Structural alterations in brainstem, basal ganglia and thalamus associated with parkinsonism in schizophrenia spectrum disorders.

The relative roles of brainstem, thalamus and striatum in parkinsonism in schizophrenia spectrum disorder (SSD) patients are largely unknown. To determine whether topographical alterations of the brainstem, thalamus and striatum contribute to parkinsonism in SSD patients, we conducted structural magnetic resonance imaging (MRI) of SSD patients with (SSD-P, n = 35) and without (SSD-nonP, n = 64) parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥ 4 and < 4, respectively, in comparison with healthy controls (n = 20). FreeSurfer v6.0 was used for segmentation of four brainstem regions (medulla oblongata, pons, superior cerebellar peduncle and midbrain), caudate nucleus, putamen and thalamus. Patients with parkinsonism had significantly smaller medulla oblongata (p = 0.01, false discovery rate (FDR)-corrected) and putamen (p = 0.02, FDR-corrected) volumes when compared to patients without parkinsonism. Across the entire patient sample (n = 99), significant negative correlations were identified between (a) medulla oblongata volumes and both SAS total (p = 0.034) and glabella-salivation (p = 0.007) scores, and (b) thalamic volumes and both SAS total (p = 0.033) and glabella-salivation (p = 0.007) scores. These results indicate that brainstem and thalamic structures as well as basal ganglia-based motor circuits play a crucial role in the pathogenesis of parkinsonism in SSD.

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

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.