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Lower claustrum volumes are related to attentional deficits in patients with schizophrenia

Poster No:

420

Submission Type:

Abstract Submission

Authors:

David Schinz¹^,2^,3, Antonia Neubauer¹^,2^,4, Rebecca Hippen¹^,2, Julia Schulz¹^,2, Hongwei Li⁵, Melissa Thalhammer¹^,2, Benita Schmitz-Koep¹^,2, Aurore Menegaux¹^,2, Sevilay Ayyildiz¹^,2, Felix Brandl⁶, Josef Priller⁶, Michael Uder³, Claus Zimmer¹^,2, Dennis Hedderich¹^,2, Christian Sorg¹^,2^,6

Institutions:

¹Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM, Munich, Germany, ²TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM, Munich, Germany, ³Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen, Nürnberg, Germany, ⁴Center for Neuropathology and Prion Research, University Hospital Munich, LMU, Munich, Germany, ⁵Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, ⁶Department of Psychiatry, School of Medicine and Health, TUM, Munich, Germany

First Author:

David Schinz
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM|Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen
Munich, Germany|Munich, Germany|Nürnberg, Germany

Co-Author(s):

Antonia Neubauer
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM|Center for Neuropathology and Prion Research, University Hospital Munich, LMU
Munich, Germany|Munich, Germany|Munich, Germany

Rebecca Hippen
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Julia Schulz
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Hongwei Li
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
Boston, MA

Melissa Thalhammer
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Benita Schmitz-Koep
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Aurore Menegaux
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Sevilay Ayyildiz
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Felix Brandl
Department of Psychiatry, School of Medicine and Health, TUM
Munich, Germany

Josef Priller
Department of Psychiatry, School of Medicine and Health, TUM
Munich, Germany

Michael Uder
Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen
Nürnberg, Germany

Claus Zimmer
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Dennis Hedderich
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany

Christian Sorg
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM|TUM-NIC Neuroimaging Center, School of Medicine and Health, TUM|Department of Psychiatry, School of Medicine and Health, TUM
Munich, Germany|Munich, Germany|Munich, Germany

Introduction:

Schizophrenia is a psychiatric disorder characterized by multiple symptom clusters. Cognitive symptoms - such as impairments in attention, memory, executive functioning and language (Fioravanti et al., 2005) - usually appear years before the onset of psychotic symptoms (Kahn et al., 2015), predict later functioning (Kahn & Keefe, 2013), and severely impact quality of life (Paudel et al., 2020). The claustrum is a small brain grey matter structure that is suggested to modulate attention by suppressing representations of task-irrelevant sensory stimuli (Atlan et al., 2018). Previously, post-mortem analysis revealed smaller claustrum volumes in patients with paranoid schizophrenia (Bernstein et al., 2016). We hypothesized that structural MRI would confirm reduced claustrum volumes in schizophrenia in vivo, and that volumetric reductions would be associated with impaired attention in patients.

Methods:

This study included data from the Center for Biomedical Research Excellence (COBRE) dataset (Aine et al., 2017) and an in-house dataset (MUNICH). The COBRE dataset contained 72 patients with schizophrenia and 73 healthy controls while the MUNICH dataset contained 26 patients with schizophrenia and 24 healthy controls. In both datasets, T1-weighted images with a reconstructed resolution of 1mm isotropic voxels were acquired using MPRAGE sequences. Five subjects were excluded due to insufficient image quality. All images were skull-stripped with ROBEX, denoised using an adaptive non-local means filter, and normalized. After preprocessing, the claustrum was automatically segmented by a deep learning-based algorithm using a pre-trained model based on manual claustrum segmentations (Li et al., 2021). All segmentations underwent visual quality control, and four subjects were excluded for failed segmentation. Thus, the total sample included 90 patients and 96 healthy controls. Bilateral claustrum volumes were normalized by total intracranial volume. Attention and processing speed were assessed using the Symbol Coding Task (SCT) (Keefe, 2004) while processing speed alone was tested with the Trail Making Test Part A (TMT-A) (Tombaugh, 2004).

Results:

Compared to healthy control subjects, patients with schizophrenia showed smaller (-13.4%) claustrum volumes (Fig. 1B; p<0.001, Hedges' g=0.63). Furthermore, SCT scores were significantly positively correlated with claustrum volumes in patients (Fig. 1C; r=0.24, p=0.014). As there was no significant correlation between claustrum volumes and TMT-A scores (r=-0.09, p=0.41), cognitive impairment associated with reduced claustrum volumes in patients may be specific to the domain of attention, not processing speed. The findings were robust when controlling for sex, age, hemisphere effects, smoking, medication, global and adjacent grey matter changes, and MRI scanners used. Mediation analysis revealed a significant indirect effect of the grouping variable (schizophrenia or healthy control) on SCT scores via claustrum volumes (Fig. 1D; ab=-1.30±0.69; CI[-3.73; -1.04]), showing that reduced claustrum volumes partially mediate impairments of attention in patients with schizophrenia.

Conclusions:

The results suggest that claustrum volumes are significantly reduced in patients with schizophrenia and mediate attentional deficits in patients. Therefore, claustrum changes may play a role in the pathophysiology of schizophrenia, specifically in the manifestation of attention-related cognitive symptoms.

Disorders of the Nervous System:

Psychiatric (eg. Depression, Anxiety, Schizophrenia) ¹

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Subcortical Structures ²

Keywords:

Schizophrenia

Other - claustrum, attentional deficits, T1w-MRI

^1|2Indicates the priority used for review

Supporting Image: OHBM_abstract_claustrum_schizophrenia_figure.png

Abstract Information

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Please indicate below if your study was a "resting state" or "task-activation” study.

Other

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was this research conducted in the United States?

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Structural MRI

Neuropsychological testing

For human MRI, what field strength scanner do you use?

3.0T

Which processing packages did you use for your study?

Free Surfer

Provide references using APA citation style.

1. Aine, C. J. et al. (2017). Multimodal Neuroimaging in Schizophrenia: Description and Dissemination. Neuroinformatics, 15(4), 343–364.

2. Atlan, G. et al. (2018). The Claustrum Supports Resilience to Distraction. Current Biology, 28(17), 2752-2762.e7.

3. Bernstein, H.-G. et al. (2016). Bilaterally reduced claustral volumes in schizophrenia and major depressive disorder: A morphometric postmortem study. European Archives of Psychiatry and Clinical Neuroscience, 266(1), 25–33.

4. Fioravanti, M. et al. (2005). A Meta-Analysis of Cognitive Deficits in Adults with a Diagnosis of Schizophrenia. Neuropsychology Review, 15(2), 73–95.

5. Kahn, R. S. et al. (2013). Schizophrenia Is a Cognitive Illness: Time for a Change in Focus. JAMA Psychiatry, 70(10), 1107.

6. Kahn, R. S. et al. (2015). Schizophrenia. Nature Reviews Disease Primers, 1(1), 15067.

7. Keefe, R. (2004). The Brief Assessment of Cognition in Schizophrenia: Reliability, sensitivity, and comparison with a standard neurocognitive battery. Schizophrenia Research, 68(2–3), 283–297.

8. Li, H. et al. (2021). Automated claustrum segmentation in human brain MRI using deep learning. Human Brain Mapping, 42(18), 5862–5872.

9. Paudel, S. et al. (2020). Subjective experience of cognitive difficulties as an important attribute of quality of life among individuals with schizophrenia spectrum disorders. Schizophrenia Research, 215, 476–478.

10. Tombaugh, T. (2004). Trail Making Test A and B: Normative data stratified by age and education. Archives of Clinical Neuropsychology, 19(2), 203–214.

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