1
|
Torres-Carmona E, Ueno F, Iwata Y, Nakajima S, Song J, Mar W, Abdolizadeh A, Agarwal SM, de Luca V, Remington G, Gerretsen P, Graff-Guerrero A. Elevated intrinsic cortical curvature in treatment-resistant schizophrenia: Evidence of structural deformation in functional connectivity areas and comparison with alternate indices of structure. Schizophr Res 2024; 269:103-113. [PMID: 38761434 DOI: 10.1016/j.schres.2024.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 04/14/2024] [Accepted: 05/02/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Research suggests structural and connectivity abnormalities in patients with treatment-resistant schizophrenia (TRS) compared to first-line responders and healthy-controls. However, measures of these abnormalities are often influenced by external factors like nicotine and antipsychotics, limiting their clinical utility. Intrinsic-cortical-curvature (ICC) presents a millimetre-scale measure of brain gyrification, highly sensitive to schizophrenia differences, and associated with TRS-like traits in early stages of the disorder. Despite this evidence, ICC in TRS remains unexplored. This study investigates ICC as a marker for treatment resistance in TRS, alongside structural indices for comparison. METHODS We assessed ICC in anterior cingulate, dorsolateral prefrontal, temporal, and parietal cortices of 38 first-line responders, 30 clozapine-resistant TRS, 37 clozapine-responsive TRS, and 52 healthy-controls. For comparative purposes, Fold and Curvature indices were also analyzed. RESULTS Adjusting for age, sex, nicotine-use, and chlorpromazine equivalence, principal findings indicate ICC elevations in the left hemisphere dorsolateral prefrontal (p < 0.001, η2partial = 0.142) and temporal cortices (LH p = 0.007, η2partial = 0.060; RH p = 0.011, η2partial = 0.076) of both TRS groups, and left anterior cingulate cortex of clozapine-resistant TRS (p = 0.026, η2partial = 0.065), compared to healthy-controls. Elevations that correlated with reduced cognition (p = 0.001) and negative symptomology (p < 0.034) in clozapine-resistant TRS. Fold and Curvature indices only detected group differences in the right parietal cortex, showing interactions with age, sex, and nicotine use. ICC showed interactions with age. CONCLUSION ICC elevations were found among patients with TRS, and correlated with symptom severity. ICCs relative independence from sex, nicotine-use, and antipsychotics, may support ICC's potential as a viable marker for TRS, though age interactions should be considered.
Collapse
Affiliation(s)
- Edgardo Torres-Carmona
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Fumihiko Ueno
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Neuropsychiatry, Keio University, Minato, Tokyo, Japan
| | - Shinichiro Nakajima
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Neuropsychiatry, Keio University, Minato, Tokyo, Japan
| | - Jianmeng Song
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Wanna Mar
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Ali Abdolizadeh
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Sri Mahavir Agarwal
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Vincenzo de Luca
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada.
| |
Collapse
|
2
|
Sone D, Young A, Shinagawa S, Tsugawa S, Iwata Y, Tarumi R, Ogyu K, Honda S, Ochi R, Matsushita K, Ueno F, Hondo N, Koreki A, Torres-Carmona E, Mar W, Chan N, Koizumi T, Kato H, Kusudo K, de Luca V, Gerretsen P, Remington G, Onaya M, Noda Y, Uchida H, Mimura M, Shigeta M, Graff-Guerrero A, Nakajima S. Disease Progression Patterns of Brain Morphology in Schizophrenia: More Progressed Stages in Treatment Resistance. Schizophr Bull 2024; 50:393-402. [PMID: 38007605 PMCID: PMC10919766 DOI: 10.1093/schbul/sbad164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2023]
Abstract
BACKGROUND AND HYPOTHESIS Given the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance. STUDY DESIGN In this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machine-learning analysis. STUDY RESULTS SuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P = .001). The GP-CX type presented earlier stages than the pure CX type (P = .009). CONCLUSIONS The brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker.
Collapse
Affiliation(s)
- Daichi Sone
- Department of Psychiatry, Jikei University School of Medicine, Tokyo, Japan
- Department of Clinical and Experimental Epilepsy, Queen Square Institute of Neurology, University College London, London, UK
| | - Alexandra Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Ryosuke Tarumi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kamiyu Ogyu
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Ryo Ochi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Karin Matsushita
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Fumihiko Ueno
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Nobuaki Hondo
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Akihiro Koreki
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | | | - Wanna Mar
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Nathan Chan
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Teruki Koizumi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Hideo Kato
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Keisuke Kusudo
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Vincenzo de Luca
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Philip Gerretsen
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Mitsumoto Onaya
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Masahiro Shigeta
- Department of Psychiatry, Jikei University School of Medicine, Tokyo, Japan
| | | | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| |
Collapse
|
3
|
Griffiths K, Mellado MR, Chung R, Lally J, McQueen G, Sendt KV, Gillespie A, Ibrahim M, Richter A, Shields A, Ponsford M, Jolles S, Hodsoll J, Pollak TA, Upthegrove R, Egerton A, MacCabe JH. Changes in immunoglobulin levels during clozapine treatment in schizophrenia. Brain Behav Immun 2024; 115:223-228. [PMID: 37832895 DOI: 10.1016/j.bbi.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 09/20/2023] [Accepted: 10/06/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND AND HYPOTHESIS Use of clozapine in treatment-resistant schizophrenia is often limited due to risk of adverse effects. Cross-sectional associations between clozapine treatment and low immunoglobulin levels have been reported, however prospective studies are required to establish temporal relationships. We tested the hypothesis that reductions in immunoglobulin levels would occur over the first 6 months following initiation of clozapine treatment. Relationships between immunoglobulin levels and symptom severity over the course of clozapine treatment were also explored. DESIGN This prospective observational study measured immunoglobulin (Ig) levels (A, M and G) in 56 patients with treatment-resistant schizophrenia at 6-, 12- and 24-weeks following initiation with clozapine. Clinical symptoms were also measured at 12 weeks using the positive and negative syndrome scale (PANSS). RESULTS IgA, IgG and IgM all decreased during clozapine treatment. For IgA and IgG the reduction was significant at 24 weeks (IgA: β = -32.66, 95% CI = -62.38, -2.93, p = 0.03; IgG: β = -63.96, 95% CI = -118.00, -9.31, p = 0.02). For IgM the reduction was significant at 12 and 24 weeks (12 weeks: β = -23.48, 95% CI = -39.56, -7.42, p = 0.004; 24 weeks: β = -33.12, 95 %CI = -50.30, -15.94, p = <0.001). Reductions in IgA and IgG during clozapine treatment were correlated with reductions in PANSS-total over 12 weeks (n = 32, IgA r = 0.59, p = 0.005; IgG r = 0.48, p = 0.03). CONCLUSIONS The observed reductions in immunoglobulin levels over six months of clozapine treatment add further evidence linking clozapine to secondary antibody deficiency. Associations between Ig reduction and symptom improvement may however indicate that immune mechanisms contribute to both desirable and undesirable effects of clozapine.
Collapse
Affiliation(s)
- Kira Griffiths
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - Maria Ruiz Mellado
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - Raymond Chung
- Department of Social Genetic and Developmental Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - John Lally
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK; Department of Psychiatry, School of Medicine and Medical Science, University College Dublin, Dublin, Ireland; Department of Psychiatry, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Grant McQueen
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - Kyra-Verena Sendt
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | | | - Muhammad Ibrahim
- Department of Immunobiology, Faculty of Life Sciences and Medicine, King's College London, UK
| | - Alex Richter
- Institute of Immunology and Immunotherapy, University of Birmingham, UK
| | - Adrian Shields
- Institute of Immunology and Immunotherapy, University of Birmingham, UK
| | - Mark Ponsford
- Immunodeficiency Centre for Wales, University Hospital of Wales, Cardiff, UK; Henry Wellcome Building, School of Medicine, Cardiff University, Cardiff, UK
| | - Stephen Jolles
- Immunodeficiency Centre for Wales, University Hospital of Wales, Cardiff, UK
| | - John Hodsoll
- Department of Biostatistics and Health Informatics, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - Thomas A Pollak
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, UK; Early Intervention Service, Birmingham Womens and Childrens NHS Foundation Trust, UK
| | - Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, UK.
| |
Collapse
|
4
|
Joo SW, Jo YT, Kim Y, Lee WH, Chung YC, Lee J. Structural variability of the cerebral cortex in schizophrenia and its association with clinical symptoms. Psychol Med 2024; 54:399-408. [PMID: 37485703 DOI: 10.1017/s0033291723001988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
BACKGROUND Substantial evidence indicates structural abnormalities in the cerebral cortex of patients with schizophrenia (SCZ), although their clinical implications remain unclear. Previous case-control studies have investigated group-level differences in structural abnormalities, although the study design cannot account for interindividual differences. Recent research has focused on the association between the heterogeneity of the cerebral cortex morphometric features and clinical heterogeneity. METHODS We used neuroimaging data from 420 healthy controls and 695 patients with SCZ from seven studies. Four cerebral cortex measures were obtained: surface area, gray matter volume, thickness, and local gyrification index. We calculated the coefficient of variation (CV) and person-based similarity index (PBSI) scores and performed group comparisons. Associations between the PBSI scores and cognitive functions were evaluated using Spearman's rho test and normative modeling. RESULTS Patients with SCZ had a greater CV of surface area and cortical thickness than those of healthy controls. All PBSI scores across cortical measures were lower in patients with SCZ than in HCs. In the patient group, the PBSI scores for gray matter volume and all cortical measures taken together positively correlated with the full-scale IQ scores. Patients with deviant PBSI scores for gray matter volume and all cortical measures taken together had lower full-scale IQ scores than those of other patients. CONCLUSIONS The cerebral cortex in patients with SCZ showed greater regional and global structural variability than that in healthy controls. Patients with deviant similarity of cortical structural profiles exhibited a lower general intelligence than those exhibited by the other patients.
Collapse
Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Yangsik Kim
- Department of Psychiatry, Inha University Hospital, Incheon, Republic of Korea
| | - Won Hee Lee
- Department of Software Convergence, Kyung Hee University, Yongin, Republic of Korea
| | - Young-Chul Chung
- Department of Psychiatry, Chonbuk National University Medical School, Jeonju, Republic of Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| |
Collapse
|
5
|
Tuovinen N, Hofer A. Resting-state functional MRI in treatment-resistant schizophrenia. FRONTIERS IN NEUROIMAGING 2023; 2:1127508. [PMID: 37554635 PMCID: PMC10406237 DOI: 10.3389/fnimg.2023.1127508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/17/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND Abnormalities in brain regions involved in the pathophysiology of schizophrenia (SCZ) may present insight into individual clinical symptoms. Specifically, functional connectivity irregularities may provide potential biomarkers for treatment response or treatment resistance, as such changes can occur before any structural changes are visible. We reviewed resting-state functional magnetic resonance imaging (rs-fMRI) findings from the last decade to provide an overview of the current knowledge on brain functional connectivity abnormalities and their associations to symptoms in treatment-resistant schizophrenia (TRS) and ultra-treatment-resistant schizophrenia (UTRS) and to look for support for the dysconnection hypothesis. METHODS PubMed database was searched for articles published in the last 10 years applying rs-fMRI in TRS patients, i.e., who had not responded to at least two adequate treatment trials with different antipsychotic drugs. RESULTS Eighteen articles were selected for this review involving 648 participants (TRS and control cohorts). The studies showed frontal hypoconnectivity before the initiation of treatment with CLZ or riluzole, an increase in frontal connectivity after riluzole treatment, fronto-temporal hypoconnectivity that may be specific for non-responders, widespread abnormal connectivity during mixed treatments, and ECT-induced effects on the limbic system. CONCLUSION Probably due to the heterogeneity in the patient cohorts concerning antipsychotic treatment and other clinical variables (e.g., treatment response, lifetime antipsychotic drug exposure, duration of illness, treatment adherence), widespread abnormalities in connectivity were noted. However, irregularities in frontal brain regions, especially in the prefrontal cortex, were noted which are consistent with previous SCZ literature and the dysconnectivity hypothesis. There were major limitations, as most studies did not differentiate between TRS and UTRS (i.e., CLZ-resistant schizophrenia) and investigated heterogeneous cohorts treated with mixed treatments (with or without CLZ). This is critical as in different subtypes of the disorder an interplay between dopaminergic and glutamatergic pathways involving frontal, striatal, and hippocampal brain regions in separate ways is likely. Better definitions of TRS and UTRS are necessary in future longitudinal studies to correctly differentiate brain regions underlying the pathophysiology of SCZ, which could serve as potential functional biomarkers for treatment resistance.
Collapse
Affiliation(s)
- Noora Tuovinen
- Division of Psychiatry I, Department of Psychiatry, Psychotherapy, Psychosomatics and Medical Psychology, Medical University of Innsbruck, Innsbruck, Austria
| | | |
Collapse
|