Cerebral white matter structure is associated with DSM-5 schizophrenia symptom dimensions

Viher, Petra; Stegmayer, Katharina; Giezendanner, Stéphanie; Federspiel, Andrea; Bohlhalter, Stephan; Vanbellingen, Tim; Wiest, Roland; Strik, Werner; Walther, Sebastian

doi:10.1016/j.nicl.2016.06.013

Cited by 36 publications

(18 citation statements)

References 65 publications

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“…There are ongoing efforts to account for brain heterogeneity by means of delineating patient subtypes 8,55 , as well as characterizing patients by their differential degree of affectedness along one or multiple symptom-axes 11,56 . Here we report that SZ is associated with widespread and increased heterogeneity in cortical thickness, and cortical as well as hippocampal volume, beyond the known mean differences, compared controls.…”

Section: Resultsmentioning

confidence: 99%

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk

Alnæs

Kaufmann

Meer

et al. 2018

Preprint

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Telephone: +47 23 02 73 50, Fax: +47 23 02 73 33 32 33 34 3 Key Points 35Question: Is schizophrenia and its polygenic risk associated with brain structural 36 heterogeneity in addition to mean changes? 37Findings: In a sample of 1151 patients and 2010 controls, schizophrenia was associated with 38 increased heterogeneity in fronto-temporal thickness, cortical, ventricle, and hippocampal 39 volumes, besides robust reductions in mean estimates. In an independent sample of 12,490 40 controls, polygenic risk for schizophrenia was associated with thinner fronto-temporal 41 cortices and smaller CA2/3 of the left hippocampus, but not with heterogeneity. 42Meaning: Schizophrenia is associated with increased inter-individual differences in brain 43 structure, possibly reflecting clinical heterogeneity, gene-environment interactions, or 44 secondary disease factors. 45 46 4 Abstract 47 Importance: Between-subject variability in brain structure is determined by gene-48 environment interactions, possibly reflecting differential sensitivity to environmental and 49 genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner 50 cortices and smaller subcortical volumes in patients. However, such group-level comparisons 51 may mask considerable within-group heterogeneity, which has largely remained unnoticed in 52 the literature 53Objective: To compare brain structural variability between individuals with SZ and healthy 54 controls (HC) and to test if respective variability reflects the polygenic risk for SZ (PRS) in 55 HC. 56Design, Setting, and Participants: We compared MRI derived cortical thickness and 57 subcortical volumes between 2,010 healthy controls and 1,151 patients with SZ across 16 58cohorts. Secondly, we tested for associations between PRS and MRI features in 12,490 59 participants from UK Biobank. 60 Main Outcomes and Measures:We modeled mean and dispersion effects of SZ and PRS 61 using double generalized linear models. We performed vertex-wise analyses for thickness, 62 and region-of-interest analysis for cortical, subcortical and hippocampal subfield volumes. 63Follow-up analyses included within-sample analysis, controlling for intracranial volume and 64 population covariates, test of robustness of PRS threshold, and outlier removal. 65Results: Compared to controls, patients with SZ showed higher heterogeneity in cortical 66 thickness, cortical and ventricle volumes, and hippocampal subfields. Higher PRS was 67 associated with thinner frontal and temporal cortices, as well as smaller left CA2/3, but was 68 not significantly associated with dispersion. 69Conclusion and relevance: SZ is associated with substantial brain structural heterogeneity 70 beyond the mean differences. These findings possibly reflect higher differential sensitivity to 71 5 environmental and genetic perturbations in patients, supporting the heterogeneous nature of 72 SZ. Higher PRS for SZ was associated with thinner fronto-temporal cortices and smaller 73 subcortical volumes, but there were no significant associati...

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Section: Resultsmentioning

confidence: 99%

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk

Alnæs

Kaufmann

Meer

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Furthermore, anatomical connectivity values for a range of specific ROI-pairs that were reduced in individuals with schizophrenia were found to be unrelated to the severity of total TD (Skudlarski et al, 2010). Finally, Viher et al (2016) investigated several diffusivity measures within white matter but did not find voxel-clusters that were significantly related to positive TD.…”

Section: White Matter Tracts and Commissuresmentioning

confidence: 89%

A systematic review of the structural neuroimaging correlates of thought disorder

Sumner

Bell

Rossell

2018

Neuroscience & Biobehavioral Reviews

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“…The relationship of white matter alterations and clinical symptoms in SZ has been examined with inconsistent evidence. Viher et al reported that negative symptoms are related to white matter microstructure of the prefrontal and right temporal lobes, but no association of white matter microstructure and positive symptoms was found [ 86 ]. Conversely, Lener et al showed that lower FA in the genu is associated with greater positive symptom and none of the correlations with negative symptoms are significant [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect

et al. 2018

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Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.

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Cerebral white matter structure is associated with DSM-5 schizophrenia symptom dimensions

Cited by 36 publications

References 65 publications

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk

A systematic review of the structural neuroimaging correlates of thought disorder

Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect

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