Accelerated Gray and White Matter Deterioration With Age in Schizophrenia

Cropley, Vanessa; Klauser, Paul; Lenroot, Rhoshel; Bruggemann, Jason; Sundram, Suresh; Bousman, Chad; Pereira, Avril; Biase, Maria A Di; Weickert, Thomas; Weickert, Cynthia Shannon; Pantelis, Christos; Zalesky, Andrew

doi:10.1176/appi.ajp.2016.16050610

Cited by 174 publications

(126 citation statements)

References 41 publications

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“…The results depicted in Fig. 3C,D demonstrate that areas with significantly high mean rankings across both lists are primarily located in the bilateral cingulate cortices, consistent with previous literature [19]. To ensure that the effect is not driven by the number of con-nections (i.e., biased towards high-degree nodes), we normalized the deformation values of neighbours' of a given node by its degree.…”

Section: Identifying the Disease Epicentersupporting

confidence: 86%

Spatial patterning of tissue volume loss in schizophrenia reflects brain network architecture

Shafiei

Markello

Talpalaru

et al. 2019

Preprint

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∀These authors contributed equally to this work. AbstractBackground. There is growing recognition that connectome architecture shapes cortical and subcortical grey matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown. Methods. Here we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Grey matter deformation was estimated in a sample of N = 133 individuals with chronic schizophrenia (48 female, 34.7 ± 12.9 years) and N = 113 controls (64 female, 23.5 ± 8.4 years). Deformation-based morphometry (DBM) was used to estimate cortical and subcortical grey matter deformation from T1-weighted MR images. Structural and functional connectivity patterns were derived from an independent sample of N = 70 healthy participants using diffusion spectrum imaging and resting-state functional MRI. Results. We find that regional deformation is correlated with the deformation of structurally-and functionally-connected neighbours. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex. Conclusions. Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25-35% of regional variance in deformation. Keywords. connectome | schizophrenia | intrinsic networks | disease epicenter | anterior cingulate | ventral attention network Running title. Network-driven tissue volume loss in schizophrenia

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Section: Identifying the Disease Epicentersupporting

confidence: 86%

Spatial patterning of tissue volume loss in schizophrenia reflects brain network architecture

Shafiei

Markello

Talpalaru

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Nodes were ranked based on their deformation values and their neighbors' deformation values in ascending order in two separate lists; we then identified nodes that were highly ranked in both lists ( Figure 3B) and assessed the significance of rankings using the spatial permutation testing (spin tests; 10,000 repetitions). The results depicted in Figure 3C, D demonstrate that areas with significantly high mean rankings across both lists are primarily located in the bilateral cingulate cortices, consistent with previous literature (47). To ensure that the effect was not driven by the number of connections (i.e., biased toward high-degree nodes), we normalized the deformation values of neighbors of a given node by its degree.…”

Section: Identifying the Disease Epicentersupporting

confidence: 85%

Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture

Shafiei

Markello

Makowski

et al. 2020

Biological Psychiatry

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BACKGROUND: There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown. METHODS: Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 6 12.9 years) and 113 control subjects (64 women, mean age 23.5 6 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging. RESULTS: We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex. CONCLUSIONS: Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.

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“…In the current study, we did not find any group differences when looking at average FA/MD over an atlas-based ROI. This might be related to the relatively small sample size, or to the fact that most patients had recent onset psychotic illness, whereas previous research suggests that white matter deterioration in schizophrenia increases with duration of 40 . However, we did find significant group differences on clusters of voxels using voxel-wise analyses with TBSS in all language tracts, as well as the corpus callosum, cingulum and the corona radiata.…”

Section: Discussionmentioning

confidence: 76%

Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts

et al. 2020

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Language deviations are a core symptom of schizophrenia. With the advances in computational linguistics, language can be easily assessed in exact and reproducible measures. This study investigated how language characteristics relate to schizophrenia diagnosis, symptom, severity and integrity of the white matter language tracts in patients with schizophrenia and healthy controls. Spontaneous speech was recorded and diffusion tensor imaging was performed in 26 schizophrenia patients and 22 controls. We were able to classify both groups with a sensitivity of 89% and a specificity of 82%, based on mean length of utterance and clauses per utterance. Language disturbances were associated with negative symptom severity. Computational language measures predicted language tract integrity in patients (adjusted R 2 = 0.467) and controls (adjusted R 2 = 0.483). Quantitative language analyses have both clinical and biological validity, offer a simple, helpful marker of both severity and underlying pathology, and provide a promising tool for schizophrenia research and clinical practice.

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Accelerated Gray and White Matter Deterioration With Age in Schizophrenia

Abstract: The findings suggest that schizophrenia is characterized by an initial, rapid rate of gray matter loss that slows in middle life, followed by the emergence of a deficit in white matter that progressively worsens with age at a constant rate.

Cited by 174 publications

References 41 publications

Spatial patterning of tissue volume loss in schizophrenia reflects brain network architecture

Spatial patterning of tissue volume loss in schizophrenia reflects brain network architecture

Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture

Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts

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