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Agid O. Re-evaluating the prognosis of schizophrenia: tackling the issue of inadequate treatment. Expert Rev Neurother 2024; 24:831-835. [PMID: 38879827 DOI: 10.1080/14737175.2024.2365943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 06/05/2024] [Indexed: 08/09/2024]
Affiliation(s)
- Ofer Agid
- Schizophrenia Program, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Canada
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Hua JPY, Abram SV, Loewy RL, Stuart B, Fryer SL, Vinogradov S, Mathalon DH. Brain Age Gap in Early Illness Schizophrenia and the Clinical High-Risk Syndrome: Associations With Experiential Negative Symptoms and Conversion to Psychosis. Schizophr Bull 2024; 50:1159-1170. [PMID: 38815987 PMCID: PMC11349027 DOI: 10.1093/schbul/sbae074] [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: 06/01/2024]
Abstract
BACKGROUND AND HYPOTHESIS Brain development/aging is not uniform across individuals, spawning efforts to characterize brain age from a biological perspective to model the effects of disease and maladaptive life processes on the brain. The brain age gap represents the discrepancy between estimated brain biological age and chronological age (in this case, based on structural magnetic resonance imaging, MRI). Structural MRI studies report an increased brain age gap (biological age > chronological age) in schizophrenia, with a greater brain age gap related to greater negative symptom severity. Less is known regarding the nature of this gap early in schizophrenia (ESZ), if this gap represents a psychosis conversion biomarker in clinical high-risk (CHR-P) individuals, and how altered brain development and/or aging map onto specific symptom facets. STUDY DESIGN Using structural MRI, we compared the brain age gap among CHR-P (n = 51), ESZ (n = 78), and unaffected comparison participants (UCP; n = 90), and examined associations with CHR-P psychosis conversion (CHR-P converters n = 10; CHR-P non-converters; n = 23) and positive and negative symptoms. STUDY RESULTS ESZ showed a greater brain age gap relative to UCP and CHR-P (Ps < .010). CHR-P individuals who converted to psychosis showed a greater brain age gap (P = .043) relative to CHR-P non-converters. A larger brain age gap in ESZ was associated with increased experiential (P = .008), but not expressive negative symptom severity. CONCLUSIONS Consistent with schizophrenia pathophysiological models positing abnormal brain maturation, results suggest abnormal brain development is present early in psychosis. An increased brain age gap may be especially relevant to motivational and functional deficits in schizophrenia.
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Affiliation(s)
- Jessica P Y Hua
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco VA Medical Center, University of California, San Francisco, CA, USA
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Samantha V Abram
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Barbara Stuart
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Susanna L Fryer
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Daniel H Mathalon
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
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Li X, Zeng J, Liu N, Yang C, Tao B, Sun H, Gong Q, Zhang W, Li CSR, Lui S. Progressive alterations of resting-state hypothalamic dysconnectivity in schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111127. [PMID: 39181307 DOI: 10.1016/j.pnpbp.2024.111127] [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: 04/15/2024] [Revised: 08/07/2024] [Accepted: 08/20/2024] [Indexed: 08/27/2024]
Abstract
BACKGROUND The hypothalamus may be involved in the pathogenesis of schizophrenia. Investigating hypothalamus dysfunction in schizophrenia and probing how it is related to symptoms and responds to antipsychotic medication is crucial for understanding the potential mechanism of hypothalamus dysfunction under the long-term illness. METHODS We recruited 216 patients with schizophrenia, including 140 antipsychotic-naïve first-episode patients (FES, including 44 patients with 1-year follow-up data), 76 chronically treated schizophrenia (CTS), and 210 healthy controls (HC). Hypothalamic seed-based functional connectivity (FC) was calculated and compared among the FES, CTS, and HC groups using analysis of covariance. Exploratory analysis was conducted between the FES patients at baseline and after 1-year follow-up. Significantly altered hypothalamic FCs were then related to clinical symptomology, while age- and illness-related regression analyses were also conducted and compared between diagnostic groups. RESULTS The FES patients showed decreased hypothalamic FCs with the midbrain and right thalamus, whereas the CTS patients showed more severe decreased hypothalamic FCs with the midbrain, right thalamus, left putamen, right caudate, and bilateral anterior cingulate cortex compared to HCs. These abnormalities were not correlated to the symptomology or illness duration, or not reversed by the antipsychotic treatment. Age-related hypothalamic FC decrease was also identified in the abovementioned regions, and a faster age-related decline of the hypothalamic FC was observed with the left putamen and bilateral anterior cingulate cortex. CONCLUSION Age-related hypothalamic FC decrease extends the functional alterations that characterize the neurodegenerative nature of schizophrenia. Future studies are required to further probe the hormonal or endocrinal underpinnings of such alterations and trace the precise progressive trajectories.
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Affiliation(s)
- Xing Li
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Jiaxin Zeng
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Naici Liu
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Chengmin Yang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Bo Tao
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hui Sun
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
| | - Chiang-Shan R Li
- Departments of Psychiatry and of Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
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4
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Jacobs GR, Coleman MJ, Lewandowski KE, Pasternak O, Cetin-Karayumak S, Mesholam-Gately RI, Wojcik J, Kennedy L, Knyazhanskaya E, Reid B, Swago S, Lyons MG, Rizzoni E, John O, Carrington H, Kim N, Kotler E, Veale S, Haidar A, Prunier N, Haaf M, Levitt JJ, Seitz-Holland J, Rathi Y, Kubicki M, Keshavan MS, Holt DJ, Seidman LJ, Öngür D, Breier A, Bouix S, Shenton ME. An Introduction to the Human Connectome Project for Early Psychosis. Schizophr Bull 2024:sbae123. [PMID: 39036958 DOI: 10.1093/schbul/sbae123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
BACKGROUND The time following a recent onset of psychosis is a critical period during which intervention may be maximally effective. Studying individuals in this period also offers an opportunity to investigate putative brain biomarkers of illness prior to the long-term effects of chronicity and medication. The Human Connectome Project for Early Psychosis (HCP-EP) was funded by the National Institutes of Mental Health (NIMH) as an extension of the original Human Connectome Project's approach to understanding the human brain and its structural and functional connections. DESIGN The HCP-EP data were collected at 3 sites in Massachusetts (Beth Israel Deaconess Medical Center, McLean Hospital, and Massachusetts General Hospital), and one site in Indiana (Indiana University). Brigham and Women's Hospital served as the data coordination center and as an imaging site. RESULTS The HCP-EP dataset includes high-quality clinical, cognitive, functional, neuroimaging, and blood specimen data acquired from 303 individuals between the ages of 16-35 years old with affective psychosis (n = 75), non-affective psychosis (n = 148), and healthy controls (n = 80). Participants with early psychosis were within 5 years of illness onset (mean duration = 1.9 years, standard deviation = 1.4 years). All data and novel or modified analytic tools developed as part of the study are publicly available to the research community through the NIMH Data Archive (NDA) or GitHub (https://github.com/pnlbwh). CONCLUSIONS This paper provides an overview of the specific HCP-EP procedures, assessments, and protocols, as well as a brief characterization of the study participants to make it easier for researchers to use this rich dataset. Although we focus here on discussing and comparing affective and non-affective psychosis groups, the HCP-EP dataset also provides sufficient information for investigators to group participants differently.
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Affiliation(s)
- Grace R Jacobs
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael J Coleman
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Ofer Pasternak
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, 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
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Raquelle I Mesholam-Gately
- Massachusetts Mental Health Center Public Psychiatry Division, Department of Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Joanne Wojcik
- Massachusetts Mental Health Center Public Psychiatry Division, Department of Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Leda Kennedy
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Evdokiya Knyazhanskaya
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Benjamin Reid
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sophia Swago
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Monica G Lyons
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth Rizzoni
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Omar John
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Holly Carrington
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicholas Kim
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elana Kotler
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Simone Veale
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Anastasia Haidar
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicholas Prunier
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Moritz Haaf
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry and Psychotherapy, Psychiatry Neuroimaging Branch (PNB), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - James J Levitt
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, VA Boston Healthcare System, Brockton Division, Brockton, MA, United States
| | - Johanna Seitz-Holland
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, 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
| | - Marek Kubicki
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, 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
| | - Matcheri S Keshavan
- Massachusetts Mental Health Center Public Psychiatry Division, Department of Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daphne J Holt
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Larry J Seidman
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Massachusetts Mental Health Center Public Psychiatry Division, Department of Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dost Öngür
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Alan Breier
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sylvain Bouix
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Software Engineering and Information Technology, École de Technologie Supérieure, Université du Québec, Montréal, QC, Canada
| | - Martha E Shenton
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, 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
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Leroux E, Masson L, Tréhout M, Dollfus S. Effects of Adapted Physical Activity on White Matter Integrity in Patients with Schizophrenia. Brain Sci 2024; 14:710. [PMID: 39061450 PMCID: PMC11274719 DOI: 10.3390/brainsci14070710] [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: 04/30/2024] [Revised: 07/12/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
Schizophrenia is associated with changes in white matter (WM) integrity and with reduced life expectancy, in part because of the cardiometabolic side effects of antipsychotics. Physical activity (PA) has emerged as a candidate lifestyle intervention that is safe and effective. The study aimed to assess how an adapted PA program delivered remotely by web (e-APA) improved WM integrity in patients with schizophrenia (SZPs) and healthy controls (HCs) and to evaluate associations among WM integrity, cardiorespiratory fitness, and symptom severity. This longitudinal study was conducted over 16 weeks with 31 participants (18 SZPs and 13 HCs). Diffusion tensor imaging and tract-based spatial statistics were employed to assess WM integrity. Cardiorespiratory fitness was measured by maximal oxygen uptake (VO2max), and assessments for clinical symptoms included the Positive and Negative Syndrome Scale, Self-evaluation of Negative Symptoms and the Brief Negative Syndrome Scale (BNSS). Only the SZPs had significantly increased WM integrity after the e-APA program, with increased fractional anisotropy and decreased radial diffusivity in fasciculi involved in motor functions and language process. Furthermore, decreased negative symptoms assessed with BNSS were associated with greater WM integrity following the program. These findings suggest that e-APA may improve WM integrity abnormalities and support e-APA as a promising therapeutic strategy.
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Affiliation(s)
- Elise Leroux
- “Physiopathology and Imaging of Neurological Disorders” PhIND, UMR-S U1237, INSERM, GIP Cyceron, 14000 Caen, France; (L.M.); (M.T.); (S.D.)
| | - Laura Masson
- “Physiopathology and Imaging of Neurological Disorders” PhIND, UMR-S U1237, INSERM, GIP Cyceron, 14000 Caen, France; (L.M.); (M.T.); (S.D.)
| | - Maxime Tréhout
- “Physiopathology and Imaging of Neurological Disorders” PhIND, UMR-S U1237, INSERM, GIP Cyceron, 14000 Caen, France; (L.M.); (M.T.); (S.D.)
- CHU de Caen Normandie, Centre Esquirol, Service de Psychiatrie Adulte, 14000 Caen, France
| | - Sonia Dollfus
- “Physiopathology and Imaging of Neurological Disorders” PhIND, UMR-S U1237, INSERM, GIP Cyceron, 14000 Caen, France; (L.M.); (M.T.); (S.D.)
- CHU de Caen Normandie, Centre Esquirol, Service de Psychiatrie Adulte, 14000 Caen, France
- Normandie Univ, Université de Caen Normandie, UFR de Santé, 14000 Caen, France
- Fédération Hospitalo-Universitaire “Améliorer le Pronostic des Troubles Addictifs et Mentaux par une Médecine Personnalisée (A2M2P)“, 14000 Caen, France
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6
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Hahn W, Tsalouchidou PE, Nagels A, Straube B. Neural activation during natural speech and rests in patients with schizophrenia and schizophrenia spectrum disorders-an fMRI pilot trial. Front Psychiatry 2024; 15:1402818. [PMID: 38938468 PMCID: PMC11210388 DOI: 10.3389/fpsyt.2024.1402818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/24/2024] [Indexed: 06/29/2024] Open
Abstract
Background In schizophrenia patients, spontaneous speech production has been hypothesized as correlating with right hemispheric activation, including the inferior frontal and superior temporal gyri as speech-relevant areas. However, robust evidence for this association is still missing. The aim of the present fMRI study is to examine BOLD signal changes during natural, fluent speech production in patients with schizophrenia in the chronic phase of their disease. Methods Using a case-control design, the study included 15 right-handed patients with schizophrenia spectrum disorders as well as 15 healthy controls. The participants described eight pictures from the Thematic Apperception Test for 1 min each, while BOLD signal changes were measured with 3T fMRI. The occurrence of positive and negative formal thought disorders was determined using standardized psychopathological assessments. Results We found significant BOLD signal changes during spontaneous speech production in schizophrenia patients compared to healthy controls, particularly in the right hemispheric network. A post-hoc analysis showed that this right-hemispheric lateralization was mainly driven by activation during experimental rests. Furthermore, the TLI sum value in patients correlated negatively with BOLD signal changes in the right Rolandic operculum. Conclusions Possible underlying factors for this inverse right-hemispheric lateralization of speech-associated areas are structural changes and transmitter system alterations, as well as a lack of neural downregulation in schizophrenia patients during rest periods due to dysfunctional executive functions. When examining spontaneous speech as the most natural form of language, other influencing factors, such as social cognition or emotional processing, should be considered. Our results indicate that future studies should consider group differences during rest, which might provide additional information typically covered in differential contrasts.
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Affiliation(s)
- Wiebke Hahn
- Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | | | - Arne Nagels
- Department of English and Linguistics, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
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Sapienza J, Pacchioni F, Spangaro M, Bosia M. Dysconnection in schizophrenia: Filling the dots from old to new evidence. Clin Neurophysiol 2024; 162:226-228. [PMID: 38555237 DOI: 10.1016/j.clinph.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 03/14/2024] [Accepted: 03/14/2024] [Indexed: 04/02/2024]
Affiliation(s)
- Jacopo Sapienza
- Schizophrenia Research and Clinical Unit, IRCCS San Raffaele Hospital, Milan, Italy; Department of Humanities and Life Sciences, University School for Advanced Studies IUSS, Pavia, Italy.
| | - Federico Pacchioni
- Schizophrenia Research and Clinical Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Marco Spangaro
- Schizophrenia Research and Clinical Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Marta Bosia
- Schizophrenia Research and Clinical Unit, IRCCS San Raffaele Hospital, Milan, Italy; School of Medicine, Vita -Salute San Raffaele University, Milan, Italy
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8
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Cole RH, Moussawi K, Joffe ME. Opioid modulation of prefrontal cortex cells and circuits. Neuropharmacology 2024; 248:109891. [PMID: 38417545 PMCID: PMC10939756 DOI: 10.1016/j.neuropharm.2024.109891] [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: 11/10/2023] [Revised: 01/30/2024] [Accepted: 02/26/2024] [Indexed: 03/01/2024]
Abstract
Several neurochemical systems converge in the prefrontal cortex (PFC) to regulate cognitive and motivated behaviors. A rich network of endogenous opioid peptides and receptors spans multiple PFC cell types and circuits, and this extensive opioid system has emerged as a key substrate underlying reward, motivation, affective behaviors, and adaptations to stress. Here, we review the current evidence for dysregulated cortical opioid signaling in the pathogenesis of psychiatric disorders. We begin by providing an introduction to the basic anatomy and function of the cortical opioid system, followed by a discussion of endogenous and exogenous opioid modulation of PFC function at the behavioral, cellular, and synaptic level. Finally, we highlight the therapeutic potential of endogenous opioid targets in the treatment of psychiatric disorders, synthesizing clinical reports of altered opioid peptide and receptor expression and activity in human patients and summarizing new developments in opioid-based medications. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".
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Affiliation(s)
- Rebecca H Cole
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15219, USA; Translational Neuroscience Program, University of Pittsburgh, Pittsburgh, PA, USA; Center for Neuroscience University of Pittsburgh, Pittsburgh, PA, USA
| | - Khaled Moussawi
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15219, USA; Translational Neuroscience Program, University of Pittsburgh, Pittsburgh, PA, USA; Center for Neuroscience University of Pittsburgh, Pittsburgh, PA, USA
| | - Max E Joffe
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15219, USA; Translational Neuroscience Program, University of Pittsburgh, Pittsburgh, PA, USA; Center for Neuroscience University of Pittsburgh, Pittsburgh, PA, USA.
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9
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Svancer P, Capek V, Skoch A, Kopecek M, Vochoskova K, Fialova M, Furstova P, Jakob L, Bakstein E, Kolenic M, Hlinka J, Knytl P, Spaniel F. Longitudinal assessment of ventricular volume trajectories in early-stage schizophrenia: evidence of both enlargement and shrinkage. BMC Psychiatry 2024; 24:309. [PMID: 38658884 PMCID: PMC11040899 DOI: 10.1186/s12888-024-05749-5] [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: 10/19/2023] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. METHODS We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. RESULTS Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. CONCLUSION Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.
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Affiliation(s)
- Patrik Svancer
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Vaclav Capek
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Miloslav Kopecek
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Kristyna Vochoskova
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Marketa Fialova
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Petra Furstova
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Lea Jakob
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eduard Bakstein
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Marian Kolenic
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jaroslav Hlinka
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Pavel Knytl
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic.
- Third Faculty of Medicine, Charles University, Prague, Czech Republic.
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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] [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, η 2p = 0.104) and right ( p < 0.001, η 2 = 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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Onwordi EC, Whitehurst T, Shatalina E, Mansur A, Arumuham A, Osugo M, Marques TR, Jauhar S, Gupta S, Mehrotra R, Rabiner EA, Gunn RN, Natesan S, Howes OD. Synaptic Terminal Density Early in the Course of Schizophrenia: An In Vivo UCB-J Positron Emission Tomographic Imaging Study of SV2A. Biol Psychiatry 2024; 95:639-646. [PMID: 37330164 PMCID: PMC10923626 DOI: 10.1016/j.biopsych.2023.05.022] [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: 10/26/2022] [Revised: 05/19/2023] [Accepted: 05/22/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND The synaptic hypothesis is an influential theory of the pathoetiology of schizophrenia (SCZ), which is supported by the finding that there is lower uptake of the synaptic terminal density marker [11C]UCB-J in patients with chronic SCZ than in control participants. However, it is unclear whether these differences are present early in the illness. To address this, we investigated [11C]UCB-J volume of distribution (VT) in antipsychotic-naïve/free patients with SCZ who were recruited from first-episode services compared with healthy volunteers. METHODS Forty-two volunteers (SCZ n = 21, healthy volunteers n = 21) underwent [11C]UCB-J positron emission tomography to index [11C]UCB-J VT and distribution volume ratio in the anterior cingulate, frontal, and dorsolateral prefrontal cortices; the temporal, parietal and occipital lobes; and the hippocampus, thalamus, and amygdala. Symptom severity was assessed in the SCZ group using the Positive and Negative Syndrome Scale. RESULTS We found no significant effects of group on [11C]UCB-J VT or distribution volume ratio in most regions of interest (effect sizes from d = 0.0-0.7, p > .05), with two exceptions: we found lower distribution volume ratio in the temporal lobe (d = 0.7, uncorrected p < .05) and lower VT/fp in the anterior cingulate cortex in patients (d = 0.7, uncorrected p < .05). The Positive and Negative Syndrome Scale total score was negatively associated with [11C]UCB-J VT in the hippocampus in the SCZ group (r = -0.48, p = .03). CONCLUSIONS These findings indicate that large differences in synaptic terminal density are not present early in SCZ, although there may be more subtle effects. When taken together with previous evidence of lower [11C]UCB-J VT in patients with chronic illness, this may indicate synaptic density changes during the course of SCZ.
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Affiliation(s)
- Ellis Chika Onwordi
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; Centre for Psychiatry and Mental Health, Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.
| | - Thomas Whitehurst
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Ekaterina Shatalina
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Ayla Mansur
- Department of Brain Sciences, Imperial College London, The Commonwealth Building, Hammersmith Hospital, London, United Kingdom; Invicro, Burlington Danes Building, London, United Kingdom
| | - Atheeshaan Arumuham
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Martin Osugo
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Tiago Reis Marques
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Sameer Jauhar
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Susham Gupta
- Early Detection and Early Intervention, East London National Health Service Foundation Trust, London, United Kingdom
| | - Ravi Mehrotra
- Early Intervention in Psychosis Team, West Middlesex University Hospital, West London National Health Service Trust, Isleworth, London, United Kingdom
| | - Eugenii A Rabiner
- Invicro, Burlington Danes Building, London, United Kingdom; Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Roger N Gunn
- Department of Brain Sciences, Imperial College London, The Commonwealth Building, Hammersmith Hospital, London, United Kingdom; Invicro, Burlington Danes Building, London, United Kingdom
| | - Sridhar Natesan
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Oliver D Howes
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
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12
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Normand F, Gajwani M, Côté DC, Allard A. NBS-SNI, an extension of the network-based statistic: Abnormal functional connections between important structural actors. Netw Neurosci 2024; 8:44-80. [PMID: 38562286 PMCID: PMC10861162 DOI: 10.1162/netn_a_00344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 10/11/2023] [Indexed: 04/04/2024] Open
Abstract
Elucidating the coupling between the structure and the function of the brain and its development across maturation has attracted a lot of interest in the field of network neuroscience in the last 15 years. Mounting evidence supports the hypothesis that the onset of certain brain disorders is linked with the interplay between the structural architecture of the brain and its functional processes, often accompanied with unusual connectivity features. This paper introduces a method called the network-based statistic-simultaneous node investigation (NBS-SNI) that integrates both representations into a single framework, and identifies connectivity abnormalities in case-control studies. With this method, significance is given to the properties of the nodes, as well as to their connections. This approach builds on the well-established network-based statistic (NBS) proposed in 2010. We uncover and identify the regimes in which NBS-SNI offers a gain in statistical resolution to identify a contrast of interest using synthetic data. We also apply our method on two real case-control studies, one consisting of individuals diagnosed with autism and the other consisting of individuals diagnosed with early psychosis. Using NBS-SNI and node properties such as the closeness centrality and local information dimension, we found hypo- and hyperconnected subnetworks and show that our method can offer a 9 percentage points gain in prediction power over the standard NBS.
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Affiliation(s)
- Francis Normand
- Centre de Recherche CERVO, Québec, Canada
- Centre Interdisciplinaire en Modélisation Mathématique, Université Laval, Québec, Canada
- The Turner Institute for Brain and Mental Health and Monash Biomedical Imaging, Monash University, Melbourne, Australia
| | - Mehul Gajwani
- The Turner Institute for Brain and Mental Health and Monash Biomedical Imaging, Monash University, Melbourne, Australia
| | - Daniel C. Côté
- Centre de Recherche CERVO, Québec, Canada
- Département de Physique, de Génie Physique et d’Optique, Université Laval, Québec, Canada
| | - Antoine Allard
- Centre Interdisciplinaire en Modélisation Mathématique, Université Laval, Québec, Canada
- Département de Physique, de Génie Physique et d’Optique, Université Laval, Québec, Canada
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Konttajärvi T, Haapea M, Huhtaniska S, Björnholm L, Miettunen J, Isohanni M, Penttilä M, Murray GK, Koponen H, Vernon AC, Jääskeläinen E, Lieslehto J. The contribution of first-episode illness characteristics and cumulative antipsychotic usage to progressive structural brain changes over a long-term follow-up in schizophrenia. Psychiatry Res Neuroimaging 2024; 339:111790. [PMID: 38354478 DOI: 10.1016/j.pscychresns.2024.111790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 11/26/2023] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
Exposure to antipsychotics as well as certain first-episode illness characteristics have been associated with greater gray matter (GM) deficits in the early phase of schizophrenia. Whether the first-episode illness characteristics affect the long-term progression of the structural brain changes remain unexplored. We therefore assessed the role of first-episode illness characteristics and life-time antipsychotic use in relation to long-term structural brain GM changes in schizophrenia. Individuals with schizophrenia (SZ, n = 29) and non-psychotic controls (n = 61) from the Northern Finland Birth Cohort 1966 underwent structural MRI at the ages of 34 (baseline) and 43 (follow-up) years. At follow-up, the average duration of illness was 19.8 years. Voxel-based morphometry was used to assess the effects of predictors on longitudinal GM changes in schizophrenia-relevant brain areas. Younger age of onset (AoO), higher cumulative antipsychotic dose and severity of symptoms were associated with greater GM deficits in the SZ group at follow-up. None of the first-episode illness characteristics were associated with longitudinal GM changes during 9-year follow-up period. We conclude that a younger AoO and high life-time antipsychotic use may contribute to progression of structural brain changes in schizophrenia. Apart from AoO, other first-episode illness characteristics may not contribute to longitudinal GM changes in midlife.
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Affiliation(s)
| | - Marianne Haapea
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University of Hospital, Finland; Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Sanna Huhtaniska
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Lassi Björnholm
- Department of Psychiatry, Oulu University of Hospital, Finland; Research Unit of Clinical Neuroscience, University of Oulu, Finland
| | - Jouko Miettunen
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland
| | - Matti Isohanni
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Matti Penttilä
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Hannu Koponen
- University of Helsinki, Helsinki University Hospital, Psychiatry, Helsinki, Finland
| | - Anthony C Vernon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London,United Kingdom
| | - Erika Jääskeläinen
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University of Hospital, Finland
| | - Johannes Lieslehto
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland; Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden
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14
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Deng L, Wei W, Qiao C, Yin Y, Li X, Yu H, Jian L, Ma X, Zhao L, Wang Q, Deng W, Guo W, Li T. Dynamic aberrances of substantia nigra-relevant coactivation patterns in first-episode treatment-naïve patients with schizophrenia. Psychol Med 2024:1-11. [PMID: 38523252 DOI: 10.1017/s0033291724000655] [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: 03/26/2024]
Abstract
BACKGROUND Although dopaminergic disturbances are well-known in schizophrenia, the understanding of dopamine-related brain dynamics remains limited. This study investigates the dynamic coactivation patterns (CAPs) associated with the substantia nigra (SN), a key dopaminergic nucleus, in first-episode treatment-naïve patients with schizophrenia (FES). METHODS Resting-state fMRI data were collected from 84 FES and 94 healthy controls (HCs). Frame-wise clustering was implemented to generate CAPs related to SN activation or deactivation. Connectome features of each CAP were derived using an edge-centric method. The occurrence for each CAP and the balance ratio for antagonistic CAPs were calculated and compared between two groups, and correlations between temporal dynamic metrics and symptom burdens were explored. RESULTS Functional reconfigurations in CAPs exhibited significant differences between the activation and deactivation states of SN. During SN activation, FES more frequently recruited a CAP characterized by activated default network, language network, control network, and the caudate, compared to HCs (F = 8.54, FDR-p = 0.030). Moreover, FES displayed a tilted balance towards a CAP featuring SN-coactivation with the control network, caudate, and thalamus, as opposed to its antagonistic CAP (F = 7.48, FDR-p = 0.030). During SN deactivation, FES exhibited increased recruitment of a CAP with activated visual and dorsal attention networks but decreased recruitment of its opposing CAP (F = 6.58, FDR-p = 0.034). CONCLUSION Our results suggest that neuroregulatory dysfunction in dopaminergic pathways involving SN potentially mediates aberrant time-varying functional reorganizations in schizophrenia. This finding enriches the dopamine hypothesis of schizophrenia from the perspective of brain dynamics.
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Affiliation(s)
- Lihong Deng
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, Zhejiang, China
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wei Wei
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Chunxia Qiao
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yubing Yin
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaojing Li
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hua Yu
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Lingqi Jian
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, 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
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, Zhejiang, China
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15
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Komatsu H, Onoguchi G, Silverstein SM, Jerotic S, Sakuma A, Kanahara N, Kakuto Y, Ono T, Yabana T, Nakazawa T, Tomita H. Retina as a potential biomarker in schizophrenia spectrum disorders: a systematic review and meta-analysis of optical coherence tomography and electroretinography. Mol Psychiatry 2024; 29:464-482. [PMID: 38081943 PMCID: PMC11116118 DOI: 10.1038/s41380-023-02340-4] [Citation(s) in RCA: 1] [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: 08/24/2023] [Revised: 11/16/2023] [Accepted: 11/23/2023] [Indexed: 05/25/2024]
Abstract
INTRODUCTION Abnormal findings on optical coherence tomography (OCT) and electroretinography (ERG) have been reported in participants with schizophrenia spectrum disorders (SSDs). This study aims to reveal the pooled standard mean difference (SMD) in retinal parameters on OCT and ERG among participants with SSDs and healthy controls and their association with demographic characteristics, clinical symptoms, smoking, diabetes mellitus, and hypertension. METHODS Using PubMed, Scopus, Web of Science, and PSYNDEX, we searched the literature from inception to March 31, 2023, using specific search terms. This study was registered with PROSPERO (CRD4202235795) and conducted according to PRISMA 2020. RESULTS We included 65 studies in the systematic review and 44 in the meta-analysis. Participants with SSDs showed thinning of the peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell layer- inner plexiform cell layer, and retinal thickness in all other segments of the macula. A meta-analysis of studies that excluded SSD participants with diabetes and hypertension showed no change in results, except for pRNFL inferior and nasal thickness. Furthermore, a significant difference was found in the pooled SMD of pRNFL temporal thickness between the left and right eyes. Meta-regression analysis revealed an association between retinal thinning and duration of illness, positive and negative symptoms. In OCT angiography, no differences were found in the foveal avascular zone and superficial layer foveal vessel density between SSD participants and controls. In flash ERG, the meta-analysis showed reduced amplitude of both a- and b-waves under photopic and scotopic conditions in SSD participants. Furthermore, the latency of photopic a-wave was significantly shorter in SSD participants in comparison with HCs. DISCUSSION Considering the prior report of retinal thinning in unaffected first-degree relatives and the results of the meta-analysis, the findings suggest that retinal changes in SSDs have both trait and state aspects. Future longitudinal multimodal retinal imaging studies are needed to clarify the pathophysiological mechanisms of these changes and to clarify their utility in individual patient monitoring efforts.
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Affiliation(s)
- Hiroshi Komatsu
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan.
- Miyagi Psychiatric Center, Natori, Japan.
| | - Goh Onoguchi
- Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
| | - Stefan Jerotic
- Clinic for Psychiatry, University Clinical Centre of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Atsushi Sakuma
- Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - 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, Tohoku University Graduate School of Medicine, 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
- 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, Tohoku University Graduate School of Medicine, Sendai, Japan
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16
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Gao T, Wang X, Cen H, Li X, Zhai Z, Lu C, Dong Y, Zhang S, Zhuo K, Xiang Q, Wang Y, Liu D. Cross-modal associative memory impairment in schizophrenia. Neuropsychologia 2023; 191:108721. [PMID: 37918479 DOI: 10.1016/j.neuropsychologia.2023.108721] [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: 05/03/2023] [Revised: 10/30/2023] [Accepted: 10/30/2023] [Indexed: 11/04/2023]
Abstract
Impaired associative memory function in patients with schizophrenia has received considerable attention. However, previous studies have primarily concentrated on unisensory materials, which limits our understanding of the broader implications of this impairment. In this study, we sought to expand on this knowledge by examining two types of associative memory domains in individuals with schizophrenia, leveraging both visual (Vis) and auditory (Aud) materials. A total of 32 patients with schizophrenia and 29 healthy controls were recruited to participate in the study. Each participant participated in an experiment composed of three paradigms in which different abstract materials (Aud-Aud, Aud-Vis, and Vis-Vis) were presented. Subsequently, the discriminability scores of the two groups were calculated and compared in different modal tasks. Results from the study indicated that individuals with schizophrenia demonstrated varying degrees of associative memory dysfunction in both the same and cross-modalities, with the latter having a significantly lower score than healthy controls (t = 4.120, p < 0.001). Additionally, the cross-modal associative memory function was significantly and negatively correlated with the severity of negative symptoms among individuals diagnosed with schizophrenia (r = -0.362, p = 0.042). This study provides evidence of abnormalities in the processing and memorization of information that integrates multiple sensory modalities in individuals with schizophrenia. This is of great significance for further understanding the cognitive symptoms and pathological mechanisms of schizophrenia, potentially guiding the development of relevant interventions and treatment methods.
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Affiliation(s)
- Tianhao Gao
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Xiaoliang Wang
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Haixin Cen
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Xuan Li
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Zhaolin Zhai
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Chang Lu
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Yuke Dong
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Suzhen Zhang
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Kaiming Zhuo
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Qiong Xiang
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Yan Wang
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China.
| | - Dengtang Liu
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China; Institute of Mental Health, Fudan University, Shanghai, 200030, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
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17
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Moon SY, Park H, Lee W, Lee S, Lho SK, Kim M, Kim KW, Kwon JS. Magnetic resonance texture analysis reveals stagewise nonlinear alterations of the frontal gray matter in patients with early psychosis. Mol Psychiatry 2023; 28:5309-5318. [PMID: 37500824 DOI: 10.1038/s41380-023-02163-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/13/2023] [Accepted: 06/23/2023] [Indexed: 07/29/2023]
Abstract
Although gray matter (GM) abnormalities are present from the early stages of psychosis, subtle/miniscule changes may not be detected by conventional volumetry. Texture analysis (TA), which permits quantification of the complex interrelationship between contrasts at the individual voxel level, may capture subtle GM changes with more sensitivity than does volume or cortical thickness (CTh). We performed three-dimensional TA in nine GM regions of interest (ROIs) using T1 magnetic resonance images from 101 patients with first-episode psychosis (FEP), 85 patients at clinical high risk (CHR) for psychosis, and 147 controls. Via principal component analysis, three features of gray-level cooccurrence matrix - informational measure of correlation 1 (IMC1), autocorrelation (AC), and inverse difference (ID) - were selected to analyze cortical texture in the ROIs that showed a significant change in volume or CTh in the study groups. Significant reductions in GM volume and CTh of various frontotemporal regions were found in the FEP compared with the controls. Increased frontal AC was found in the FEP group compared to the controls after adjusting for volume and CTh changes. While volume and CTh were preserved in the CHR group, a stagewise nonlinear increase in frontal IMC1 was found, which exceeded both the controls and FEP group. Increased frontal IMC1 was also associated with a lesser severity of attenuated positive symptoms in the CHR group, while neither volume nor CTh was. The results of the current study suggest that frontal IMC1 may reflect subtle, dynamic GM changes and the symptomatology of the CHR stage with greater sensitivity, even in the absence of gross GM abnormalities. Some structural mechanisms that may contribute to texture changes (e.g., macrostructural cortical lamina, neuropil/myelination, cortical reorganization) and their possible implications are explored and discussed. Texture may be a useful tool to investigate subtle and dynamic GM abnormalities, especially during the CHR period.
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Affiliation(s)
- Sun Young Moon
- Department of Public Health Service, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Hyungyou Park
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | - Won Lee
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | - Subin Lee
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | | | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ki Woong Kim
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Jun Soo Kwon
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea.
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
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18
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Chopra S, Segal A, Oldham S, Holmes A, Sabaroedin K, Orchard ER, Francey SM, O’Donoghue B, Cropley V, Nelson B, Graham J, Baldwin L, Tiego J, Yuen HP, Allott K, Alvarez-Jimenez M, Harrigan S, Fulcher BD, Aquino K, Pantelis C, Wood SJ, Bellgrove M, McGorry PD, Fornito A. Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis. JAMA Psychiatry 2023; 80:1246-1257. [PMID: 37728918 PMCID: PMC10512169 DOI: 10.1001/jamapsychiatry.2023.3293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/21/2023] [Indexed: 09/22/2023]
Abstract
Importance Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. Objective To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. Design, Settings, and Participants This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. Main Outcomes and Measures Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. Results Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. Conclusion and Relevance These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.
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Affiliation(s)
- Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Ashlea Segal
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Stuart Oldham
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Alexander Holmes
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Kristina Sabaroedin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Radiology, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Paediatrics, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Edwina R. Orchard
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Child Study Centre, Yale University, New Haven, Connecticut
| | - Shona M. Francey
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Brian O’Donoghue
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
| | - Barnaby Nelson
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jessica Graham
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lara Baldwin
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Kelly Allott
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Susy Harrigan
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Mental Health, Melbourne School of Global and Population Health, The University of Melbourne, Parkville, Victoria, Australian
| | - Ben D. Fulcher
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Kevin Aquino
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Centre for Complex Systems, University of Sydney, Sydney, New South Wales, Australia
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
- NorthWestern Mental Health, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Western Health Sunshine Hospital, St Albans, Victoria, Australia
| | - Stephen J. Wood
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- School of Psychology, University of Birmingham, Edgbaston, United Kingdom
| | - Mark Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
| | - Patrick D. McGorry
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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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: 1.0] [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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Sfera A, Andronescu L, Britt WG, Himsl K, Klein C, Rahman L, Kozlakidis Z. Receptor-Independent Therapies for Forensic Detainees with Schizophrenia-Dementia Comorbidity. Int J Mol Sci 2023; 24:15797. [PMID: 37958780 PMCID: PMC10647468 DOI: 10.3390/ijms242115797] [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: 08/31/2023] [Revised: 10/23/2023] [Accepted: 10/28/2023] [Indexed: 11/15/2023] Open
Abstract
Forensic institutions throughout the world house patients with severe psychiatric illness and history of criminal violations. Improved medical care, hygiene, psychiatric treatment, and nutrition led to an unmatched longevity in this population, which previously lived, on average, 15 to 20 years shorter than the public at large. On the other hand, longevity has contributed to increased prevalence of age-related diseases, including neurodegenerative disorders, which complicate clinical management, increasing healthcare expenditures. Forensic institutions, originally intended for the treatment of younger individuals, are ill-equipped for the growing number of older offenders. Moreover, as antipsychotic drugs became available in 1950s and 1960s, we are observing the first generation of forensic detainees who have aged on dopamine-blocking agents. Although the consequences of long-term treatment with these agents are unclear, schizophrenia-associated gray matter loss may contribute to the development of early dementia. Taken together, increased lifespan and the subsequent cognitive deficit observed in long-term forensic institutions raise questions and dilemmas unencountered by the previous generations of clinicians. These include: does the presence of neurocognitive dysfunction justify antipsychotic dose reduction or discontinuation despite a lifelong history of schizophrenia and violent behavior? Should neurolipidomic interventions become the standard of care in elderly individuals with lifelong schizophrenia and dementia? Can patients with schizophrenia and dementia meet the Dusky standard to stand trial? Should neurocognitive disorders in the elderly with lifelong schizophrenia be treated differently than age-related neurodegeneration? In this article, we hypothesize that gray matter loss is the core symptom of schizophrenia which leads to dementia. We hypothesize further that strategies to delay or stop gray matter depletion would not only improve the schizophrenia sustained recovery, but also avert the development of major neurocognitive disorders in people living with schizophrenia. Based on this hypothesis, we suggest utilization of both receptor-dependent and independent therapeutics for chronic psychosis.
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Affiliation(s)
- Adonis Sfera
- Paton State Hospital, 3102 Highland Ave, Patton, CA 92369, USA; (L.A.); (K.H.)
- School of Behavioral Health, Loma Linda University, 11139 Anderson St., Loma Linda, CA 92350, USA
- Department of Psychiatry, University of California, Riverside 900 University Ave, Riverside, CA 92521, USA
| | - Luminita Andronescu
- Paton State Hospital, 3102 Highland Ave, Patton, CA 92369, USA; (L.A.); (K.H.)
| | - William G. Britt
- Department of Psychiatry, School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA;
| | - Kiera Himsl
- Paton State Hospital, 3102 Highland Ave, Patton, CA 92369, USA; (L.A.); (K.H.)
| | - Carolina Klein
- California Department of State Hospitals, Sacramento, CA 95814, USA;
| | - Leah Rahman
- Department of Neuroscience, University of Oregon, 1585 E 13th Ave, Eugene, OR 97403, USA;
| | - Zisis Kozlakidis
- International Agency for Research on Cancer, 69366 Lyon Cedex, France;
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21
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Emsley R. Antipsychotics and structural brain changes: could treatment adherence explain the discrepant findings? Ther Adv Psychopharmacol 2023; 13:20451253231195258. [PMID: 37701891 PMCID: PMC10493054 DOI: 10.1177/20451253231195258] [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: 03/15/2023] [Accepted: 07/11/2023] [Indexed: 09/14/2023] Open
Abstract
Progressive structural brain changes are well documented in schizophrenia and have been linked to both illness progression and the extent of antipsychotic treatment exposure. Literature reporting longitudinal changes in brain structure in individuals with schizophrenia is selectively reviewed to assess the roles of illness, antipsychotic treatment, adherence and other factors in the genesis of these changes. This narrative review considers literature investigating longitudinal changes in brain structure in individuals with schizophrenia. The review focusses on structural changes in the cortex, basal ganglia and white matter. It also examines effects of medication non-adherence and relapse on the clinical course of the illness and on structural brain changes. Studies investigating structural magnetic resonance imaging changes in patients treated with long-acting injectable antipsychotics are reviewed. Temporal changes in brain structure in schizophrenia can be divided into those that are associated with antipsychotic treatment and those that are not. Changes associated with treatment include increases in basal ganglia and white matter volumes. Relapse episodes may be a critical factor in illness progression and brain volume reductions. Medication adherence may be an important factor that could explain the findings that brain volume reductions are associated with poor treatment response, higher intensity of antipsychotic treatment exposure and more time spent in relapse. Improved adherence via long-acting injectable antipsychotics and adherence focussed psychosocial interventions could maximize protective effects of antipsychotics against illness progression.
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Affiliation(s)
- Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Tygerberg Campus, Cape Town 8000, South Africa
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22
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Dai R, Herold CJ, Wang X, Kong L, Schröder J. Structural brain networks in schizophrenia based on nonnegative matrix factorization. Psychiatry Res Neuroimaging 2023; 334:111690. [PMID: 37480705 DOI: 10.1016/j.pscychresns.2023.111690] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 06/11/2023] [Accepted: 07/18/2023] [Indexed: 07/24/2023]
Abstract
Schizophrenia is a severe mental disease with significant morphometric reductions in gray matter volume and cortical thickness in a variety of brain regions. However, most studies only focused on the voxel level alterations in specific cerebral regions and ignored the spatial relationship between voxels. In the present study, we used a novel, data-driven technique-nonnegative matrix factorization (NMF) to group voxels with similar information into a network, and studied the structural covariance at the network level in schizophrenia. Our sample included 36 patients with schizophrenia and 21 healthy controls. Compared with healthy controls, patients with schizophrenia showed significant gray matter volume reductions in six structural covariance networks (dorsal striatum, thalamus, hippocampus-parahippocampus, supplementary motor area-fusiform, middle/inferior temporal network, frontal-parietal-occipital network). Our findings confirmed the assumption of a disturbance in the cortical-subcortical circuit in schizophrenia and suggested that NMF is a useful multivariate method to identify brain networks, which provides a new perspective to study the neural mechanism in schizophrenia.
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Affiliation(s)
- Rongjie Dai
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | - Christina J Herold
- Section of Geriatric Psychiatry, Department of Psychiatry, University of Heidelberg, Germany
| | - Xingsong Wang
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | - Li Kong
- Department of Psychology, Shanghai Normal University, Shanghai, China.
| | - Johannes Schröder
- Section of Geriatric Psychiatry, Department of Psychiatry, University of Heidelberg, Germany
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23
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Quinn ME, Shields GS. The Insidious Influence of Stress: An Integrated Model of Stress, Executive Control, and Psychopathology. Clin Psychol Sci 2023; 11:773-800. [PMID: 37701497 PMCID: PMC10497220 DOI: 10.1177/21677026221149736] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
Although exposure to acute stress undoubtedly contributes to psychopathology, most individuals do not develop psychopathology following stress exposure. To explain this, biological, emotional, and cognitive responses to stress have been implicated, but individual differences in executive control (i.e., top-down control of cognition and behavior) measured in response to stress has only recently emerged as a potential factor contributing to psychopathology. In this review, we introduce a model-the integrated model of stress, executive control, and psychopathology-positing how the impairing effects of acute stress on executive control can contribute to psychopathology. We link to research on biological, emotional, and cognitive processes, all of which can be impacted by executive control, to propose a framework for how poorer executive control under conditions of acute stress can contribute to psychopathology. This integrated model is intended to further our understanding of who is more susceptible to the negative consequences of stress.
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24
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Todd J, Salisbury D, Michie PT. Why mismatch negativity continues to hold potential in probing altered brain function in schizophrenia. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2023; 2:e144. [PMID: 38867817 PMCID: PMC11114358 DOI: 10.1002/pcn5.144] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/21/2023] [Accepted: 08/30/2023] [Indexed: 06/14/2024]
Abstract
The brain potential known as mismatch negativity (MMN) is one of the most studied indices of altered brain function in schizophrenia. This review looks at what has been learned about MMN in schizophrenia over the last three decades and why the level of interest and activity in this field of research remains strong. A diligent consideration of available evidence suggests that MMN can serve as a biomarker in schizophrenia, but perhaps not the kind of biomarker that early research supposed. This review concludes that MMN measurement is likely to be most useful as a monitoring and response biomarker enabling tracking of an underlying pathology and efficacy of interventions, respectively. The role of, and challenges presented by, pre-clinical models is discussed as well as the merits of different methodologies that can be brought to bear in pursuing a deeper understanding of pathophysiology that might explain smaller MMN in schizophrenia.
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Affiliation(s)
- Juanita Todd
- School of Psychological SciencesUniversity of NewcastleNewcastleNew South WalesAustralia
| | - Dean Salisbury
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Patricia T. Michie
- School of Psychological SciencesUniversity of NewcastleNewcastleNew South WalesAustralia
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25
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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 DOI: 10.1186/s12916-023-02935-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [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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26
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Hua JPY, Loewy RL, Stuart B, Fryer SL, Niendam TA, Carter CS, Vinogradov S, Mathalon DH. Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia. Psychiatry Res Neuroimaging 2023; 332:111653. [PMID: 37121090 PMCID: PMC10362971 DOI: 10.1016/j.pscychresns.2023.111653] [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: 01/23/2023] [Revised: 03/27/2023] [Accepted: 04/18/2023] [Indexed: 05/02/2023]
Abstract
Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.
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Affiliation(s)
- Jessica P Y Hua
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco VA Medical Center, and the University of California, San Francisco, CA, United States; Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States; Department of Psychological Sciences, University of Missouri, Columbia, 65211, MO, United States
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States
| | - Barbara Stuart
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States
| | - Susanna L Fryer
- Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States
| | - Tara A Niendam
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, 95616, CA, United States
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, 95616, CA, United States
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, 55455, MN, United States
| | - Daniel H Mathalon
- Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States.
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27
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Messina A, Cuccì G, Crescimanno C, Signorelli MS. Clinical anatomy of the precuneus and pathogenesis of the schizophrenia. Anat Sci Int 2023:10.1007/s12565-023-00730-w. [PMID: 37340095 DOI: 10.1007/s12565-023-00730-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 05/12/2023] [Indexed: 06/22/2023]
Abstract
Recent evidence has shown that the precuneus plays a role in the pathogenesis of schizophrenia. The precuneus is a structure of the parietal lobe's medial and posterior cortex, representing a central hub involved in multimodal integration processes. Although neglected for several years, the precuneus is highly complex and crucial for multimodal integration. It has extensive connections with different cerebral areas and is an interface between external stimuli and internal representations. In human evolution, the precuneus has increased in size and complexity, allowing the development of higher cognitive functions, such as visual-spatial ability, mental imagery, episodic memory, and other tasks involved in emotional processing and mentalization. This paper reviews the functions of the precuneus and discusses them concerning the psychopathological aspects of schizophrenia. The different neuronal circuits, such as the default mode network (DMN), in which the precuneus is involved and its alterations in the structure (grey matter) and the disconnection of pathways (white matter) are described.
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Affiliation(s)
- Antonino Messina
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Catania, Italy.
| | | | | | - Maria Salvina Signorelli
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Catania, Italy
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28
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Li M, Deng W, Li Y, Zhao L, Ma X, Yu H, Li X, Meng Y, Wang Q, Du X, Sham PC, Palaniyappan L, Li T. Ameliorative patterns of grey matter in patients with first-episode and treatment-naïve schizophrenia. Psychol Med 2023; 53:3500-3510. [PMID: 35164887 PMCID: PMC10277763 DOI: 10.1017/s0033291722000058] [Citation(s) in RCA: 1] [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: 06/28/2021] [Revised: 12/30/2021] [Accepted: 01/05/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Grey matter (GM) reduction is a consistent observation in established late stages of schizophrenia, but patients in the untreated early stages of illness display an increase as well as a decrease in GM distribution relative to healthy controls (HC). The relative excess of GM may indicate putative compensatory responses, though to date its relevance is unclear. METHODS 343 first-episode treatment-naïve patients with schizophrenia (FES) and 342 HC were recruited. Multivariate source-based morphometry was performed to identify covarying 'networks' of grey matter concentration (GMC). Neurocognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and symptom burden using the Positive and Negative Symptoms Scale (PANSS) were obtained. Bivariate linear relationships between GMC and cognition/symptoms were studied. RESULTS Compared to healthy subjects, FES had prominently lower GMC in two components; the first consists of the anterior insula, inferior frontal gyrus, anterior cingulate and the second component with the superior temporal gyrus, precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Higher GMC was seen in adjacent areas of the middle and superior temporal gyrus, middle frontal gyrus, inferior parietal cortex and putamen. Greater GMC of this component was associated with lower duration of untreated psychosis, less severe positive symptoms and better performance on cognitive tests. CONCLUSIONS In untreated stages of schizophrenia, both a distributed lower and higher GMC is observable. While the higher GMC is relatively modest, it occurs across frontoparietal, temporal and subcortical regions in association with reduced illness burden suggesting a compensatory role for higher GMC in the early stages of schizophrenia.
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Affiliation(s)
- Mingli Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Wei Deng
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yinfei Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Hua Yu
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaojing Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Yajing Meng
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiangdong Du
- Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Pak Chung Sham
- Centre for Genomic Sciences and State Key Laboratory in Cognitive and Brain Sciences, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Lena Palaniyappan
- Robarts Research Institute & The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada
- Lawson Health Research Institute, London, Ontario, Canada
| | - Tao Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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29
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Chen Y, Cao H, Liu S, Zhang B, Zhao G, Zhang Z, Li S, Li H, Yu X, Deng H. Brain Structure Measurements Predict Individualized Treatment Outcome of 12-Week Antipsychotic Monotherapies in First-episode Schizophrenia. Schizophr Bull 2023; 49:697-705. [PMID: 37010371 PMCID: PMC10154710 DOI: 10.1093/schbul/sbad043] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
BACKGROUND AND HYPOTHESIS Early prediction of treatment response to antipsychotics in schizophrenia remains a challenge in clinical practice. This study aimed to investigate if brain morphometries including gray matter volume and cortical thickness could serve as potential predictive biomarkers in first-episode schizophrenia. STUDY DESIGN Sixty-eight drug-naïve first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single antipsychotic throughout the first 12 weeks. Assessments for symptoms and social functioning were conducted by eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8) and the Personal and Social performance scale (PSP) multiple times during follow-ups. Treatment outcome was evaluated as subject-specific slope coefficients for PANSS-8 and PSP scores using linear mixed model. LASSO regression model were conducted to examine the performance of baseline gray matter volume and cortical thickness in prediction of individualized treatment outcome. STUDY RESULTS The study showed that individual brain morphometries at baseline, especially the orbitofrontal, temporal and parietal cortex, pallidum and amygdala, significantly predicted 12-week treatment outcome of PANSS-8 (r[predicted vs observed] = 0.49, P = .001) and PSP (r[predicted vs observed] = 0.40, P = .003) in first-episode schizophrenia. Moreover, the gray matter volume performed better than cortical thickness in the prediction the symptom changes (P = .034), while cortical thickness outperformed gray matter volume in the prediction of outcome of social functioning (P = .029). CONCLUSIONS These findings provide initial evidence that brain morphometry have potential to be used as prognostic predictors for antipsychotic response in patients, encouraging the future investigation of the translational value of these measures in precision psychiatry.
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Affiliation(s)
- Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Hope Recovery and Rehabilitation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Center for Psychiatric Neuroscience, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Shanming Liu
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Bo Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | | | - Zhuoqiu Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Shuiying Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Haiming Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hong Deng
- Hope Recovery and Rehabilitation Center, West China Hospital of Sichuan University, Chengdu, China
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
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30
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Howes OD, Onwordi EC. The synaptic hypothesis of schizophrenia version III: a master mechanism. Mol Psychiatry 2023; 28:1843-1856. [PMID: 37041418 PMCID: PMC10575788 DOI: 10.1038/s41380-023-02043-w] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 04/13/2023]
Abstract
The synaptic hypothesis of schizophrenia has been highly influential. However, new approaches mean there has been a step-change in the evidence available, and some tenets of earlier versions are not supported by recent findings. Here, we review normal synaptic development and evidence from structural and functional imaging and post-mortem studies that this is abnormal in people at risk and with schizophrenia. We then consider the mechanism that could underlie synaptic changes and update the hypothesis. Genome-wide association studies have identified a number of schizophrenia risk variants converging on pathways regulating synaptic elimination, formation and plasticity, including complement factors and microglial-mediated synaptic pruning. Induced pluripotent stem cell studies have demonstrated that patient-derived neurons show pre- and post-synaptic deficits, synaptic signalling alterations, and elevated, complement-dependent elimination of synaptic structures compared to control-derived lines. Preclinical data show that environmental risk factors linked to schizophrenia, such as stress and immune activation, can lead to synapse loss. Longitudinal MRI studies in patients, including in the prodrome, show divergent trajectories in grey matter volume and cortical thickness compared to controls, and PET imaging shows in vivo evidence for lower synaptic density in patients with schizophrenia. Based on this evidence, we propose version III of the synaptic hypothesis. This is a multi-hit model, whereby genetic and/or environmental risk factors render synapses vulnerable to excessive glia-mediated elimination triggered by stress during later neurodevelopment. We propose the loss of synapses disrupts pyramidal neuron function in the cortex to contribute to negative and cognitive symptoms and disinhibits projections to mesostriatal regions to contribute to dopamine overactivity and psychosis. It accounts for the typical onset of schizophrenia in adolescence/early adulthood, its major risk factors, and symptoms, and identifies potential synaptic, microglial and immune targets for treatment.
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Affiliation(s)
- Oliver D Howes
- Faculty of Medicine, Institute of Clinical Sciences (ICS), Imperial College London, London, W12 0NN, UK.
- Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, W12 0NN, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
| | - Ellis Chika Onwordi
- Faculty of Medicine, Institute of Clinical Sciences (ICS), Imperial College London, London, W12 0NN, UK.
- Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, W12 0NN, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
- Centre for Psychiatry and Mental Health, Wolfson Institute of Population Health, Queen Mary University of London, London, E1 2AB, UK.
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31
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Gupta N, Gupta M, Esang M. Lost in Translation: Challenges in the Diagnosis and Treatment of Early-Onset Schizophrenia. Cureus 2023; 15:e39488. [PMID: 37362509 PMCID: PMC10290525 DOI: 10.7759/cureus.39488] [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] [Accepted: 05/25/2023] [Indexed: 06/28/2023] Open
Abstract
Early-onset schizophrenia (EOS) is a heterogeneous condition that has a serious, insidious clinical course and poor long-term mental health outcomes. The clinical presentations are highly complex due to the overlapping symptomatology with other illnesses, which contributes to a delay in the diagnosis. The objective of the review is to study if an earlier age of onset (AAO) of EOS has poor clinical outcomes, the diagnostic challenges of EOS, and effective treatment strategies. The review provides a comprehensive literature search of 5966 articles and summarizes 126 selected for empirical evidence to methodically consider challenges in diagnosing and treating EOS for practicing clinicians. The risk factors of EOS are unique but have been shared with many other neuropsychiatric illnesses. Most of the risk factors, including genetics and obstetric complications, are nonmodifiable. The role of early diagnosis in reducing the duration of untreated psychosis (DUP) remains critical to reducing overall morbidity. Many specific issues contribute to the risk and clinical outcomes. Therefore, issues around diagnostic ambiguity, treatment resistance, nonadherence, and rehospitalizations further extend the DUP. There is hesitancy to initiate clozapine early, even though the empirical evidence strongly supports its use. There is a growing body of research that suggests the use of long-acting injectables to address nonadherence, and these measures are largely underutilized in acute settings. The clinical presentations of EOS are complex. In addition to the presence of specific risk factors, patients with an early onset of illness are also at a higher risk for treatment resistance. While there is a need to develop tools for early diagnosis, established evidence-based measures to address nonadherence, psychoeducation, and resistance must be incorporated into the treatment planning.
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Affiliation(s)
- Nihit Gupta
- Psychiatry, Dayton Children's Hospital, Dayton, USA
| | - Mayank Gupta
- Psychiatry and Behavioral Sciences, Southwood Psychiatric Hospital, Pittsburgh, USA
| | - Michael Esang
- Psychiatry and Behavioral Sciences, Clarion Psychiatric Center, Clarion, USA
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32
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Holton KM, Chan SY, Brockmeier AJ, Öngür D, Hall MH. Exploring the influence of functional architecture on cortical thickness networks in early psychosis - a longitudinal study. Neuroimage 2023; 274:120127. [PMID: 37086876 DOI: 10.1016/j.neuroimage.2023.120127] [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: 02/25/2023] [Revised: 04/17/2023] [Accepted: 04/19/2023] [Indexed: 04/24/2023] Open
Abstract
Cortical thickness reductions differ between individuals with psychotic disorders and comparison subjects even in early stages of illness. Whether these reductions covary as expected by functional network membership or simply by spatial proximity has not been fully elucidated. Through orthonormal projective non-negative matrix factorization, cortical thickness measurements in functionally-annotated regions from MRI scans of early-stage psychosis and matched healthy controls were reduced in dimensionality into features capturing positive covariance. Rather than matching the functional networks, the covarying regions in each feature displayed a more localized spatial organization. With Bayesian belief networks, the covarying regions per feature were arranged into a network topology to visualize the dependency structure and identify key driving regions. The features demonstrated diagnosis-specific differences in cortical thickness distributions per feature, identifying reduction-vulnerable spatial regions. Differences in key cortical thickness features between psychosis and control groups were delineated, as well as those between affective and non-affective psychosis. Clustering of the participants, stratified by diagnosis and clinical variables, characterized the clinical traits that define the cortical thickness patterns. Longitudinal follow-up revealed that in select clusters with low baseline cortical thickness, clinical traits improved over time. Our study represents a novel effort to characterize brain structure in relation to functional networks in healthy and clinical populations and to map patterns of cortical thickness alterations among ESP patients onto clinical variables for a better understanding of brain pathophysiology.
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Affiliation(s)
- Kristina M Holton
- Computational Neural Information Engineering Lab, University of Delaware, 139 The Green, Newark, DE 19716.
| | - Shi Yu Chan
- Psychosis Neurobiology Laboratory, McLean Hospital, 115 Mill St, Belmont, MA 02478; Division of Psychotic Disorders, McLean Hospital, 115 Mill St, Belmont, MA 02478
| | - Austin J Brockmeier
- Computational Neural Information Engineering Lab, University of Delaware, 139 The Green, Newark, DE 19716
| | - Dost Öngür
- Department of Psychiatry, Harvard Medical School, 25 Shattuck St, Boston, MA 02115; Division of Psychotic Disorders, McLean Hospital, 115 Mill St, Belmont, MA 02478
| | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, McLean Hospital, 115 Mill St, Belmont, MA 02478; Department of Psychiatry, Harvard Medical School, 25 Shattuck St, Boston, MA 02115; Division of Psychotic Disorders, McLean Hospital, 115 Mill St, Belmont, MA 02478.
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33
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Wang C, Tishler TA, Oughourlian T, Nuechterlein KH, de la Fuente-Sandoval C, Ellingson BM. Prospective, randomized, multicenter clinical trial evaluating longitudinal changes in brain function and microstructure in first-episode schizophrenia patients treated with long-acting injectable paliperidone palmitate versus oral antipsychotics. Schizophr Res 2023; 255:222-232. [PMID: 37019033 DOI: 10.1016/j.schres.2023.03.040] [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: 03/28/2022] [Revised: 02/23/2023] [Accepted: 03/18/2023] [Indexed: 04/07/2023]
Abstract
Widespread anatomical alterations and abnormal functional connectivity have shown strong association with symptom severity in first-episode schizophrenia (FES) patients. Second-generation antipsychotic treatment might slow disease progression and possibly modify the cerebral plasticity in FES patients. However, whether a long-acting injectable antipsychotic (paliperidone palmitate [PP]), available in monthly and every-3-months formulations, is more effective than oral antipsychotics (OAP) in improving cerebral organization has been unclear. Therefore, in the current longitudinal study, we evaluated the differences in functional and microstructural changes of 68 FES patients in a randomized clinical trial of PP vs OAP. When compared to OAP treatment, PP treatment was more effective in decreasing abnormally high fronto-temporal and thalamo-temporal connectivity, as well as increasing fronto-sensorimotor and thalamo-insular connectivity. Consistent with previous studies, multiple white matter pathways showed larger changes in fractional anisotropy (FA) and mean diffusivity (MD) in response to PP compared with OAP treatment. These findings suggest that PP treatment might reduce regional abnormalities and improve cerebral connectivity networks compared with OAP treatment, and identified changes that may serve as reliable imaging biomarkers associated with medication treatment efficacy.
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Affiliation(s)
- Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America.
| | - Todd A Tishler
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Talia Oughourlian
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America; Department of Psychology, University of California Los Angeles, Los Angeles, CA, 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
| | - Benjamin M Ellingson
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America; Neuroscience Interdisciplinary Graduate Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
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34
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Chen J, Wei Y, Xue K, Han S, Wang C, Wen B, Cheng J. The interaction between first-episode drug-naïve schizophrenia and age based on gray matter volume and its molecular analysis: a multimodal magnetic resonance imaging study. Psychopharmacology (Berl) 2023; 240:813-826. [PMID: 36719459 DOI: 10.1007/s00213-023-06323-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 01/19/2023] [Indexed: 02/01/2023]
Abstract
OBJECTIVES Schizophrenia is a neurodevelopmental disorder characterized by progressive and widespread gray matter (GM) atrophy. Studies have shown that normal brain development has an impact on schizophrenia-induced GM alterations. However, the neuropathology and underlying molecular mechanisms of interaction between age and schizophrenia are unclear. METHODS This study enrolled 66/84 first-episode drug-naïve patients with early-onset/adult-onset schizophrenia ((EOS)/(AOS)) and matched normal controls (NC) (46 adolescents/73 adults), undergoing T1-weighted high-resolution magnetic resonance imaging. Gray matter volume (GMV) in four groups was detected using 2-way analyses of variance with diagnosis and age as factors. Then, factors-related volume maps and neurotransmitter maps were spatially correlated using JuSpace to determine the relationship to molecular structure. RESULTS Compared to AOS, EOS and adult NC had larger GMV in right middle frontal gyrus. Compared to adolescent NC, EOS and adult NC had smaller GMV in right lingual gyrus, right fusiform gyrus, and right cerebellum_6. Disease-induced GMV reductions were mainly distributed in frontal, parietal, thalamus, visual, motor cortex, and medial temporal lobe structures. Age-induced GMV alterations were mainly distributed in visual and motor cortex. The changed GMV induced by schizophrenia, age, and their interaction was related to dopaminergic and serotonergic receptors. Age is also related to glutamate receptors, and schizophrenia is also associated with GABAaergic and noradrenergic receptors. CONCLUSIONS Our results revealed the multimodal neural mechanism of interaction between disease and age. We emphasized age-related GM abnormalities of ventral stream of visual perceptual pathways and high-level cognitive brain in EOS, which may be affected by imbalance of excitatory and inhibitory neurotransmitters.
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Affiliation(s)
- Jingli Chen
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, Two Seven District, The First Affiliated Hospital of Zhengzhou University, 1St Construction of E Rd, Zhengzhou, 450052, China.
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China.
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Emsley R, du Plessis S, Phahladira L, Luckhoff HK, Scheffler F, Kilian S, Smit R, Buckle C, Chiliza B, Asmal L. Antipsychotic treatment effects and structural MRI brain changes in schizophrenia. Psychol Med 2023; 53:2050-2059. [PMID: 35441587 PMCID: PMC10106303 DOI: 10.1017/s0033291721003809] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 07/21/2021] [Accepted: 09/01/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Progressive brain structural MRI changes are described in schizophrenia and have been ascribed to both illness progression and antipsychotic treatment. We investigated treatment effects, in terms of total cumulative antipsychotic dose, efficacy and tolerability, on brain structural changes over the first 24 months of treatment in schizophrenia. METHODS A prospective, 24-month, single-site cohort study in 99 minimally treated patients with first-episode schizophrenia, schizophreniform and schizoaffective disorder, and 98 matched healthy controls. We treated the patients according to a fixed protocol with flupenthixol decanoate, a long-acting injectable antipsychotic. We assessed psychopathology, cognition, extrapyramidal symptoms and BMI, and acquired MRI scans at months 0, 12 and 24. We selected global cortical thickness, white matter volume and basal ganglia volume as the regions of interest. RESULTS The only significant group × time interaction was for basal ganglia volumes. However, patients, but not controls, displayed cortical thickness reductions and increases in white matter and basal ganglia volumes. Cortical thickness reductions were unrelated to treatment. White matter volume increases were associated with lower cumulative antipsychotic dose, greater improvements in psychopathology and cognition, and more extrapyramidal symptoms. Basal ganglia volume increases were associated with greater improvements in psychopathology, greater increases in BMI and more extrapyramidal symptoms. CONCLUSIONS We provide evidence for plasticity in white matter and basal ganglia associated with antipsychotic treatment in schizophrenia, most likely linked to the dopamine blocking actions of these agents. Cortical changes may be more closely related to the neurodevelopmental, non-dopaminergic aspects of the illness.
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Affiliation(s)
- Robin Emsley
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Stefan du Plessis
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Lebogang Phahladira
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Hilmar K. Luckhoff
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Frederika Scheffler
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Sanja Kilian
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Retha Smit
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Chanelle Buckle
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Bonginkosi Chiliza
- Department of Psychiatry, Nelson R Mandela School of Medicine, University of Kwazulu-Natal, Durban, South Africa
| | - Laila Asmal
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
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36
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Nguyen T, Efimova OI, Tokarchuk AV, Morozova AY, Zorkina YA, Andreyuk DS, Kostyuk GP, Khaitovich PE. Dysregulation of Long Intergenic Non-Coding RNA Expression in the Schizophrenia Brain. CONSORTIUM PSYCHIATRICUM 2023; 4:5-16. [PMID: 38239571 PMCID: PMC10790728 DOI: 10.17816/cp219] [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: 10/09/2022] [Accepted: 11/07/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Transcriptomic studies of the brains of schizophrenia (SZ) patients have produced abundant but largely inconsistent findings about the disorders pathophysiology. These inconsistencies might stem not only from the heterogeneous nature of the disorder, but also from the unbalanced focus on particular cortical regions and protein-coding genes. Compared to protein-coding transcripts, long intergenic non-coding RNA (lincRNA) display substantially greater brain region and disease response specificity, positioning them as prospective indicators of SZ-associated alterations. Further, a growing understanding of the systemic character of the disorder calls for a more systematic screening involving multiple diverse brain regions. AIM We aimed to identify and interpret alterations of the lincRNA expression profiles in SZ by examining the transcriptomes of 35 brain regions. METHODS We measured the transcriptome of 35 brain regions dissected from eight adult brain specimens, four SZ patients, and four healthy controls, using high-throughput RNA sequencing. Analysis of these data yielded 861 annotated human lincRNAs passing the detection threshold. RESULTS Of the 861 detected lincRNA, 135 showed significant region-dependent expression alterations in SZ (two-way ANOVA, BH-adjusted p 0.05) and 37 additionally showed significant differential expression between HC and SZ individuals in at least one region (post hoc Tukey test, p 0.05). For these 37 differentially expressed lincRNAs (DELs), 88% of the differences occurred in a cluster of brain regions containing axon-rich brain regions and cerebellum. Functional annotation of the DEL targets further revealed stark enrichment in neurons and synaptic transmission terms and pathways. CONCLUSION Our study highlights the utility of a systematic brain transcriptome analysis relying on the expression profiles measured across multiple brain regions and singles out white matter regions as a prospective target for further SZ research.
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Affiliation(s)
- Tuan Nguyen
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology
| | - Olga I. Efimova
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology
| | - Artem V. Tokarchuk
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology
| | - Anna Yu. Morozova
- V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation
- Mental-health Clinic No. 1 named after N.A. Alexeev
| | - Yana A. Zorkina
- V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation
- Mental-health Clinic No. 1 named after N.A. Alexeev
| | | | | | - Philipp E. Khaitovich
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology
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37
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Vila È, Pinacho R, Prades R, Tarragó T, Castro E, Munarriz-Cuezva E, Meana JJ, Eugui-Anta A, Roldan M, Vera-Montecinos A, Ramos B. Inhibition of Prolyl Oligopeptidase Restores Prohibitin 2 Levels in Psychosis Models: Relationship to Cognitive Deficits in Schizophrenia. Int J Mol Sci 2023; 24:6016. [PMID: 37046989 PMCID: PMC10093989 DOI: 10.3390/ijms24076016] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/10/2023] [Accepted: 03/16/2023] [Indexed: 04/14/2023] Open
Abstract
Cognitive impairment represents one of the core features of schizophrenia. Prolyl Oligopeptidase (POP) inhibition is an emerging strategy for compensating cognitive deficits in hypoglutamatergic states such as schizophrenia, although little is known about how POP inhibitors exert their pharmacological activity. The mitochondrial and nuclear protein Prohibitin 2 (PHB2) could be dysregulated in schizophrenia. However, altered PHB2 levels in schizophrenia linked to N-methyl-D-aspartate receptor (NMDAR) activity and cognitive deficits are still unknown. To shed light on this, we measured the PHB2 levels by immunoblot in a postmortem dorsolateral prefrontal cortex (DLPFC) of schizophrenia subjects, in the frontal pole of mice treated with the NMDAR antagonists phencyclidine and dizocilpine, and in rat cortical astrocytes and neurons treated with dizocilpine. Mice and cells were treated in combination with the POP inhibitor IPR19. The PHB2 levels were also analyzed by immunocytochemistry in rat neurons. The PHB2 levels increased in DLPFC in cases of chronic schizophrenia and were associated with cognitive impairments. NMDAR antagonists increased PHB2 levels in the frontal pole of mice and in rat astrocytes and neurons. High levels of PHB2 were found in the nucleus and cytoplasm of neurons upon NMDAR inhibition. IPR19 restored PHB2 levels in the acute NMDAR inhibition. These results show that IPR19 restores the upregulation of PHB2 in an acute NMDAR hypoactivity stage suggesting that the modulation of PHB2 could compensate NMDAR-dependent cognitive impairments in schizophrenia.
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Affiliation(s)
- Èlia Vila
- Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Dr. Antoni Pujadas, 42, 08830 Sant Boi de Llobregat, Spain
| | - Raquel Pinacho
- Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Dr. Antoni Pujadas, 42, 08830 Sant Boi de Llobregat, Spain
| | - Roger Prades
- Iproteos S.L., Baldiri i Reixac, 10, 08028 Barcelona, Spain
| | - Teresa Tarragó
- Iproteos S.L., Baldiri i Reixac, 10, 08028 Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), Baldiri i Reixac, 10, 08028 Barcelona, Spain
| | - Elena Castro
- Departamento de Fisiología y Farmacología, Universidad de Cantabria, Avda. Cardenal Herrera Oria s/n, 39011 Santander, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM (Biomedical Network Research Center of Mental Health), Institute of Health Carlos III, 28029 Madrid, Spain
| | - Eva Munarriz-Cuezva
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM (Biomedical Network Research Center of Mental Health), Institute of Health Carlos III, 28029 Madrid, Spain
- Department of Pharmacology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain
- Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - J. Javier Meana
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM (Biomedical Network Research Center of Mental Health), Institute of Health Carlos III, 28029 Madrid, Spain
- Department of Pharmacology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain
- Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - Ania Eugui-Anta
- Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Dr. Antoni Pujadas, 42, 08830 Sant Boi de Llobregat, Spain
| | - Mònica Roldan
- Unitat de Microscòpia Confocal i Imatge Cel·lular, Servei de Medicina Genètica i Molecular, Institut Pediàtric de Malaties Rares (IPER), Hospital Sant Joan de Déu, 08950 Esplugues de Llobregat, Spain
| | - América Vera-Montecinos
- Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Dr. Antoni Pujadas, 42, 08830 Sant Boi de Llobregat, Spain
| | - Belén Ramos
- Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Dr. Antoni Pujadas, 42, 08830 Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM (Biomedical Network Research Center of Mental Health), Institute of Health Carlos III, 28029 Madrid, Spain
- Departament de Bioquímica i Biologia Molecular, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain
- Faculty of Medicine, University of Vic-Central University of Catalonia, 08500 Vic, Spain
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38
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Dimitriadis SI, Perry G, Lancaster TM, Tansey KE, Singh KD, Holmans P, Pocklington A, Davey Smith G, Zammit S, Hall J, O’Donovan MC, Owen MJ, Jones DK, Linden DE. Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk. Cereb Cortex 2023; 33:2997-3011. [PMID: 35830871 PMCID: PMC10016061 DOI: 10.1093/cercor/bhac256] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 02/02/2023] Open
Abstract
Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ.
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Affiliation(s)
- S I Dimitriadis
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Neuroinformatics Group, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - G Perry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - T M Lancaster
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Department of Psychology, Bath University, Claverton Down BA2 7AY, Bath, Wales, UK
| | - K E Tansey
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Queens Road BS8 1QU, Bristol, Wales, UK
| | - K D Singh
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - P Holmans
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - A Pocklington
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - G Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Queens Road BS8 1QU, Bristol, Wales, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, 1-5 Whiteladies Road BS8 1NU, Bristol, Wales, UK
| | - S Zammit
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, 1-5 Whiteladies Road BS8 1NU, Bristol, Wales, UK
| | - J Hall
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - M C O’Donovan
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - M J Owen
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - D K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
| | - D E Linden
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, 1-5 Whiteladies Road BS8 1NU, Bristol, Wales, UK
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40 UNS40 6229 ER, Maastricht, The Netherlands
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Constantinides C, Han LKM, Alloza C, Antonucci LA, Arango C, Ayesa-Arriola R, Banaj N, Bertolino A, Borgwardt S, Bruggemann J, Bustillo J, Bykhovski O, Calhoun V, Carr V, Catts S, Chung YC, Crespo-Facorro B, Díaz-Caneja CM, Donohoe G, Plessis SD, Edmond J, Ehrlich S, Emsley R, Eyler LT, Fuentes-Claramonte P, Georgiadis F, Green M, Guerrero-Pedraza A, Ha M, Hahn T, Henskens FA, Holleran L, Homan S, Homan P, Jahanshad N, Janssen J, Ji E, Kaiser S, Kaleda V, Kim M, Kim WS, Kirschner M, Kochunov P, Kwak YB, Kwon JS, Lebedeva I, Liu J, Mitchie P, Michielse S, Mothersill D, Mowry B, de la Foz VOG, Pantelis C, Pergola G, Piras F, Pomarol-Clotet E, Preda A, Quidé Y, Rasser PE, Rootes-Murdy K, Salvador R, Sangiuliano M, Sarró S, Schall U, Schmidt A, Scott RJ, Selvaggi P, Sim K, Skoch A, Spalletta G, Spaniel F, Thomopoulos SI, Tomecek D, Tomyshev AS, Tordesillas-Gutiérrez D, van Amelsvoort T, Vázquez-Bourgon J, Vecchio D, Voineskos A, Weickert CS, Weickert T, Thompson PM, Schmaal L, van Erp TGM, Turner J, Cole JH, Dima D, Walton E. Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium. Mol Psychiatry 2023; 28:1201-1209. [PMID: 36494461 PMCID: PMC10005935 DOI: 10.1038/s41380-022-01897-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 10/14/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022]
Abstract
Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.
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Affiliation(s)
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, Parkville, VIC, Australia
- Department of Psychiatry, Amsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Linda Antonella Antonucci
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians Universität-Munich, Munich, Germany
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Rosa Ayesa-Arriola
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Stefan Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
- Department of Psychiatry, Psychosomatics and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Juan Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, NM, USA
| | - Oleg Bykhovski
- Department of Psychiatry, Psychiatric University Hospital (UPK), University of Basel, Basel, Switzerland
- Division of Addiction Medicine, Centre Hospitalier des Quatre Villes, St. Cloud, France
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Vaughan Carr
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Psychiatry, Monash University, Clayton, VIC, Australia
| | - Stanley Catts
- School of Medicine, University of Queensland, Herston, QLD, Australia
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Hospital Universitario Virgen del Rocío, IBiS-CSIC, Universidad de Sevilla, Seville, Spain
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Stefan Du Plessis
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
- Stellenbosch University Genomics of Brain Disorders Research Unit, South African Medical Research Council, Cape Town, South Africa
| | - Jesse Edmond
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Germany
| | - Robin Emsley
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Paola Fuentes-Claramonte
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Melissa Green
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
- Hospital Benito Menni CASM, Sant Boi de Llobregat, Catalonia, Spain
| | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Frans A Henskens
- School of Medicine & Public Health, The University of Newcastle, Newcastle, NSW, Australia
- Priority Research Centre for Health Behaviour, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Stephanie Homan
- Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Experimental Psychopathology and Psychotherapy, University of Zurich, Zurich, Switzerland
| | - Philipp Homan
- Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Ellen Ji
- Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | | | - Minah Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | | | - Jingyu Liu
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
- Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Patricia Mitchie
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- School of Psychological Sciences, University of Newcastle, Callaghan, NSW, Australia
| | - Stijn Michielse
- Department of Neurosurgery, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - David Mothersill
- Centre for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- The Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, QLD, Australia
| | - Víctor Ortiz-García de la Foz
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia
- Florey Institute of Neuroscience & Mental Health, Parkville, VIC, Australia
| | - Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Edith Pomarol-Clotet
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Yann Quidé
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Paul E Rasser
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Newcastle, NSW, Australia
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Raymond Salvador
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Marina Sangiuliano
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Salvador Sarró
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Newcastle, NSW, Australia
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | | | - Diana Tordesillas-Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
- Advanced Computation and e-Science, Instituto de Física de Cantabria CSIC, Santander, Spain
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Javier Vázquez-Bourgon
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Aristotle Voineskos
- Campbell Family Mental Health Research Institute, CAMH, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Cynthia S Weickert
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Thomas Weickert
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
| | - Jessica Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - James H Cole
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Queen Square, Institute of Neurology, University College London, London, UK
| | - Danai Dima
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology, School of Arts and Social Sciences, City, University of London, London, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK.
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Yoon JH, Zhang Z, Mormino E, Davidzon G, Minzenberg MJ, Ballon J, Kalinowski A, Hardy K, Naganawa M, Carson RE, Khalighi M, Park JH, Levinson DF, Chin FT. Reductions in synaptic marker SV2A in early-course Schizophrenia. J Psychiatr Res 2023; 161:213-217. [PMID: 36934603 DOI: 10.1016/j.jpsychires.2023.02.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/14/2023] [Accepted: 02/22/2023] [Indexed: 03/21/2023]
Abstract
Excess synaptic pruning during neurodevelopment has emerged as one of the leading hypotheses on the causal mechanism for schizophrenia. It proposes that excess synaptic elimination occurs during development before the formal onset of illness. Accordingly, synaptic deficits may be observable at all stages of illnesses, including in the early phases. The availability of [11C]UCB-J, the first-in-human in vivo synaptic marker, represents an opportunity for testing this hypothesis with a relatively high level of precision. The first two published [11C]UCB-J schizophrenia studies have documented significant, widespread reductions in binding in chronic patients. The present study tested the hypothesis that reductions are present in early-course patients. 18 subjects completed [11C]UCB-J PET scans, (nine with schizophrenia, average duration of illness of 3.36 years, and nine demographically-matched healthy individuals). We compared binding levels, quantified as non-displaceable specific binding (BPND), in a set of a priori-specified brain regions of interest (ROIs). Eight ROIs (left and right hippocampus, right superior temporal and Heschl's gyrus, left and right putamen, and right caudal and rostral middle frontal gyrus) showed large reductions meeting Bonferroni corrected significant levels, p < 0.0036. Exploratory, atlas-wide analyses confirmed widespread reductions in schizophrenia. We also observed significant positive correlations between binding levels and cognitive performance and a negative correlation with the severity of delusions. These results largely replicate findings from chronic patients, indicating that extensive [11C]UCB-J binding deficits are reliable and reproducible. Moreover, these results add to the growing evidence that excess synaptic pruning is a major disease mechanism for schizophrenia.
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Affiliation(s)
- Jong H Yoon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine and VA Palo Alto Health Care System, Palo Alto, CA, USA.
| | - Zhener Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine and VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Elizabeth Mormino
- Department of Neurology, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Guido Davidzon
- Department of Radiology - Nuclear Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Michael J Minzenberg
- Department of Psychiatry, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Jacob Ballon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Agnieszka Kalinowski
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Kate Hardy
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Mika Naganawa
- Department of Radiology, Yale University, New Haven, CT, USA
| | | | - Mehdi Khalighi
- Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Jun Hyung Park
- Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Douglas F Levinson
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Frederick T Chin
- Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, USA
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Cohen LS, Vanderkruik R, Arakelian M, Church TR, Dunk MM, Freeman MP. Establishment of the MGH Postpartum Psychosis Project: MGHP3. PLoS One 2023; 18:e0281133. [PMID: 36758024 PMCID: PMC9910633 DOI: 10.1371/journal.pone.0281133] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 01/13/2023] [Indexed: 02/10/2023] Open
Abstract
OBJECTIVE Postpartum psychosis (PP) is a severe psychiatric disorder, with incomplete consensus on definition and diagnostic criteria. The Massachusetts General Hospital Postpartum Psychosis Project (MGHP3) was established to better ascertain the phenomenology of PP in a large cohort of diverse women spanning a wide geographical range (primarily in the US), including time of onset, symptom patterns, and associated comorbidities, psychiatric diagnoses pre- and post- the episode of PP, and also to identify genomic and clinical predictors of PP. This report describes the methods of MGHP3 and provides a status update. METHOD Data are collected from women who experienced PP within 6 months of childbirth and who provided this information within ten years of the study interview. Subject data are gathered during a one-time structured clinical interview conducted by phone, which includes administration of the Mini International Neuropsychiatric Interview for Psychotic Disorders Studies (Version 7.0.2), the MGHP3© Questionnaire, and other information including lifetime mental health history and use of psychiatric medications both prior to the episode of PP and during the subsequent time period prior to study interview. Subjects also provide a saliva sample to be processed for genomic analyses; a neuroimaging assessment is also conducted for a subset of participants. RESULTS As of July 1, 2022, 311 subjects from 44 states and 7 countries were enrolled in MGHP3. Recruitment sources include social media, online advertisements, physician referral, community outreach, and partnership with PP advocacy groups. CONCLUSIONS The rigorous phenotyping, genetic sampling, and neuroimaging studies in this sample of women with histories of PP will contribute to better understanding of this serious illness. Findings from MGHP3 can catalyze ongoing discussions in the field regarding proper nosologic classification of PP as well as relevant treatment implications.
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Affiliation(s)
- Lee S. Cohen
- Department of Psychiatry, Ammon-Pinizzotto Center for Women’s Mental Health, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail:
| | - Rachel Vanderkruik
- Department of Psychiatry, Ammon-Pinizzotto Center for Women’s Mental Health, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Miranda Arakelian
- Department of Psychiatry, Ammon-Pinizzotto Center for Women’s Mental Health, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Taylor R. Church
- Department of Psychiatry, Ammon-Pinizzotto Center for Women’s Mental Health, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Madison M. Dunk
- Department of Psychiatry, Ammon-Pinizzotto Center for Women’s Mental Health, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Marlene P. Freeman
- Department of Psychiatry, Ammon-Pinizzotto Center for Women’s Mental Health, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
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Goel T, Varaprasad SA, Tanveer M, Pilli R. Investigating White Matter Abnormalities Associated with Schizophrenia Using Deep Learning Model and Voxel-Based Morphometry. Brain Sci 2023; 13:brainsci13020267. [PMID: 36831810 PMCID: PMC9954172 DOI: 10.3390/brainsci13020267] [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: 12/30/2022] [Revised: 01/19/2023] [Accepted: 01/27/2023] [Indexed: 02/09/2023] Open
Abstract
Schizophrenia (SCZ) is a devastating mental condition with significant negative consequences for patients, making correct and prompt diagnosis crucial. The purpose of this study is to use structural magnetic resonance image (MRI) to better classify individuals with SCZ from control normals (CN) and to locate a region of the brain that represents abnormalities associated with SCZ. Deep learning (DL), which is based on the nervous system, could be a very useful tool for doctors to accurately predict, diagnose, and treat SCZ. Gray Matter (GM), Cerebrospinal Fluid (CSF), and White Matter (WM) brain regions are extracted from 99 MRI images obtained from the open-source OpenNeuro database to demonstrate SCZ's regional relationship. In this paper, we use a pretrained ResNet-50 deep network to extract features from MRI images and an ensemble deep random vector functional link (edRVFL) network to classify those features. By examining the results obtained, the edRVFL deep model provides the highest classification accuracy of 96.5% with WM and is identified as the best-performing algorithm compared to the traditional algorithms. Furthermore, we examined the GM, WM, and CSF tissue volumes in CN subjects and SCZ patients using voxel-based morphometry (VBM), and the results show 1363 significant voxels, 6.90 T-value, and 6.21 Z-value in the WM region of SCZ patients. In SCZ patients, WM is most closely linked to structural alterations, as evidenced by VBM analysis and the DL model.
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Affiliation(s)
- Tripti Goel
- Biomedical Imaging Lab, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, Assam, India
- Correspondence: (T.G.); (M.T.)
| | - Sirigineedi A. Varaprasad
- Biomedical Imaging Lab, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, Assam, India
| | - M. Tanveer
- Department of Mathematics, Indian Institute of Technology Indore, Simrol 453552, Madhya Pradesh, India
- Correspondence: (T.G.); (M.T.)
| | - Raveendra Pilli
- Biomedical Imaging Lab, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, Assam, India
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Nasrallah HA. Is preventing the second psychotic episode a disease-modifying strategy for schizophrenia? Schizophr Res 2023; 252:326-328. [PMID: 36708622 DOI: 10.1016/j.schres.2022.12.032] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/11/2022] [Accepted: 12/26/2022] [Indexed: 01/27/2023]
Affiliation(s)
- Henry A Nasrallah
- Department Psychiatry & Behavioral Neuroscience, University of Cincinnati College of Medicine, 260 Stetson St., Suite 3200, Cincinnati, OH 45219, United States.
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Ghazarian TC, Hall MG, Horton LA, Miller BL, Rubin RT. Behavioral variant frontotemporal dementia in a 23-year-old man. Neurocase 2023; 29:6-13. [PMID: 36998234 PMCID: PMC10544695 DOI: 10.1080/13554794.2023.2191858] [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: 10/21/2022] [Accepted: 03/10/2023] [Indexed: 04/01/2023]
Abstract
A 23-year-old man presented with behavioral disinhibition, stereotypies, motor apathy, flattened affect, and inappropriate laughter. CT demonstrated generalized cerebral atrophy. He was admitted with a diagnosis of unspecified psychosis and discharged on antipsychotic medication. He was readmitted 3 months later, was diagnosed with schizophrenia, and antipsychotic medication was continued. Owing to symptom progression and aggressive behavior, he was readmitted 2 months later. CT again demonstrated moderate central and cortical cerebral atrophy. MRI showed severe, stable atrophy with frontotemporal predominance, and he was diagnosed with probable behavioral variant frontotemporal dementia (bvFTD). Over the next year he rapidly deteriorated, with loss of cognitive abilities. Genetic testing revealed several variants, none of which are clearly disease-causing.
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Affiliation(s)
- Tania C. Ghazarian
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA
- Department of Psychiatry, Loma Linda University School of Medicine, Loma Linda, CA
| | - Matthew G.H. Hall
- Weill Institute for Neurosciences, Department of Neurology, and Memory and Aging Center, University of California San Francisco, San Francisco, CA
| | - Leslie A. Horton
- Psychiatry Residency Program, Community Memorial Health System, Ventura, CA
- Department of Psychiatry, Ventura County Medical Center, Ventura, CA
| | - Bruce L. Miller
- Weill Institute for Neurosciences, Department of Neurology, and Memory and Aging Center, University of California San Francisco, San Francisco, CA
| | - Robert T. Rubin
- Psychiatry Residency Program, Community Memorial Health System, Ventura, CA
- Department of Psychiatry, Ventura County Medical Center, Ventura, CA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
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Nath M, Bhardwaj SK, Srivastava LK, Wong TP. Altered excitatory and decreased inhibitory transmission in the prefrontal cortex of male mice with early developmental disruption to the ventral hippocampus. Cereb Cortex 2023; 33:865-880. [PMID: 35297476 PMCID: PMC9890473 DOI: 10.1093/cercor/bhac107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 02/20/2022] [Accepted: 02/22/2022] [Indexed: 02/04/2023] Open
Abstract
Ventral hippocampal (vHPC)-prefrontal cortical (PFC) pathway dysfunction is a core neuroimaging feature of schizophrenia. However, mechanisms underlying impaired connectivity within this pathway remain poorly understood. The vHPC has direct projections to the PFC that help shape its maturation. Here, we wanted to investigate the effects of early developmental vHPC perturbations on long-term functional PFC organization. Using whole-cell recordings to assess PFC cellular activity in transgenic male mouse lines, we show early developmental disconnection of vHPC inputs, by excitotoxic lesion or cell-specific ablations, impairs pyramidal cell firing output and produces a persistent increase in excitatory and decrease in inhibitory synaptic inputs onto pyramidal cells. We show this effect is specific to excitatory vHPC projection cell ablation. We further identify PV-interneurons as a source of deficit in inhibitory transmission. We find PV-interneurons are reduced in density, show a reduced ability to sustain high-frequency firing, and show deficits in excitatory inputs that emerge over time. We additionally show differences in vulnerabilities to early developmental vHPC disconnection, wherein PFC PV-interneurons but not pyramidal cells show deficits in NMDA receptor-mediated current. Our results highlight mechanisms by which the PFC adapts to early developmental vHPC perturbations, providing insights into schizophrenia circuit pathology.
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Affiliation(s)
- Moushumi Nath
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3A 0G4, Canada.,Basic Neuroscience Division, Douglas Hospital Research Centre, Montreal, QC H4H 1R3, Canada
| | - Sanjeev K Bhardwaj
- Basic Neuroscience Division, Douglas Hospital Research Centre, Montreal, QC H4H 1R3, Canada
| | - Lalit K Srivastava
- Basic Neuroscience Division, Douglas Hospital Research Centre, Montreal, QC H4H 1R3, Canada.,Department of Psychiatry, McGill University, Montreal, QC H3A 1A1, Canada
| | - Tak Pan Wong
- Basic Neuroscience Division, Douglas Hospital Research Centre, Montreal, QC H4H 1R3, Canada.,Department of Psychiatry, McGill University, Montreal, QC H3A 1A1, Canada
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Howes OD, Cummings C, Chapman GE, Shatalina E. Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology 2023; 48:151-167. [PMID: 36056106 PMCID: PMC9700830 DOI: 10.1038/s41386-022-01426-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/03/2022] [Accepted: 08/05/2022] [Indexed: 11/09/2022]
Abstract
Over the last five decades, a large body of evidence has accrued for structural and metabolic brain alterations in schizophrenia. Here we provide an overview of these findings, focusing on measures that have traditionally been thought to reflect synaptic spine density or synaptic activity and that are relevant for understanding if there is lower synaptic density in the disorder. We conducted literature searches to identify meta-analyses or other relevant studies in patients with chronic or first-episode schizophrenia, or in people at high genetic or clinical risk for psychosis. We identified 18 meta-analyses including over 50,000 subjects in total, covering: structural MRI measures of gyrification index, grey matter volume, grey matter density and cortical thickness, neurite orientation dispersion and density imaging, PET imaging of regional glucose metabolism and magnetic resonance spectroscopy measures of N-acetylaspartate. We also review preclinical evidence on the relationship between ex vivo synaptic measures and structural MRI imaging, and PET imaging of synaptic protein 2A (SV2A). These studies show that schizophrenia is associated with lower grey matter volumes and cortical thickness, accelerated grey matter loss over time, abnormal gyrification patterns, and lower regional SV2A levels and metabolic markers in comparison to controls (effect sizes from ~ -0.11 to -1.0). Key regions affected include frontal, anterior cingulate and temporal cortices and the hippocampi. We identify several limitations for the interpretation of these findings in terms of understanding synaptic alterations. Nevertheless, taken with post-mortem findings, they suggest that schizophrenia is associated with lower synaptic density in some brain regions. However, there are several gaps in evidence, in particular whether SV2A findings generalise to other cohorts.
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Affiliation(s)
- Oliver D Howes
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- South London and Maudsley NHS Foundation Trust, London, UK.
| | - Connor Cummings
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Clare Hall (College), University of Cambridge, Cambridge, UK
| | - George E Chapman
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Ekaterina Shatalina
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
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Planchuelo-Gómez Á, García-Azorín D, Guerrero ÁL, Rodríguez M, Aja-Fernández S, de Luis-García R. Structural brain changes in patients with persistent headache after COVID-19 resolution. J Neurol 2023; 270:13-31. [PMID: 36178541 PMCID: PMC9522538 DOI: 10.1007/s00415-022-11398-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 01/09/2023]
Abstract
Headache is among the most frequently reported symptoms after resolution of COVID-19. We assessed structural brain changes using T1- and diffusion-weighted MRI processed data from 167 subjects: 40 patients who recovered from COVID-19 but suffered from persistent headache without prior history of headache (COV), 41 healthy controls, 43 patients with episodic migraine and 43 patients with chronic migraine. To evaluate gray matter and white matter changes, morphometry parameters and diffusion tensor imaging-based measures were employed, respectively. COV patients showed significant lower cortical gray matter volume and cortical thickness than healthy subjects (p < 0.05, false discovery rate corrected) in the inferior frontal and the fusiform cortex. Lower fractional anisotropy and higher radial diffusivity (p < 0.05, family-wise error corrected) were observed in COV patients compared to controls, mainly in the corpus callosum and left hemisphere. COV patients showed higher cortical volume and thickness than migraine patients in the cingulate and frontal gyri, paracentral lobule and superior temporal sulcus, lower volume in subcortical regions and lower curvature in the precuneus and cuneus. Lower diffusion metric values in COV patients compared to migraine were identified prominently in the right hemisphere. COV patients present diverse changes in the white matter and gray matter structure. White matter changes seem to be associated with impairment of fiber bundles. Besides, the gray matter changes and other white matter modifications such as axonal integrity loss seemed subtle and less pronounced than those detected in migraine, showing that persistent headache after COVID-19 resolution could be an intermediate state between normality and migraine.
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Affiliation(s)
- Álvaro Planchuelo-Gómez
- Laboratorio de Procesado de Imagen (LPI), Universidad de Valladolid, 47011, Valladolid, Spain
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, CF24 4HQ, UK
| | - David García-Azorín
- Department of Neurology, Headache Unit, Hospital Clínico Universitario de Valladolid, Avenida Ramón y Cajal, 3, 47003, Valladolid, Spain.
- Department of Medicine, Universidad de Valladolid, 47005, Valladolid, Spain.
| | - Ángel L Guerrero
- Department of Neurology, Headache Unit, Hospital Clínico Universitario de Valladolid, Avenida Ramón y Cajal, 3, 47003, Valladolid, Spain
- Department of Medicine, Universidad de Valladolid, 47005, Valladolid, Spain
| | - Margarita Rodríguez
- Department of Radiology, Hospital Clínico Universitario de Valladolid, 47003, Valladolid, Spain
| | - Santiago Aja-Fernández
- Laboratorio de Procesado de Imagen (LPI), Universidad de Valladolid, 47011, Valladolid, Spain
| | - Rodrigo de Luis-García
- Laboratorio de Procesado de Imagen (LPI), Universidad de Valladolid, 47011, Valladolid, Spain
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48
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Relationships between cognitive performance, clinical insight and regional brain volumes in schizophrenia. SCHIZOPHRENIA 2022; 8:33. [PMID: 35853892 PMCID: PMC9261092 DOI: 10.1038/s41537-022-00243-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 02/23/2022] [Indexed: 11/22/2022]
Abstract
Impairments in cognitive performance are common in schizophrenia, and these contribute to poor awareness of symptoms and treatment (‘clinical insight’), which is an important predictor of functional outcome. Although relationships between cognitive impairment and reductions in regional brain volumes in patients are relatively well characterised, less is known about the brain structural correlates of clinical insight. To address this gap, we aimed to explore brain structural correlates of cognitive performance and clinical insight in the same sample. 108 patients with schizophrenia (SZH) and 94 age and gender-matched controls (CON) (from the Northwestern University Schizophrenia Data and Software Tool (NUSDAST) database) were included. SZH had smaller grey matter volume across most fronto-temporal regions and significantly poorer performance on all cognitive domains. Multiple regression showed that higher positive symptoms and poorer attention were significant predictors of insight in SZH; however, no significant correlations were seen between clinical insight and regional brain volumes. In contrast, symptomology did not contribute to cognitive performance, but robust positive relationships were found between regional grey matter volumes in fronto-temporal regions and cognitive performance (particularly executive function). Many of these appeared to be unique to SZH as they were not observed in CON. Findings suggest that while there exists a tight link between cognitive functioning and neuropathological processes affecting gross brain anatomy in SZH, this is not the case for clinical insight. Instead, clinical insight levels seem to be influenced by symptomology, attentional performance and other subject-specific variables.
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49
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Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence. Transl Psychiatry 2022; 12:481. [PMID: 36385133 PMCID: PMC9668814 DOI: 10.1038/s41398-022-02242-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 10/21/2022] [Accepted: 10/27/2022] [Indexed: 11/17/2022] Open
Abstract
Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics texture features describe the interrelationship between voxel intensities across multiple spatial scales capturing the hidden information of underlying disease dynamics in addition to volumetric changes. Structural MR images were acquired from 77 first-episode psychosis (FEP) patients, 58 clinical high-risk subjects with no later transition to psychosis (CHR_NT), 15 clinical high-risk subjects with later transition (CHR_T), and 44 healthy controls (HC). Radiomics texture features were extracted from non-segmented images, and two-classification schemas were performed for the identification of FEP vs. HC and FEP vs. CHR_NT. The group of CHR_T was used as external validation in both schemas. The classification of a subject's clinical status was predicted by importing separately (a) the difference of entropy feature map and (b) the contrast feature map, resulting in classification balanced accuracy above 72% in both analyses. The proposed framework enhances the classification decision for FEP, CHR_NT, and HC subjects, verifies diagnosis-relevant features and may potentially contribute to identification of structural biomarkers for psychosis, beyond and above volumetric brain changes.
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50
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Chang X, Zhao W, Kang J, Xiang S, Xie C, Corona-Hernández H, Palaniyappan L, Feng J. Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:95. [PMID: 36371445 PMCID: PMC9653408 DOI: 10.1038/s41537-022-00308-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.
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Affiliation(s)
- Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Shanghai Center for Mathematical Sciences, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Hugo Corona-Hernández
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.
- Lawson Health Research Institute, London, Ontario, Canada.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Shanghai Center for Mathematical Sciences, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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