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Latent Clinical-Anatomical Dimensions of Schizophrenia

Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether dis...

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Autores principales: Kirschner, Matthias, Shafiei, Golia, Markello, Ross D, Makowski, Carolina, Talpalaru, Alexandra, Hodzic-Santor, Benazir, Devenyi, Gabriel A, Paquola, Casey, Bernhardt, Boris C, Lepage, Martin, Chakravarty, M Mallar, Dagher, Alain, Mišić, Bratislav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496914/
https://www.ncbi.nlm.nih.gov/pubmed/32744604
http://dx.doi.org/10.1093/schbul/sbaa097
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author Kirschner, Matthias
Shafiei, Golia
Markello, Ross D
Makowski, Carolina
Talpalaru, Alexandra
Hodzic-Santor, Benazir
Devenyi, Gabriel A
Paquola, Casey
Bernhardt, Boris C
Lepage, Martin
Chakravarty, M Mallar
Dagher, Alain
Mišić, Bratislav
author_facet Kirschner, Matthias
Shafiei, Golia
Markello, Ross D
Makowski, Carolina
Talpalaru, Alexandra
Hodzic-Santor, Benazir
Devenyi, Gabriel A
Paquola, Casey
Bernhardt, Boris C
Lepage, Martin
Chakravarty, M Mallar
Dagher, Alain
Mišić, Bratislav
author_sort Kirschner, Matthias
collection PubMed
description Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.
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spelling pubmed-84969142021-10-08 Latent Clinical-Anatomical Dimensions of Schizophrenia Kirschner, Matthias Shafiei, Golia Markello, Ross D Makowski, Carolina Talpalaru, Alexandra Hodzic-Santor, Benazir Devenyi, Gabriel A Paquola, Casey Bernhardt, Boris C Lepage, Martin Chakravarty, M Mallar Dagher, Alain Mišić, Bratislav Schizophr Bull Regular Articles Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia. Oxford University Press 2020-08-03 /pmc/articles/PMC8496914/ /pubmed/32744604 http://dx.doi.org/10.1093/schbul/sbaa097 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Regular Articles
Kirschner, Matthias
Shafiei, Golia
Markello, Ross D
Makowski, Carolina
Talpalaru, Alexandra
Hodzic-Santor, Benazir
Devenyi, Gabriel A
Paquola, Casey
Bernhardt, Boris C
Lepage, Martin
Chakravarty, M Mallar
Dagher, Alain
Mišić, Bratislav
Latent Clinical-Anatomical Dimensions of Schizophrenia
title Latent Clinical-Anatomical Dimensions of Schizophrenia
title_full Latent Clinical-Anatomical Dimensions of Schizophrenia
title_fullStr Latent Clinical-Anatomical Dimensions of Schizophrenia
title_full_unstemmed Latent Clinical-Anatomical Dimensions of Schizophrenia
title_short Latent Clinical-Anatomical Dimensions of Schizophrenia
title_sort latent clinical-anatomical dimensions of schizophrenia
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496914/
https://www.ncbi.nlm.nih.gov/pubmed/32744604
http://dx.doi.org/10.1093/schbul/sbaa097
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