A Neural Signature of Parkinsonism in Patients With Schizophrenia Spectrum Disorders: A Multimodal MRI Study Using Parallel ICA

Author:

Wolf Robert C1,Rashidi Mahmoud12,Fritze Stefan2,Kubera Katharina M1,Northoff Georg3,Sambataro Fabio4,Calhoun Vince D5,Geiger Lena S6,Tost Heike6,Hirjak Dusan2

Affiliation:

1. Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany

2. Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

3. Mind, Brain Imaging and Neuroethics Research Unit, The Royal’s Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada

4. Department of Neuroscience (DNS), University of Padova, Padua, Italy

5. Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA

6. Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

Abstract

Abstract Motor abnormalities in schizophrenia spectrum disorders (SSD) have increasingly attracted scientific interest in the past years. However, the neural mechanisms underlying parkinsonism in SSD are unclear. The present multimodal magnetic resonance imaging (MRI) study examined SSD patients with and without parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥4 (SAS group, n = 22) or <4 (non-SAS group, n = 22). Parallel independent component analysis (p-ICA) was used to examine the covarying components among gray matter volume maps computed from structural MRI (sMRI) and fractional amplitude of low-frequency fluctuations (fALFF) maps computed from resting-state functional MRI (rs-fMRI) patient data. We found a significant correlation (P = .020, false discovery rate [FDR] corrected) between an sMRI component and an rs-fMRI component, which also significantly differed between the SAS and non-SAS group (P = .042, z = −2.04). The rs-fMRI component comprised the cortical sensorimotor network, and the sMRI component included predominantly a frontothalamic/cerebellar network. Across the patient sample, correlations adjusted for the Positive and Negative Syndrome Scale (PANSS) total scores showed a significant relationship between tremor score and loadings of the cortical sensorimotor network, as well as between glabella-salivation score, frontothalamic/cerebellar and cortical sensorimotor network loadings. These data provide novel insights into neural mechanisms of parkinsonism in SSD. Aberrant bottom-up modulation of cortical motor regions may account for these specific motor symptoms, at least in patients with SSD.

Funder

German Research Foundation

German Federal Ministry of Education and Research

Publisher

Oxford University Press (OUP)

Subject

Psychiatry and Mental health

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