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Cilia BJ, Eratne D, Wannan C, Malpas C, Janelidze S, Hansson O, Everall I, Bousman C, Thomas N, Santillo AF, Velakoulis D, Pantelis C. Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia. Aust N Z J Psychiatry 2025:48674241307906. [PMID: 39754499 DOI: 10.1177/00048674241307906] [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] [Indexed: 01/06/2025]
Abstract
OBJECTIVE Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia). Abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often described in schizophrenia. Novel biomarkers of active brain pathology such as neurofilament light chain protein are now expected to improve current understanding of psychiatric disorders, including schizophrenia. This study explored whether treatment-resistant schizophrenia individuals exhibit different associations between plasma neurofilament light chain protein levels and regional cortical thickness reductions compared with controls. METHODS Plasma neurofilament light chain protein levels were measured, and T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer for each participant. General linear models adjusting for age and body mass index were estimated to determine whether the interaction between diagnostic group and plasma neurofilament light chain protein level predicted lower cortical thickness across frontotemporal structures and the insula. RESULTS A total of 79 participants were included: 37 treatment-resistant schizophrenia and 42 healthy controls. Significant (false discovery rate-corrected) cortical thinning of the left (p = 0.005, η2p = 0.100) and right (p = 0.002, η2p = 0.149) insula, and left inferior temporal gyrus (p < 0.001, η2p = 0.143) was associated with higher levels of plasma neurofilament light chain protein in treatment-resistant schizophrenia, but not in healthy controls. CONCLUSIONS The association between regional thickness reduction of the bilateral insula and left inferior temporal gyrus with plasma neurofilament light chain protein may reflect a neuroprogressive component to schizophrenia, which is not observed in the normal population.
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Affiliation(s)
- Brandon-Joe Cilia
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Melbourne Medical School, The University of Melbourne, Parkville, VIC, Australia
| | - Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
| | - Cassandra Wannan
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Charles Malpas
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Ian Everall
- Visiting Professor, King's College London, London, UK
| | - Chad Bousman
- Department of Medical Genetics, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Naveen Thomas
- Mental Health and Wellbeing Services, Western Health, St Albans VIC, Australia
| | - Alexander F Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
- Monash Institute of Pharmaceutical Sciences (MIPS), Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
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Squitti R, Fiorenza A, Martinelli A, Brembati V, Crescenti D, Rongioletti M, Ghidoni R. Neurofilament Light Protein as a Biomarker in Severe Mental Disorders: A Systematic Review. Int J Mol Sci 2024; 26:61. [PMID: 39795920 PMCID: PMC11719531 DOI: 10.3390/ijms26010061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2024] [Revised: 12/17/2024] [Accepted: 12/23/2024] [Indexed: 01/13/2025] Open
Abstract
Severe mental disorders (SMDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), are heterogeneous psychiatric diseases that impose a significant societal burden due to their chronic disabling nature. There are no objective and reliable diagnostic tests for SMDs; thus, there is an urgent need for specific biomarkers to improve diagnosis, treatment, and resource allocation. Neurofilaments, found in cerebrospinal fluid and blood, offer reliable diagnostic and prognostic potential. This review discusses the link between neurofilament light chain (NfL) involvement in psychiatric and neurodegenerative diseases and gives insights into the diagnostic and prognostic value of NfL in SMDs. This systematic review searched PubMed, Scopus, and Web of Science databases to answer the research question "Are NfL levels higher in individuals with SMDs compared to healthy controls?" using terms related to neurofilament, SMDs, SZ, BD, and depression. Of 8577 initial papers, 115 were relevant. After exclusions and manual additions, 17 articles were included. Studies indicate elevated NfL levels in SMDs compared to healthy controls, suggesting its potential as a biomarker for SMDs and for distinguishing neurodegenerative diseases from psychiatric disorders. However, further longitudinal research is needed to confirm its reliability for differential diagnosis, disease prediction, and treatment assessment in psychiatry.
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Affiliation(s)
- Rosanna Squitti
- Department of Laboratory Science, Research and Development Division, Ospedale Isola Tiberina—Gemelli Isola, 00186 Rome, Italy;
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (V.B.); (R.G.)
| | - Antonio Fiorenza
- Department of Psychology, Uninettuno University, 00186 Rome, Italy;
| | - Alessandra Martinelli
- Unit of Epidemiological and Evaluation Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy;
| | - Viviana Brembati
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (V.B.); (R.G.)
| | - Daniela Crescenti
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (V.B.); (R.G.)
| | - Mauro Rongioletti
- Department of Laboratory Science, Research and Development Division, Ospedale Isola Tiberina—Gemelli Isola, 00186 Rome, Italy;
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (V.B.); (R.G.)
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Berthet P, Haatveit BC, Kjelkenes R, Worker A, Kia SM, Wolfers T, Rutherford S, Alnaes D, Dinga R, Pedersen ML, Dahl A, Fernandez-Cabello S, Dazzan P, Agartz I, Nesvåg R, Ueland T, Andreassen OA, Simonsen C, Westlye LT, Melle I, Marquand A. A 10-Year Longitudinal Study of Brain Cortical Thickness in People with First-Episode Psychosis Using Normative Models. Schizophr Bull 2024; 51:95-107. [PMID: 38970378 PMCID: PMC11661960 DOI: 10.1093/schbul/sbae107] [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: 07/08/2024]
Abstract
BACKGROUND Clinical forecasting models have potential to optimize treatment and improve outcomes in psychosis, but predicting long-term outcomes is challenging and long-term follow-up data are scarce. In this 10-year longitudinal study, we aimed to characterize the temporal evolution of cortical correlates of psychosis and their associations with symptoms. DESIGN Structural magnetic resonance imaging (MRI) from people with first-episode psychosis and controls (n = 79 and 218) were obtained at enrollment, after 12 months (n = 67 and 197), and 10 years (n = 23 and 77), within the Thematically Organized Psychosis (TOP) study. Normative models for cortical thickness estimated on public MRI datasets (n = 42 983) were applied to TOP data to obtain deviation scores for each region and timepoint. Positive and Negative Syndrome Scale (PANSS) scores were acquired at each timepoint along with registry data. Linear mixed effects models assessed effects of diagnosis, time, and their interactions on cortical deviations plus associations with symptoms. RESULTS LMEs revealed conditional main effects of diagnosis and time × diagnosis interactions in a distributed cortical network, where negative deviations in patients attenuate over time. In patients, symptoms also attenuate over time. LMEs revealed effects of anterior cingulate on PANSS total, and insular and orbitofrontal regions on PANSS negative scores. CONCLUSIONS This long-term longitudinal study revealed a distributed pattern of cortical differences which attenuated over time together with a reduction in symptoms. These findings are not in line with a simple neurodegenerative account of schizophrenia, and deviations from normative models offer a promising avenue to develop biomarkers to track clinical trajectories over time.
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Affiliation(s)
- Pierre Berthet
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Beathe C Haatveit
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Rikka Kjelkenes
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Amanda Worker
- Department of Psychosis Studies, Institute of Psychiatry, King’s College, London, UK
| | - Seyed Mostafa Kia
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands
- Department of Psychiatry, Utrecht University Medical Center, Utrecht, the Netherlands
- Department Cognitive Science and Artificial Intelligence, Tilburg University, the Netherlands
| | - Thomas Wolfers
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
| | - Saige Rutherford
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Dag Alnaes
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Richard Dinga
- Department Cognitive Science and Artificial Intelligence, Tilburg University, the Netherlands
| | - Mads L Pedersen
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Paola Dazzan
- Department of Psychosis Studies, Institute of Psychiatry, King’s College, London, UK
| | - Ingrid Agartz
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ragnar Nesvåg
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Torill Ueland
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Carmen Simonsen
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Ingrid Melle
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Andre Marquand
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
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Ohi K, Fujikane D, Shioiri T. Genetic overlap between schizophrenia spectrum disorders and Alzheimer's disease: Current evidence and future directions - An integrative review. Neurosci Biobehav Rev 2024; 167:105900. [PMID: 39298993 DOI: 10.1016/j.neubiorev.2024.105900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Revised: 09/15/2024] [Accepted: 09/16/2024] [Indexed: 09/22/2024]
Abstract
Schizophrenia and Alzheimer's disease (AD) are distinct neurodegenerative disorders characterized by progressive cognitive deficits and structural alterations in the brain. Schizophrenia typically emerges in adolescence or early adulthood with symptoms such as hallucinations, delusions, and cognitive impairments, whereas AD primarily affects elderly individuals, causing progressive memory loss, cognitive decline, and behavioral changes. Delusional disorder, which often emerges later in life, shares some features with schizophrenia and is considered a schizophrenia spectrum disorder. Patients with schizophrenia or delusional disorder, particularly women and those aged 65 years or older, have an increased risk of developing AD later in life. In contrast, approximately 30 % of AD patients exhibit psychotic symptoms, which accelerate cognitive decline and worsen health outcomes. This integrative review explored the genetic overlap between schizophrenia spectrum disorders and AD to identify potential shared genetic factors. The genetic correlations between schizophrenia and AD were weak but positive (rg=0.03-0.10). Polygenic risk scores (PRSs) for schizophrenia and AD indicate some genetic predisposition, although findings are inconsistent among studies; e.g., PRS-schizophrenia or PRS-AD were associated with the risk of developing psychosis in patients with AD. A higher PRS for various developmental and psychiatric disorders was correlated with an earlier age at onset of schizophrenia. Research gaps include the need for studies on the impacts of PRS-AD on the risk of schizophrenia, genetic correlations between later-onset delusional disorder and AD, and genetic relationships between AD and late-onset schizophrenia (LOS) with a greater risk of progressing to AD. Further investigation into these genetic overlaps is crucial to enhance prevention, treatment, and prognosis for affected patients.
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Affiliation(s)
- Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan; Department of General Internal Medicine, Kanazawa Medical University, Ishikawa, Japan.
| | - Daisuke Fujikane
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Toshiki Shioiri
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
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Di Stefano V, D’Angelo M, Monaco F, Vignapiano A, Martiadis V, Barone E, Fornaro M, Steardo L, Solmi M, Manchia M, Steardo L. Decoding Schizophrenia: How AI-Enhanced fMRI Unlocks New Pathways for Precision Psychiatry. Brain Sci 2024; 14:1196. [PMID: 39766395 PMCID: PMC11674252 DOI: 10.3390/brainsci14121196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Revised: 11/24/2024] [Accepted: 11/25/2024] [Indexed: 01/11/2025] Open
Abstract
Schizophrenia, a highly complex psychiatric disorder, presents significant challenges in diagnosis and treatment due to its multifaceted neurobiological underpinnings. Recent advancements in functional magnetic resonance imaging (fMRI) and artificial intelligence (AI) have revolutionized the understanding and management of this condition. This manuscript explores how the integration of these technologies has unveiled key insights into schizophrenia's structural and functional neural anomalies. fMRI research highlights disruptions in crucial brain regions like the prefrontal cortex and hippocampus, alongside impaired connectivity within networks such as the default mode network (DMN). These alterations correlate with the cognitive deficits and emotional dysregulation characteristic of schizophrenia. AI techniques, including machine learning (ML) and deep learning (DL), have enhanced the detection and analysis of these complex patterns, surpassing traditional methods in precision. Algorithms such as support vector machines (SVMs) and Vision Transformers (ViTs) have proven particularly effective in identifying biomarkers and aiding early diagnosis. Despite these advancements, challenges such as variability in methodologies and the disorder's heterogeneity persist, necessitating large-scale, collaborative studies for clinical translation. Moreover, ethical considerations surrounding data integrity, algorithmic transparency, and patient individuality must guide AI's integration into psychiatry. Looking ahead, AI-augmented fMRI holds promise for tailoring personalized interventions, addressing unique neural dysfunctions, and improving therapeutic outcomes for individuals with schizophrenia. This convergence of neuroimaging and computational innovation heralds a transformative era in precision psychiatry.
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Affiliation(s)
- Valeria Di Stefano
- Psychiatry Unit, Department of Health Sciences, University of Catanzaro Magna Graecia, 88100 Catanzaro, Italy; (V.D.S.); (L.S.J.)
| | - Martina D’Angelo
- Psychiatry Unit, Department of Health Sciences, University of Catanzaro Magna Graecia, 88100 Catanzaro, Italy; (V.D.S.); (L.S.J.)
| | - Francesco Monaco
- Department of Mental Health, Azienda Sanitaria Locale Salerno, 84125 Salerno, Italy; (F.M.); (A.V.)
- European Biomedical Research Institute of Salerno (EBRIS), 84125 Salerno, Italy
| | - Annarita Vignapiano
- Department of Mental Health, Azienda Sanitaria Locale Salerno, 84125 Salerno, Italy; (F.M.); (A.V.)
- European Biomedical Research Institute of Salerno (EBRIS), 84125 Salerno, Italy
| | - Vassilis Martiadis
- Department of Mental Health, Azienda Sanitaria Locale (ASL) Napoli 1 Centro, 80145 Naples, Italy;
| | - Eugenia Barone
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy;
| | - Michele Fornaro
- Department of Neuroscience, Reproductive Science and Odontostomatology, University of Naples Federico II, 80138 Naples, Italy;
| | - Luca Steardo
- Department of Clinical Psychology, University Giustino Fortunato, 82100 Benevento, Italy;
- Department of Physiology and Pharmacology “Vittorio Erspamer”, SAPIENZA University of Rome, 00185 Rome, Italy
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, ON K1N 6N5, Canada;
- On Track: The Champlain First Episode Psychosis Program, Department of Mental Health, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Department of Child and Adolescent Psychiatry, Charité-Universitätsmedizin, 10117 Berlin, Germany
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09124 Cagliari, Italy;
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09123 Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, NS B3H 4R2, Canada
| | - Luca Steardo
- Psychiatry Unit, Department of Health Sciences, University of Catanzaro Magna Graecia, 88100 Catanzaro, Italy; (V.D.S.); (L.S.J.)
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6
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Kochunov P, Hong LE, Summerfelt A, Gao S, Brown PL, Terzi M, Acheson A, Woldorff MG, Fieremans E, Abdollahzadeh A, Sathyasaikumar KV, Clark SM, Schwarcz R, Shepard PD, Elmer GI. White matter and latency of visual evoked potentials during maturation: A miniature pig model of adolescent development. J Neurosci Methods 2024; 411:110252. [PMID: 39159872 DOI: 10.1016/j.jneumeth.2024.110252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 07/17/2024] [Accepted: 08/16/2024] [Indexed: 08/21/2024]
Abstract
BACKGROUND Continuous myelination of cerebral white matter (WM) during adolescence overlaps with the formation of higher cognitive skills and the onset of many neuropsychiatric disorders. We developed a miniature-pig model of adolescent brain development for neuroimaging and neurophysiological assessment during this critical period. Minipigs have gyroencephalic brains with a large cerebral WM compartment and a well-defined adolescence period. METHODS Eight Sinclair™ minipigs (Sus scrofa domestica) were evaluated four times during weeks 14-28 (40, 28 and 28 days apart) of adolescence using monocular visual stimulation (1 Hz)-evoked potentials and diffusion MRI (dMRI) of WM. The latency for the pre-positive 30 ms (PP30), positive 30 ms (P30) and negative 50 ms (N50) components of the flash visual evoked potentials (fVEPs) and their interhemispheric latency (IL) were recorded in the frontal, central and occipital areas during ten 60-second stimulations for each eye. The dMRI imaging protocol consisted of fifteen b-shells (b = 0-3500 s/mm2) with 32 directions/shell, providing measurements that included fractional anisotropy (FA), radial kurtosis, kurtosis anisotropy (KA), axonal water fraction (AWF), and the permeability-diffusivity index (PDI). RESULTS Significant reductions (p < 0.05) in the latency and IL of fVEP measurements paralleled significant rises in FA, KA, AWF and PDI over the same period. The longitudinal latency changes in fVEPs were primarily associated with whole-brain changes in diffusion parameters, while fVEP IL changes were related to maturation of the corpus callosum. CONCLUSIONS Good agreement between reduction in the latency of fVEPs and maturation of cerebral WM was interpreted as evidence for ongoing myelination and confirmation of the minipig as a viable research platform. Adolescent development in minipigs can be studied using human neuroimaging and neurophysiological protocols and followed up with more invasive assays to investigate key neurodevelopmental hypotheses in psychiatry.
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Affiliation(s)
- Peter Kochunov
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA; Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - L Elliot Hong
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ann Summerfelt
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Si Gao
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA; Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - P Leon Brown
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Matthew Terzi
- Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ashley Acheson
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Marty G Woldorff
- Center for Cognitive Neuroscience, Duke University, Durham, NC. USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Ali Abdollahzadeh
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Korrapati V Sathyasaikumar
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Sarah M Clark
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Robert Schwarcz
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paul D Shepard
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Greg I Elmer
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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7
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Zhang W, Zhai X, Zhang C, Cheng S, Zhang C, Bai J, Deng X, Ji J, Li T, Wang Y, Tong HHY, Li J, Li K. Regional brain structural network topology mediates the associations between white matter damage and disease severity in first-episode, Treatment-naïve pubertal children with major depressive disorder. Psychiatry Res Neuroimaging 2024; 344:111862. [PMID: 39153232 DOI: 10.1016/j.pscychresns.2024.111862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/22/2024] [Accepted: 07/31/2024] [Indexed: 08/19/2024]
Abstract
Puberty is a vulnerable period for the onset of major depressive disorder (MDD) due to considerable neurodevelopmental changes. Prior diffusion tensor imaging (DTI) studies in depressed youth have had heterogeneous participants, making assessment of early pathology challenging due to illness chronicity and medication confounds. This study leveraged whole-brain DTI and graph theory approaches to probe white matter (WM) abnormalities and disturbances in structural network topology related to first-episode, treatment-naïve pediatric MDD. Participants included 36 first-episode, unmedicated adolescents with MDD (mean age 15.8 years) and 29 age- and sex-matched healthy controls (mean age 15.2 years). Compared to controls, the MDD group showed reduced fractional anisotropy in the internal and external capsules, unveiling novel regions of WM disruption in early-onset depression. The right thalamus and superior temporal gyrus were identified as network hubs where betweenness centrality changes mediated links between WM anomalies and depression severity. A diagnostic model incorporating demographics, DTI, and network metrics achieved an AUROC of 0.88 and a F1 score of 0.80 using a neural network algorithm. By examining first-episode, treatment-naïve patients, this work identified novel WM abnormalities and a potential causal pathway linking WM damage to symptom severity via regional structural network alterations in brain hubs.
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Affiliation(s)
- Wenjie Zhang
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Xiaobing Zhai
- Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
| | - Chan Zhang
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Song Cheng
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Chaoqing Zhang
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Jinji Bai
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Xuan Deng
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Junjun Ji
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
| | - Ting Li
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Yu Wang
- Department of Psychiatry, Changzhi Mental Health Center, Changzhi, Shanxi, China
| | - Henry H Y Tong
- Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
| | - Junfeng Li
- Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China; Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China
| | - Kefeng Li
- Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China.
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8
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Mana L, Schwartz-Pallejà M, Vila-Vidal M, Deco G. Overview on cognitive impairment in psychotic disorders: From impaired microcircuits to dysconnectivity. Schizophr Res 2024; 269:132-143. [PMID: 38788432 DOI: 10.1016/j.schres.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
Schizophrenia's cognitive deficits, often overshadowed by positive symptoms, significantly contribute to the disorder's morbidity. Increasing attention highlights these deficits as reflections of neural circuit dysfunction across various cortical regions. Numerous connectivity alterations linked to cognitive symptoms in psychotic disorders have been reported, both at the macroscopic and microscopic level, emphasizing the potential role of plasticity and microcircuits impairment during development and later stages. However, the heterogeneous clinical presentation of cognitive impairment and diverse connectivity findings pose challenges in summarizing them into a cohesive picture. This review aims to synthesize major cognitive alterations, recent insights into network structural and functional connectivity changes and proposed mechanisms and microcircuit alterations underpinning these symptoms, particularly focusing on neurodevelopmental impairment, E/I balance, and sleep disturbances. Finally, we will also comment on some of the most recent and promising therapeutic approaches that aim to target these mechanisms to address cognitive symptoms. Through this comprehensive exploration, we strive to provide an updated and nuanced overview of the multiscale connectivity impairment underlying cognitive impairment in psychotic disorders.
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Affiliation(s)
- L Mana
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain.
| | - M Schwartz-Pallejà
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Department of Experimental and Health Science, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Eurecat, Technology Center of Catalonia, Multimedia Technologies, Barcelona, Spain.
| | - M Vila-Vidal
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Computational Biology and Complex Systems Group, Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
| | - G Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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9
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Panikratova YR, Tomyshev AS, Abdullina EG, Rodionov GI, Arkhipov AY, Tikhonov DV, Bozhko OV, Kaleda VG, Strelets VB, Lebedeva IS. Resting-state functional connectivity correlates of brain structural aging in schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01837-5. [PMID: 38914851 DOI: 10.1007/s00406-024-01837-5] [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] [Received: 11/07/2023] [Accepted: 05/27/2024] [Indexed: 06/26/2024]
Abstract
A large body of research has shown that schizophrenia patients demonstrate increased brain structural aging. Although this process may be coupled with aberrant changes in intrinsic functional architecture of the brain, they remain understudied. We hypothesized that there are brain regions whose whole-brain functional connectivity at rest is differently associated with brain structural aging in schizophrenia patients compared to healthy controls. Eighty-four male schizophrenia patients and eighty-six male healthy controls underwent structural MRI and resting-state fMRI. The brain-predicted age difference (b-PAD) was a measure of brain structural aging. Resting-state fMRI was applied to obtain global correlation (GCOR) maps comprising voxelwise values of the strength and sign of functional connectivity of a given voxel with the rest of the brain. Schizophrenia patients had higher b-PAD compared to controls (mean between-group difference + 2.9 years). Greater b-PAD in schizophrenia patients, compared to controls, was associated with lower whole-brain functional connectivity of a region in frontal orbital cortex, inferior frontal gyrus, Heschl's Gyrus, plana temporale and polare, insula, and opercular cortices of the right hemisphere (rFTI). According to post hoc seed-based correlation analysis, decrease of functional connectivity with the posterior cingulate gyrus, left superior temporal cortices, as well as right angular gyrus/superior lateral occipital cortex has mainly driven the results. Lower functional connectivity of the rFTI was related to worse verbal working memory and language production. Our findings demonstrate that well-established frontotemporal functional abnormalities in schizophrenia are related to increased brain structural aging.
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Affiliation(s)
| | | | | | - Georgiy I Rodionov
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
| | - Andrey Yu Arkhipov
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
| | | | | | | | - Valeria B Strelets
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
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10
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Patterson EJ, Bounds AD, Wagner SK, Kadri-Langford R, Taylor R, Daly D. Oculomics: A Crusade Against the Four Horsemen of Chronic Disease. Ophthalmol Ther 2024; 13:1427-1451. [PMID: 38630354 PMCID: PMC11109082 DOI: 10.1007/s40123-024-00942-x] [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: 02/02/2024] [Accepted: 03/25/2024] [Indexed: 05/22/2024] Open
Abstract
Chronic, non-communicable diseases present a major barrier to living a long and healthy life. In many cases, early diagnosis can facilitate prevention, monitoring, and treatment efforts, improving patient outcomes. There is therefore a critical need to make screening techniques as accessible, unintimidating, and cost-effective as possible. The association between ocular biomarkers and systemic health and disease (oculomics) presents an attractive opportunity for detection of systemic diseases, as ophthalmic techniques are often relatively low-cost, fast, and non-invasive. In this review, we highlight the key associations between structural biomarkers in the eye and the four globally leading causes of morbidity and mortality: cardiovascular disease, cancer, neurodegenerative disease, and metabolic disease. We observe that neurodegenerative disease is a particularly promising target for oculomics, with biomarkers detected in multiple ocular structures. Cardiovascular disease biomarkers are present in the choroid, retinal vasculature, and retinal nerve fiber layer, and metabolic disease biomarkers are present in the eyelid, tear fluid, lens, and retinal vasculature. In contrast, only the tear fluid emerged as a promising ocular target for the detection of cancer. The retina is a rich source of oculomics data, the analysis of which has been enhanced by artificial intelligence-based tools. Although not all biomarkers are disease-specific, limiting their current diagnostic utility, future oculomics research will likely benefit from combining data from various structures to improve specificity, as well as active design, development, and optimization of instruments that target specific disease signatures, thus facilitating differential diagnoses.
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Affiliation(s)
| | | | - Siegfried K Wagner
- Moorfields Eye Hospital NHS Trust, 162 City Road, London, EC1V 2PD, UK
- UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK
| | | | - Robin Taylor
- Occuity, The Blade, Abbey Square, Reading, Berkshire, RG1 3BE, UK
| | - Dan Daly
- Occuity, The Blade, Abbey Square, Reading, Berkshire, RG1 3BE, UK
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11
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Cilia BJ, Eratne D, Wannan C, Malpas C, Janelidze S, Hansson O, Everall I, Bousman C, Thomas N, Santillo AF, Velakoulis D, Pantelis C. Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.07.24305362. [PMID: 38645076 PMCID: PMC11030485 DOI: 10.1101/2024.04.07.24305362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background and Hypothesis Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia; TRS). While abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often observed in schizophrenia, it is anticipated that biomarkers of neuronal injury like neurofilament light chain protein (NfL) can improve our understanding of the pathological basis underlying schizophrenia. The current study aimed to determine whether people with TRS demonstrate different associations between plasma NfL levels and regional cortical thickness reductions compared with controls. Study Design Measurements of plasma NfL and cortical thickness were obtained from 39 individuals with TRS, and 43 healthy controls. T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer. General linear mixed models adjusting for age and weight were estimated to determine whether the interaction between diagnostic group and plasma NfL level predicted lower cortical thickness across frontotemporal structures and the insula. Study Results Significant (false discovery rate corrected) cortical thinning of the left (p = 0.001, η2p = 0.104) and right (p < 0.001, η2p = 0.167) insula was associated with higher levels of plasma NfL in TRS, but not in healthy controls. Conclusions The association between regional thickness reduction of the insula bilaterally and plasma NfL may reflect a neurodegenerative process during the course of TRS. The findings of the present study suggest that some level of cortical degeneration localised to the bilateral insula may exist in people with TRS, which is not observed in the normal population.
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Affiliation(s)
- Brandon-Joe Cilia
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Melbourne Medical School, The University of Melbourne, Parkville, VIC, Australia
| | - Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
| | - Cassandra Wannan
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Charles Malpas
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | - Chad Bousman
- Department of Medical Genetics, University of Calgary
- Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Naveen Thomas
- Mental Health and Wellbeing Services, Western Health, St Albans VIC, Australia
| | - Alexander F Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
- Monash Institute of Pharmaceutical Sciences (MIPS), Faculty of Pharmacy and Pharmaceutical Sciences Monash University, Parkville, VIC, Australia
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Seitz-Holland J, Haas SS, Penzel N, Reichenberg A, Pasternak O. BrainAGE, brain health, and mental disorders: A systematic review. Neurosci Biobehav Rev 2024; 159:105581. [PMID: 38354871 PMCID: PMC11119273 DOI: 10.1016/j.neubiorev.2024.105581] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/05/2024] [Accepted: 02/09/2024] [Indexed: 02/16/2024]
Abstract
The imaging-based method of brainAGE aims to characterize an individual's vulnerability to age-related brain changes. The present study systematically reviewed brainAGE findings in neuropsychiatric conditions and discussed the potential of brainAGE as a marker for biological age. A systematic PubMed search (from inception to March 6th, 2023) identified 273 articles. The 30 included studies compared brainAGE between neuropsychiatric and healthy groups (n≥50). We presented results qualitatively and adapted a bias risk assessment questionnaire. The imaging modalities, design, and input features varied considerably between studies. While the studies found higher brainAGE in neuropsychiatric conditions (11 mild cognitive impairment/ dementia, 11 schizophrenia spectrum/ other psychotic and bipolar disorder, six depression/ anxiety, two multiple groups), the associations with clinical characteristics were mixed. While brainAGE is sensitive to group differences, limitations include the lack of diverse training samples, multi-modal studies, and external validation. Only a few studies obtained longitudinal data, and all have used algorithms built solely to predict chronological age. These limitations impede the validity of brainAGE as a biological age marker.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nora Penzel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Abraham Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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13
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Yu K, Zhou H, Chen Z, Lei Y, Wu J, Yuan Q, He J. Mechanism of cognitive impairment and white matter damage in the MK-801 mice model of schizophrenia treated with quetiapine. Behav Brain Res 2024; 461:114838. [PMID: 38157989 DOI: 10.1016/j.bbr.2023.114838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/11/2023] [Accepted: 12/23/2023] [Indexed: 01/03/2024]
Abstract
Schizophrenia has been linked to cognitive impairment and white matter damage in a growing number of studies this year. In this study, we used the MK-801-induced schizophrenia-like mice model to investigate the effects of quetiapine on behavioral changes and myelin loss in the model mice. The subjects selected for this study were C57B6/J male mice, MK-801 (1 mg/kg/d intraperitoneal injection) modeling for 1 week and quetiapine (10 mg/kg/d intraperitoneal injection) treatment for 2 weeks. Behavioral tests were then performed using the three-chamber paradigm test and the Y maze test. Moreover, western blot, immunohistochemistry, and immunofluorescence were conducted to investigate the changes in oligodendrocyte spectrum markers. In addition, we performed some mechanism-related proteins by western blot. Quetiapine ameliorated cognitive impairment and cerebral white matter damage in MK-801 model mice, and the mechanism may be related to the PI3K/AKT pathways. The present study suggests that quetiapine has a possible mechanism for treating cognitive impairment and white matter damage caused by schizophrenia.
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Affiliation(s)
- Kai Yu
- School of Mental Health and the Affiliated Kangning Hospital, Wenzhou Key Laboratory for Basic and Translational Research in Mental Health, Zhejiang Provincial Clinical Research Center for Mental Disorders, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Han Zhou
- School of Mental Health and the Affiliated Kangning Hospital, Wenzhou Key Laboratory for Basic and Translational Research in Mental Health, Zhejiang Provincial Clinical Research Center for Mental Disorders, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhuo Chen
- School of Mental Health and the Affiliated Kangning Hospital, Wenzhou Key Laboratory for Basic and Translational Research in Mental Health, Zhejiang Provincial Clinical Research Center for Mental Disorders, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yuying Lei
- School of Mental Health and the Affiliated Kangning Hospital, Wenzhou Key Laboratory for Basic and Translational Research in Mental Health, Zhejiang Provincial Clinical Research Center for Mental Disorders, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Junnan Wu
- School of Mental Health and the Affiliated Kangning Hospital, Wenzhou Key Laboratory for Basic and Translational Research in Mental Health, Zhejiang Provincial Clinical Research Center for Mental Disorders, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Qianfa Yuan
- Xiamen Xian Yue Hospital, Xiamen, Fujian, China
| | - Jue He
- School of Mental Health and the Affiliated Kangning Hospital, Wenzhou Key Laboratory for Basic and Translational Research in Mental Health, Zhejiang Provincial Clinical Research Center for Mental Disorders, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China; Institute of Neurological Disease, First Affiliated Hospital, Henan University, Kaifeng, Henan, China.
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14
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Klaassen AL, Michel C, Stüble M, Kaess M, Morishima Y, Kindler J. Reduced anterior callosal white matter in risk for psychosis associated with processing speed as a fundamental cognitive impairment. Schizophr Res 2024; 264:211-219. [PMID: 38157681 DOI: 10.1016/j.schres.2023.12.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/29/2023] [Accepted: 12/17/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Previous research in psychotic disorders discovered associations between reduced integrity of white matter (WM) in the corpus callosum (CC) and impaired cognitive functions, suggesting processing speed as a central construct. However, it is still largely unexplored to what extent disruption in callosal WM is related to cognitive deficits during the risk stage prior to psychosis. METHODS To address this gap, we measured the WM integrity in CC by fractional anisotropy (FA) and assessed cognition in 60 clinical-high risk for psychosis (CHR) patients during adolescence/young adulthood and 38 healthy control (HC) subjects. We employed tract based spatial statistics to examine group differences and associations between CC-FA and processing speed, executive function, and spatial working memory. RESULTS We revealed deficits in processing speed, executive function, and spatial working memory of CHR patients, and reductions in FA of the genu and the body of the CC (p < 0.05, corrected for multiple comparisons) compared to HC. A mediation analysis using the combined sample (CHR + HC) showed that processing speed mediates the associations between the impaired CC structure and executive function and spatial working memory, respectively. Exploratory analyses between CC-FA and the cognitive domains located associations of processing speed in the genu and the body of CC with distinct spatial distributions of executive function and spatial working memory. CONCLUSION We suggest processing speed as a subordinate cognitive factor contributing to the associations between callosal WM, executive function and working memory. These results extend findings in psychotic disorders to the prior risk stage.
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Affiliation(s)
- Arndt-Lukas Klaassen
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy Bern, University of Bern, Switzerland.
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy Bern, University of Bern, Switzerland
| | - Miriam Stüble
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy Bern, University of Bern, Switzerland; Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy Bern, University of Bern, Switzerland; University Hospital Heidelberg, Department of Child and Adolescent Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Germany
| | - Yosuke Morishima
- University Hospital of Psychiatry Bern, Department of Psychiatric Neurophysiology, University of Bern, Switzerland
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy Bern, University of Bern, Switzerland
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15
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Xenaki LA, Dimitrakopoulos S, Selakovic M, Stefanis N. Stress, Environment and Early Psychosis. Curr Neuropharmacol 2024; 22:437-460. [PMID: 37592817 PMCID: PMC10845077 DOI: 10.2174/1570159x21666230817153631] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/02/2023] [Accepted: 01/04/2023] [Indexed: 08/19/2023] Open
Abstract
Existing literature provides extended evidence of the close relationship between stress dysregulation, environmental insults, and psychosis onset. Early stress can sensitize genetically vulnerable individuals to future stress, modifying their risk for developing psychotic phenomena. Neurobiological substrate of the aberrant stress response to hypothalamic-pituitary-adrenal axis dysregulation, disrupted inflammation processes, oxidative stress increase, gut dysbiosis, and altered brain signaling, provides mechanistic links between environmental risk factors and the development of psychotic symptoms. Early-life and later-life exposures may act directly, accumulatively, and repeatedly during critical neurodevelopmental time windows. Environmental hazards, such as pre- and perinatal complications, traumatic experiences, psychosocial stressors, and cannabis use might negatively intervene with brain developmental trajectories and disturb the balance of important stress systems, which act together with recent life events to push the individual over the threshold for the manifestation of psychosis. The current review presents the dynamic and complex relationship between stress, environment, and psychosis onset, attempting to provide an insight into potentially modifiable factors, enhancing resilience and possibly influencing individual psychosis liability.
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Affiliation(s)
- Lida-Alkisti Xenaki
- First Department of Psychiatry, School of Medicine, Eginition Hospital, National and Kapodistrian University of Athens, 72 Vas. Sophias Ave., Athens, 115 28, Greece
| | - Stefanos Dimitrakopoulos
- First Department of Psychiatry, School of Medicine, Eginition Hospital, National and Kapodistrian University of Athens, 72 Vas. Sophias Ave., Athens, 115 28, Greece
| | - Mirjana Selakovic
- First Department of Psychiatry, School of Medicine, Eginition Hospital, National and Kapodistrian University of Athens, 72 Vas. Sophias Ave., Athens, 115 28, Greece
| | - Nikos Stefanis
- First Department of Psychiatry, School of Medicine, Eginition Hospital, National and Kapodistrian University of Athens, 72 Vas. Sophias Ave., Athens, 115 28, Greece
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16
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Van Dyken PC, MacKinley M, Khan AR, Palaniyappan L. Cortical Network Disruption Is Minimal in Early Stages of Psychosis. SCHIZOPHRENIA BULLETIN OPEN 2024; 5:sgae010. [PMID: 39144115 PMCID: PMC11207789 DOI: 10.1093/schizbullopen/sgae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Background and Hypothesis Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness. Study Design Diffusion and T1-weighted 7T MR scans were obtained from N = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with N = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset. Study Results Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics. Conclusions The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.
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Affiliation(s)
- Peter C Van Dyken
- Neuroscience Graduate Program, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Michael MacKinley
- Lawson Health Research Institute, London Health Sciences Centre, London, ON, Canada
| | - Ali R Khan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, London, ON, Canada
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
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17
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Davies MR, Greenberg Z, van Vuurden DG, Cross CB, Zannettino ACW, Bardy C, Wardill HR. More than a small adult brain: Lessons from chemotherapy-induced cognitive impairment for modelling paediatric brain disorders. Brain Behav Immun 2024; 115:229-247. [PMID: 37858741 DOI: 10.1016/j.bbi.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 10/10/2023] [Accepted: 10/14/2023] [Indexed: 10/21/2023] Open
Abstract
Childhood is recognised as a period of immense physical and emotional development, and this, in part, is driven by underlying neurophysiological transformations. These neurodevelopmental processes are unique to the paediatric brain and are facilitated by augmented rates of neuroplasticity and expanded neural stem cell populations within neurogenic niches. However, given the immaturity of the developing central nervous system, innate protective mechanisms such as neuroimmune and antioxidant responses are functionally naïve which results in periods of heightened sensitivity to neurotoxic insult. This is highly relevant in the context of paediatric cancer, and in particular, the neurocognitive symptoms associated with treatment, such as surgery, radio- and chemotherapy. The vulnerability of the developing brain may increase susceptibility to damage and persistent symptomology, aligning with reports of more severe neurocognitive dysfunction in children compared to adults. It is therefore surprising, given this intensified neurocognitive burden, that most of the pre-clinical, mechanistic research focuses exclusively on adult populations and extrapolates findings to paediatric cohorts. Given this dearth of age-specific research, throughout this review we will draw comparisons with neurodevelopmental disorders which share comparable pathways to cancer treatment related side-effects. Furthermore, we will examine the unique nuances of the paediatric brain along with the somatic systems which influence neurological function. In doing so, we will highlight the importance of developing in vitro and in vivo paediatric disease models to produce age-specific discovery and clinically translatable research.
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Affiliation(s)
- Maya R Davies
- School of Biomedicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, Australia; Supportive Oncology Research Group, Precision Cancer Medicine Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia.
| | - Zarina Greenberg
- South Australian Health and Medical Research Institute (SAHMRI), Laboratory of Human Neurophysiology and Genetics, Adelaide, SA, Australia
| | - Dannis G van Vuurden
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS Utrecht, the weNetherlands
| | - Courtney B Cross
- Supportive Oncology Research Group, Precision Cancer Medicine Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia
| | - Andrew C W Zannettino
- School of Biomedicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, Australia
| | - Cedric Bardy
- South Australian Health and Medical Research Institute (SAHMRI), Laboratory of Human Neurophysiology and Genetics, Adelaide, SA, Australia; Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Hannah R Wardill
- School of Biomedicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, Australia; Supportive Oncology Research Group, Precision Cancer Medicine Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia
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Howes OD, Bukala BR, Beck K. Schizophrenia: from neurochemistry to circuits, symptoms and treatments. Nat Rev Neurol 2024; 20:22-35. [PMID: 38110704 DOI: 10.1038/s41582-023-00904-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2023] [Indexed: 12/20/2023]
Abstract
Schizophrenia is a leading cause of global disability. Current pharmacotherapy for the disease predominantly uses one mechanism - dopamine D2 receptor blockade - but often shows limited efficacy and poor tolerability. These limitations highlight the need to better understand the aetiology of the disease to aid the development of alternative therapeutic approaches. Here, we review the latest meta-analyses and other findings on the neurobiology of prodromal, first-episode and chronic schizophrenia, and the link to psychotic symptoms, focusing on imaging evidence from people with the disorder. This evidence demonstrates regionally specific neurotransmitter alterations, including higher glutamate and dopamine measures in the basal ganglia, and lower glutamate, dopamine and γ-aminobutyric acid (GABA) levels in cortical regions, particularly the frontal cortex, relative to healthy individuals. We consider how dysfunction in cortico-thalamo-striatal-midbrain circuits might alter brain information processing to underlie psychotic symptoms. Finally, we discuss the implications of these findings for developing new, mechanistically based treatments and precision medicine for psychotic symptoms, as well as negative and cognitive symptoms.
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Affiliation(s)
- Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Faculty of Medicine, Institute of Clinical Sciences, Imperial College London, London, UK.
| | - Bernard R Bukala
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Katherine Beck
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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19
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Luo Y, Dong D, Huang H, Zhou J, Zuo X, Hu J, He H, Jiang S, Duan M, Yao D, Luo C. Associating Multimodal Neuroimaging Abnormalities With the Transcriptome and Neurotransmitter Signatures in Schizophrenia. Schizophr Bull 2023; 49:1554-1567. [PMID: 37607339 PMCID: PMC10686354 DOI: 10.1093/schbul/sbad047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is a multidimensional disease. This study proposes a new research framework that combines multimodal meta-analysis and genetic/molecular architecture to solve the consistency in neuroimaging biomarkers of schizophrenia and whether these link to molecular genetics. STUDY DESIGN We systematically searched Web of Science, PubMed, and BrainMap for the amplitude of low-frequency fluctuations (ALFF) or fractional ALFF, regional homogeneity, regional cerebral blood flow, and voxel-based morphometry analysis studies investigating schizophrenia. The pooled-modality, single-modality, and illness duration-dependent meta-analyses were performed using the activation likelihood estimation algorithm. Subsequently, Spearman correlation and partial least squares regression analyses were conducted to assess the relationship between identified reliable convergent patterns of multimodality and neurotransmitter/transcriptome, using prior molecular imaging and brain-wide gene expression. STUDY RESULTS In total, 203 experiments comprising 10 613 patients and 10 461 healthy controls were included. Multimodal meta-analysis showed that brain regions of significant convergence in schizophrenia were mainly distributed in the frontotemporal cortex, anterior cingulate cortex, insula, thalamus, striatum, and hippocampus. Interestingly, the analyses of illness-duration subgroups identified aberrant functional and structural evolutionary patterns: Lines from the striatum to the cortical core networks to extensive cortical and subcortical regions. Subsequently, we found that these robust multimodal neuroimaging abnormalities were associated with multiple neurobiological abnormalities, such as dopaminergic, glutamatergic, serotonergic, and GABAergic systems. CONCLUSIONS This work links transcriptome/neurotransmitters with reliable structural and functional signatures of brain abnormalities underlying disease effects in schizophrenia, which provides novel insight into the understanding of schizophrenia pathophysiology and targeted treatments.
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Affiliation(s)
- Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Debo Dong
- Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaojun Zuo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jian Hu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Mental Health Center of Chengdu, The fourth people’s Hospital of Chengdu, Chengdu, China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Mental Health Center of Chengdu, The fourth people’s Hospital of Chengdu, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
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20
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Kochunov P, Ma Y, Hatch KS, Gao S, Acheson A, Jahanshad N, Thompson PM, Adhikari BM, Bruce H, Van der Vaart A, Chiappelli J, Du X, Sotiras A, Kvarta MD, Ma T, Chen S, Hong LE. Ancestral, Pregnancy, and Negative Early-Life Risks Shape Children's Brain (Dis)similarity to Schizophrenia. Biol Psychiatry 2023; 94:332-340. [PMID: 36948435 PMCID: PMC10511664 DOI: 10.1016/j.biopsych.2023.03.009] [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: 10/14/2022] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Familial, obstetric, and early-life environmental risks for schizophrenia spectrum disorder (SSD) alter normal cerebral development, leading to the formation of characteristic brain deficit patterns prior to onset of symptoms. We hypothesized that the insidious effects of these risks may increase brain similarity to adult SSD deficit patterns in prepubescent children. METHODS We used data collected by the Adolescent Brain Cognitive Development (ABCD) Study (N = 8940, age = 9.9 ± 0.1 years, 4307/4633 female/male), including 727 (age = 9.9 ± 0.1 years, 351/376 female/male) children with family history of SSD, to evaluate unfavorable cerebral effects of ancestral SSD history, pre/perinatal environment, and negative early-life environment. We used a regional vulnerability index to measure the alignment of a child's cerebral patterns with the adult SSD pattern derived from a large meta-analysis of case-control differences. RESULTS In children with a family history of SSD, the regional vulnerability index captured significantly more variance in ancestral history than traditional whole-brain and regional brain measurements. In children with and without family history of SSD, the regional vulnerability index also captured more variance associated with negative pre/perinatal environment and early-life experiences than traditional brain measurements. CONCLUSIONS In summary, in a cohort in which most children will not develop SSD, familial, pre/perinatal, and early developmental risks can alter brain patterns in the direction observed in adult patients with SSD. Individual similarity to adult SSD patterns may provide an early biomarker of the effects of genetic and developmental risks on the brain prior to psychotic or prodromal symptom onset.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland.
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Ashley Acheson
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Andrew Van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Aris Sotiras
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, University of Maryland, College Park, Maryland
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
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21
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Waszkiewicz N. The Immunoseasonal Theory of Psychiatric Disorders. J Clin Med 2023; 12:4615. [PMID: 37510730 PMCID: PMC10380681 DOI: 10.3390/jcm12144615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/26/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
Although the influence of the weather on the well-being and mental health of psychiatric patients has been widely seen, the relationships between various seasonal weather factors and depressive, manic, anxiety, and psychotic states have not been systematized in the literature. The current article describes the seasonal changes in weather-related immune responses and their impact on the development of episodes of depression, mania, psychosis, and anxiety, highlighting the T-helper 1 (Th1) and Th2 immune balance as their potential trigger. In autumn-winter depression, the hyperactivation of the Th1 system, possibly by microbial/airborne pathogens, may lead to the inflammatory inhibition of prefrontal activity and the subcortical centers responsible for mood, drive, and motivation. Depressive mood periods are present in most people suffering from schizophrenia. In the spring and summertime, when the compensating anti-Th1 property of the Th2 immune system is activated, it decreases the Th1 response. In individuals immunogenetically susceptible to psychosis and mania, the inhibition of Th1 by the Th2 system may be excessive and lead to Th2-related frontal and subcortical hyperactivation and subsequent psychosis. In people suffering from bipolar disorder, hyperintense changes in white matter may be responsible for the partial activation of subcortical areas, preventing full paranoid psychosis. Thus, psychosis may be mood-congruent in affective disorders.
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Affiliation(s)
- Napoleon Waszkiewicz
- Department of Psychiatry, Medical University of Białystok, Wołodyjowskiego 2, 15-272 Białystok, Poland
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22
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Jiang S, Huang H, Zhou J, Li H, Duan M, Yao D, Luo C. Progressive trajectories of schizophrenia across symptoms, genes, and the brain. BMC Med 2023; 21:237. [PMID: 37400838 PMCID: PMC10318676 DOI: 10.1186/s12916-023-02935-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 06/12/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND Schizophrenia is characterized by complex psychiatric symptoms and unclear pathological mechanisms. Most previous studies have focused on the morphological changes that occur over the development of the disease; however, the corresponding functional trajectories remain unclear. In the present study, we aimed to explore the progressive trajectories of patterns of dysfunction after diagnosis. METHODS Eighty-six patients with schizophrenia and 120 healthy controls were recruited as the discovery dataset. Based on multiple functional indicators of resting-state brain functional magnetic resonance imaging, we conducted a duration-sliding dynamic analysis framework to investigate trajectories in association with disease progression. Neuroimaging findings were associated with clinical symptoms and gene expression data from the Allen Human Brain Atlas database. A replication cohort of patients with schizophrenia from the University of California, Los Angeles, was used as the replication dataset for the validation analysis. RESULTS Five stage-specific phenotypes were identified. A symptom trajectory was characterized by positive-dominated, negative ascendant, negative-dominated, positive ascendant, and negative surpassed stages. Dysfunctional trajectories from primary and subcortical regions to higher-order cortices were recognized; these are associated with abnormal external sensory gating and a disrupted internal excitation-inhibition equilibrium. From stage 1 to stage 5, the importance of neuroimaging features associated with behaviors gradually shifted from primary to higher-order cortices and subcortical regions. Genetic enrichment analysis identified that neurodevelopmental and neurodegenerative factors may be relevant as schizophrenia progresses and highlighted multiple synaptic systems. CONCLUSIONS Our convergent results indicate that progressive symptoms and functional neuroimaging phenotypes are associated with genetic factors in schizophrenia. Furthermore, the identification of functional trajectories complements previous findings of structural abnormalities and provides potential targets for drug and non-drug interventions in different stages of schizophrenia.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Mingjun Duan
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China.
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China.
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China.
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23
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Langhein M, Lyall AE, Steinmann S, Seitz-Holland J, Nägele FL, Cetin-Karayumak S, Zhang F, Rauh J, Mußmann M, Billah T, Makris N, Pasternak O, O’Donnell LJ, Rathi Y, Leicht G, Kubicki M, Shenton ME, Mulert C. The decoupling of structural and functional connectivity of auditory networks in individuals at clinical high-risk for psychosis. World J Biol Psychiatry 2023; 24:387-399. [PMID: 36083108 PMCID: PMC10399965 DOI: 10.1080/15622975.2022.2112974] [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: 04/20/2022] [Revised: 08/09/2022] [Accepted: 08/10/2022] [Indexed: 10/14/2022]
Abstract
OBJECTIVES Disrupted auditory networks play an important role in the pathophysiology of psychosis, with abnormalities already observed in individuals at clinical high-risk for psychosis (CHR). Here, we examine structural and functional connectivity of an auditory network in CHR utilising state-of-the-art electroencephalography and diffusion imaging techniques. METHODS Twenty-six CHR subjects and 13 healthy controls (HC) underwent diffusion MRI and electroencephalography while performing an auditory task. We investigated structural connectivity, measured as fractional anisotropy in the Arcuate Fasciculus (AF), Cingulum Bundle, and Superior Longitudinal Fasciculus-II. Gamma-band lagged-phase synchronisation, a functional connectivity measure, was calculated between cortical regions connected by these tracts. RESULTS CHR subjects showed significantly higher structural connectivity in the right AF than HC (p < .001). Although non-significant, functional connectivity between cortical areas connected by the AF was lower in CHR than HC (p = .078). Structural and functional connectivity were correlated in HC (p = .056) but not in CHR (p = .29). CONCLUSIONS We observe significant differences in structural connectivity of the AF, without a concomitant significant change in functional connectivity in CHR subjects. This may suggest that the CHR state is characterised by a decoupling of structural and functional connectivity, possibly due to abnormal white matter maturation.
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Affiliation(s)
- Mina Langhein
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Saskia Steinmann
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Felix L. Nägele
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Suheyla Cetin-Karayumak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Jonas Rauh
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marius Mußmann
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tashrif Billah
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, 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
| | - Lauren J O’Donnell
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, 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
| | - Gregor Leicht
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Christoph Mulert
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Centre for Psychiatry, Justus-Liebig-University, Giessen, Germany
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24
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Brito A, Franco F, Brentani H, Beltrão-Braga PCB. Assessment of vulnerability dimensions considering Family History and environmental interplay in Autism Spectrum Disorder. BMC Psychiatry 2023; 23:254. [PMID: 37059985 PMCID: PMC10105456 DOI: 10.1186/s12888-023-04747-3] [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] [Received: 09/12/2022] [Accepted: 04/03/2023] [Indexed: 04/16/2023] Open
Abstract
BACKGROUND Despite previous studies have recently shown Autism Spectrum Disorders (ASD) as having a strong genetics background, over a minimum environmental background, no study up to date has investigated the interplay between genetics and environment. METHODS We have collected data regarding Family History (FH) and Environmental Factors (EF) from 2,141 individuals with ASD and their caretakers throughout Brazil, based on an online questionnaire. Most of the ASD individuals were males (81%) and the average age was 02 years minimum for males and females, and the maximum age was 41 years for males and 54 for females. People from all states in Brazil have answered the questionnaire. Genetic inheritance was obtained based on the declared FH of Psychiatric and Neurological diagnosis. As for EF, exposure to risk factors during pregnancy was considered, like infections, diabetes, drugs/chemicals exposure, socioeconomic, and psychological factors. Respondents were invited to answer the questionnaire in lectures given throughout Brazil, and by the social networks of the NGO "The Tooth Fairy Project". A Multiple Correspondence Analysis (MCA) was conducted to search vulnerability dimensions, and a Cluster Analysis was conducted to classify and identify the subgroups. RESULTS Regarding EF, social and psychological exposures contributed to the first two dimensions. Concerning FH, the first dimension represented psychiatric FH, while the second represented neurological FH. When analyzed together, EF and FH contributed to two new dimensions: 1. psychiatric FH, and 2. a psychosocial component. Using Cluster Analysis, it was not possible to isolate subgroups by genetic vulnerability or environmental exposure. Instead, a gradient of psychiatric FH with similar contributions of EF was observed. CONCLUSION In this study, it was not possible to isolate groups of patients that correspond to only one component, but rather a continuum with different compositions of genetic and environmental interplay.
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Affiliation(s)
- Anita Brito
- Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
- Scientific Platform Pasteur-USP, São Paulo, SP, Brazil
| | - Felipe Franco
- Psychiatry Institute, University of São Paulo's Faculty of Medicine (IPq-FMUSP), São Paulo, SP, Brazil
- Interunit Postgraduate Program On Bioinformatics, Institute of Mathematics and Statistics (IME), University of São Paulo, São Paulo, SP, Brazil
| | - Helena Brentani
- Psychiatry Institute, University of São Paulo's Faculty of Medicine (IPq-FMUSP), São Paulo, SP, Brazil
| | - Patrícia Cristina Baleeiro Beltrão-Braga
- Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil.
- Scientific Platform Pasteur-USP, São Paulo, SP, Brazil.
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25
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Le H, Dimitrakopoulou K, Patel H, Curtis C, Cordero-Grande L, Edwards AD, Hajnal J, Tournier JD, Deprez M, Cullen H. Effect of schizophrenia common variants on infant brain volumes: cross-sectional study in 207 term neonates in developing Human Connectome Project. Transl Psychiatry 2023; 13:121. [PMID: 37037832 PMCID: PMC10085987 DOI: 10.1038/s41398-023-02413-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 03/16/2023] [Accepted: 03/24/2023] [Indexed: 04/12/2023] Open
Abstract
Increasing lines of evidence suggest deviations from the normal early developmental trajectory could give rise to the onset of schizophrenia during adolescence and young adulthood, but few studies have investigated brain imaging changes associated with schizophrenia common variants in neonates. This study compared the brain volumes of both grey and white matter regions with schizophrenia polygenic risk scores (PRS) for 207 healthy term-born infants of European ancestry. Linear regression was used to estimate the relationship between PRS and brain volumes, with gestational age at birth, postmenstrual age at scan, ancestral principal components, sex and intracranial volumes as covariates. The schizophrenia PRS were negatively associated with the grey (β = -0.08, p = 4.2 × 10-3) and white (β = -0.13, p = 9.4 × 10-3) matter superior temporal gyrus volumes, white frontal lobe volume (β = -0.09, p = 1.5 × 10-3) and the total white matter volume (β = -0.062, p = 1.66 × 10-2). This result also remained robust when incorporating individuals of Asian ancestry. Explorative functional analysis of the schizophrenia risk variants associated with the right frontal lobe white matter volume found enrichment in neurodevelopmental pathways. This preliminary result suggests possible involvement of schizophrenia risk genes in early brain growth, and potential early life structural alterations long before the average age of onset of the disease.
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Affiliation(s)
- Hai Le
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK.
| | - Konstantina Dimitrakopoulou
- Translational Bioinformatics Platform, NIHR Biomedical Research Centre, Guy's and St. Thomas' NHS Foundation Trust and King's College London, London, UK
| | - Hamel Patel
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Charles Curtis
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, ISCIII, Madrid, Spain
| | - A David Edwards
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Joseph Hajnal
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Maria Deprez
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Harriet Cullen
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
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Cai J, Xie M, Zhao L, Li X, Liang S, Deng W, Guo W, Ma X, Sham PC, Wang Q, Li T. White matter changes and its relationship with clinical symptom in medication-naive first-episode early onset schizophrenia. Asian J Psychiatr 2023; 82:103482. [PMID: 36709613 DOI: 10.1016/j.ajp.2023.103482] [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: 11/04/2022] [Revised: 01/17/2023] [Accepted: 01/23/2023] [Indexed: 01/26/2023]
Abstract
Previous studies have highlighted the role of white matter (WM) alterations as biomarkers of the disease state and prognosis of schizophrenia. However, less is known about WM abnormalities in the rarely occurring adolescent early onset schizophrenia (EOS). In this study, T1-weighted and diffusion-weighted images were collected in 56 medication-naive first-episode participants with EOS and 43 healthy controls (HCs). Using Tract-based Spatial Statistics, we calculate case-control differences in scalar diffusion measures, i.e. fractional anisotropy (FA) and mean diffusivity (MD), and investigated their association with clinical feature in participants with EOS. Compared with HCs, decreased MD was found in EOS group most notably in the inferior longitudinal fasciculus, anterior thalamic radiation, inferior fronto-occipital fasciculus and corticospinal tract in the right hemisphere. No significant difference was found in FA between these two groups. The FA values of the forceps minor and the right superior longitudinal fasciculus were suggested to be related to the severity of clinical symptom in participants with EOS. These results provide clues about the neural basis of schizophrenia and a potential biomarker for clinical studies.
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Affiliation(s)
- Jia Cai
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Min Xie
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Liansheng Zhao
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaojing Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Sugai Liang
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wanjun Guo
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaohong Ma
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Pak C Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
| | - Qiang Wang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
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Ceylan MF, Tural Hesapcioglu S, Kanoğlu Yüksekkaya S, Erçin G, Yavas CP, Neşelіoğlu S, Erel O. Changes in neurofilament light chain protein (NEFL) in children and adolescents with Schizophrenia and Bipolar Disorder: Early period neurodegeneration. J Psychiatr Res 2023; 161:342-347. [PMID: 37003244 DOI: 10.1016/j.jpsychires.2023.03.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/08/2022] [Accepted: 03/16/2023] [Indexed: 04/03/2023]
Abstract
AIM Neurofilament light chain protein (NEFL), is defined as a structural protein which exists particularly in axones of neurons and is released to the cerum in consequence of neuroaxonal damage. The aim of this study is to investigate the peripheral cerumNEFLlevels of children and adolescents with early onset schizophrenia and bipolar disorder. METHOD In this study, we evaluated serum levels of NEFL in children and adolescents (13-17 years) with schizophrenia, bipolar disorder and healthy control group. The study is conducted with 35 schizophrenia, 38 bipolar disorder manic episode patients and 40 healthy controls. RESULTS The median age of the patient and control groups was 16 (IQR- Interquartile Range: 2). There was no statistical difference in median age (p = 0.52) and gender distribution(p = 0.53) between groups. NEFL levels of the patients with schizophrenia were significantly higher than the controls. NEFL levels of the patients with bipolar disorder were significantly higher than the controls. Serum levels of NEFL of the schizophrenia were higher than the bipolar disorder; however, the difference was not statistically significant. CONCLUSION In conclusion, serum NEFL level, as a confidential marker of neural damage, is increased in the children and adolescents with bipolar disorder and schizophrenia. This result may indicatea degenerative period in neurons of children and adolescents with schizophrenia or bipolar disorder and may play a role in the pathophisiology of these disorders. This result shows that there is neuronal damage in both diseases, but neuronal damage may be more in schizophrenia.
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Affiliation(s)
- Mehmet Fatih Ceylan
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey.
| | - Selma Tural Hesapcioglu
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Seda Kanoğlu Yüksekkaya
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Görkem Erçin
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Cansu Pınar Yavas
- Ankara Yildirim Beyazit University, Faculty of Medicine, Child and Adolescent Psychiatry Department, Ankara, Turkey
| | - Salim Neşelіoğlu
- Ankara Yildirim Beyazit University, Faculty of Medicine, Clinical Biochemistry Department, Ankara, Turkey
| | - Ozcan Erel
- Ankara Yildirim Beyazit University, Faculty of Medicine, Clinical Biochemistry Department, Ankara, Turkey
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28
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Runge K, Balla A, Fiebich BL, Maier SJ, von Zedtwitz K, Nickel K, Dersch R, Domschke K, Tebartz van Elst L, Endres D. Neurodegeneration Markers in the Cerebrospinal Fluid of 100 Patients with Schizophrenia Spectrum Disorder. Schizophr Bull 2023; 49:464-473. [PMID: 36200879 PMCID: PMC10016411 DOI: 10.1093/schbul/sbac135] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Schizophrenia spectrum disorders (SSD) can be associated with neurodegenerative processes causing disruption of neuronal, synaptic, or axonal integrity. Some previous studies have reported alterations of neurodegenerative markers (such as amyloid beta [Aβ], tau, or neurofilaments) in patients with SSD. However, the current state of research remains inconclusive. Therefore, the rationale of this study was to investigate established neurodegenerative markers in the cerebrospinal fluid (CSF) of a large group of patients with SSD. STUDY DESIGN Measurements of Aβ1-40, Aß1-42, phospho- and total-tau in addition to neurofilament light (NFL), medium (NFM), and heavy (NFH) chains were performed in the CSF of 100 patients with SSD (60 F, 40 M; age 33.7 ± 12.0) and 39 controls with idiopathic intracranial hypertension (33 F, 6 M; age 34.6 ± 12.0) using enzyme-linked immunoassays. STUDY RESULTS The NFM levels were significantly increased in SSD patients (P = .009), whereas phospho-tau levels were lower in comparison to the control group (P = .018). No other significant differences in total-tau, beta-amyloid-quotient (Aβ1-42/Aβ1-40), NFL, and NFH were identified. CONCLUSIONS The findings argue against a general tauopathy or amyloid pathology in patients with SSD. However, high levels of NFM, which has been linked to regulatory functions in dopaminergic neurotransmission, were associated with SSD. Therefore, NFM could be a promising candidate for further research on SSD.
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Affiliation(s)
- Kimon Runge
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Agnes Balla
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bernd L Fiebich
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Simon J Maier
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katharina von Zedtwitz
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Kathrin Nickel
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Rick Dersch
- Clinic of Neurology and Neurophysiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ludger Tebartz van Elst
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dominique Endres
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study. Transl Psychiatry 2023; 13:82. [PMID: 36882419 PMCID: PMC9992684 DOI: 10.1038/s41398-023-02379-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/09/2023] Open
Abstract
Although many studies on brain-age prediction in patients with schizophrenia have been reported recently, none has predicted brain age based on different neuroimaging modalities and different brain regions in these patients. Here, we constructed brain-age prediction models with multimodal MRI and examined the deviations of aging trajectories in different brain regions of participants with schizophrenia recruited from multiple centers. The data of 230 healthy controls (HCs) were used for model training. Next, we investigated the differences in brain age gaps between participants with schizophrenia and HCs from two independent cohorts. A Gaussian process regression algorithm with fivefold cross-validation was used to train 90, 90, and 48 models for gray matter (GM), functional connectivity (FC), and fractional anisotropy (FA) maps in the training dataset, respectively. The brain age gaps in different brain regions for all participants were calculated, and the differences in brain age gaps between the two groups were examined. Our results showed that most GM regions in participants with schizophrenia in both cohorts exhibited accelerated aging, particularly in the frontal lobe, temporal lobe, and insula. The parts of the white matter tracts, including the cerebrum and cerebellum, indicated deviations in aging trajectories in participants with schizophrenia. However, no accelerated brain aging was noted in the FC maps. The accelerated aging in 22 GM regions and 10 white matter tracts in schizophrenia potentially exacerbates with disease progression. In individuals with schizophrenia, different brain regions demonstrate dynamic deviations of brain aging trajectories. Our findings provided more insights into schizophrenia neuropathology.
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Karbalaee M, Jameie M, Amanollahi M, TaghaviZanjani F, Parsaei M, Basti FA, Mokhtari S, Moradi K, Ardakani MRK, Akhondzadeh S. Efficacy and safety of adjunctive therapy with fingolimod in patients with schizophrenia: A randomized, double-blind, placebo-controlled clinical trial. Schizophr Res 2023; 254:92-98. [PMID: 36805834 DOI: 10.1016/j.schres.2023.02.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 02/05/2023] [Accepted: 02/13/2023] [Indexed: 02/21/2023]
Abstract
OBJECTIVES Studies have suggested that fingolimod, a sphingosine-1-phosphate receptor modulator, exerts neuroprotective and anti-inflammatory effects. Although fingolimod is approved for the treatment of relapsing-remitting multiple sclerosis, limited studies have investigated its effects in patients with schizophrenia. This study investigated the efficacy and safety of fingolimod adjuvant to risperidone in schizophrenia treatment. METHODS This eight-week, randomized, double-blinded, placebo-controlled trial included 80 (clinical trials registry code: IRCT20090117001556N137) patients with chronic schizophrenia. Participants were assigned to two equal arms and received risperidone plus either fingolimod (0.5 mg/day) or a matched placebo. The positive and negative symptom scale (PANSS) was used to measure and compare the effectiveness of treatment strategies at baseline and weeks 2, 4, 6, and 8. Treatment side effects were also compared. RESULTS Seventy participants completed the trial (35 in each arm). The baseline characteristics of the groups were comparable (P-value > 0.05). There were significant time-treatment interaction effects on negative symptoms (P-value = 0.003), general symptoms (P-value = 0.037), and the PANSS total score (P-value = 0.035), suggesting greater improvement in symptoms following the fingolimod adjuvant therapy. In contrast, the longitudinal changes in positive and depressive symptoms were similar between the groups (P-values > 0.05). Regarding the safety of treatments, there were no differences in extrapyramidal symptoms [assessed by the extrapyramidal symptom rating scale (ESRS)] or frequency of other complications between the fingolimod and the placebo groups (P-values > 0.05). CONCLUSIONS This study indicated that fingolimod is a safe and effective adjuvant agent for schizophrenia treatment. However, further clinical trials are required to suggest extensive clinical application.
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Affiliation(s)
- Monire Karbalaee
- Psychiatric Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Melika Jameie
- Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran; Neuroscience Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Mobina Amanollahi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Fateme TaghaviZanjani
- Psychiatric Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Fatemeh A Basti
- Islamic Azad University, Tehran Medical Branch, Tehran, Iran
| | - Saba Mokhtari
- Department of Psychiatry, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Kamyar Moradi
- Psychiatric Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Shahin Akhondzadeh
- Psychiatric Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran.
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31
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Goo BS, Mun DJ, Kim S, Nhung TTM, Lee SB, Woo Y, Kim SJ, Suh BK, Park SJ, Lee HE, Park K, Jang H, Rah JC, Yoon KJ, Baek ST, Park SY, Park SK. Schizophrenia-associated Mitotic Arrest Deficient-1 (MAD1) regulates the polarity of migrating neurons in the developing neocortex. Mol Psychiatry 2023; 28:856-870. [PMID: 36357673 PMCID: PMC9908555 DOI: 10.1038/s41380-022-01856-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/20/2022] [Accepted: 10/24/2022] [Indexed: 11/11/2022]
Abstract
Although large-scale genome-wide association studies (GWAS) have identified an association between MAD1L1 (Mitotic Arrest Deficient-1 Like 1) and the pathology of schizophrenia, the molecular mechanisms underlying this association remain unclear. In the present study, we aimed to address these mechanisms by examining the role of MAD1 (the gene product of MAD1L1) in key neurodevelopmental processes in mice and human organoids. Our findings indicated that MAD1 is highly expressed during active cortical development and that MAD1 deficiency leads to impairments in neuronal migration and neurite outgrowth. We also observed that MAD1 is localized to the Golgi apparatus and regulates vesicular trafficking from the Golgi apparatus to the plasma membrane, which is required for the growth and polarity of migrating neurons. In this process, MAD1 physically interacts and collaborates with the kinesin-like protein KIFC3 (kinesin family member C3) to regulate the morphology of the Golgi apparatus and neuronal polarity, thereby ensuring proper neuronal migration and differentiation. Consequently, our findings indicate that MAD1 is an essential regulator of neuronal development and that alterations in MAD1 may underlie schizophrenia pathobiology.
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Affiliation(s)
- Bon Seong Goo
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Dong Jin Mun
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Seunghyun Kim
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Truong Thi My Nhung
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Su Been Lee
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Youngsik Woo
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Soo Jeong Kim
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Bo Kyoung Suh
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Sung Jin Park
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Hee-Eun Lee
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Kunyou Park
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Hyunsoo Jang
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Jong-Cheol Rah
- Korea Brain Research Institute, Daegu, 41062, Republic of Korea
| | - Ki-Jun Yoon
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Seung Tae Baek
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Seung-Yeol Park
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea.
| | - Sang Ki Park
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea.
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32
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Fišar Z. Biological hypotheses, risk factors, and biomarkers of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2023; 120:110626. [PMID: 36055561 DOI: 10.1016/j.pnpbp.2022.110626] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 12/19/2022]
Abstract
Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.
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Affiliation(s)
- Zdeněk Fišar
- Charles University and General University Hospital in Prague, First Faculty of Medicine, Department of Psychiatry, Czech Republic.
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33
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Vinogradov S, Chafee MV, Lee E, Morishita H. Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity. Neuropsychopharmacology 2023; 48:168-185. [PMID: 36180784 PMCID: PMC9700720 DOI: 10.1038/s41386-022-01451-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/17/2022] [Accepted: 08/21/2022] [Indexed: 01/05/2023]
Abstract
Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.
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Affiliation(s)
- Sophia Vinogradov
- Department of Psychiatry & Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Matthew V Chafee
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Erik Lee
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Hirofumi Morishita
- Department of Psychiatry, Neuroscience, & Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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León-Ortiz P, Reyes-Madrigal F, Kochunov P, Gómez-Cruz G, Moncada-Habib T, Malacara M, Mora-Durán R, Rowland LM, de la Fuente-Sandoval C. White matter alterations and the conversion to psychosis: A combined diffusion tensor imaging and glutamate 1H MRS study. Schizophr Res 2022; 249:85-92. [PMID: 32595100 PMCID: PMC10025976 DOI: 10.1016/j.schres.2020.06.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 06/08/2020] [Accepted: 06/10/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Widespread white matter abnormalities and alterations in glutamate levels have been reported in patients with schizophrenia. We hypothesized that alterations in white matter integrity and glutamate levels in individuals at clinical high risk (CHR) for psychosis are associated with the subsequent development of psychosis. METHODS Participants included 33 antipsychotic naïve CHR (Female 7/Male 26, Age 19.55 (4.14) years) and 38 healthy controls (Female 10/Male 28, Age 20.92 (3.37) years). Whole brain diffusion tensor imaging for fractional anisotropy (FA) and right frontal white matter proton magnetic resonance spectroscopy for glutamate levels were acquired. CHR participants were clinically followed for 2 years to determine conversion to psychosis. RESULTS CHR participants that transitioned to psychosis (N = 7, 21%) were characterized by significantly lower FA values in the posterior thalamic radiation compared to those who did not transition and healthy controls. In the CHR group that transitioned to psychosis only, positive exploratory correlations between glutamate levels and FA values of the posterior thalamic radiation and the retrolenticular part of the internal capsule and a negative correlation between glutamate levels and the cingulum FA values were found. CONCLUSION The results of the present study highlight that alterations in white matter structure and glutamate are related with the conversion to psychosis.
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Affiliation(s)
- Pablo León-Ortiz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico; Department of Education, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, United States of America
| | - Gladys Gómez-Cruz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Tomás Moncada-Habib
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Melanie Malacara
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Ricardo Mora-Durán
- Emergency Department, Hospital Fray Bernardino Álvarez, Mexico City, Mexico
| | - Laura M Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, United States of America
| | - Camilo de la Fuente-Sandoval
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico; Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico.
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35
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Eratne D, Janelidze S, Malpas CB, Loi S, Walterfang M, Merritt A, Diouf I, Blennow K, Zetterberg H, Cilia B, Wannan C, Bousman C, Everall I, Zalesky A, Jayaram M, Thomas N, Berkovic SF, Hansson O, Velakoulis D, Pantelis C, Santillo A, Stehmann C, Cadwallader C, Fowler C, Ravanfar P, Farrand S, Keem M, Kang M, Watson R, Yassi N, Kaylor-Hughes C, Kanaan R, Perucca P, Vivash L, Ali R, O’Brien TJ, Masters CL, Collins S, Kelso W, Evans A, King A, Kwan P, Gunn J, Goranitis I, Pan T, Lewis C, Kalincik T. Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives. Aust N Z J Psychiatry 2022; 56:1295-1305. [PMID: 35179048 DOI: 10.1177/00048674211058684] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuroprogressive or neurodegenerative component to schizophrenia, remain largely unknown. Examining fluid biomarkers of diverse types of neuronal damage could increase our understanding of these processes, as well as potentially provide clinically useful biomarkers, for example with assisting with differentiation from progressive neurodegenerative disorders such as Alzheimer and frontotemporal dementias. METHODS This study measured plasma neurofilament light chain protein (NfL) using ultrasensitive Simoa technology, to investigate the degree of neuronal injury in a well-characterised cohort of people with treatment-resistant schizophrenia on clozapine (n = 82), compared to first-degree relatives (an at-risk group, n = 37), people with schizophrenia not treated with clozapine (n = 13), and age- and sex-matched controls (n = 59). RESULTS We found no differences in NfL levels between treatment-resistant schizophrenia (mean NfL, M = 6.3 pg/mL, 95% confidence interval: [5.5, 7.2]), first-degree relatives (siblings, M = 6.7 pg/mL, 95% confidence interval: [5.2, 8.2]; parents, M after adjusting for age = 6.7 pg/mL, 95% confidence interval: [4.7, 8.8]), controls (M = 5.8 pg/mL, 95% confidence interval: [5.3, 6.3]) and not treated with clozapine (M = 4.9 pg/mL, 95% confidence interval: [4.0, 5.8]). Exploratory, hypothesis-generating analyses found weak correlations in treatment-resistant schizophrenia, between NfL and clozapine levels (Spearman's r = 0.258, 95% confidence interval: [0.034, 0.457]), dyslipidaemia (r = 0.280, 95% confidence interval: [0.064, 0.470]) and a negative correlation with weight (r = -0.305, 95% confidence interval: [-0.504, -0.076]). CONCLUSION Treatment-resistant schizophrenia does not appear to be associated with neuronal, particularly axonal degeneration. Further studies are warranted to investigate the utility of NfL to differentiate treatment-resistant schizophrenia from neurodegenerative disorders such as behavioural variant frontotemporal dementia, and to explore NfL in other stages of schizophrenia such as the prodome and first episode.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Charles B Malpas
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia.,Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Samantha Loi
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mark Walterfang
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Antonia Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Ibrahima Diouf
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute, University College London (UCL), London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Brandon Cilia
- The University of Melbourne, Parkville, VIC, Australia
| | - Cassandra Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Chad Bousman
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Ian Everall
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mahesh Jayaram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Naveen Thomas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Alexander Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
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Davidson M, Rashidi N, Nurgali K, Apostolopoulos V. The Role of Tryptophan Metabolites in Neuropsychiatric Disorders. Int J Mol Sci 2022; 23:ijms23179968. [PMID: 36077360 PMCID: PMC9456464 DOI: 10.3390/ijms23179968] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/27/2022] [Accepted: 08/31/2022] [Indexed: 12/20/2022] Open
Abstract
In recent decades, neuropsychiatric disorders such as major depressive disorder, schizophrenia, bipolar, etc., have become a global health concern, causing various detrimental influences on patients. Tryptophan is an important amino acid that plays an indisputable role in several physiological processes, including neuronal function and immunity. Tryptophan’s metabolism process in the human body occurs using different pathways, including the kynurenine and serotonin pathways. Furthermore, other biologically active components, such as serotonin, melatonin, and niacin, are by-products of Tryptophan pathways. Current evidence suggests that a functional imbalance in the synthesis of Tryptophan metabolites causes the appearance of pathophysiologic mechanisms that leads to various neuropsychiatric diseases. This review summarizes the pharmacological influences of tryptophan and its metabolites on the development of neuropsychiatric disorders. In addition, tryptophan and its metabolites quantification following the neurotransmitters precursor are highlighted. Eventually, the efficiency of various biomarkers such as inflammatory, protein, electrophysiological, genetic, and proteomic biomarkers in the diagnosis/treatment of neuropsychiatric disorders was discussed to understand the biomarker application in the detection/treatment of various diseases.
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Affiliation(s)
- Majid Davidson
- Institute for Health and Sport, Victoria University, Melbourne, VIC 3011, Australia
- Regenerative Medicine and Stem Cells Program, Australian Institute of Musculoskeletal Science (AIMSS), Melbourne, VIC 3021, Australia
| | - Niloufar Rashidi
- Institute for Health and Sport, Victoria University, Melbourne, VIC 3011, Australia
- Regenerative Medicine and Stem Cells Program, Australian Institute of Musculoskeletal Science (AIMSS), Melbourne, VIC 3021, Australia
| | - Kulmira Nurgali
- Institute for Health and Sport, Victoria University, Melbourne, VIC 3011, Australia
- Regenerative Medicine and Stem Cells Program, Australian Institute of Musculoskeletal Science (AIMSS), Melbourne, VIC 3021, Australia
- Department of Medicine Western Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Vasso Apostolopoulos
- Institute for Health and Sport, Victoria University, Melbourne, VIC 3011, Australia
- Immunology Program, Australian Institute of Musculoskeletal Science (AIMSS), Melbourne, VIC 3021, Australia
- Correspondence:
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Koutsouleris N, Pantelis C, Velakoulis D, McGuire P, Dwyer DB, Urquijo-Castro MF, Paul R, Dong S, Popovic D, Oeztuerk O, Kambeitz J, Salokangas RKR, Hietala J, Bertolino A, Brambilla P, Upthegrove R, Wood SJ, Lencer R, Borgwardt S, Maj C, Nöthen M, Degenhardt F, Polyakova M, Mueller K, Villringer A, Danek A, Fassbender K, Fliessbach K, Jahn H, Kornhuber J, Landwehrmeyer B, Anderl-Straub S, Prudlo J, Synofzik M, Wiltfang J, Riedl L, Diehl-Schmid J, Otto M, Meisenzahl E, Falkai P, Schroeter ML. Exploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning: Dementia Praecox Revisited. JAMA Psychiatry 2022; 79:907-919. [PMID: 35921104 PMCID: PMC9350851 DOI: 10.1001/jamapsychiatry.2022.2075] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 06/12/2022] [Indexed: 12/04/2022]
Abstract
Importance The behavioral and cognitive symptoms of severe psychotic disorders overlap with those seen in dementia. However, shared brain alterations remain disputed, and their relevance for patients in at-risk disease stages has not been explored so far. Objective To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia based on sociodemographic, clinical, and biological data; and examine prognostic value, genetic underpinnings, and progression in patients with clinical high-risk (CHR) states for psychosis or recent-onset depression (ROD). Design, Setting, and Participants This study included 1870 individuals from 5 cohorts, including (1) patients with bvFTD (n = 108), established AD (n = 44), mild cognitive impairment or early-stage AD (n = 96), schizophrenia (n = 157), or major depression (n = 102) to derive and compare diagnostic patterns and (2) patients with CHR (n = 160) or ROD (n = 161) to test patterns' prognostic relevance and progression. Healthy individuals (n = 1042) were used for age-related and cohort-related data calibration. Data were collected from January 1996 to July 2019 and analyzed between April 2020 and April 2022. Main Outcomes and Measures Case assignments based on diagnostic patterns; sociodemographic, clinical, and biological data; 2-year functional outcomes and genetic separability of patients with CHR and ROD with high vs low pattern expression; and pattern progression from baseline to follow-up MRI scans in patients with nonrecovery vs preserved recovery. Results Of 1870 included patients, 902 (48.2%) were female, and the mean (SD) age was 38.0 (19.3) years. The bvFTD pattern comprising prefrontal, insular, and limbic volume reductions was more expressed in patients with schizophrenia (65 of 157 [41.2%]) and major depression (22 of 102 [21.6%]) than the temporo-limbic AD patterns (28 of 157 [17.8%] and 3 of 102 [2.9%], respectively). bvFTD expression was predicted by high body mass index, psychomotor slowing, affective disinhibition, and paranoid ideation (R2 = 0.11). The schizophrenia pattern was expressed in 92 of 108 patients (85.5%) with bvFTD and was linked to the C9orf72 variant, oligoclonal banding in the cerebrospinal fluid, cognitive impairment, and younger age (R2 = 0.29). bvFTD and schizophrenia pattern expressions forecasted 2-year psychosocial impairments in patients with CHR and were predicted by polygenic risk scores for frontotemporal dementia, AD, and schizophrenia. Findings were not associated with AD or accelerated brain aging. Finally, 1-year bvFTD/schizophrenia pattern progression distinguished patients with nonrecovery from those with preserved recovery. Conclusions and Relevance Neurobiological links may exist between bvFTD and psychosis focusing on prefrontal and salience system alterations. Further transdiagnostic investigations are needed to identify shared pathophysiological processes underlying the neuroanatomical interface between the 2 disease spectra.
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Affiliation(s)
- Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Max-Planck Institute of Psychiatry, Munich, Germany
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Australia
| | - Philip McGuire
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Dominic B. Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | | | - Riya Paul
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Sen Dong
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - David Popovic
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Oemer Oeztuerk
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | | | - Jarmo Hietala
- Department of Psychiatry, University of Turku, Turku, Finland
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Rachel Upthegrove
- Institute of Mental Health, University of Birmingham, Birmingham, United Kingdom
- Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation Trust, Birmingham, United Kingdom
| | - Stephen J. Wood
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Institute for Translational Psychiatry, University Muenster, Muenster, Germany
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Department of Psychiatry, University Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland
| | - Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Markus Nöthen
- Institute of Human Genetics, School of Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, School of Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Duisburg, Germany
| | - Maryna Polyakova
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Karsten Mueller
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig Maximilian University Munich, Munich, Germany
| | - Klaus Fassbender
- Department of Neurology, Saarland University Hospital, Homburg, Germany
| | - Klaus Fliessbach
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
| | - Holger Jahn
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg, Hamburg, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | | | | | - Johannes Prudlo
- Department of Neurology, University Medicine Rostock, Rostock, Germany
| | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Neurodegenerative Diseases, Center of Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, Medical University Göttingen, Göttingen, Germany
| | - Lina Riedl
- Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Matthias L. Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
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Vanes LD, Murray RM, Nosarti C. Adult outcome of preterm birth: Implications for neurodevelopmental theories of psychosis. Schizophr Res 2022; 247:41-54. [PMID: 34006427 DOI: 10.1016/j.schres.2021.04.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 12/22/2022]
Abstract
Preterm birth is associated with an elevated risk of developmental and adult psychiatric disorders, including psychosis. In this review, we evaluate the implications of neurodevelopmental, cognitive, motor, and social sequelae of preterm birth for developing psychosis, with an emphasis on outcomes observed in adulthood. Abnormal brain development precipitated by early exposure to the extra-uterine environment, and exacerbated by neuroinflammation, neonatal brain injury, and genetic vulnerability, can result in alterations of brain structure and function persisting into adulthood. These alterations, including abnormal regional brain volumes and white matter macro- and micro-structure, can critically impair functional (e.g. frontoparietal and thalamocortical) network connectivity in a manner characteristic of psychotic illness. The resulting executive, social, and motor dysfunctions may constitute the basis for behavioural vulnerability ultimately giving rise to psychotic symptomatology. There are many pathways to psychosis, but elucidating more precisely the mechanisms whereby preterm birth increases risk may shed light on that route consequent upon early neurodevelopmental insult.
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Affiliation(s)
- Lucy D Vanes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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Komatsu H, Onoguchi G, Jerotic S, Kanahara N, Kakuto Y, Ono T, Funakoshi S, Yabana T, Nakazawa T, Tomita H. Retinal layers and associated clinical factors in schizophrenia spectrum disorders: a systematic review and meta-analysis. Mol Psychiatry 2022; 27:3592-3616. [PMID: 35501407 DOI: 10.1038/s41380-022-01591-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/13/2022] [Accepted: 04/14/2022] [Indexed: 02/08/2023]
Abstract
INTRODUCTION The retina shares structural and functional similarities with the brain. Furthermore, structural changes in the retina have been observed in patients with schizophrenia spectrum disorders (SSDs). This systematic review and meta-analysis investigated retinal abnormalities and their association with clinical factors for SSD. METHODS Studies related to retinal layers in SSD patients were retrieved from PubMed, Scopus, Web of Science, Cochrane Controlled Register of Trials, International Clinical Trials Registry Platform, and PSYNDEX databases from inception to March 31, 2021. We screened and assessed the eligibility of the identified studies. EZR ver.1.54 and the metafor package in R were used for the meta-analysis and a random-effects or fixed-effects model was used to report standardized mean differences (SMDs). RESULTS Twenty-three studies (2079 eyes of patients and 1571 eyes of controls) were included in the systematic review and meta-analysis. The average peripapillary retinal nerve fiber layer (pRNFL) thickness, average macular thickness (MT), and macular ganglion cell layer-inner plexiform layer (GCL-IPL) thickness were significantly lower in patients than in controls (n = 14, 6, and 3, respectively; SMD = -0.33, -0.49, and -0.43, respectively). Patients also had significantly reduced macular volume (MV) compared to controls (n = 7; SMD = -0.53). The optic cup volume (OCV) was significantly larger in patients than in controls (n = 3; SMD = 0.28). The meta-regression analysis indicated an association between several clinical factors, such as duration of illness and the effect size of the pRNFL, macular GCL-IPL, MT, and MV. CONCLUSION Thinning of the pRNFL, macular GCL-IPL, MT, and MV and enlargement of the OCV in SSD were observed. Retinal abnormalities may be applicable as state/trait markers in SSDs. The accumulated evidence was mainly cross-sectional and requires verification by longitudinal studies to characterize the relationship between OCT findings and clinical factors.
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Affiliation(s)
- Hiroshi Komatsu
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan. .,Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan. .,Miyagi Psychiatric Center, Natori, Japan.
| | - Goh Onoguchi
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Stefan Jerotic
- Clinic for Psychiatry, University Clinical Centre of Serbia, Belgrade, Serbia.,Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Nobuhisa Kanahara
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan.,Division of Medical Treatment and Rehabilitation, Chiba University Center for Forensic Mental Health, Chiba, Japan
| | - Yoshihisa Kakuto
- Miyagi Psychiatric Center, Natori, Japan.,Department of Community Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | | | - Shunichi Funakoshi
- Miyagi Psychiatric Center, Natori, Japan.,Department of Community Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Takeshi Yabana
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Toru Nakazawa
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan.,Collaborative Program for Ophthalmic Drug Discovery, Tohoku University Graduate School of Medicine, Sendai, Japan.,Department of Ophthalmic Imaging and Information Analytics, Tohoku University Graduate School of Medicine, Sendai, Japan.,Department of Retinal Disease Control, Tohoku University Graduate School of Medicine, Sendai, Japan.,Department of Advanced Ophthalmic Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Hiroaki Tomita
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan.,Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
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Casas BS, Arancibia-Altamirano D, Acevedo-La Rosa F, Garrido-Jara D, Maksaev V, Pérez-Monje D, Palma V. It takes two to tango: Widening our understanding of the onset of schizophrenia from a neuro-angiogenic perspective. Front Cell Dev Biol 2022; 10:946706. [PMID: 36092733 PMCID: PMC9448889 DOI: 10.3389/fcell.2022.946706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/14/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia is a chronic debilitating mental disorder characterized by perturbations in thinking, perception, and behavior, along with brain connectivity deficiencies, neurotransmitter dysfunctions, and loss of gray brain matter. To date, schizophrenia has no cure and pharmacological treatments are only partially efficacious, with about 30% of patients describing little to no improvement after treatment. As in most neurological disorders, the main descriptions of schizophrenia physiopathology have been focused on neural network deficiencies. However, to sustain proper neural activity in the brain, another, no less important network is operating: the vast, complex and fascinating vascular network. Increasing research has characterized schizophrenia as a systemic disease where vascular involvement is important. Several neuro-angiogenic pathway disturbances have been related to schizophrenia. Alterations, ranging from genetic polymorphisms, mRNA, and protein alterations to microRNA and abnormal metabolite processing, have been evaluated in plasma, post-mortem brain, animal models, and patient-derived induced pluripotent stem cell (hiPSC) models. During embryonic brain development, the coordinated formation of blood vessels parallels neuro/gliogenesis and results in the structuration of the neurovascular niche, which brings together physical and molecular signals from both systems conforming to the Blood-Brain barrier. In this review, we offer an upfront perspective on distinctive angiogenic and neurogenic signaling pathways that might be involved in the biological causality of schizophrenia. We analyze the role of pivotal angiogenic-related pathways such as Vascular Endothelial Growth Factor and HIF signaling related to hypoxia and oxidative stress events; classic developmental pathways such as the NOTCH pathway, metabolic pathways such as the mTOR/AKT cascade; emerging neuroinflammation, and neurodegenerative processes such as UPR, and also discuss non-canonic angiogenic/axonal guidance factor signaling. Considering that all of the mentioned above pathways converge at the Blood-Brain barrier, reported neurovascular alterations could have deleterious repercussions on overall brain functioning in schizophrenia.
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Chien YL, Lin HY, Tung YH, Hwang TJ, Chen CL, Wu CS, Shang CY, Hwu HG, Tseng WYI, Liu CM, Gau SSF. Neurodevelopmental model of schizophrenia revisited: similarity in individual deviation and idiosyncrasy from the normative model of whole-brain white matter tracts and shared brain-cognition covariation with ADHD and ASD. Mol Psychiatry 2022; 27:3262-3271. [PMID: 35794186 DOI: 10.1038/s41380-022-01636-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 05/08/2022] [Accepted: 05/18/2022] [Indexed: 11/09/2022]
Abstract
The neurodevelopmental model of schizophrenia is supported by multi-level impairments shared among schizophrenia and neurodevelopmental disorders. Despite schizophrenia and typical neurodevelopmental disorders, i.e., autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), as disorders of brain dysconnectivity, no study has ever elucidated whether whole-brain white matter (WM) tracts integrity alterations overlap or diverge between these three disorders. Moreover, whether the linked dimensions of cognition and brain metrics per the Research Domain Criteria framework cut across diagnostic boundaries remains unknown. We aimed to map deviations from normative ranges of whole-brain major WM tracts for individual patients to investigate the similarity and differences among schizophrenia (281 patients subgrouped into the first-episode, subchronic and chronic phases), ASD (175 patients), and ADHD (279 patients). Sex-specific WM tract normative development was modeled from diffusion spectrum imaging of 626 typically developing controls (5-40 years). There were three significant findings. First, the patterns of deviation and idiosyncrasy of WM tracts were similar between schizophrenia and ADHD alongside ASD, particularly at the earlier stages of schizophrenia relative to chronic stages. Second, using the WM deviation patterns as features, schizophrenia cannot be separated from neurodevelopmental disorders in the unsupervised machine learning algorithm. Lastly, the canonical correlation analysis showed schizophrenia, ADHD, and ASD shared linked cognitive dimensions driven by WM deviations. Together, our results provide new insights into the neurodevelopmental facet of schizophrenia and its brain basis. Individual's WM deviations may contribute to diverse arrays of cognitive function along a continuum with phenotypic expressions from typical neurodevelopmental disorders to schizophrenia.
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Affiliation(s)
- Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre and Adult Neurodevelopmental and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Yu-Hung Tung
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Tzung-Jeng Hwang
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan.,Neurobiology & Cognitive Science Center, National Taiwan University, Taipei, Taiwan
| | - Chang-Le Chen
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chi-Shin Wu
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Chi-Yung Shang
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Hai-Gwo Hwu
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Wen-Yih Isaac Tseng
- Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan. .,Neurobiology & Cognitive Science Center, National Taiwan University, Taipei, Taiwan. .,Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan.
| | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan. .,Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan. .,Neurobiology & Cognitive Science Center, National Taiwan University, Taipei, Taiwan.
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Kuo SS, Roalf DR, Prasad KM, Musket CW, Rupert PE, Wood J, Gur RC, Almasy L, Gur RE, Nimgaonkar VL, Pogue-Geile MF. Age-dependent effects of schizophrenia genetic risk on cortical thickness and cortical surface area: Evaluating evidence for neurodevelopmental and neurodegenerative models of schizophrenia. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2022; 131:674-688. [PMID: 35737559 PMCID: PMC9339500 DOI: 10.1037/abn0000765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Risk for schizophrenia peaks during early adulthood, a critical period for brain development. Although several influential theoretical models have been proposed for the developmental relationship between brain pathology and clinical onset, to our knowledge, no study has directly evaluated the predictions of these models for schizophrenia developmental genetic effects on brain structure. To address this question, we introduce a framework to estimate the effects of schizophrenia genetic variation on brain structure phenotypes across the life span. Five-hundred and six participants, including 30 schizophrenia probands, 200 of their relatives (aged 12-85 years) from 32 families with at least two first-degree schizophrenia relatives, and 276 unrelated controls, underwent MRI to assess regional cortical thickness (CT) and cortical surface area (CSA). Genetic variance decomposition analyses were conducted to distinguish among schizophrenia neurogenetic effects that are most salient before schizophrenia peak age-of-risk (i.e., early neurodevelopmental effects), after peak age-of-risk (late neurodevelopmental effects), and during the later plateau of age-of-risk (neurodegenerative effects). Genetic correlations between schizophrenia and cortical traits suggested early neurodevelopmental effects for frontal and insula CSA, late neurodevelopmental effects for overall CSA and frontal, parietal, and occipital CSA, and possible neurodegenerative effects for temporal CT and parietal CSA. Importantly, these developmental neurogenetic effects were specific to schizophrenia and not found with nonpsychotic depression. Our findings highlight the potentially dynamic nature of schizophrenia genetic effects across the lifespan and emphasize the utility of integrating neuroimaging methods with developmental behavior genetic approaches to elucidate the nature and timing of risk-conferring processes in psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Yue W, Huang H, Duan J. Potential diagnostic biomarkers for schizophrenia. MEDICAL REVIEW (BERLIN, GERMANY) 2022; 2:385-416. [PMID: 37724326 PMCID: PMC10388817 DOI: 10.1515/mr-2022-0009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/20/2022] [Indexed: 09/20/2023]
Abstract
Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.
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Affiliation(s)
- Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University Health System, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
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Göverti D, Yüksel RN, Kaya H, Büyüklüoğlu N, Yücel Ç, Göka E. Serum concentrations of aminoacylase 1 in schizophrenia as a potential biomarker: a case-sibling-control study. Nord J Psychiatry 2022; 76:380-385. [PMID: 35791057 DOI: 10.1080/08039488.2021.1981435] [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] [Indexed: 10/17/2022]
Abstract
PURPOSE Aminoacylase 1 (ACY1) catalyzes the hydrolysis reaction during protein degradation. N-acetylamino acids are accumulated in the urine in Aminoacylase 1 deficiency (ACY1D). This study attempts to evaluate the potential of ACY1 as a biomarker for schizophrenia and predict genetic vulnerability in the high-risk population. MATERIAL AND METHODS Seventy patients with schizophrenia, twenty-five of which have newly diagnosed, forty-nine unaffected siblings of patients, and fifty-six healthy controls were included in the study. The ELISA method was used to measure serum ACY1. The Positive and Negative Syndrome Scale (PANSS) and The Clinical Global Impression - Severity scale (CGI-S) were used to analyze the severity of the symptoms. Data were analysed statistically by non-parametric tests. RESULTS The finding of the study indicated that the serum levels of ACY1 in patients and siblings were lower compared to healthy controls (p < 0.001 and p = 0.023). There was no statistically significant difference between patients and siblings (p = 0.067). The duration of disease, PANSS total scores, and CGI-S scores did not have a significant association with the ACY1 levels in the patient group (p > 0.005). ACY1 levels among the drug-using patient group and the newly diagnosed patient group showed no notable difference (respectively, p = 0.120 and p = 0.843). CONCLUSION This study is the first to evaluate the serum ACY1 levels in patients with schizophrenia. The result of the study provides us insight regarding the first hints that ACY1 might be a potential biomarker. Being aware of the molecule will pave the way for further explorations in the field.
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Affiliation(s)
- Diğdem Göverti
- Department of Psychiatry, Erenkoy Mental Health and Neurologic Disorders Training and Research Hospital, University of Health Sciences, İstanbul, Turkey
| | - Rabia Nazik Yüksel
- Department of Psychiatry, Ankara City Hospital, University of Health Sciences, Ankara, Turkey
| | - Hasan Kaya
- Department of Psychiatry, Ankara City Hospital, University of Health Sciences, Ankara, Turkey
| | - Nihan Büyüklüoğlu
- Department of Psychiatry, Ankara City Hospital, University of Health Sciences, Ankara, Turkey
| | - Çiğdem Yücel
- Department of Biochemistry, Gulhane Training and Research Hospital, University of Health Sciences, Ankara, Turkey
| | - Erol Göka
- Department of Psychiatry, Ankara City Hospital, University of Health Sciences, Ankara, Turkey
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Smigielski L, Stämpfli P, Wotruba D, Buechler R, Sommer S, Gerstenberg M, Theodoridou A, Walitza S, Rössler W, Heekeren K. White matter microstructure and the clinical risk for psychosis: A diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk. Neuroimage Clin 2022; 35:103067. [PMID: 35679786 PMCID: PMC9178487 DOI: 10.1016/j.nicl.2022.103067] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/19/2022] [Accepted: 05/28/2022] [Indexed: 12/29/2022]
Abstract
This DTI cross-sectional study compared UHR, basic symptom & control groups (n = 112). The splenium of UHR individuals exhibited differences in fractional anisotropy (FA). Basic symptoms alone were not associated with white matter microstructure changes. Large differences in FA & radial diffusivity were found in converters to psychosis. Regional FA was inversely correlated with the general psychopathology domain.
Background Widespread white matter abnormalities are a frequent finding in chronic schizophrenia patients. More inconsistent results have been provided by the sparser literature on at-risk states for psychosis, i.e., emerging subclinical symptoms. However, considering risk as a homogenous construct, an approach of earlier studies, may impede our understanding of neuro-progression into psychosis. Methods An analysis was conducted of 3-Tesla MRI diffusion and symptom data from 112 individuals (mean age, 21.97 ± 4.19) within two at-risk paradigm subtypes, only basic symptoms (n = 43) and ultra-high risk (n = 37), and controls (n = 32). Between-group comparisons (involving three study groups and further split based on the subsequent transition to schizophrenia) of four diffusion-tensor-imaging-derived scalars were performed using voxelwise tract-based spatial statistics, followed by correlational analyses with Structured Interview for Prodromal Syndromes responses. Results Relative to controls, fractional anisotropy was lower in the splenium of the corpus callosum of ultra-high-risk individuals, but only before stringent multiple-testing correction, and negatively correlated with General Symptom severity among at-risk individuals. At-risk participants who transitioned to schizophrenia within 3 years, compared to those that did not transition, had more severe WM differences in fractional anisotropy and radial diffusivity (particularly in the corpus callosum, anterior corona radiata, and motor/sensory tracts), which were even more extensive compared to healthy controls. Conclusions These findings align with the subclinical symptom presentation and more extensive disruptions in converters, suggestive of severity-related demyelination or axonal pathology. Fine-grained but detectable differences among ultra-high-risk subjects (i.e., with brief limited intermittent and/or attenuated psychotic symptoms) point to the splenium as a discrete site of emerging psychopathology, while basic symptoms alone were not associated with altered fractional anisotropy.
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Affiliation(s)
- Lukasz Smigielski
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Diana Wotruba
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Roman Buechler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich, Zurich, Switzerland
| | - Stefan Sommer
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Miriam Gerstenberg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anastasia Theodoridou
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Wulf Rössler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany; Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, Universidade de São Paulo, São Paulo, Brazil
| | - Karsten Heekeren
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy I, LVR-Hospital, Cologne, Germany
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Li C, Pang D, Lin J, Yang T, Shang H. Shared genetic links between frontotemporal dementia and psychiatric disorders. BMC Med 2022; 20:131. [PMID: 35509074 PMCID: PMC9069762 DOI: 10.1186/s12916-022-02335-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 03/14/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Epidemiological and clinical studies have suggested comorbidity between frontotemporal dementia (FTD) and psychiatric disorders. FTD patients carrying specific mutations were at higher risk for some psychiatric disorders, and vice versa, implying potential shared genetic etiology, which is still less explored. METHODS We examined the genetic correlation using summary statistics from genome-wide association studies and analyzed their genetic enrichment leveraging the conditional false discovery rate method. Furthermore, we explored the causal association between FTD and psychiatric disorders with Mendelian randomization (MR) analysis. RESULTS We identified a significant genetic correlation between FTD and schizophrenia at both genetic and transcriptomic levels. Meanwhile, robust genetic enrichment was observed between FTD and schizophrenia and alcohol use disorder. Seven shared genetic loci were identified, which were mainly involved in interleukin-induced signaling, synaptic vesicle, and brain-derived neurotrophic factor signaling pathways. By integrating cis-expression quantitative trait loci analysis, we identified MAPT and CADM2 as shared risk genes. MR analysis showed mutual causation between FTD and schizophrenia with nominal association. CONCLUSIONS Our findings provide evidence of shared etiology between FTD and schizophrenia and indicate potential common molecular mechanisms contributing to the overlapping pathophysiological and clinical characteristics. Our results also demonstrate the essential role of autoimmunity in these diseases. These findings provide a better understanding of the pleiotropy between FTD and psychiatric disorders and have implications for therapeutic trials.
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Affiliation(s)
- Chunyu Li
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Dejiang Pang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Junyu Lin
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Tianmi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, No.37, Guoxue Lane, Chengdu, 610041, Sichuan, China.
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Janssen J, Alloza C, Díaz-Caneja CM, Santonja J, Pina-Camacho L, Gordaliza PM, Fernández-Pena A, Lois NG, Buimer EEL, van Haren NEM, Cahn W, Vieta E, Castro-Fornieles J, Bernardo M, Arango C, Kahn RS, Hulshoff Pol HE, Schnack HG. Longitudinal Allometry of Sulcal Morphology in Health and Schizophrenia. J Neurosci 2022; 42:3704-3715. [PMID: 35318286 PMCID: PMC9087719 DOI: 10.1523/jneurosci.0606-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 02/24/2022] [Accepted: 03/01/2022] [Indexed: 11/21/2022] Open
Abstract
Scaling between subcomponents of folding and total brain volume (TBV) in healthy individuals (HIs) is allometric. It is unclear whether this is true in schizophrenia (SZ) or first-episode psychosis (FEP). This study confirmed normative allometric scaling norms in HIs using discovery and replication samples. Cross-sectional and longitudinal diagnostic differences in folding subcomponents were then assessed using an allometric framework. Structural imaging from a longitudinal (Sample 1: HI and SZ, nHI Baseline = 298, nSZ Baseline = 169, nHI Follow-up = 293, nSZ Follow-up = 168, totaling 1087 images, all individuals ≥ 2 images, age 16-69 years) and a cross-sectional sample (Sample 2: nHI = 61 and nFEP = 89, age 10-30 years), all human males and females, is leveraged to calculate global folding and its nested subcomponents: sulcation index (SI, total sulcal/cortical hull area) and determinants of sulcal area: sulcal length and sulcal depth. Scaling of SI, sulcal area, and sulcal length with TBV in SZ and FEP was allometric and did not differ from HIs. Longitudinal age trajectories demonstrated steeper loss of SI and sulcal area through adulthood in SZ. Longitudinal allometric analysis revealed that both annual change in SI and sulcal area was significantly stronger related to change in TBV in SZ compared with HIs. Our results detail the first evidence of the disproportionate contribution of changes in SI and sulcal area to TBV changes in SZ. Longitudinal allometric analysis of sulcal morphology provides deeper insight into lifespan trajectories of cortical folding in SZ.SIGNIFICANCE STATEMENT Psychotic disorders are associated with deficits in cortical folding and brain size, but we lack knowledge of how these two morphometric features are related. We leverage cross-sectional and longitudinal samples in which we decompose folding into a set of nested subcomponents: sulcal and hull area, and sulcal depth and length. We reveal that, in both schizophrenia and first-episode psychosis, (1) scaling of subcomponents with brain size is different from expected scaling laws and (2) caution is warranted when interpreting results from traditional methods for brain size correction. Longitudinal allometric scaling points to loss of sulcal area as a principal contributor to loss of brain size in schizophrenia. These findings advance the understanding of cortical folding atypicalities in psychotic disorders.
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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, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- School of Medicine, Universidad Complutense, 28040 Madrid, Spain
| | - Javier Santonja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
| | - Laura Pina-Camacho
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- School of Medicine, Universidad Complutense, 28040 Madrid, Spain
| | - Pedro M Gordaliza
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, 28911 Madrid, Spain
| | - Alberto Fernández-Pena
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, 28911 Madrid, Spain
| | - Noemi González Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
| | - Elizabeth E L Buimer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Neeltje E M van Haren
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Sophia Children's Hospital, 3015 GD Rotterdam, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Eduard Vieta
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Bipolar Disorders Unit, Clinical Institute of Neurosciences, Hospital Clínic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, 08036 Barcelona, Spain
| | - Josefina Castro-Fornieles
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Department of Child and Adolescent Psychiatry and Psychology, Clinical Institute of Neurosciences, Hospital Clínic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, 08036 Barcelona, Spain
| | - Miquel Bernardo
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Barcelona Clinic Schizophrenia Unit, Hospital Clinic of Barcelona, Neuroscience Institute, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, 08036 Barcelona, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- School of Medicine, Universidad Complutense, 28040 Madrid, Spain
| | - René S Kahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 10029 New York
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
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Stone WS, Phillips MR, Yang LH, Kegeles LS, Susser ES, Lieberman JA. Neurodegenerative model of schizophrenia: Growing evidence to support a revisit. Schizophr Res 2022; 243:154-162. [PMID: 35344853 PMCID: PMC9189010 DOI: 10.1016/j.schres.2022.03.004] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/07/2022] [Accepted: 03/11/2022] [Indexed: 12/21/2022]
Abstract
Multidimensional progressive declines in the absence of standard biomarkers for neurodegeneration are observed commonly in the development of schizophrenia, and are accepted as consistent with neurodevelopmental etiological hypotheses to explain the origins of the disorder. Far less accepted is the possibility that neurodegenerative processes are involved as well, or even that key dimensions of function, such as cognition and aspects of biological integrity, such as white matter function, decline in chronic schizophrenia beyond levels associated with normal aging. We propose that recent research germane to these issues warrants a current look at the question of neurodegeneration. We propose the view that a neurodegenerative hypothesis provides a better explanation of some features of chronic schizophrenia, including accelerated aging, than is provided by neurodevelopmental hypotheses. Moreover, we suggest that neurodevelopmental influences in early life, including those that may extend to later life, do not preclude the development of neurodegenerative processes in later life, including some declines in cognitive and biological integrity. We evaluate these views by integrating recent findings in representative domains such as cognition and white and gray matter integrity with results from studies on accelerated aging, together with functional implications of neurodegeneration for our understanding of chronic schizophrenia.
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Affiliation(s)
- William S. Stone
- Harvard Medical School Department of Psychiatry at Beth Israel Deaconess Medical Center, Boston, Massachusetts,Corresponding Author: William S. Stone, Ph.D., Massachusetts Mental Health Center, 75 Fenwood Road, Boston, Massachusetts, USA,
| | - Michael R. Phillips
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, Shanghai, China,Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Lawrence H. Yang
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York,New York University College of Global Public Health, New York, New York
| | - Lawrence S. Kegeles
- Department of Psychiatry, Columbia University, New York, New York,New York State Psychiatric Institute, New York, New York
| | - Ezra S. Susser
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
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Jiang Y, Yao D, Zhou J, Tan Y, Huang H, Wang M, Chang X, Duan M, Luo C. Characteristics of disrupted topological organization in white matter functional connectome in schizophrenia. Psychol Med 2022; 52:1333-1343. [PMID: 32880241 DOI: 10.1017/s0033291720003141] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function. METHODS Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks. RESULTS At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions. CONCLUSIONS These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, P. R. China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yue Tan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - MeiLin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Department of Psychiatry, Chengdu Mental Health Center, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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Demro C, Shen C, Hendrickson TJ, Arend JL, Disner SG, Sponheim SR. Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins. Front Aging Neurosci 2022; 14:872867. [PMID: 35527740 PMCID: PMC9074783 DOI: 10.3389/fnagi.2022.872867] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 03/11/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.
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Affiliation(s)
- Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Chen Shen
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | | | - Jessica L. Arend
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Seth G. Disner
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
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