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Yu JC, Hawco C, Bassman L, Oliver LD, Argyelan M, Gold JM, Tang SX, Foussias G, Buchanan RW, Malhotra AK, Ameis SH, Voineskos AN, Dickie EW. Multivariate Association between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00268-4. [PMID: 39260567 DOI: 10.1016/j.bpsc.2024.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 08/21/2024] [Accepted: 09/02/2024] [Indexed: 09/13/2024]
Abstract
BACKGROUND Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in "unimodal" (e.g., visual, auditory) and "multimodal" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs. METHODS We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group. RESULTS The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group. CONCLUSIONS These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.
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Affiliation(s)
- Ju-Chi Yu
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada.
| | - Colin Hawco
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; University of Toronto, Temerty Faculty of Medicine, Department of Psychiatry, Toronto, Canada
| | - Lucy Bassman
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - Lindsay D Oliver
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; University of Toronto, Temerty Faculty of Medicine, Department of Psychiatry, Toronto, Canada
| | | | - James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - George Foussias
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; University of Toronto, Temerty Faculty of Medicine, Department of Psychiatry, Toronto, Canada
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Stephanie H Ameis
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; University of Toronto, Temerty Faculty of Medicine, Department of Psychiatry, Toronto, Canada
| | - Aristotle N Voineskos
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; University of Toronto, Temerty Faculty of Medicine, Department of Psychiatry, Toronto, Canada
| | - Erin W Dickie
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; University of Toronto, Temerty Faculty of Medicine, Department of Psychiatry, Toronto, Canada.
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Chopra S, Levi PT, Holmes A, Orchard ER, Segal A, Francey SM, O'Donoghue B, Cropley VL, Nelson B, Graham J, Baldwin L, Yuen HP, Allott K, Alvarez-Jimenez M, Harrigan S, Pantelis C, Wood SJ, McGorry P, Fornito A. Brain-wide Anatomical Connectivity and Prediction of Longitudinal Outcomes in Antipsychotic-Naïve First Episode Psychosis. Biol Psychiatry 2024:S0006-3223(24)01483-5. [PMID: 39069164 DOI: 10.1016/j.biopsych.2024.07.016] [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: 02/17/2024] [Revised: 06/05/2024] [Accepted: 07/16/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND Disruptions of axonal connectivity are thought to be a core pathophysiological feature of psychotic illness, but whether they are present early in the illness, prior to antipsychotic exposure, and whether they can predict clinical outcome remains unknown. METHODS We acquired diffusion-weighted MRI to map structural connectivity between each pair of 319 parcellated brain regions in 61 antipsychotic-naive individuals with First Episode Psychosis (FEP; 15-25 years, 46% female) and a demographically matched sample of 27 control participants, along with clinical follow-up data in patients three months and 12 months after the scan. We used connectome-wide analyses to map disruptions of inter-regional pairwise connectivity and connectome-based predictive modelling to predict longitudinal change in symptoms and functioning. RESULTS Individuals with FEP showed disrupted connectivity in a brain-wide network linking all brain regions when compared with controls (pFWE=.03). Baseline structural connectivity significantly predicted change in functioning over 12 months (r=.44;pFWE=.041), such that lower connectivity within fronto-striato-thalamic systems predicted worse functional outcomes. CONCLUSIONS Brain-wide reductions of structural connectivity exist during the early stages of psychotic illness and cannot be attributed to antipsychotic medication. Moreover, baseline measures of structural connectivity can predict change in patient functional outcomes up to one year after engagement with treatment services.
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Affiliation(s)
- Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia; Monash Biomedical Imaging, Monash University, Clayton, Australia; Department of Psychology, Yale University, New Haven, USA.
| | - Priscila T Levi
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia; Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Alexander Holmes
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia; Monash Biomedical Imaging, Monash University, Clayton, Australia
| | | | - Ashlea Segal
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia; Monash Biomedical Imaging, Monash University, Clayton, Australia; Wu Tsai Institute, Department of Neuroscience, Yale University, New Haven, USA
| | - Shona M Francey
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Brian O'Donoghue
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; St Vincent's University Hospital, Elm Park, Dublin 4, Ireland; Department of Psychiatry, University College, Dublin, Ireland
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne
| | - Barnaby Nelson
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Jessica Graham
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Lara Baldwin
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Kelly Allott
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Susy Harrigan
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; Centre for Mental Health, Melbourne School of Global and Population Health, The University of Melbourne, Parkville, Australian
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne; Western Hospital Sunshine, St Albans, Victoria, Australia
| | - Stephen J Wood
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; School of Psychology, University of Birmingham, Edgbaston, UK
| | - Patrick McGorry
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia; Monash Biomedical Imaging, Monash University, Clayton, Australia
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Keane BP, Abrham YT, Hearne LJ, Bi H, Hu B. Increased whole-brain functional heterogeneity in psychosis during rest and task. Neuroimage Clin 2024; 43:103630. [PMID: 38875745 PMCID: PMC11225660 DOI: 10.1016/j.nicl.2024.103630] [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: 12/19/2023] [Revised: 05/09/2024] [Accepted: 06/06/2024] [Indexed: 06/16/2024]
Abstract
Past work has shown that people with schizophrenia exhibit more cross-subject heterogeneity in their functional connectivity patterns. However, it remains unclear whether specific brain networks are implicated, whether common confounds could explain the results, or whether task activations might also be more heterogeneous. Unambiguously establishing the existence and extent of functional heterogeneity constitutes a first step toward understanding why it emerges and what it means clinically. METHODS We first leveraged data from the HCP Early Psychosis project. Functional connectivity (FC) was extracted from 718 parcels via principal components regression. Networks were defined via a brain network partition (Ji et al., 2019). We also examined an independent data set with controls, later-stage schizophrenia patients, and ADHD patients during rest and during a working memory task. We quantified heterogeneity by averaging the Pearson correlation distance of each subject's FC or task activity pattern to that of every other subject of the same cohort. RESULTS Affective and non-affective early psychosis patients exhibited more cross-subject whole-brain heterogeneity than healthy controls (ps < 0.001, Hedges' g > 0.74). Increased heterogeneity could be found in up to seven networks. In-scanner motion, medication, nicotine, and comorbidities could not explain the results. Later-stage schizophrenia patients exhibited heterogeneous connectivity patterns and task activations compared to ADHD and control subjects. Interestingly, individual connection weights, parcel-wise task activations, and network averages thereof were not more variable in patients, suggesting that heterogeneity becomes most obvious over large-scale patterns. CONCLUSION Whole-brain cross-subject functional heterogeneity characterizes psychosis during rest and task. Developmental and pathophysiological consequences are discussed.
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Affiliation(s)
- Brian P Keane
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Neuroscience, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA; Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA.
| | - Yonatan T Abrham
- Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA
| | - Luke J Hearne
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Howard Bi
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA
| | - Boyang Hu
- Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA
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Chen YC, Tiego J, Segal A, Chopra S, Holmes A, Suo C, Pang JC, Fornito A, Aquino KM. A multiscale characterization of cortical shape asymmetries in early psychosis. Brain Commun 2024; 6:fcae015. [PMID: 38347944 PMCID: PMC10859637 DOI: 10.1093/braincomms/fcae015] [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: 10/12/2023] [Revised: 12/29/2023] [Accepted: 01/19/2024] [Indexed: 02/15/2024] Open
Abstract
Psychosis has often been linked to abnormal cortical asymmetry, but prior results have been inconsistent. Here, we applied a novel spectral shape analysis to characterize cortical shape asymmetries in patients with early psychosis across different spatial scales. We used the Human Connectome Project for Early Psychosis dataset (aged 16-35), comprising 56 healthy controls (37 males, 19 females) and 112 patients with early psychosis (68 males, 44 females). We quantified shape variations of each hemisphere over different spatial frequencies and applied a general linear model to compare differences between healthy controls and patients with early psychosis. We further used canonical correlation analysis to examine associations between shape asymmetries and clinical symptoms. Cortical shape asymmetries, spanning wavelengths from about 22 to 75 mm, were significantly different between healthy controls and patients with early psychosis (Cohen's d = 0.28-0.51), with patients showing greater asymmetry in cortical shape than controls. A single canonical mode linked the asymmetry measures to symptoms (canonical correlation analysis r = 0.45), such that higher cortical asymmetry was correlated with more severe excitement symptoms and less severe emotional distress. Significant group differences in the asymmetries of traditional morphological measures of cortical thickness, surface area, and gyrification, at either global or regional levels, were not identified. Cortical shape asymmetries are more sensitive than other morphological asymmetries in capturing abnormalities in patients with early psychosis. These abnormalities are expressed at coarse spatial scales and are correlated with specific symptom domains.
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Affiliation(s)
- Yu-Chi Chen
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Data Futures Institute, Monash University, Melbourne 3800, Australia
- Brain and Mind Centre, University of Sydney, Sydney 2050, Australia
- Brain Dynamic Centre, Westmead Institute for Medical Research, University of Sydney, Sydney 2145, Australia
| | - Jeggan Tiego
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
| | - Ashlea Segal
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - Sidhant Chopra
- Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - Alexander Holmes
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
| | - Chao Suo
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- BrainPark, School of Psychological Sciences, Monash University, Melbourne 3800, Australia
| | - James C Pang
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
| | - Alex Fornito
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
| | - Kevin M Aquino
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
- School of Physics, University of Sydney, Sydney 2050, Australia
- Center of Excellence for Integrative Brain Function, University of Sydney, Sydney 2050, Australia
- BrainKey Inc, San Francisco, CA 94103, USA
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