Latent clinical-anatomical dimensions of schizophrenia Article Swipe
Matthias Kirschner
,
Golia Shafiei
,
Ross D. Markello
,
Carolina Makowski
,
Alexandra Talpalaru
,
Benazir Hodzic-Santor
,
Gabriel A. Devenyi
,
Casey Paquola
,
Boris C. Bernhardt
,
Martín Lepage
,
M. Mallar Chakravarty
,
Alain Dagher
,
Bratislav Mišić
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.03.25.20040592
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.03.25.20040592
Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is un-clear 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 MRI, and clinical data were derived from one discovery sample (133 patients, 113 controls) and one independent validation sample (108 patients, 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 three 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 two 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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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2020.03.25.20040592
- https://www.medrxiv.org/content/medrxiv/early/2020/03/27/2020.03.25.20040592.full.pdf
- OA Status
- green
- Cited By
- 8
- References
- 109
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3013910154
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3013910154Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2020.03.25.20040592Digital Object Identifier
- Title
-
Latent clinical-anatomical dimensions of schizophreniaWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-03-27Full publication date if available
- Authors
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Matthias Kirschner, Golia Shafiei, Ross D. Markello, Carolina Makowski, Alexandra Talpalaru, Benazir Hodzic-Santor, Gabriel A. Devenyi, Casey Paquola, Boris C. Bernhardt, Martín Lepage, M. Mallar Chakravarty, Alain Dagher, Bratislav MišićList of authors in order
- Landing page
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https://doi.org/10.1101/2020.03.25.20040592Publisher landing page
- PDF URL
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https://www.medrxiv.org/content/medrxiv/early/2020/03/27/2020.03.25.20040592.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.medrxiv.org/content/medrxiv/early/2020/03/27/2020.03.25.20040592.full.pdfDirect OA link when available
- Concepts
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Schizophrenia (object-oriented programming), Cognition, Neuropsychology, Default mode network, Neuroimaging, Psychology, Voxel-based morphometry, Neuroscience, Clinical psychology, Medicine, Psychiatry, Magnetic resonance imaging, Radiology, White matterTop concepts (fields/topics) attached by OpenAlex
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8Total citation count in OpenAlex
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2025: 1, 2024: 1, 2023: 1, 2022: 1, 2021: 2Per-year citation counts (last 5 years)
- References (count)
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109Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.latent | 132, 151 |
| abstract_inverted_index.model. | 127 |
| abstract_inverted_index.races. | 190 |
| abstract_inverted_index.sample | 82, 91 |
| abstract_inverted_index.single | 125 |
| abstract_inverted_index.status | 184 |
| abstract_inverted_index.taking | 207 |
| abstract_inverted_index.visual | 174 |
| abstract_inverted_index.within | 169 |
| abstract_inverted_index.Partial | 106 |
| abstract_inverted_index.account | 209 |
| abstract_inverted_index.avenues | 221 |
| abstract_inverted_index.between | 62, 143 |
| abstract_inverted_index.default | 171 |
| abstract_inverted_index.derived | 78 |
| abstract_inverted_index.domains | 65 |
| abstract_inverted_index.present | 217 |
| abstract_inverted_index.profile | 47 |
| abstract_inverted_index.regions | 31 |
| abstract_inverted_index.remains | 19 |
| abstract_inverted_index.results | 218 |
| abstract_inverted_index.sample, | 159 |
| abstract_inverted_index.squares | 108 |
| abstract_inverted_index.symptom | 64, 164 |
| abstract_inverted_index.whether | 26, 38 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.analysis | 109, 129 |
| abstract_inverted_index.approach | 57 |
| abstract_inverted_index.centered | 200 |
| abstract_inverted_index.clinical | 17, 46, 75, 144, 211 |
| abstract_inverted_index.discrete | 30, 35 |
| abstract_inverted_index.multiple | 63, 189 |
| abstract_inverted_index.negative | 163 |
| abstract_inverted_index.patterns | 61 |
| abstract_inverted_index.relation | 13 |
| abstract_inverted_index.reported | 8 |
| abstract_inverted_index.severity | 165 |
| abstract_inverted_index.un-clear | 25 |
| abstract_inverted_index.unknown. | 20 |
| abstract_inverted_index.accounted | 137 |
| abstract_inverted_index.biotyping | 226 |
| abstract_inverted_index.clinical, | 115 |
| abstract_inverted_index.cognitive | 161 |
| abstract_inverted_index.controls) | 86 |
| abstract_inverted_index.dimension | 153, 178, 197 |
| abstract_inverted_index.discovery | 81 |
| abstract_inverted_index.estimated | 101 |
| abstract_inverted_index.intrinsic | 203 |
| abstract_inverted_index.networks. | 175, 204 |
| abstract_inverted_index.patients, | 84, 93 |
| abstract_inverted_index.symptoms, | 36 |
| abstract_inverted_index.Structural | 72 |
| abstract_inverted_index.Widespread | 1 |
| abstract_inverted_index.anatomical | 27 |
| abstract_inverted_index.associated | 48, 180 |
| abstract_inverted_index.continuous | 195 |
| abstract_inverted_index.controls). | 95 |
| abstract_inverted_index.covariance | 60, 142 |
| abstract_inverted_index.dimensions | 134 |
| abstract_inverted_index.identified | 130, 193 |
| abstract_inverted_index.multi-omic | 223 |
| abstract_inverted_index.replicated | 155 |
| abstract_inverted_index.structural | 2 |
| abstract_inverted_index.validation | 90 |
| abstract_inverted_index.voxel-wise | 97 |
| abstract_inverted_index.Altogether, | 191 |
| abstract_inverted_index.data-driven | 56 |
| abstract_inverted_index.deformation | 103, 122 |
| abstract_inverted_index.demographic | 118 |
| abstract_inverted_index.distributed | 39, 67, 121 |
| abstract_inverted_index.independent | 89, 158 |
| abstract_inverted_index.individuals | 228 |
| abstract_inverted_index.investigate | 59 |
| abstract_inverted_index.particular, | 22 |
| abstract_inverted_index.represented | 187 |
| abstract_inverted_index.collectively | 136 |
| abstract_inverted_index.consistently | 7 |
| abstract_inverted_index.deformation. | 148 |
| abstract_inverted_index.encompassing | 160 |
| abstract_inverted_index.impairments, | 162 |
| abstract_inverted_index.morphometry. | 105 |
| abstract_inverted_index.multivariate | 55, 126 |
| abstract_inverted_index.abnormalities | 4, 28, 40, 69, 99, 168 |
| abstract_inverted_index.heterogeneous | 16 |
| abstract_inverted_index.socioeconomic | 183 |
| abstract_inverted_index.abnormalities, | 215 |
| abstract_inverted_index.manifestations | 18, 212 |
| abstract_inverted_index.schizophrenia, | 10, 199 |
| abstract_inverted_index.schizophrenia. | 50, 71, 230 |
| abstract_inverted_index.simultaneously | 206 |
| abstract_inverted_index.stratification | 224 |
| abstract_inverted_index.Disease-related | 96 |
| abstract_inverted_index.comprehensively | 113 |
| abstract_inverted_index.neuroanatomical | 214 |
| abstract_inverted_index.cognitive-negative | 177, 196 |
| abstract_inverted_index.neuropsychological | 116 |
| abstract_inverted_index.clinical-anatomical | 133, 152 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5054222172, https://openalex.org/A5054295358 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I1292859797, https://openalex.org/I5023651 |
| citation_normalized_percentile.value | 0.66935232 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |