showed smaller thalamus and hippocampus volume and hyper-synchronic electroencephalogram than the group with milder deficits (N = 105, including 58 chronic schizophrenia, 25 FE and 22 bipolar disorder patients). We predicted that if these biotypes indeed corresponded to different cognitive and biological substrates, their adaptation to real life would be different. To this end, in the present work we have followed up the patients' population included in that work at 1st and 3rd years after the date of inclusion in the 2021 study and we report on the statistical comparisons of each clinical and real-life outcomes between them. The first cluster, with larger cognitive deficits and more severe biological alterations, showed during that period a decreased capacity for job tenure (1st and 3rd years), more admissions to a psychiatric ward (1st year) and a higher likelihood for quitting psychiatric follow-up (3rd year). Patients in the second cluster, with moderate cognitive deficits, were less compliant with prescribed treatment at the 3rd year. The differences in real-life outcomes may give additional external validity to that yielded by biological measurements to the described biotypes based on neurocognition.
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Affiliation(s)
- Vicente Molina
- Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain.
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain.
| | - Inés Fernández-Linsenbarth
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain
| | | | | | | | | | | | | | - Álvaro Díez
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain
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10
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Kesler SR, Henneghan AM, Prinsloo S, Palesh O, Wintermark M. Neuroimaging based biotypes for precision diagnosis and prognosis in cancer-related cognitive impairment. Front Med (Lausanne) 2023; 10:1199605. [PMID: 37720513 PMCID: PMC10499624 DOI: 10.3389/fmed.2023.1199605] [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: 04/03/2023] [Accepted: 08/15/2023] [Indexed: 09/19/2023] Open
Abstract
Cancer related cognitive impairment (CRCI) is commonly associated with cancer and its treatments, yet the present binary diagnostic approach fails to capture the full spectrum of this syndrome. Cognitive function is highly complex and exists on a continuum that is poorly characterized by dichotomous categories. Advanced statistical methodologies applied to symptom assessments have demonstrated that there are multiple subclasses of CRCI. However, studies suggest that relying on symptom assessments alone may fail to account for significant differences in the neural mechanisms that underlie a specific cognitive phenotype. Treatment plans that address the specific physiologic mechanisms involved in an individual patient's condition is the heart of precision medicine. In this narrative review, we discuss how biotyping, a precision medicine framework being utilized in other mental disorders, could be applied to CRCI. Specifically, we discuss how neuroimaging can be used to determine biotypes of CRCI, which allow for increased precision in prediction and diagnosis of CRCI via biologic mechanistic data. Biotypes may also provide more precise clinical endpoints for intervention trials. Biotyping could be made more feasible with proxy imaging technologies or liquid biomarkers. Large cross-sectional phenotyping studies are needed in addition to evaluation of longitudinal trajectories, and data sharing/pooling is highly feasible with currently available digital infrastructures.
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Affiliation(s)
- Shelli R. Kesler
- Division of Adult Health, School of Nursing, The University of Texas at Austin, Austin, TX, United States
- Department of Diagnostic Medicine, Dell School of Medicine, The University of Texas at Austin, Austin, TX, United States
- Department of Oncology, Dell School of Medicine, The University of Texas at Austin, Austin, TX, United States
| | - Ashley M. Henneghan
- Division of Adult Health, School of Nursing, The University of Texas at Austin, Austin, TX, United States
- Department of Oncology, Dell School of Medicine, The University of Texas at Austin, Austin, TX, United States
| | - Sarah Prinsloo
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Oxana Palesh
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
| | - Max Wintermark
- Department of Neuroradiology, The University of Texas MD Anderson Cancer, Houston, TX, United States
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11
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Koen JD, Lewis L, Rugg MD, Clementz BA, Keshavan MS, Pearlson GD, Sweeney JA, Tamminga CA, Ivleva EI. Supervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP). Sci Rep 2023; 13:12980. [PMID: 37563219 PMCID: PMC10415369 DOI: 10.1038/s41598-023-38101-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/03/2023] [Indexed: 08/12/2023] Open
Abstract
Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.
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Affiliation(s)
- Joshua D Koen
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA.
- Department of Psychology, University of Notre Dame, Notre Dame, IN, 46556, USA.
| | - Leslie Lewis
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Michael D Rugg
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
- UT Southwestern Medical Center, Dallas, TX, USA
- University of East Anglia, Norwich, UK
| | | | | | - Godfrey D Pearlson
- Institute of Living, Hartford Hospital, Hartford, CT, USA
- Yale School of Medicine, New Haven, CT, USA
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12
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Misiak B, Samochowiec J, Kowalski K, Gaebel W, Bassetti CLA, Chan A, Gorwood P, Papiol S, Dom G, Volpe U, Szulc A, Kurimay T, Kärkkäinen H, Decraene A, Wisse J, Fiorillo A, Falkai P. The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia. Eur Psychiatry 2023; 66:e58. [PMID: 37476977 PMCID: PMC10486256 DOI: 10.1192/j.eurpsy.2023.2432] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/12/2023] [Accepted: 06/14/2023] [Indexed: 07/22/2023] Open
Abstract
The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries.
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Affiliation(s)
- Błażej Misiak
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland
| | | | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Düsseldorf, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
- WHO Collaborating Centre on Quality Assurance and Empowerment in Mental Health, DEU-131, Düsseldorf, Germany
| | - Claudio L. A. Bassetti
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Switzerland
- Interdisciplinary Sleep-Wake-Epilepsy-Center, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Andrew Chan
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Switzerland
| | - Philip Gorwood
- Université Paris Cité, INSERM, U1266 (Institute of Psychiatry and Neuroscience of Paris), Paris, France
- CMME, GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte-Anne, Paris, France
| | - Sergi Papiol
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University, Munich, Germany
| | - Geert Dom
- Collaborative Antwerp Psychiatric Research Institute, University of Antwerp, B-2610Antwerp, Belgium
- Multiversum Psychiatric Hospital, B-2530Boechout, Belgium
| | - Umberto Volpe
- Unit of Clinical Psychiatry, Department of Clinical Neurosciences/DIMSC, Polytechnic University of Marche, 60126Ancona, Italy
| | - Agata Szulc
- Department of Psychiatry, Medical University of Warsaw, Warsaw, Poland
| | - Tamas Kurimay
- Department of Psychiatry, St. Janos Hospital, Budapest, Hungary
| | | | - Andre Decraene
- European Federation of Associations of Families of People with Mental Illness (EUFAMI), Leuven, Belgium
| | - Jan Wisse
- Century House, Wargrave Road, Henley-on-Thames, OxfordshireRG9 2LT, UK
| | - Andrea Fiorillo
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336Munich, Germany
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13
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Szocsics P, Papp P, Havas L, Lőke J, Maglóczky Z. Interhemispheric differences of pyramidal cells in the primary motor cortices of schizophrenia patients investigated postmortem. Cereb Cortex 2023; 33:8179-8193. [PMID: 36967112 PMCID: PMC10321096 DOI: 10.1093/cercor/bhad107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 07/20/2023] Open
Abstract
Motor disturbances are observed in schizophrenia patients, but the neuroanatomical background is unknown. Our aim was to investigate the pyramidal cells of the primary motor cortex (BA 4) in both hemispheres of postmortem control and schizophrenia subjects-8 subjects in each group-with 2.5-5.5 h postmortem interval. The density and size of the Sternberger monoclonal incorporated antibody 32 (SMI32)-immunostained pyramidal cells in layer 3 and 5 showed no change; however, the proportion of larger pyramidal cells is decreased in layer 5. Giant pyramidal neurons (Betz cells) were investigated distinctively with SMI32- and parvalbumin (PV) immunostainings. In the right hemisphere of schizophrenia subjects, the density of Betz cells was decreased and their PV-immunopositive perisomatic input showed impairment. Part of the Betz cells contained PV in both groups, but the proportion of PV-positive cells has declined with age. The rat model of antipsychotic treatment with haloperidol and olanzapine showed no differences in size and density of SMI32-immunopositive pyramidal cells. Our results suggest that motor impairment of schizophrenia patients may have a morphological basis involving the Betz cells in the right hemisphere. These alterations can have neurodevelopmental and neurodegenerative explanations, but antipsychotic treatment does not explain them.
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Affiliation(s)
- Péter Szocsics
- Human Brain Research Laboratory, Institute of Experimental Medicine, ELKH, Budapest 1083, Hungary
- János Szentágothai Doctoral School of Neuroscience, Semmelweis University, Budapest 1085, Hungary
| | - Péter Papp
- Cerebral Cortex Research Group, Institute of Experimental Medicine, ELKH, Budapest 1083, Hungary
| | - László Havas
- Department of Pathology, Szt. Borbála Hospital, Tatabánya 2800, Hungary
- Department of Psychiatry, Szt. Borbála Hospital, Tatabánya 2800, Hungary
| | - János Lőke
- Department of Psychiatry, Szt. Borbála Hospital, Tatabánya 2800, Hungary
| | - Zsófia Maglóczky
- Human Brain Research Laboratory, Institute of Experimental Medicine, ELKH, Budapest 1083, Hungary
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14
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Percie du Sert O, Unrau J, Gauthier CJ, Chakravarty M, Malla A, Lepage M, Raucher-Chéné D. Cerebral blood flow in schizophrenia: A systematic review and meta-analysis of MRI-based studies. Prog Neuropsychopharmacol Biol Psychiatry 2023; 121:110669. [PMID: 36341843 DOI: 10.1016/j.pnpbp.2022.110669] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 10/19/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Schizophrenia-spectrum disorders (SSD) represent one of the leading causes of disability worldwide and are usually underpinned by neurodevelopmental brain abnormalities observed on a structural and functional level. Nuclear medicine imaging studies of cerebral blood flow (CBF) have already provided insights into the pathophysiology of these disorders. Recent developments in non-invasive MRI techniques such as arterial spin labeling (ASL) have allowed broader examination of CBF across SSD prompting us to conduct an updated literature review of MRI-based perfusion studies. In addition, we conducted a focused meta-analysis of whole brain studies to provide a complete picture of the literature on the topic. METHODS A systematic OVID search was performed in Embase, MEDLINEOvid, and PsycINFO. Studies eligible for inclusion in the review involved: 1) individuals with SSD, first-episode psychosis or clinical-high risk for psychosis, or; 2) had healthy controls for comparison; 3) involved MRI-based perfusion imaging methods; and 4) reported CBF findings. No time span was specified for the database queries (last search: 08/2022). Information related to participants, MRI techniques, CBF analyses, and results were systematically extracted. Whole-brain studies were then selected for the meta-analysis procedure. The methodological quality of each included studies was assessed. RESULTS For the systematic review, the initial Ovid search yielded 648 publications of which 42 articles were included, representing 3480 SSD patients and controls. The most consistent finding was that negative symptoms were linked to cortical fronto-limbic hypoperfusion while positive symptoms seemed to be associated with hyperperfusion, notably in subcortical structures. The meta-analysis integrated results from 13 whole-brain studies, across 426 patients and 401 controls, and confirmed the robustness of the hypoperfusion in the left superior and middle frontal gyri and right middle occipital gyrus while hyperperfusion was found in the left putamen. CONCLUSION This updated review of the literature supports the implication of hemodynamic correlates in the pathophysiology of psychosis symptoms and disorders. A more systematic exploration of brain perfusion could complete the search of a multimodal biomarker of SSD.
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Affiliation(s)
- Olivier Percie du Sert
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Joshua Unrau
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Claudine J Gauthier
- Concordia University, Montreal, QC, Canada; Montreal Heart Institute, Montreal, QC, Canada
| | - Mallar Chakravarty
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Ashok Malla
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Martin Lepage
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada.
| | - Delphine Raucher-Chéné
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada; University of Reims Champagne-Ardenne, Cognition, Health, and Society Laboratory (EA 6291), Reims, France; Academic Department of Psychiatry, University Hospital of Reims, EPSM Marne, Reims, France
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15
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Shang MY, Zhang CY, Wu Y, Wang L, Wang C, Li M. Genetic associations between bipolar disorder and brain structural phenotypes. Cereb Cortex 2023:7024717. [PMID: 36734292 DOI: 10.1093/cercor/bhad014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/12/2023] [Accepted: 01/13/2023] [Indexed: 02/04/2023] Open
Abstract
Patients with bipolar disorder (BD) and their first-degree relatives exhibit alterations in brain volume and cortical structure, whereas the underlying genetic mechanisms remain unclear. In this study, based on the published genome-wide association studies (GWAS), the extent of polygenic overlap between BD and 15 brain structural phenotypes was investigated using linkage disequilibrium score regression and MiXeR tool, and the shared genomic loci were discovered by conjunctional false discovery rate (conjFDR) and expression quantitative trait loci (eQTL) analyses. MiXeR estimated the overall measure of polygenic overlap between BD and brain structural phenotypes as 4-53% on a 0-100% scale (as quantified by the Dice coefficient). Subsequent conjFDR analyses identified 54 independent loci (71 risk single-nucleotide polymorphisms) jointly associated with BD and brain structural phenotypes with a conjFDR < 0.05, among which 33 were novel that had not been reported in the previous BD GWAS. Follow-up eQTL analyses in respective brain regions both confirmed well-known risk genes (e.g. CACNA1C, NEK4, GNL3, MAPK3) and discovered novel risk genes (e.g. LIMK2 and CAMK2N2). This study indicates a substantial shared genetic basis between BD and brain structural phenotypes, and provides novel insights into the developmental origin of BD and related biological mechanisms.
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Affiliation(s)
- Meng-Yuan Shang
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, 818 Fenghua Road, Ningbo, 315211, Zhejiang, China.,School of Basic Medical Science, School of Medicine, Ningbo University, 818 Fenghua Road, Ningbo, 315211, Zhejiang, China
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, No. 17 Long-Xin Lu, Kunming, 650201, Yunnan, China
| | - Yong Wu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, No. 920 Jianshe Road, Wuhan, 430012, Hubei, China
| | - Lu Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, No. 17 Long-Xin Lu, Kunming, 650201, Yunnan, China
| | - Chuang Wang
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, 818 Fenghua Road, Ningbo, 315211, Zhejiang, China.,School of Basic Medical Science, School of Medicine, Ningbo University, 818 Fenghua Road, Ningbo, 315211, Zhejiang, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, No. 17 Long-Xin Lu, Kunming, 650201, Yunnan, China
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16
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Kishimoto T, Nakamura H, Kano Y, Eguchi Y, Kitazawa M, Liang KC, Kudo K, Sento A, Takamiya A, Horigome T, Yamasaki T, Sunami Y, Kikuchi T, Nakajima K, Tomita M, Bun S, Momota Y, Sawada K, Murakami J, Takahashi H, Mimura M. Understanding psychiatric illness through natural language processing (UNDERPIN): Rationale, design, and methodology. Front Psychiatry 2022; 13:954703. [PMID: 36532181 PMCID: PMC9752868 DOI: 10.3389/fpsyt.2022.954703] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 11/11/2022] [Indexed: 12/04/2022] Open
Abstract
Introduction Psychiatric disorders are diagnosed through observations of psychiatrists according to diagnostic criteria such as the DSM-5. Such observations, however, are mainly based on each psychiatrist's level of experience and often lack objectivity, potentially leading to disagreements among psychiatrists. In contrast, specific linguistic features can be observed in some psychiatric disorders, such as a loosening of associations in schizophrenia. Some studies explored biomarkers, but biomarkers have yet to be used in clinical practice. Aim The purposes of this study are to create a large dataset of Japanese speech data labeled with detailed information on psychiatric disorders and neurocognitive disorders to quantify the linguistic features of those disorders using natural language processing and, finally, to develop objective and easy-to-use biomarkers for diagnosing and assessing the severity of them. Methods This study will have a multi-center prospective design. The DSM-5 or ICD-11 criteria for major depressive disorder, bipolar disorder, schizophrenia, and anxiety disorder and for major and minor neurocognitive disorders will be regarded as the inclusion criteria for the psychiatric disorder samples. For the healthy subjects, the absence of a history of psychiatric disorders will be confirmed using the Mini-International Neuropsychiatric Interview (M.I.N.I.). The absence of current cognitive decline will be confirmed using the Mini-Mental State Examination (MMSE). A psychiatrist or psychologist will conduct 30-to-60-min interviews with each participant; these interviews will include free conversation, picture-description task, and story-telling task, all of which will be recorded using a microphone headset. In addition, the severity of disorders will be assessed using clinical rating scales. Data will be collected from each participant at least twice during the study period and up to a maximum of five times at an interval of at least one month. Discussion This study is unique in its large sample size and the novelty of its method, and has potential for applications in many fields. We have some challenges regarding inter-rater reliability and the linguistic peculiarities of Japanese. As of September 2022, we have collected a total of >1000 records from >400 participants. To the best of our knowledge, this data sample is one of the largest in this field. Clinical Trial Registration Identifier: UMIN000032141.
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Affiliation(s)
- Taishiro Kishimoto
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
- Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, Keio University School of Medicine, Tokyo, Japan
| | - Hironobu Nakamura
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshinobu Kano
- Faculty of Informatics, Shizuoka University, Shizuoka, Japan
| | - Yoko Eguchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Momoko Kitazawa
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kuo-ching Liang
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Koki Kudo
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
- Department of Neuropsychiatry, St. Marianna University School of Medicine Hospital, Kawasaki, Japan
| | - Ayako Sento
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Akihiro Takamiya
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Toshiro Horigome
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Toshihiko Yamasaki
- Computer Vision and Media Lab (Yamasaki Lab), Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Yuki Sunami
- Keio University School of Medicine, Tokyo, Japan
| | - Toshiaki Kikuchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kazuki Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | | | - Shogyoku Bun
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
- Department of Psychiatry, Koutokukai Sato Hospital, Yamagata, Japan
| | - Yuki Momota
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kyosuke Sawada
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | | | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
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17
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Zhao Q, Cao H, Zhang W, Li S, Xiao Y, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Hill SK, Keedy SK, Ivleva EI, Lencer R, Sweeney JA, Gong Q, Lui S. A subtype of institutionalized patients with schizophrenia characterized by pronounced subcortical and cognitive deficits. Neuropsychopharmacology 2022; 47:2024-2032. [PMID: 35260788 PMCID: PMC9556672 DOI: 10.1038/s41386-022-01300-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 01/28/2022] [Accepted: 02/19/2022] [Indexed: 02/05/2023]
Abstract
Some patients with schizophrenia have severe cognitive impairment and functional deficits that require long-term institutional care. The patterns of brain-behavior alterations in these individuals, and their differences from patients living successfully in the community, remain poorly understood. Previous cognition-based studies for stratifying schizophrenia patients highlight the importance of subcortical structures in the context of illness heterogeneity. In the present study, subcortical volumes from 96 institutionalized patients with long-term schizophrenia were evaluated using cluster analysis to test for heterogeneity. These data were compared to those from two groups of community-dwelling individuals with schizophrenia for comparison purposes, including 68 long-term ill and 126 first-episode individuals. A total of 290 demographically matched healthy participants were included as normative references at a 1:1 ratio for each patient sample. A subtype of institutionalized patients was identified based on their pattern of subcortical alterations. Using a machine learning algorithm developed to discriminate the two groups of institutionalized patients, all three patient samples were found to have similar rates of patients assigned to the two subtypes (approximately 50% each). In institutionalized patients, only the subtype with the identified pattern of subcortical alterations had greater neocortical and cognitive abnormalities than those in the similarity classified community-dwelling patients with long-term illness. Thus, for the subtype of patients with a distinctive pattern of subcortical alterations, when the distinct pattern of subcortical alterations is present and particularly severe, it is associated with cognitive impairments that may contribute to persistent disability and institutionalization.
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Affiliation(s)
- Qiannan Zhao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Hengyi Cao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Wenjing Zhang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Siyi Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Yuan Xiao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, 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 Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Scot Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
| | - Su Lui
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
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18
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Regional and Sex-Specific Alterations in the Visual Cortex of Individuals With Psychosis Spectrum Disorders. Biol Psychiatry 2022; 92:396-406. [PMID: 35688762 DOI: 10.1016/j.biopsych.2022.03.023] [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: 11/04/2021] [Revised: 03/10/2022] [Accepted: 03/29/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Impairments of the visual system are implicated in psychotic disorders. However, studies exploring visual cortex (VC) morphology in this population are limited. Using data from the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium, we examined VC structure in psychosis probands and their first-degree relatives (RELs), sex differences in VC measures, and their relationships with cognitive and peripheral inflammatory markers. METHODS Cortical thickness, surface area, and volume of the primary (Brodmann area 17/V1) and secondary (Brodmann area 18/V2) visual areas and the middle temporal (V5/MT) region were quantified using FreeSurfer version 6.0 in psychosis probands (n = 530), first-degree RELs (n = 544), and healthy control subjects (n = 323). Familiality estimates were determined for probands and RELs. General cognition, response inhibition, and emotion recognition functions were assessed. Systemic inflammation was measured in a subset of participants. RESULTS Psychosis probands demonstrated significant area, thickness, and volume reductions in V1, V2, and MT, and their first-degree RELs demonstrated area and volume reductions in MT compared with control subjects. There was a higher degree of familiality for VC area than thickness. Area and volume reductions in V1 and V2 were sex dependent, affecting only female probands in a regionally specific manner. Reductions in some VC regions were correlated with poor general cognition, worse response inhibition, and increased C-reactive protein levels. CONCLUSIONS The visual cortex is a site of significant pathology in psychotic disorders, with distinct patterns of area and thickness changes, sex-specific and regional effects, potential contributions to cognitive impairments, and association with C-reactive protein levels.
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19
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Bari S, Vike NL, Stetsiv K, Woodward S, Lalvani S, Stefanopoulos L, Kim BW, Maglaveras N, Breiter HC, Katsaggelos AK. The Prevalence of Psychotic Symptoms, Violent Ideation, and Disruptive Behavior in a Population With SARS-CoV-2 Infection: Preliminary Study. JMIR Form Res 2022; 6:e36444. [PMID: 35763758 PMCID: PMC9384857 DOI: 10.2196/36444] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 04/06/2022] [Accepted: 05/14/2022] [Indexed: 11/26/2022] Open
Abstract
Background The COVID-19 disease results from infection by the SARS-CoV-2 virus to produce a range of mild to severe physical, neurological, and mental health symptoms. The COVID-19 pandemic has indirectly caused significant emotional distress, triggering the emergence of mental health symptoms in individuals who were not previously affected or exacerbating symptoms in those with existing mental health conditions. Emotional distress and certain mental health conditions can lead to violent ideation and disruptive behavior, including aggression, threatening acts, deliberate harm toward other people or animals, and inattention to or noncompliance with education or workplace rules. Of the many mental health conditions that can be associated with violent ideation and disruptive behavior, psychosis can evidence greater vulnerability to unpredictable changes and being at a greater risk for them. Individuals with psychosis can also be more susceptible to contracting COVID-19 disease. Objective This study aimed to investigate whether violent ideation, disruptive behavior, or psychotic symptoms were more prevalent in a population with COVID-19 and did not precede the pandemic. Methods In this preliminary study, we analyzed questionnaire responses from a population sample (N=366), received between the end of February 2021 and the start of March 2021 (1 year into the COVID-19 pandemic), regarding COVID-19 illness, violent ideation, disruptive behavior, and psychotic symptoms. Using the Wilcoxon rank sum test followed by multiple comparisons correction, we compared the self-reported frequency of these variables for 3 time windows related to the past 1 month, past 1 month to 1 year, and >1 year ago among the distributions of people who answered whether they tested positive or were diagnosed with COVID-19 by a clinician. We also used multivariable logistic regression with iterative resampling to investigate the relationship between these variables occurring >1 year ago (ie, before the pandemic) and the likelihood of contracting COVID-19. Results We observed a significantly higher frequency of self-reported violent ideation, disruptive behavior, and psychotic symptoms, for all 3 time windows of people who tested positive or were diagnosed with COVID-19 by a clinician. Using multivariable logistic regression, we observed 72% to 94% model accuracy for an increased incidence of COVID-19 in participants who reported violent ideation, disruptive behavior, or psychotic symptoms >1 year ago. Conclusions This preliminary study found that people who reported a test or clinician diagnosis of COVID-19 also reported higher frequencies of violent ideation, disruptive behavior, or psychotic symptoms across multiple time windows, indicating that they were not likely to be the result of COVID-19. In parallel, participants who reported these behaviors >1 year ago (ie, before the pandemic) were more likely to be diagnosed with COVID-19, suggesting that violent ideation, disruptive behavior, in addition to psychotic symptoms, were associated with COVID-19 with an approximately 70% to 90% likelihood.
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Affiliation(s)
- Sumra Bari
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Nicole L Vike
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Khrystyna Stetsiv
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Sean Woodward
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Shamal Lalvani
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | - Leandros Stefanopoulos
- Laboratory of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Byoung Woo Kim
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Nicos Maglaveras
- Laboratory of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Hans C Breiter
- Laboratory of Neuroimaging and Genetics, Division of Psychiatric Neuroscience, Massachusetts General Hospital, Charlestown, MA, United States
| | - Aggelos K Katsaggelos
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
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20
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Zeng J, Zhang W, Wu G, Wang X, Shah C, Li S, Xiao Y, Yao L, Cao H, Li Z, Sweeney JA, Lui S, Gong Q. Effects of Antipsychotic Medications and Illness Duration on Brain Features That Distinguish Schizophrenia Patients. Schizophr Bull 2022; 48:1354-1362. [PMID: 35925035 PMCID: PMC9673268 DOI: 10.1093/schbul/sbac094] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Previous studies have reported effects of antipsychotic treatment and illness duration on brain features. This study used a machine learning approach to examine whether these factors in aggregate impacted the utility of MRI features for differentiating individual schizophrenia patients from healthy controls. STUDY DESIGN This case-control study used patients with never-treated first-episode schizophrenia (FES, n = 179) and long-term ill schizophrenia (LTSZ, n = 30), with follow-up of the FES group after treatment (n = 71), a group of patients who had received long-term antipsychotic treatment (n = 93) and age and sex-matched healthy controls (n = 373) for each patient group. A multiple kernel learning classifier combining both structural and functional brain features was used to discriminate individual patients from controls. STUDY RESULTS MRI features differentiated untreated FES (0.73) and LTSZ (0.83) patients from healthy controls with moderate accuracy, but accuracy was significantly higher in antipsychotic-treated FES (0.94) and LTSZ (0.98) patients. Treatment was associated with significantly increased accuracy of case identification in both early course and long-term ill patients (both p < .001). Effects of illness duration, examined separately in treated and untreated patients, were less robust. CONCLUSIONS Our results demonstrate that initiation of antipsychotic treatment alters brain features in ways that further distinguish individual schizophrenia patients from healthy individuals, and have a modest effect of illness duration. Intrinsic illness-related brain alterations in untreated patients, regardless of illness duration, are not sufficiently robust for accurate identification of schizophrenia patients.
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Affiliation(s)
| | | | - Guorong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China
| | - Xiaowan Wang
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China
| | - Chandan Shah
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Siyi Li
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Li Yao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China,Center for Psychiatry Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA,Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Zhenlin Li
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Su Lui
- To whom correspondence should be addressed; Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China, tel/fax: +86-28-85423960; e-mail:
| | - Qiyong Gong
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China,Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
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21
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Markers of Schizophrenia—A Critical Narrative Update. J Clin Med 2022; 11:jcm11143964. [PMID: 35887728 PMCID: PMC9323796 DOI: 10.3390/jcm11143964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/04/2022] [Accepted: 07/05/2022] [Indexed: 12/17/2022] Open
Abstract
Schizophrenia is a long-term mental disease, associated with functional impairment. Therefore, it is important to make an accurate diagnosis and implement the proper treatment. Biomarkers may be a potential tool for these purposes. Regarding advances in biomarker studies in psychosis, the current symptom-based criteria seem to be no longer sufficient in clinical settings. This narrative review describes biomarkers of psychosis focusing on the biochemical (peripheral and central), neurophysiological, neuropsychological and neuroimaging findings as well as the multimodal approach related with them. Endophenotype markers (especially neuropsychological and occulomotor disturbances) can be currently used in a clinical settings, whereas neuroimaging glutamate/glutamine and D2/D3 receptor density changes, as well as immunological Th2 and PRL levels, seem to be potential biomarkers that need further accuracy tests. When searching for biochemical/immunological markers in the diagnosis of psychosis, the appropriate time of body fluid collection needs to be considered to minimize the influence of the stress axis on their concentrations. In schizophrenia diagnostics, a multimodal approach seems to be highly recommended.
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22
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Yanagi M, Tsuchiya A, Hosomi F, Terada T, Ozaki S, Shirakawa O, Hashimoto M. Evaluating delay of gamma oscillations in patients with schizophrenia using evoked response audiometry system. Sci Rep 2022; 12:11327. [PMID: 35790750 PMCID: PMC9256618 DOI: 10.1038/s41598-022-15311-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/22/2022] [Indexed: 11/11/2022] Open
Abstract
Impaired gamma oscillations found in a 40-Hz auditory steady-state response (ASSR) in patients with schizophrenia are the robust findings that can be used for future biomarker-based therapeutics. To apply these significant observations into the clinical practice, a clinical system for evoked response audiometry (ERA) may be available. In this study, the delayed 40-Hz ASSR, which was reported as a potent biomarker for schizophrenia, was examined using the ERA system in patients with schizophrenia and its clinical relevance was investigated. The phase of ASSR was significantly delayed in patients with schizophrenia compared with the healthy subjects. The delayed phase was associated with severity of the disease symptoms in the patients. A phase delay with aging was found in healthy subjects, but not in patients with schizophrenia. These findings show availability of the ERA system to identify the delayed 40-Hz ASSR and its clinical implication in patients with schizophrenia. Further applications of the ERA system in clinical psychiatry are warranted in developing biological assessments of schizophrenia with 40-Hz ASSR.
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Affiliation(s)
- Masaya Yanagi
- Department of Neuropsychiatry, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-sayama, Osaka, 589-8511, Japan.
| | - Aki Tsuchiya
- Department of Neuropsychiatry, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-sayama, Osaka, 589-8511, Japan
| | - Fumiharu Hosomi
- Department of Neuropsychiatry, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-sayama, Osaka, 589-8511, Japan
| | - Toru Terada
- Department of Neuropsychiatry, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-sayama, Osaka, 589-8511, Japan
| | | | - Osamu Shirakawa
- Department of Neuropsychiatry, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-sayama, Osaka, 589-8511, Japan
| | - Mamoru Hashimoto
- Department of Neuropsychiatry, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-sayama, Osaka, 589-8511, Japan
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23
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Wada M, Noda Y, Iwata Y, Tsugawa S, Yoshida K, Tani H, Hirano Y, Koike S, Sasabayashi D, Katayama H, Plitman E, Ohi K, Ueno F, Caravaggio F, Koizumi T, Gerretsen P, Suzuki T, Uchida H, Müller DJ, Mimura M, Remington G, Grace AA, Graff-Guerrero A, Nakajima S. Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment. Mol Psychiatry 2022; 27:2950-2967. [PMID: 35444257 DOI: 10.1038/s41380-022-01572-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/31/2022] [Accepted: 04/07/2022] [Indexed: 12/13/2022]
Abstract
Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.
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Affiliation(s)
- Masataka Wada
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Kazunari Yoshida
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Hideaki Tani
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan.,Neural Dynamics Laboratory, Research Service, VA Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Haruyuki Katayama
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Eric Plitman
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Fumihiko Ueno
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Fernando Caravaggio
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Teruki Koizumi
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Department of Psychiatry, National Hospital Organization Shimofusa Psychiatric Medical Center, Chiba, Japan
| | - Philip Gerretsen
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Takefumi Suzuki
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Daniel J Müller
- Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Anthony A Grace
- Departments of Neuroscience, Psychiatry and Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ariel Graff-Guerrero
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan. .,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
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24
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McCarthy MJ, Gottlieb JF, Gonzalez R, McClung CA, Alloy LB, Cain S, Dulcis D, Etain B, Frey BN, Garbazza C, Ketchesin KD, Landgraf D, Lee H, Marie‐Claire C, Nusslock R, Porcu A, Porter R, Ritter P, Scott J, Smith D, Swartz HA, Murray G. Neurobiological and behavioral mechanisms of circadian rhythm disruption in bipolar disorder: A critical multi-disciplinary literature review and agenda for future research from the ISBD task force on chronobiology. Bipolar Disord 2022; 24:232-263. [PMID: 34850507 PMCID: PMC9149148 DOI: 10.1111/bdi.13165] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
AIM Symptoms of bipolar disorder (BD) include changes in mood, activity, energy, sleep, and appetite. Since many of these processes are regulated by circadian function, circadian rhythm disturbance has been examined as a biological feature underlying BD. The International Society for Bipolar Disorders Chronobiology Task Force (CTF) was commissioned to review evidence for neurobiological and behavioral mechanisms pertinent to BD. METHOD Drawing upon expertise in animal models, biomarkers, physiology, and behavior, CTF analyzed the relevant cross-disciplinary literature to precisely frame the discussion around circadian rhythm disruption in BD, highlight key findings, and for the first time integrate findings across levels of analysis to develop an internally consistent, coherent theoretical framework. RESULTS Evidence from multiple sources implicates the circadian system in mood regulation, with corresponding associations with BD diagnoses and mood-related traits reported across genetic, cellular, physiological, and behavioral domains. However, circadian disruption does not appear to be specific to BD and is present across a variety of high-risk, prodromal, and syndromic psychiatric disorders. Substantial variability and ambiguity among the definitions, concepts and assumptions underlying the research have limited replication and the emergence of consensus findings. CONCLUSIONS Future research in circadian rhythms and its role in BD is warranted. Well-powered studies that carefully define associations between BD-related and chronobiologically-related constructs, and integrate across levels of analysis will be most illuminating.
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Affiliation(s)
- Michael J. McCarthy
- UC San Diego Department of Psychiatry & Center for Circadian BiologyLa JollaCaliforniaUSA
- VA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - John F. Gottlieb
- Department of PsychiatryFeinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Robert Gonzalez
- Department of Psychiatry and Behavioral HealthPennsylvania State UniversityHersheyPennsylvaniaUSA
| | - Colleen A. McClung
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Lauren B. Alloy
- Department of PsychologyTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Sean Cain
- School of Psychological Sciences and Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
| | - Davide Dulcis
- UC San Diego Department of Psychiatry & Center for Circadian BiologyLa JollaCaliforniaUSA
| | - Bruno Etain
- Université de ParisINSERM UMR‐S 1144ParisFrance
| | - Benicio N. Frey
- Department Psychiatry and Behavioral NeuroscienceMcMaster UniversityHamiltonOntarioCanada
| | - Corrado Garbazza
- Centre for ChronobiologyPsychiatric Hospital of the University of Basel and Transfaculty Research Platform Molecular and Cognitive NeurosciencesUniversity of BaselBaselSwitzerland
| | - Kyle D. Ketchesin
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Dominic Landgraf
- Circadian Biology GroupDepartment of Molecular NeurobiologyClinic of Psychiatry and PsychotherapyUniversity HospitalLudwig Maximilian UniversityMunichGermany
| | - Heon‐Jeong Lee
- Department of Psychiatry and Chronobiology InstituteKorea UniversitySeoulSouth Korea
| | | | - Robin Nusslock
- Department of Psychology and Institute for Policy ResearchNorthwestern UniversityChicagoIllinoisUSA
| | - Alessandra Porcu
- UC San Diego Department of Psychiatry & Center for Circadian BiologyLa JollaCaliforniaUSA
| | | | - Philipp Ritter
- Clinic for Psychiatry and PsychotherapyCarl Gustav Carus University Hospital and Technical University of DresdenDresdenGermany
| | - Jan Scott
- Institute of NeuroscienceNewcastle UniversityNewcastleUK
| | - Daniel Smith
- Division of PsychiatryUniversity of EdinburghEdinburghUK
| | - Holly A. Swartz
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Greg Murray
- Centre for Mental HealthSwinburne University of TechnologyMelbourneVictoriaAustralia
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25
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Di Biase MA, Geaghan MP, Reay WR, Seidlitz J, Weickert CS, Pébay A, Green MJ, Quidé Y, Atkins JR, Coleman MJ, Bouix S, Knyazhanskaya EE, Lyall AE, Pasternak O, Kubicki M, Rathi Y, Visco A, Gaunnac M, Lv J, Mesholam-Gately RI, Lewandowski KE, Holt DJ, Keshavan MS, Pantelis C, Öngür D, Breier A, Cairns MJ, Shenton ME, Zalesky A. Cell type-specific manifestations of cortical thickness heterogeneity in schizophrenia. Mol Psychiatry 2022; 27:2052-2060. [PMID: 35145230 PMCID: PMC9126812 DOI: 10.1038/s41380-022-01460-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 01/06/2022] [Accepted: 01/20/2022] [Indexed: 12/16/2022]
Abstract
Brain morphology differs markedly between individuals with schizophrenia, but the cellular and genetic basis of this heterogeneity is poorly understood. Here, we sought to determine whether cortical thickness (CTh) heterogeneity in schizophrenia relates to interregional variation in distinct neural cell types, as inferred from established gene expression data and person-specific genomic variation. This study comprised 1849 participants in total, including a discovery (140 cases and 1267 controls) and a validation cohort (335 cases and 185 controls). To characterize CTh heterogeneity, normative ranges were established for 34 cortical regions and the extent of deviation from these ranges was measured for each individual with schizophrenia. CTh deviations were explained by interregional gene expression levels of five out of seven neural cell types examined: (1) astrocytes; (2) endothelial cells; (3) oligodendrocyte progenitor cells (OPCs); (4) excitatory neurons; and (5) inhibitory neurons. Regional alignment between CTh alterations with cell type transcriptional maps distinguished broad patient subtypes, which were validated against genomic data drawn from the same individuals. In a predominantly neuronal/endothelial subtype (22% of patients), CTh deviations covaried with polygenic risk for schizophrenia (sczPRS) calculated specifically from genes marking neuronal and endothelial cells (r = -0.40, p = 0.010). Whereas, in a predominantly glia/OPC subtype (43% of patients), CTh deviations covaried with sczPRS calculated from glia and OPC-linked genes (r = -0.30, p = 0.028). This multi-scale analysis of genomic, transcriptomic, and brain phenotypic data may indicate that CTh heterogeneity in schizophrenia relates to inter-individual variation in cell-type specific functions. Decomposing heterogeneity in relation to cortical cell types enables prioritization of schizophrenia subsets for future disease modeling efforts.
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Affiliation(s)
- Maria A Di Biase
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Michael P Geaghan
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - William R Reay
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Cynthia Shannon Weickert
- Neuroscience Research Australia, Randwick, NSW, Australia
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, NY, USA
| | - Alice Pébay
- Department of Anatomy and Physiology, School of Biomedical Sciences, The University of Melbourne, Melbourne, VIC, Australia
- Department of Surgery, Royal Melbourne Hospital, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia
| | - Melissa J Green
- Neuroscience Research Australia, Randwick, NSW, Australia
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Yann Quidé
- Neuroscience Research Australia, Randwick, NSW, Australia
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Joshua R Atkins
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Michael J Coleman
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew Visco
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Megan Gaunnac
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jinglei Lv
- School of Biomedical Engineering & Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
| | | | - Kathryn E Lewandowski
- Division of Psychotic Disorders, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Daphne J Holt
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Matcheri S Keshavan
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Dost Öngür
- Division of Psychotic Disorders, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Alan Breier
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, VIC, Australia
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26
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Hollunder B, Rajamani N, Siddiqi SH, Finke C, Kühn AA, Mayberg HS, Fox MD, Neudorfer C, Horn A. Toward personalized medicine in connectomic deep brain stimulation. Prog Neurobiol 2022; 210:102211. [PMID: 34958874 DOI: 10.1016/j.pneurobio.2021.102211] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/15/2021] [Accepted: 12/22/2021] [Indexed: 02/08/2023]
Abstract
At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.
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Affiliation(s)
- Barbara Hollunder
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.
| | - Nanditha Rajamani
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Carsten Finke
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andrea A Kühn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA
| | - Clemens Neudorfer
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andreas Horn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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27
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Cearns M, Amare AT, Schubert KO, Thalamuthu A, Frank J, Streit F, Adli M, Akula N, Akiyama K, Ardau R, Arias B, Aubry JM, Backlund L, Bhattacharjee AK, Bellivier F, Benabarre A, Bengesser S, Biernacka JM, Birner A, Brichant-Petitjean C, Cervantes P, Chen HC, Chillotti C, Cichon S, Cruceanu C, Czerski PM, Dalkner N, Dayer A, Degenhardt F, Zompo MD, DePaulo JR, Étain B, Falkai P, Forstner AJ, Frisen L, Frye MA, Fullerton JM, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Hashimoto R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hofmann A, Hou L, Hsu YH, Jamain S, Jiménez E, Kahn JP, Kassem L, Kuo PH, Kato T, Kelsoe J, Kittel-Schneider S, Kliwicki S, König B, Kusumi I, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Maj M, Manchia M, Martinsson L, McCarthy MJ, McElroy S, Colom F, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Nöthen MM, Novák T, O'Donovan C, Ozaki N, Millischer V, Papiol S, Pfennig A, Pisanu C, Potash JB, Reif A, Reininghaus E, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schweizer BW, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Tekola-Ayele F, Tortorella A, Turecki G, Veeh J, Vieta E, Witt SH, Roberts G, Zandi PP, Alda M, Bauer M, McMahon FJ, Mitchell PB, Schulze TG, Rietschel M, Clark SR, Baune BT. Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach. Br J Psychiatry 2022; 220:1-10. [PMID: 35225756 DOI: 10.1192/bjp.2022.28] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
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Affiliation(s)
- Micah Cearns
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Australia
| | - Azmeraw T Amare
- South Australian Academic Health Science and Translation Centre, South Australian Health and Medical Research Institute (SAHMRI), Australia and Program for Quantitative Genomics, Harvard School of Public Health, USA
| | - Klaus Oliver Schubert
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Australia and Northern Adelaide Local Health Network, Mental Health Services, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Australia
| | - Joseph Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Mazda Adli
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Charité Mitte, Germany
| | - Nirmala Akula
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, USA
| | - Kazufumi Akiyama
- Department of Biological Psychiatry and Neuroscience, Dokkyo Medical University School of Medicine, Japan
| | - Raffaella Ardau
- Unit of Clinical Pharmacology, Hospital University Agency of Cagliari, Italy
| | - Bárbara Arias
- Unitat de Zoologia i Antropologia Biològica (Dpt. Biologia Evolutiva, Ecologia i Ciències Ambientals), Facultat de Biologia and Institut de Biomedicina (IBUB), University of Barcelona, CIBERSAM, Spain
| | - Jean-Michel Aubry
- Department of Psychiatry, Mood Disorders Unit, HUG - Geneva University Hospitals, Switzerland
| | - Lena Backlund
- Department of Molecular Medicine and Surgery, Karolinska Institute, Sweden and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | | | - Frank Bellivier
- INSERM UMR-S 1144, Université Paris Diderot, Département de Psychiatrie et de Médecine Addictologique, AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière-F.Widal, France
| | - Antonio Benabarre
- Bipolar Disorder Program, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Spain
| | - Susanne Bengesser
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Austria
| | - Joanna M Biernacka
- Department of Health Sciences Research, Mayo Clinic, USA and Department of Psychiatry and Psychology, Mayo Clinic, USA
| | - Armin Birner
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Austria
| | - Clara Brichant-Petitjean
- INSERM UMR-S 1144, Université Paris Diderot, Département de Psychiatrie et de Médecine Addictologique, AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière-F.Widal, France
| | - Pablo Cervantes
- The Neuromodulation Unit, McGill University Health Centre, Canada
| | - Hsi-Chung Chen
- Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taiwan
| | - Caterina Chillotti
- Unit of Clinical Pharmacology, Hospital University Agency of Cagliari, Italy
| | - Sven Cichon
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany; and Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Switzerland
| | | | - Piotr M Czerski
- Psychiatric Genetic Unit, Poznan University of Medical Sciences, Poland
| | - Nina Dalkner
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Austria
| | - Alexandre Dayer
- Department of Psychiatry, Mood Disorders Unit, HUG - Geneva University Hospitals, Switzerland
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany
| | - Maria Del Zompo
- Department of Biomedical Sciences, University of Cagliari, Italy
| | - J Raymond DePaulo
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Bruno Étain
- INSERM UMR-S 1144, Université Paris Diderot, Département de Psychiatrie et de Médecine Addictologique, AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière-F.Widal, France
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany; Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Switzerland and Department of Psychiatry (UPK), University of Basel, Switzerland
| | - Louise Frisen
- Department of Molecular Medicine and Surgery, Karolinska Institute, Sweden and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, USA
| | - Janice M Fullerton
- Neuroscience Research Australia, Australia and School of Medical Sciences, University of New South Wales, Australia
| | | | | | - Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | | | - Paul Grof
- Mood Disorders Center of Ottawa, Canada
| | - Ryota Hashimoto
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Japan and Department of Psychiatry, Osaka University Graduate School of Medicine, Japan
| | - Joanna Hauser
- Psychiatric Genetic Unit, Poznan University of Medical Sciences, Poland
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany and Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August University Göttingen, Germany
| | - Stefan Herms
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany and Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Switzerland
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany and Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Switzerland
| | - Andrea Hofmann
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany
| | - Liping Hou
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, USA
| | - Yi-Hsiang Hsu
- Program for Quantitative Genomics, Harvard School of Public Health, USA and HSL Institute for Aging Research, Harvard Medical School, USA
| | - Stephane Jamain
- Univ Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, France
| | - Esther Jiménez
- Bipolar Disorder Program, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Spain
| | - Jean-Pierre Kahn
- Service de Psychiatrie et Psychologie Clinique, Centre Psychothérapique de Nancy - Université de Lorraine, France
| | - Layla Kassem
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, USA
| | - Po-Hsiu Kuo
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taiwan
| | - Tadafumi Kato
- Department of Psychiatry & Behavioral Science, Juntendo University, Graduate School of Medicine, Japan
| | - John Kelsoe
- Department of Psychiatry, University of California San Diego, USA
| | - Sarah Kittel-Schneider
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Sebastian Kliwicki
- Department of Adult Psychiatry, Poznan University of Medical Sciences, Poland
| | - Barbara König
- Department of Psychiatry and Psychotherapeutic Medicine, Landesklinikum Neunkirchen, Austria
| | - Ichiro Kusumi
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Japan
| | - Gonzalo Laje
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, USA
| | - Mikael Landén
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden and Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Catharina Lavebratt
- Department of Molecular Medicine and Surgery, Karolinska Institute, Sweden and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Marion Leboyer
- Univ Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, AP-HP, Mondor University Hospital, DMU Impact, Fondation FondaMental, France
| | | | - Mario Maj
- Department of Psychiatry, University of Campania 'Luigi Vanvitelli', Italy; ,for a full list of Major Depressive Disorder Working Group of the PGC Investigators, see the Supplementary Material
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Italy and Department of Pharmacology, Dalhousie University, Canada
| | - Lina Martinsson
- Department of Clinical Neurosciences, Karolinska Institutet, Sweden
| | - Michael J McCarthy
- Department of Psychiatry, University of California San Diego, USA and Department of Psychiatry, VA San Diego Healthcare System, USA
| | - Susan McElroy
- Department of Psychiatry, Lindner Center of Hope / University of Cincinnati, USA
| | - Francesc Colom
- Mental Health Research Group, IMIM-Hospital del Mar, Spain and Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Marina Mitjans
- Mental Health Research Group, IMIM-Hospital del Mar, Spain and Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Francis M Mondimore
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Palmiero Monteleone
- Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Italy
| | | | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn and Department of Genomics, Life & Brain Center, Germany
| | - Tomas Novák
- National Institute of Mental Health, Czech Republic
| | | | - Norio Ozaki
- Department of Psychiatry & Department of Child and Adolescent Psychiatry, Nagoya University Graduate School of Medicine, Japan
| | - Vincent Millischer
- Department of Molecular Medicine and Surgery, Karolinska Institute, Sweden and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden and Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany and Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Germany
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Germany
| | - Claudia Pisanu
- Department of Biomedical Sciences, University of Cagliari, Italy
| | - James B Potash
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Austria
| | - Guy A Rouleau
- Montreal Neurological Institute and Hospital, McGill University, Canada
| | - Janusz K Rybakowski
- Department of Adult Psychiatry, Poznan University of Medical Sciences, Poland
| | - Martin Schalling
- Department of Molecular Medicine and Surgery, Karolinska Institute, Sweden and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Peter R Schofield
- Neuroscience Research Australia, Australia and School of Medical Sciences, University of New South Wales, Australia
| | - Barbara W Schweizer
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | | | | | - Paul D Shilling
- Department of Psychiatry, University of California San Diego, USA
| | - Katzutaka Shimoda
- Department of Psychiatry, Dokkyo Medical University School of Medicine, Japan
| | - Christian Simhandl
- Bipolar Center Wiener Neustadt, Sigmund Freud University, Medical Faculty, Austria
| | | | | | - Thomas Stamm
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Charité Mitte, Germany
| | | | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, USA
| | | | - Gustavo Turecki
- Douglas Mental Health University Institute, McGill University, Canada
| | - Julia Veeh
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Eduard Vieta
- Bipolar Disorder Program, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Spain
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Gloria Roberts
- School of Psychiatry, University of New South Wales, Australia
| | - Peter P Zandi
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, USA
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Canada
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Germany
| | - Francis J McMahon
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, USA
| | | | - Thomas G Schulze
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany; Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, USA, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany and Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August University Göttingen, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Scott R Clark
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Australia
| | - Bernhard T Baune
- Department of Psychiatry and Psychotherapy, University of Münster, Germany; Department of Psychiatry, Melbourne Medical School, University of Melbourne, Australia and The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Australia
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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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McCaffrey U, Cannon DM, Hallahan B. The muscarinic-cholinergic system as a target in the treatment of depressive or manic episodes in bipolar disorder: A systematic review and meta-analysis. JOURNAL OF AFFECTIVE DISORDERS REPORTS 2021. [DOI: 10.1016/j.jadr.2021.100235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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30
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The central executive network and executive function in healthy and persons with schizophrenia groups: a meta-analysis of structural and functional MRI. Brain Imaging Behav 2021; 16:1451-1464. [PMID: 34775552 DOI: 10.1007/s11682-021-00589-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2021] [Indexed: 10/19/2022]
Abstract
This meta-analysis evaluated the extent to which executive function can be understood with structural and functional magnetic resonance imaging. Studies included structural in schizophrenia (k = 8; n = 241) and healthy controls (k = 12; n = 1660), and functional in schizophrenia (k = 4; n = 104) and healthy controls (k = 12; n = 712). Results revealed a positive association in the brain behavior relationship when pooled across schizophrenia and control samples for structural (pr = 0.27) and functional (pr = 0.29) modalities. Subgroup analyses revealed no significant difference for functional neuroimaging (pr = .43, 95%CI = -.08-.77, p = .088) but with structural neuroimaging (pr = .37, 95%CI = -.08-.69, p = .015) the association to executive functions is lower in the control group. Subgroup analyses also revealed no significant differences in the strength of the brain-behavior relationship in the schizophrenia group (pr = .59, 95%CI = .58-.61, p = .881) or the control group (pr = 0.19, 95%CI = 0.18-0.19, p = 0.920), suggesting concordance.
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31
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Du Y, Hao H, Xing Y, Niu J, Calhoun VD. A Transdiagnostic Biotype Detection Method for Schizophrenia and Autism Spectrum Disorder Based on Graph Kernel. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:3241-3244. [PMID: 34891932 DOI: 10.1109/embc46164.2021.9629618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Psychiatric diagnoses based on clinical manifestations are prone to be inaccurate. Schizophrenia (SZ) and autism spectrum disorder (ASD) were historically considered as the same disorder, and they still have many overlaps of clinical symptoms in the current standard. Therefore, there is an urgent need to explore the potential biotypes for them using neuroimaging measures such as brain functional connectivity (FC). However, previous studies have not effectively leveraged FC in detecting biotypes. Considering that graph theory helps reveal the topological information in FC, in this paper, we propose a graph kernel-based clustering method to explore transdiagnostic biotypes using FC estimated from functional magnetic resonance imaging (fMRI) data. In our method, frequent subnetworks are identified from the whole-brain FCs of all subjects, and then the graph kernel similarity is computed to measure the relationship between subjects for clustering. Based on fMRI data of 137 SZ and 150 ASD subjects, we obtained meaningful biotypes using our method, which shows significant differences between the identified biotypes in FC. In brief, our graph kernel-based clustering method is promising for transdiagnostic biotype detection.
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32
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Guimond S, Gu F, Shannon H, Kelly S, Mike L, Devenyi GA, Chakravarty MM, Sweeney JA, Pearlson G, Clementz BA, Tamminga C, Keshavan M. A Diagnosis and Biotype Comparison Across the Psychosis Spectrum: Investigating Volume and Shape Amygdala-Hippocampal Differences from the B-SNIP Study. Schizophr Bull 2021; 47:1706-1717. [PMID: 34254147 PMCID: PMC8530385 DOI: 10.1093/schbul/sbab071] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
OBJECTIVE Brain-based Biotypes for psychotic disorders have been developed as part of the B-SNIP consortium to create neurobiologically distinct subgroups within idiopathic psychosis, independent from traditional phenomenological diagnostic methods. In the current study, we aimed to validate the Biotype model by assessing differences in volume and shape of the amygdala and hippocampus contrasting traditional clinical diagnoses with Biotype classification. METHODS A total of 811 participants from 6 sites were included: probands with schizophrenia (n = 199), schizoaffective disorder (n = 122), psychotic bipolar disorder with psychosis (n = 160), and healthy controls (n = 330). Biotype classification, previously developed using cognitive and electrophysiological data and K-means clustering, was used to categorize psychosis probands into 3 Biotypes, with Biotype-1 (B-1) showing reduced neural salience and severe cognitive impairment. MAGeT-Brain segmentation was used to determine amygdala and hippocampal volumetric data and shape deformations. RESULTS When using Biotype classification, B-1 showed the strongest reductions in amygdala-hippocampal volume and the most widespread shape abnormalities. Using clinical diagnosis, probands with schizophrenia and schizoaffective disorder showed the most significant reductions of amygdala and hippocampal volumes and the most abnormal hippocampal shape compared with healthy controls. Biotype classification provided the strongest neuroanatomical differences compared with conventional DSM diagnoses, with the best discrimination seen using bilateral amygdala and right hippocampal volumes in B-1. CONCLUSION These findings characterize amygdala and hippocampal volumetric and shape abnormalities across the psychosis spectrum. Grouping individuals by Biotype showed greater between-group discrimination, suggesting a promising approach and a favorable target for characterizing biological heterogeneity across the psychosis spectrum.
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Affiliation(s)
- Synthia Guimond
- Department of Psychiatry, The Royal’s Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Psychoeducation and Psychology, Université du Québec en Outaouais, Gatineau, QC, Canada
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Neuroscience, Carleton University, Ottawa, ON, Canada
| | - Feng Gu
- Department of Psychiatry, The Royal’s Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Holly Shannon
- Department of Psychiatry, The Royal’s Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Neuroscience, Carleton University, Ottawa, ON, Canada
| | - Sinead Kelly
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Luke Mike
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Gabriel A Devenyi
- Department of Psychiatry, McGill University, Montréal, QC, Canada
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - M Mallar Chakravarty
- Department of Psychiatry, McGill University, Montréal, QC, Canada
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, USA
| | - Godfrey Pearlson
- Department of Psychiatry, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | - Brett A Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA, USA
- Department of and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Carol Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Massachusetts Mental Health Center and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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33
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Gray matter volume covariance networks are associated with altered emotional processing in bipolar disorder: a source-based morphometry study. Brain Imaging Behav 2021; 16:738-747. [PMID: 34546520 PMCID: PMC9010334 DOI: 10.1007/s11682-021-00541-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/09/2021] [Indexed: 11/26/2022]
Abstract
Widespread regional gray matter volume (GMV) alterations have been reported in bipolar disorder (BD). Structural networks, which are thought to better reflect the complex multivariate organization of the brain, and their clinical and psychological function have not been investigated yet in BD. 24 patients with BD type-I (BD-I), and 30 with BD type-II (BD-II), and 45 controls underwent MRI scan. Voxel-based morphometry and source-based morphometry (SBM) were performed to extract structural covariation patterns of GMV. SBM components associated with morphometric differences were compared among diagnoses. Executive function and emotional processing correlated with morphometric characteristics. Compared to controls, BD-I showed reduced GMV in the temporo-insular-parieto-occipital cortex and in the culmen. An SBM component spanning the prefrontal-temporal-occipital network exhibited significantly lower GMV in BD-I compared to controls, but not between the other groups. The structural network covariance in BD-I was associated with the number of previous manic episodes and with worse executive performance. Compared to BD-II, BD-I showed a loss of GMV in the temporal-occipital regions, and this was correlated with impaired emotional processing. Altered prefrontal-temporal-occipital network structure could reflect a neural signature associated with visuospatial processing and problem-solving impairments as well as emotional processing and illness severity in BD-I.
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34
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Xiao Y, Liao W, Long Z, Tao B, Zhao Q, Luo C, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Ivleva EI, Keedy SK, Biswal BB, Mechelli A, Lencer R, Sweeney JA, Lui S, Gong Q. Subtyping Schizophrenia Patients Based on Patterns of Structural Brain Alterations. Schizophr Bull 2021; 48:241-250. [PMID: 34508358 PMCID: PMC8781382 DOI: 10.1093/schbul/sbab110] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials.
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Affiliation(s)
- Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry, University of Münster, Münster, Germany
| | - Wei Liao
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Zhiliang Long
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiannan Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Chunyan Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, 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 Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Rebekka Lencer
- Department of Psychiatry, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,To whom correspondence should be addressed; #37 GuoXue Xiang, Chengdu 610041, China; Tel: 86-28-85423960, Fax: 86-28-85423503; e-mail:
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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35
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Duan J, Wei Y, Womer FY, Zhang X, Chang M, Zhu Y, Liu Z, Li C, Yin Z, Zhang R, Sun J, Wang P, Wang S, Jiang X, Wei S, Zhang Y, Tang Y, Wang F. Neurobiological substrates of major psychiatry disorders: transdiagnostic associations between white matter abnormalities, neuregulin 1 and clinical manifestation. J Psychiatry Neurosci 2021; 46:E506-E515. [PMID: 34467747 PMCID: PMC8526153 DOI: 10.1503/jpn.200166] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Schizophrenia, bipolar disorder and major depressive disorder are increasingly being conceptualized as a transdiagnostic continuum. Disruption of white matter is a common alteration in these psychiatric disorders, but the molecular mechanisms underlying the disruption remain unclear. Neuregulin 1 (NRG1) is genetically linked with susceptibility to schizophrenia, bipolar disorder and major depressive disorder, and it is also related to white matter. METHODS Using a transdiagnostic approach, we aimed to identify white matter differences associated with NRG1 and their relationship to transdiagnostic symptoms and cognitive function. We examined the white matter of 1051 participants (318 healthy controls and 733 patients with major psychiatric disorders: 254 with schizophrenia, 212 with bipolar disorder and 267 with major depressive disorder) who underwent diffusion tensor imaging. We measured the plasma NRG1-β1 levels of 331 participants. We also evaluated clinical symptoms and cognitive function. RESULTS In the patient group, abnormal white matter was negatively associated with NRG1-β1 levels in the genu of the corpus callosum, right uncinate fasciculus, bilateral inferior fronto-occipital fasciculus, right external capsule, fornix, right optic tract, left straight gyrus white matter and left olfactory radiation. These NRG1-associated white matter abnormalities were also associated with depression and anxiety symptoms and executive function in patients with a major psychiatric disorder. Furthermore, across the 3 disorders we observed analogous alterations in white matter, NRG1-β1 levels and clinical manifestations. LIMITATIONS Medication status, the wide age range and our cross-sectional findings were limitations of this study. CONCLUSION This study is the first to provide evidence for an association between NRG1, white matter abnormalities, clinical symptoms and cognition in a transdiagnostic psychiatric cohort. These findings provide further support for an understanding of the molecular mechanisms that underlie the neuroimaging substrates of major psychiatric disorders and their clinical implications.
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Affiliation(s)
- Jia Duan
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yange Wei
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Fay Y Womer
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Xizhe Zhang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Miao Chang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yue Zhu
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Zhuang Liu
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Chao Li
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Zhiyang Yin
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Ran Zhang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Jiaze Sun
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Pengshuo Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Shuai Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Xiaowei Jiang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Shengnan Wei
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yanbo Zhang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yanqing Tang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Fei Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
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Trotti RL, Abdelmageed S, Parker DA, Sabatinelli D, Tamminga CA, Gershon ES, Keedy SK, Keshavan MS, Pearlson GD, Sweeney JA, McDowell JE, Clementz BA. Neural Processing of Repeated Emotional Scenes in Schizophrenia, Schizoaffective Disorder, and Bipolar Disorder. Schizophr Bull 2021; 47:1473-1481. [PMID: 33693875 PMCID: PMC8379546 DOI: 10.1093/schbul/sbab018] [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] [Indexed: 11/14/2022]
Abstract
Impaired emotional processing and cognitive functioning are common in schizophrenia, schizoaffective disorder, and bipolar disorders, causing significant socioemotional disability. While a large body of research demonstrates abnormal cognition/emotion interactions in these disorders, previous studies investigating abnormalities in the emotional scene response using event-related potentials (ERPs) have yielded mixed findings, and few studies compare findings across psychiatric diagnoses. The current study investigates the effects of emotion and repetition on ERPs in a large, well-characterized sample of participants with schizophrenia-bipolar syndromes. Two ERP components that are modulated by emotional content and scene repetition, the early posterior negativity (EPN) and late positive potential (LPP), were recorded in healthy controls and participants with schizophrenia, schizoaffective disorder, bipolar disorder with psychosis, and bipolar disorder without psychosis. Effects of emotion and repetition were compared across groups. Results displayed significant but small effects in schizophrenia and schizoaffective disorder, with diminished EPN amplitudes to neutral and novel scenes, reduced LPP amplitudes to emotional scenes, and attenuated effects of scene repetition. Despite significant findings, small effect sizes indicate that emotional scene processing is predominantly intact in these disorders. Multivariate analyses indicate that these mild ERP abnormalities are related to cognition, psychosocial functioning, and psychosis severity. This relationship suggests that impaired cognition, rather than diagnosis or mood disturbance, may underlie disrupted neural scene processing in schizophrenia-bipolar syndromes.
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Affiliation(s)
- Rebekah L Trotti
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Sunny Abdelmageed
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - David A Parker
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Dean Sabatinelli
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | | | | | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jennifer E McDowell
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, 613 Psychology Building, 125 Baldwin St., Athens, GA 30602, USA
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Li F, Sun H, Biswal BB, Sweeney JA, Gong Q. Artificial intelligence applications in psychoradiology. PSYCHORADIOLOGY 2021; 1:94-107. [PMID: 37881257 PMCID: PMC10594695 DOI: 10.1093/psyrad/kkab009] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 05/10/2021] [Accepted: 06/04/2021] [Indexed: 02/05/2023]
Abstract
One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose, predict, and make treatment decisions. In this review, we selectively summarize psychoradiological research using magnetic resonance imaging of the brain to explore the neural mechanism of psychiatric disorders, and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders, as well as limitations in the application of AI that should be considered in future translational research.
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Affiliation(s)
- Fei Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, P.R. China
- Functional and Molecular Imaging Key Laboratory of Sichuan Provience, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, P.R. China
- Functional and Molecular Imaging Key Laboratory of Sichuan Provience, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, P.R. China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45219, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, P.R. China
- Functional and Molecular Imaging Key Laboratory of Sichuan Provience, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
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Pu X, Li J, Ma X, Yang S, Wang L. The functional polymorphisms linked with interleukin-1β gene expression are associated with bipolar disorder. Psychiatr Genet 2021; 31:72-78. [PMID: 33707400 DOI: 10.1097/ypg.0000000000000272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Bipolar disorder (BD) is a severe psychiatric illness attributable to multifactorial risk components (e.g. environmental stimuli, neuroinflammation, etc.), and genetic variations affecting these risk components are considered pivotal predisposing factors. The interleukin-1β (IL-1β) gene and its protein product have been repeatedly highlighted in the pathogenesis of BD. As functional polymorphisms and haplotypes linked with IL-1β mRNA expression have been reported, whether they are correlated with the risk of developing BD remains to be tested. METHODS To examine whether variations in the IL-1β gene locus confer genetic risk of BD, we recruited 930 BD patients and 912 healthy controls for the current study. All subjects were Han Chinese, and were age- and gender-matched. We tested seven functional single nucleotide polymorphisms (SNPs) spanning the IL-1β gene and one haplotype composed of three SNPs for their associations with risk of BD. RESULTS We found that the functional SNPs in the promoter region of IL-1β gene were significantly associated with risk of BD. The haplotype analyses further supported the involvement of IL-1β promoter SNPs in BD. The BD risk SNPs in our study have been previously reported to predict higher IL-1β levels in the brain and peripheral blood, which is consistent with the clinical observation of elevated IL-1β levels in the lymphocytes or peripheral blood of patients with BD compared with healthy subjects. CONCLUSION Our results support the contention that IL-1β is likely a risk gene for BD, and further investigations on this gene may promote our understanding and clinical management of this illness.
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Affiliation(s)
- Xingfu Pu
- The Second People's Hospital of Yuxi City, Yuxi, Yunnan, China
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Rüppel J. ["Allowing the Data to 'Speak for Themselves'" - The Classification of Mental Disorders and the Imaginary of Computational Psychiatry]. PSYCHIATRISCHE PRAXIS 2021; 48:S16-S20. [PMID: 33652482 DOI: 10.1055/a-1364-5551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
This article focuses on hopes and expectations that are discursively linked to computational technologies in the face of the current "crisis of psychiatric diagnostics". On the basis of document analyses, expert interviews as well as laboratory and conference ethnographies, the fiction of an "unprejudiced gaze" is worked out. According to this imagination, the procedures of "artificial intelligence" may let the data - and ultimately the facts - speak for themselves. However, since "data-driven" research is also determined by conceptual and normative decisions, this fiction could obscure epistemic hierarchizations and ontological prioritizations in psychiatric discourse. Against this backdrop, dependencies and selectivities of research should not be denied but made transparent allowing for a controversial debate.
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Affiliation(s)
- Jonas Rüppel
- Institut für Soziologie, Goethe-Universität Frankfurt
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40
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Kelly S, Guimond S, Pasternak O, Lutz O, Lizano P, Cetin-Karayumak S, Sweeney JA, Pearlson G, Clementz BA, McDowell JE, Tamminga CA, Shenton ME, Keshavan MS. White matter microstructure across brain-based biotypes for psychosis - findings from the bipolar-schizophrenia network for intermediate phenotypes. Psychiatry Res Neuroimaging 2021; 308:111234. [PMID: 33385763 DOI: 10.1016/j.pscychresns.2020.111234] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/22/2020] [Accepted: 12/01/2020] [Indexed: 12/14/2022]
Abstract
The B-SNIP consortium identified three brain-based Biotypes across the psychosis spectrum, independent of clinical phenomenology. To externally validate the Biotype model, we used free-water fractional volume (FW) and free-water corrected fractional anisotropy (FAT) to compare white matter differences across Biotypes and clinical diagnoses. Diffusion tensor imaging data from 167 individuals were included: 41 healthy controls, 55 schizophrenia probands, 47 schizoaffective disorder probands, and 24 probands with psychotic bipolar disorder. Compared to healthy controls, FAt reductions were observed in the body of corpus callosum (BCC) for schizoaffective disorder (d = 0.91) and schizophrenia (d = 0.64). Grouping by Biotype, Biotype 1 showed FAt reductions in the CC and fornix, with largest effect in the BCC (d = 0.87). Biotype 2 showed significant FAt reductions in the BCC (d = 0.90). Schizoaffective disorder individuals had elevated FW in the CC, fornix and anterior corona radiata (ACR), with largest effect in the BCC (d = 0.79). Biotype 2 showed elevated FW in the CC, fornix and ACR, with largest effect in the BCC (d = 0.94). While significant diagnosis comparisons were observed, overall greater discrimination from healthy controls was observed for lower FAt in Biotype 1 and elevated FW in Biotype 2. However, between-group differences were modest, with one region (cerebral peduncle) showing a between-Biotype effect. No between-group effects were observed for diagnosis groupings.
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Affiliation(s)
- Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States.
| | - Synthia Guimond
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States; Department of Psychiatry, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Olivia Lutz
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH 45221, United States
| | - Godfrey Pearlson
- Department of Psychiatry, Yale University, New Haven, CT 06520, United States
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA 30602, United States
| | - Jennifer E McDowell
- Department of Psychology, University of Georgia, Athens, GA 30602, United States
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States
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Sato J, Hirano Y, Hirakawa N, Takahashi J, Oribe N, Kuga H, Nakamura I, Hirano S, Ueno T, Togao O, Hiwatashi A, Nakao T, Onitsuka T. Lower Hippocampal Volume in Patients with Schizophrenia and Bipolar Disorder: A Quantitative MRI Study. J Pers Med 2021; 11:jpm11020121. [PMID: 33668432 PMCID: PMC7918861 DOI: 10.3390/jpm11020121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 02/06/2021] [Accepted: 02/09/2021] [Indexed: 01/02/2023] Open
Abstract
Since patients with schizophrenia (SZ) and bipolar disorder (BD) share many biological features, detecting biomarkers that differentiate SZ and BD patients is crucial for optimized treatments. High-resolution magnetic resonance imaging (MRI) is suitable for detecting subtle brain structural differences in patients with psychiatric disorders. In the present study, we adopted a neuroanatomically defined and manually delineated region of interest (ROI) method to evaluate the amygdalae, hippocampi, Heschl’s gyrus (HG), and planum temporale (PT), because these regions are crucial in the development of SZ and BD. ROI volumes were measured using high resolution MRI in 31 healthy subjects (HS), 23 SZ patients, and 21 BD patients. Right hippocampal volumes differed significantly among groups (HS > BD > SZ), whereas left hippocampal volumes were lower in SZ patients than in HS and BD patients (HS = BD > SZ). Volumes of the amygdalae, HG, and PT did not differ among the three groups. For clinical correlations, there were no significant associations between ROI volumes and demographics/clinical symptoms. Our study revealed significant lower hippocampal volume in patients with SZ and BD, and we suggest that the right hippocampal volume is a potential biomarker for differentiation between SZ and BD.
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Affiliation(s)
- Jinya Sato
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
- Correspondence: (Y.H.); (T.O.); Tel.: +81-92-642-5627 (Y.H. & T.O.)
| | - Noriaki Hirakawa
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Junichi Takahashi
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Naoya Oribe
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Hizen Psychiatric Medical Center, Division of Clinical Research, National Hospital Organization, Saga 842-0192, Japan;
| | - Hironori Kuga
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Hizen Psychiatric Medical Center, Division of Clinical Research, National Hospital Organization, Saga 842-0192, Japan;
| | - Itta Nakamura
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Shogo Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Takefumi Ueno
- Hizen Psychiatric Medical Center, Division of Clinical Research, National Hospital Organization, Saga 842-0192, Japan;
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan;
| | - Akio Hiwatashi
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan;
| | - Tomohiro Nakao
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Toshiaki Onitsuka
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Correspondence: (Y.H.); (T.O.); Tel.: +81-92-642-5627 (Y.H. & T.O.)
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Precision Psychiatry: Biomarker-Guided Tailored Therapy for Effective Treatment and Prevention in Major Depression. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:535-563. [PMID: 33834417 DOI: 10.1007/978-981-33-6044-0_27] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Depression contributes greatly to global disability and is a leading cause of suicide. It has multiple etiologies and therefore response to treatment can vary significantly. By applying the concepts of personalized medicine, precision psychiatry attempts to optimize psychiatric patient care by better predicting which individuals will develop an illness, by giving a more accurate biologically based diagnosis, and by utilizing more effective treatments based on an individual's biological characteristics (biomarkers). In this chapter, we discuss the basic principles underlying the role of biomarkers in psychiatric pathology and then explore multiple biomarkers that are specific to depression. These include endophenotypes, gene variants/polymorphisms, epigenetic factors such as methylation, biochemical measures, circadian rhythm dysregulation, and neuroimaging findings. We also examine the role of early childhood trauma in the development of, and treatment response to, depression. In addition, we review how new developments in technology may play a greater role in the determination of new biomarkers for depression.
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Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning. Mol Psychiatry 2021; 26:2991-3002. [PMID: 33005028 PMCID: PMC8505253 DOI: 10.1038/s41380-020-00892-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 08/27/2020] [Accepted: 09/15/2020] [Indexed: 12/31/2022]
Abstract
Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurobiology of the psychotic-affective spectrum may greatly advance biological determination of psychiatric diagnosis, which is critical for the development of more effective treatments. In this study, ensemble clustering was developed to identify subtypes within a trans-diagnostic sample of MPDs. Whole brain amplitude of low-frequency fluctuations (ALFF) was used to extract the low-dimensional features for clustering in a total of 944 participants: 581 psychiatric patients (193 with SZ, 171 with BD, and 217 with MDD) and 363 healthy controls (HC). We identified two subtypes with differentiating patterns of functional imbalance between frontal and posterior brain regions, as compared to HC: (1) Archetypal MPDs (60% of MPDs) had increased frontal and decreased posterior ALFF, and decreased cortical thickness and white matter integrity in multiple brain regions that were associated with increased polygenic risk scores and enriched risk gene expression in brain tissues; (2) Atypical MPDs (40% of MPDs) had decreased frontal and increased posterior ALFF with no associated alterations in validity measures. Medicated Archetypal MPDs had lower symptom severity than their unmedicated counterparts; whereas medicated and unmedicated Atypical MPDs had no differences in symptom scores. Our findings suggest that frontal versus posterior functional imbalance as measured by ALFF is a novel putative trans-diagnostic biomarker differentiating subtypes of MPDs that could have implications for precision medicine.
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Tamminga CA, Clementz BA, Pearlson G, Keshavan M, Gershon ES, Ivleva EI, McDowell J, Meda SA, Keedy S, Calhoun VD, Lizano P, Bishop JR, Hudgens-Haney M, Alliey-Rodriguez N, Asif H, Gibbons R. Biotyping in psychosis: using multiple computational approaches with one data set. Neuropsychopharmacology 2021; 46:143-155. [PMID: 32979849 PMCID: PMC7689458 DOI: 10.1038/s41386-020-00849-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 08/24/2020] [Accepted: 08/26/2020] [Indexed: 12/15/2022]
Abstract
Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from behavioral phenomenology to quantifying brain features, requiring big data approaches for data integration. Much still needs to be accomplished, not only to refine but also to build support for the application and customization of such an analytical phenotypic approach. In this review, we present some of what Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has learned so far to guide future applications of multivariate phenotyping and their analyses to understanding psychosis. This paper describes several B-SNIP projects that use phenotype data and big data computations to generate novel outcomes and glimpse what phenotypes contribute to disease understanding and, with aspiration, to treatment. The source of the phenotypes varies from genetic data, structural neuroanatomic localization, immune markers, brain physiology, and cognition. We aim to see guiding principles emerge and areas of commonality revealed. And, we will need to demonstrate not only data stability but also the usefulness of biomarker information for subgroup identification enhancing target identification and treatment development.
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Affiliation(s)
- Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
| | - Brett A Clementz
- Departments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA, 30602, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
- Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT, USA
| | - Macheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Jennifer McDowell
- Departments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA, 30602, USA
| | - Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
- Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT, USA
| | - Sarah Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, United States
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | | | - Ney Alliey-Rodriguez
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Huma Asif
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Robert Gibbons
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
- Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, Ill, USA
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Hopkins SC, Ogirala A, Loebel A, Koblan KS. Characterization of specific and distinct patient types in clinical trials of acute schizophrenia using an uncorrelated PANSS score matrix transform (UPSM). Psychiatry Res 2020; 294:113569. [PMID: 33223272 DOI: 10.1016/j.psychres.2020.113569] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 11/07/2020] [Indexed: 10/23/2022]
Abstract
Understanding the specificity of symptom change in schizophrenia can facilitate the evaluation antipsychotic efficacy for different symptom domains. Previous work identified a transform of PANSS using an uncorrelated PANSS score matrix (UPSM) to reduce pseudospecificity among symptom domains during clinical trials of schizophrenia. Here we used UPSM-transformed factor scores to identify 5 distinct patient types, each having elevated and specific severity among each of 5 symptom domains. Subjects from placebo-controlled clinical trials of acute schizophrenia were clustered (baseline) and classified (post-baseline) by a machine-learning algorithm. At baseline, all 5 patient types were similar in PANSS total score. Post-baseline, subjects' memberships among the 5 UPSM patient types were relatively stable over treatment duration and were relatively insensitive to overall improvements in symptoms, in contrast to other methods based on untransformed PANSS items. Using UPSM-transformed PANSS, drug treatment effect sizes versus placebo were doubly-dissociated for specificity across symptom domains and within specific patient types. This approach illustrates how broader clinical trial populations can nevertheless be utilized to characterize the specificity of new mechanisms across the dimensions of schizophrenia psychopathology.
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46
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA. Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features. Biomark Neuropsychiatry 2020; 3:100014. [PMID: 36644018 PMCID: PMC9837793 DOI: 10.1016/j.bionps.2020.100014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Background EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP). Methods Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations. Results Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms. Conclusions This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.
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Affiliation(s)
| | | | - Jennifer E. McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elena I. Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - Godfrey D. Pearlson
- Neuroscience, Yale School of Medicine, Institute of Living, Hartford Hospital, United States of America
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, United States of America
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Brett A. Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia, Corresponding author at: Psychology Department, 125 Jackson Street, Athens GA, 30601, Greece. (B.A. Clementz)
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Parkes L, Satterthwaite TD, Bassett DS. Towards precise resting-state fMRI biomarkers in psychiatry: synthesizing developments in transdiagnostic research, dimensional models of psychopathology, and normative neurodevelopment. Curr Opin Neurobiol 2020; 65:120-128. [PMID: 33242721 PMCID: PMC7770086 DOI: 10.1016/j.conb.2020.10.016] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 10/11/2020] [Accepted: 10/14/2020] [Indexed: 02/01/2023]
Abstract
Searching for biomarkers has been a chief pursuit of the field of psychiatry. Toward this end, studies have catalogued candidate resting-state biomarkers in nearly all forms of mental disorder. However, it is becoming increasingly clear that these biomarkers lack specificity, limiting their capacity to yield clinical impact. We discuss three avenues of research that are overcoming this limitation: (i) the adoption of transdiagnostic research designs, which involve studying and explicitly comparing multiple disorders from distinct diagnostic axes of psychiatry; (ii) dimensional models of psychopathology that map the full spectrum of symptomatology and that cut across traditional disorder boundaries; and (iii) modeling individuals' unique functional connectomes throughout development. We provide a framework for tying these subfields together that draws on tools from machine learning and network science.
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Affiliation(s)
- Linden Parkes
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA.
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48
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Deng ZD, Luber B, Balderston NL, Velez Afanador M, Noh MM, Thomas J, Altekruse WC, Exley SL, Awasthi S, Lisanby SH. Device-Based Modulation of Neurocircuits as a Therapeutic for Psychiatric Disorders. Annu Rev Pharmacol Toxicol 2020; 60:591-614. [PMID: 31914895 DOI: 10.1146/annurev-pharmtox-010919-023253] [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] [Indexed: 12/13/2022]
Abstract
Device-based neuromodulation of brain circuits is emerging as a promising new approach in the study and treatment of psychiatric disorders. This work presents recent advances in the development of tools for identifying neurocircuits as therapeutic targets and in tools for modulating neurocircuits. We review clinical evidence for the therapeutic efficacy of circuit modulation with a range of brain stimulation approaches, including subthreshold, subconvulsive, convulsive, and neurosurgical techniques. We further discuss strategies for enhancing the precision and efficacy of neuromodulatory techniques. Finally, we survey cutting-edge research in therapeutic circuit modulation using novel paradigms and next-generation devices.
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Affiliation(s)
- Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA; .,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina 27710, USA
| | - Bruce Luber
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Nicholas L Balderston
- Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Melbaliz Velez Afanador
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Michelle M Noh
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Jeena Thomas
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - William C Altekruse
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Shannon L Exley
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Shriya Awasthi
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Sarah H Lisanby
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA; .,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina 27710, USA
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49
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de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Alonso‐Lana S, Bearden CE, Bertolino A, Bonvino A, Bramon E, Buimer EEL, Cahn W, Canales‐Rodríguez EJ, Cannon DM, Cannon TD, Caseras X, Castro‐Fornieles J, Chen Q, Chung Y, De la Serna E, del Mar Bonnin C, Demro C, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fatjó‐Vilas M, Fears SC, Foley SF, Frangou S, Fullerton JM, Glahn DC, Goghari VM, Goikolea JM, Goldman AL, Gonul AS, Gruber O, Hajek T, Hawkins EL, Heinz A, Hidiroglu Ongun C, Hillegers MHJ, Houenou J, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Mattay VS, McDonald C, Meyer‐Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Nabulsi L, Newport J, Olman CA, van Os J, Overs BJ, Ozerdem A, Pergola G, Picchioni MM, Piguet C, Pomarol‐Clotet E, Radua J, Ramsay IS, Richter A, Roberts G, Salvador R, Saricicek Aydogan A, Sarró S, Schofield PR, Simsek EM, Simsek F, Soares JC, Sponheim SR, Sugranyes G, Toulopoulou T, Tronchin G, Vieta E, Walter H, Weinberger DR, Whalley HC, Wu M, Yalin N, Andreassen OA, Ching CRK, Thomopoulos SI, van Erp TGM, Jahanshad N, Thompson PM, Kahn RS, van Haren NEM. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder. Hum Brain Mapp 2020; 43:414-430. [PMID: 33027543 PMCID: PMC8675411 DOI: 10.1002/hbm.25206] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 08/28/2020] [Accepted: 09/03/2020] [Indexed: 12/25/2022] Open
Abstract
First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.
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Affiliation(s)
- Sonja M. C. de Zwarte
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Rachel M. Brouwer
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,Department of PsychiatryDiakonhjemmet HospitalOsloNorway
| | - Martin Alda
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Silvia Alonso‐Lana
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Carrie E. Bearden
- Semel Institute for Neuroscience and Human Behavior, University of CaliforniaCaliforniaLos AngelesUSA,Department of PsychologyUniversity of CaliforniaCaliforniaLos AngelesUSA
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Aurora Bonvino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Elvira Bramon
- Division of Psychiatry, Neuroscience in Mental Health Research DepartmentUniversity College LondonLondonUK
| | - Elizabeth E. L. Buimer
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Wiepke Cahn
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Erick J. Canales‐Rodríguez
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Dara M. Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Tyrone D. Cannon
- Department of PsychologyYale UniversityNew HavenConnecticutUSA,Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUK
| | - Josefina Castro‐Fornieles
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA
| | - Yoonho Chung
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Elena De la Serna
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Caterina del Mar Bonnin
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Caroline Demro
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Gaelle E. Doucet
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA,Boys Town National Research HospitalOmahaNEUSA
| | - Mehmet Cagdas Eker
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey
| | - Susanne Erk
- Research Division of Mind and Brain, Department of Psychiatry and PsychotherapyCharité Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Mar Fatjó‐Vilas
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Scott C. Fears
- Department of Psychiatry and Biobehavioral ScienceUniversity of CaliforniaLos AngelesCaliforniaUSA,Center for Neurobehavioral GeneticsUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Sonya F. Foley
- Cardiff University Brain Research Imaging Centre, Cardiff UniversityCardiffUK
| | - Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Janice M. Fullerton
- Neuroscience Research AustraliaSydneyAustralia,School of Medical Sciences, University of New South WalesSydneyAustralia
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA,Tommy Fuss Center for Neuropsychiatric Disease ResearchBoston Children's HospitalBostonMassachusettsUSA,Harvard Medical SchoolBostonMassachusettsUSA
| | - Vina M. Goghari
- Department of Psychology and Graduate Department of Psychological Clinical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Jose M. Goikolea
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Aaron L. Goldman
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA
| | - Ali Saffet Gonul
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey,Department of Psychiatry and Behavioral SciencesMercer University School of MedicineMaconGeorgiaUSA
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Tomas Hajek
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Emma L. Hawkins
- Division of PsychiatryRoyal Edinburgh Hospital, University of EdinburghEdinburghUK
| | - Andreas Heinz
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey
| | | | - Manon H. J. Hillegers
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center‐Sophia Children's HospitalRotterdamNetherlands
| | - Josselin Houenou
- APHP, Mondor University HospitalsCréteilFrance,INSERM U955 Team 15 "Translational Psychiatry"CréteilFrance,NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA SaclayGif‐Sur‐YvetteFrance
| | - Hilleke E. Hulshoff Pol
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Christina M. Hultman
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Martin Ingvar
- Section for Neuroscience, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden,Department of NeuroradiologyKarolinska University HospitalStockholmSweden
| | - Viktoria Johansson
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden
| | - Fergus Kane
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Matthew J. Kempton
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Marinka M. G. Koenis
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA,Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA
| | - Miloslav Kopecek
- National Institute of Mental HealthKlecanyCzech Republic,Department of Psychiatry, Third Faculty of MedicineCharles UniversityPragueCzech Republic
| | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Stephen M. Lawrie
- Division of PsychiatryRoyal Edinburgh Hospital, University of EdinburghEdinburghUK
| | - Rhoshel K. Lenroot
- Neuroscience Research AustraliaSydneyAustralia,School of Psychiatry, University of New South WalesSydneyAustralia,Department of Psychiatry and Behavioral SciencesUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Machteld Marcelis
- Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | - Venkata S. Mattay
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA,Departments of Neurology and RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and PsychotherapyCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Stijn Michielse
- Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | | | - Dolores Moreno
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Child and Adolescent Psychiatry DepartmentHospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad ComplutenseMadridSpain
| | - Robin M. Murray
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Benson Mwangi
- Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Jason Newport
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada
| | - Cheryl A. Olman
- Department of Psychology and Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Jim van Os
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | | | - Aysegul Ozerdem
- Department of Psychiatry, Faculty of MedicineDokuz Eylül UniversityIzmirTurkey,Department of NeurosciencesHealth Sciences Institute, Dokuz Eylül UniversityIzmirTurkey,Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Marco M. Picchioni
- Department of Forensic and Neurodevelopmental ScienceInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Camille Piguet
- INSERM U955 Team 15 "Translational Psychiatry"CréteilFrance,NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA SaclayGif‐Sur‐YvetteFrance,Department of Psychiatry, Faculty of MedicineUniversity of GenevaGenevaSwitzerland,School of Medicine, Universitat Internacional de CatalunyaBarcelonaSpain
| | - Edith Pomarol‐Clotet
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Joaquim Radua
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Early Psychosis: Interventions and Clinical‐detection (EPIC) lab, Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUK
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Anja Richter
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Gloria Roberts
- School of Psychiatry, University of New South WalesSydneyAustralia
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Aybala Saricicek Aydogan
- Department of NeurosciencesHealth Sciences Institute, Dokuz Eylül UniversityIzmirTurkey,Department of Psychiatry, Faculty of MedicineIzmir Katip Çelebi UniversityIzmirTurkey
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Peter R. Schofield
- School of Medical Sciences, University of New South WalesSydneyAustralia,Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA
| | | | - Fatma Simsek
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey,Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK,Cigli State HospitalDepartment of PsychiatryIzmirTurkey
| | - Jair C. Soares
- Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA,Minneapolis VA Health Care SystemMinneapolisMinnesotaUSA
| | - Gisela Sugranyes
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Timothea Toulopoulou
- Department of PsychologyBilkent UniversityAnkaraTurkey,Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Giulia Tronchin
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Eduard Vieta
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Henrik Walter
- Research Division of Mind and Brain, Department of Psychiatry and PsychotherapyCharité Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Daniel R. Weinberger
- Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Heather C. Whalley
- Department of Psychology, Faculty of ArtsDokuz Eylül UniversityİzmirTurkey
| | - Mon‐Ju Wu
- Department of Psychology and Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Nefize Yalin
- Centre for Affective Disorders, Department of Psychological MedicineInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA,Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - René S. Kahn
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Neeltje E. M. van Haren
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center‐Sophia Children's HospitalRotterdamNetherlands
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50
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Janssen J, Díaz-Caneja CM, Alloza C, Schippers A, de Hoyos L, Santonja J, Gordaliza PM, Buimer EEL, van Haren NEM, Cahn W, Arango C, Kahn RS, Hulshoff Pol HE, Schnack HG. Dissimilarity in Sulcal Width Patterns in the Cortex can be Used to Identify Patients With Schizophrenia With Extreme Deficits in Cognitive Performance. Schizophr Bull 2020; 47:552-561. [PMID: 32964935 PMCID: PMC7965061 DOI: 10.1093/schbul/sbaa131] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Schizophrenia is a biologically complex disorder with multiple regional deficits in cortical brain morphology. In addition, interindividual heterogeneity of cortical morphological metrics is larger in patients with schizophrenia when compared to healthy controls. Exploiting interindividual differences in the severity of cortical morphological deficits in patients instead of focusing on group averages may aid in detecting biologically informed homogeneous subgroups. The person-based similarity index (PBSI) of brain morphology indexes an individual's morphometric similarity across numerous cortical regions amongst a sample of healthy subjects. We extended the PBSI such that it indexes the morphometric similarity of an independent individual (eg, a patient) with respect to healthy control subjects. By employing a normative modeling approach on longitudinal data, we determined an individual's degree of morphometric dissimilarity to the norm. We calculated the PBSI for sulcal width (PBSI-SW) in patients with schizophrenia and healthy control subjects (164 patients and 164 healthy controls; 656 magnetic resonance imaging scans) and associated it with cognitive performance and cortical sulcation index. A subgroup of patients with markedly deviant PBSI-SW showed extreme deficits in cognitive performance and cortical sulcation. Progressive reduction of PBSI-SW in the schizophrenia group relative to healthy controls was driven by these deviating individuals. By explicitly leveraging interindividual differences in the severity of PBSI-SW deficits, neuroimaging-driven subgrouping of patients is feasible. As such, our results pave the way for future applications of morphometric similarity indices for subtyping of clinical populations.
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Affiliation(s)
- Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain,Ciber del Área de Salud Mental, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands,To whom correspondence should be addressed; tel: 0034914265005, fax: 0034914265004, e-mail:
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain,Ciber del Área de Salud Mental, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,School of Medicine, Universidad Complutense, Madrid, Spain
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain,Ciber del Área de Salud Mental, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Anouck Schippers
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain,Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lucía de Hoyos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain
| | - Javier Santonja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain
| | - Pedro M Gordaliza
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
| | - Elizabeth E L Buimer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Neeltje E M van Haren
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands,Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, C/ Ibiza, 43. 28009 Madrid, Spain,Ciber del Área de Salud Mental, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,School of Medicine, Universidad Complutense, Madrid, Spain
| | - René S Kahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
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