Structural covariance networks of striatum subdivision in patients with Parkinson's disease

Microstructural alterations in white matter and related neurobiology based on the new clinical subtypes of Parkinson's disease

Background and objectives

The advent of new clinical subtyping systems for Parkinson's disease (PD) has led to the classification of patients into distinct groups: mild motor predominant (PD-MMP), intermediate (PD-IM), and diffuse malignant (PD-DM). Our goal was to evaluate the efficacy of diffusion tensor imaging (DTI) in the early diagnosis, assessment of clinical progression, and prediction of prognosis of these PD subtypes. Additionally, we attempted to understand the pathological mechanisms behind white matter damage using single-photon emission computed tomography (SPECT) and cerebrospinal fluid (CSF) analyses.

Methods

We classified 135 de novo PD patients based on new clinical criteria and followed them up after 1 year, along with 45 healthy controls (HCs). We utilized tract-based spatial statistics to assess the microstructural changes of white matter at baseline and employed multiple linear regression to examine the associations between DTI metrics and clinical data at baseline and after follow-up.

Results

Compared to HCs, patients with the PD-DM subtype demonstrated reduced fractional anisotropy (FA), increased axial diffusivity (AD), and elevated radial diffusivity (RD) at baseline. The FA and RD values correlated with the severity of motor symptoms, with RD also linked to cognitive performance. Changes in FA over time were found to be in sync with changes in motor scores and global composite outcome measures. Furthermore, baseline AD values and their rate of change were related to alterations in semantic verbal fluency. We also discovered the relationship between FA values and the levels of α-synuclein and β-amyloid. Reduced dopamine transporter uptake in the left putamen correlated with RD values in superficial white matter, motor symptoms, and autonomic dysfunction at baseline as well as cognitive impairments after 1 year.

Conclusions

The PD-DM subtype is characterized by severe clinical symptoms and a faster progression when compared to the other subtypes. DTI, a well-established technique, facilitates the early identification of white matter damage, elucidates the pathophysiological mechanisms of disease progression, and predicts cognitively related outcomes. The results of SPECT and CSF analyses can be used to explain the specific pattern of white matter damage in patients with the PD-DM subtype.

Multiscale brain age prediction reveals region-specific accelerated brain aging in Parkinson's disease

Brain biological age, which measures the aging process in the brain using neuroimaging data, has been used to assess advanced brain aging in neurodegenerative diseases, including Parkinson disease (PD). However, assuming that whole brain degeneration is uniform may not be sufficient for assessing the complex neurodegenerative processes in PD. In this study we constructed a multiscale brain age prediction models based on structural MRI of 1240 healthy participants. To assess the brain aging patterns using the brain age prediction model, 93 PD patients and 91 healthy controls matching for sex and age were included. We found increased global and regional brain age in PD patients. The advanced aging regions were predominantly noted in the frontal and temporal cortices, limbic system, basal ganglia, thalamus, and cerebellum. Furthermore, region-level rather than global brain age in PD patients was associated with disease severity. Our multiscale brain age prediction model could aid in the development of objective image-based biomarkers to detect advanced brain aging in neurodegenerative diseases.

Impaired topological properties of cortical morphological brain networks correlate with motor symptoms in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized by loss of selectively vulnerable neurons within the basal ganglia circuit and progressive atrophy in subcortical and cortical regions. However, the impact of neurodegenerative pathology on the topological organization of cortical morphological networks has not been explored. The aims of this study were to investigate altered network patterns of covariance in cortical thickness and complexity, and to evaluate how morphological network integrity in PD is related to motor impairment.

METHODS

Individual morphological networks were constructed for 50 PD patients and 46 healthy controls (HCs) by estimating interregional similarity distributions in surface-based indices. We performed graph theoretical analysis and network-based statistics to detect PD-related alterations and further examined the correlation of network metrics with clinical scores. Furthermore, support vector regression based on topological characteristics was applied to predict the severity of motor impairment in PD.

RESULTS

Compared with HCs, PD patients showed lower local efficiency (p = 0.004), normalized characteristic path length (p = 0.022), and clustering coefficient (p = 0.005) for gyrification index-based morphological brain networks. Nodal topological abnormalities were mainly in the frontal, parietal and temporal regions, and impaired morphological connectivity was involved in the sensorimotor and default mode networks. The support vector regression model using network-based features allowed prediction of motor symptom severity with a correlation coefficient of 0.606.

CONCLUSIONS

This study identified a disrupted topological organization of cortical morphological networks that could substantially advance our understanding of the network degeneration mechanism of PD and might offer indicators for monitoring disease progression.

Patterns of regional cerebral hypoperfusion in early Parkinson's disease: Clinical implications

INTRODUCTION

This study aimed to investigate whether regional cerebral perfusion patterns on early-phase 18F-FP-CIT PET scans, which is typically coupled to cerebral metabolism, predict the long-term prognosis of Parkinson's disease (PD).

METHODS

We enrolled 397 drug-naïve patients with early-stage PD who underwent dual-phase 18F-FP-CIT PET scans. After quantifying the early-phase 18F-FP-CIT PET images, cluster analysis was performed to delineate the PD subtypes according to the patterns of regional cerebral perfusion. We compared the risk of developing levodopa-induced dyskinesia (LID), wearing-off, freezing of gait (FOG), and dementia between the PD subtypes.

RESULTS

Cluster analysis classified patients into three subtypes: cluster 1 (relatively preserved cortical uptake; n = 175), cluster 2 (decreased uptake in the frontal, parietal, and temporal regions; n = 151), and cluster 3 (decreased uptake in more extensive regions, additionally involving the lateral occipital regions; n = 71). Cluster 1 was characterized by a younger age-of-onset, less severe motor deficits, less severely decreased 18F-FP-CIT binding in the caudate, and better cognitive performance. Cluster 3 was characterized by an older age-of-onset, more severe motor deficits, and poorer cognitive performance. Cluster 2 was intermediate between clusters 1 and 3. Cox regression analyses demonstrated that clusters 2 and 3 had a higher risk for dementia conversion than cluster 1, whereas the risk for developing LID, wearing-off, and FOG did not differ among the clusters.

CONCLUSION

The patterns of regional cerebral perfusion can provide information on long-term prognosis with regards to cognitive, but not motor aspects of patients with early-stage PD.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study

BACKGROUND

Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated.

OBJECTIVE

To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group.

METHODS

Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated.

RESULTS

Overall, people with PD had a regionally smaller posterior lobe (dmax  = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax  = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax  = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17).

CONCLUSIONS

We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Altered structural covariance of locus coeruleus in individuals with significant memory concern and patients with mild cognitive impairment

The locus coeruleus (LC) is the site where tau accumulation is preferentially observed pathologically in Alzheimer's disease (AD) patients, but the changes in gray matter co-alteration patterns between the LC and the whole brain in the predementia phase of AD remain unclear. In this study, we estimated and compared the gray matter volume of the LC and its structural covariance (SC) with the whole brain among 161 normal healthy controls (HCs), 99 individuals with significant memory concern (SMC) and 131 patients with mild cognitive impairment (MCI). We found that SC decreased in MCI groups, which mainly involved the salience network and default mode network. These results imply that seeding from LC, the gray matter network disruption and disconnection appears early in the MCI group. The altered SC network seeding from the LC can serve as an imaging biomarker for discriminating the patients in the potential predementia phase of AD from the normal subjects.

Shared alterations in hippocampal structural covariance in subjective cognitive decline and migraine

Introduction

Subjective cognitive decline (SCD) and migraine are often comorbid. Hippocampal structural abnormalities have been observed in individuals with both SCD and migraine. Given the known structural and functional heterogeneity along the long axis (anterior to posterior) of the hippocampus, we aimed to identify altered patterns of structural covariance within hippocampal subdivisions associated with SCD and migraine comorbidities.

Methods

A seed-based structural covariance network analysis was applied to examine large-scale anatomical network changes of the anterior and posterior hippocampus in individuals with SCD, migraine and healthy controls. Conjunction analyses were used to identify shared network-level alterations in the hippocampal subdivisions in individuals with both SCD and migraine.

Results

Altered structural covariance integrity of the anterior and posterior hippocampus was observed in the temporal, frontal, occipital, cingulate, precentral, and postcentral areas in individuals with SCD and migraine compared with healthy controls. Conjunction analysis revealed that, in both SCD and migraine, altered structural covariance integrity was shared between the anterior hippocampus and inferior temporal gyri and between the posterior hippocampus and precentral gyrus. Additionally, the structural covariance integrity of the posterior hippocampus-cerebellum axis was associated with the duration of SCD.

Conclusion

This study highlighted the specific role of hippocampal subdivisions and specific structural covariance alterations within these subdivisions in the pathophysiology of SCD and migraine. These network-level changes in structural covariance may serve as potential imaging signatures for individuals who have both SCD and migraine.

Association Between White Matter Networks and the Pattern of Striatal Dopamine Depletion in Patients With Parkinson Disease

OBJECTIVES

Individual variability in nigrostriatal dopaminergic denervation is an important factor underlying clinical heterogeneity in Parkinson disease (PD). This study aimed to explore whether the pattern of striatal dopamine depletion was associated with white matter (WM) networks in PD.

METHODS

A total of 240 newly diagnosed patients with PD who underwent 18F-FP-CIT PET scans and brain diffusion tensor imaging at initial assessment were enrolled in this study. We measured 18F-FP-CIT tracer uptake as an indirect marker for striatal dopamine depletion. Factor analysis-derived striatal dopamine loss patterns were estimated in each patient to calculate the composite scores of 4 striatal subregion factors (caudate, more-affected and less-affected sensorimotor striata, and anterior putamen) based on the availability of striatal dopamine transporter. The WM structural networks that were correlated with the composite scores of each striatal subregion factor were identified using a network-based statistical analysis.

RESULTS

A higher composite score of caudate (i.e., relatively preserved dopaminergic innervation in the caudate) was associated with a strong structural connectivity in a single subnetwork comprising the left caudate and left frontal gyri. Selective dopamine loss in the caudate was associated with strong connectivity in the structural subnetwork whose hub nodes were bilateral thalami and left insula, which were connected to the anterior cingulum. However, no subnetworks were correlated with the composite scores of other striatal subregion factors. The connectivity strength of the network with a positive correlation with the composite score of caudate affected the frontal/executive function either directly or indirectly through the mediation of dopamine depletion in the caudate.

CONCLUSIONS

Our findings indicate that different patterns of striatal dopamine depletion are closely associated with WM structural alterations, which may contribute to heterogeneous cognitive profiles in individuals with PD.

Predictive Biomarkers for Antipsychotic Treatment Response in Early Phase of Schizophrenia: Multi-Omic Measures Linking Subcortical Covariant Network, Transcriptomic Signatures, and Peripheral Epigenetics

Background

Volumetric alterations of subcortical structures as predictors of antipsychotic treatment response have been previously corroborated, but less is known about whether their morphological covariance relates to treatment outcome and is driven by gene expression and epigenetic modifications.

Methods

Subcortical volumetric covariance was analyzed by using baseline T1-weighted magnetic resonance imaging (MRI) in 38 healthy controls and 38 drug-naïve first-episode schizophrenia patients. Patients were treated with 8-week risperidone monotherapy and divided into responder and non-responder groups according to the Remission in Schizophrenia Working Group (RSWG). We utilized partial least squares (PLS) regression to examine the spatial associations between gene expression of subcortical structures from a publicly available transcriptomic dataset and between-group variances of structural covariance. The peripheral DNA methylation (DNAm) status of a gene of interest (GOI), overlapping between genes detected in the PLS and 108 schizophrenia candidate gene loci previously reported, was examined in parallel with MRI scanning.

Results

In the psychotic symptom dimension, non-responders had a higher baseline structural covariance in the putamen-hippocampus-pallidum-accumbens pathway compared with responders. For disorganized symptoms, significant differences in baseline structural covariant connections were found in the putamen-hippocampus-pallidum-thalamus circuit between the two subgroups. The imaging variances related to psychotic symptom response were spatially related to the expression of genes enriched in neurobiological processes and dopaminergic pathways. The DNAm of GOI demonstrated significant associations with patients' improvement of psychotic symptoms.

Conclusion

Baseline subcortical structural covariance and peripheral DNAm may relate to antipsychotic treatment response. Phenotypic variations in subcortical connectome related to psychotic symptom response may be transcriptomically and epigenetically underlaid. This study defines a roadmap for future studies investigating multimodal imaging epigenetic biomarkers for treatment response in schizophrenia.

Altered gray matter structural covariance networks at both acute and chronic stages of mild traumatic brain injury

Cognitive and emotional impairments observed in mild traumatic brain injury (mTBI) patients may reflect variances of brain connectivity within specific networks. Although previous studies found altered functional connectivity (FC) in mTBI patients, the alterations of brain structural properties remain unclear. In the present study, we analyzed structural covariance (SC) for the acute stages of mTBI (amTBI) patients, the chronic stages of mTBI (cmTBI) patients, and healthy controls. We first extracted the mean gray matter volume (GMV) of seed regions that are located in the default-mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), and the visual network (VN). Then we determined and compared the SC for each seed region among the amTBI, the cmTBI and the healthy controls. Compared with healthy controls, the amTBI patients showed lower SC for the ECN, and the cmTBI patients showed higher SC for the both DMN and SN but lower SC for the SMN. The results revealed disrupted ECN in the amTBI patients and disrupted DMN, SN and SMN in the cmTBI patients. These alterations suggest that early disruptions in SC between bilateral insula and the bilateral prefrontal cortices may appear in amTBI and persist into cmTBI, which might be potentially related to the cognitive and emotional impairments.

Identifying neuroanatomical signatures in insomnia and migraine comorbidity

STUDY OBJECTIVES

While insomnia and migraine are often comorbid, the shared and distinct neuroanatomical substrates underlying these disorders and the brain structures associated with the comorbidity are unknown. We aimed to identify patterns of neuroanatomical substrate alterations associated with migraine and insomnia comorbidity.

METHODS

High-resolution T1-weighted images were acquired from subjects with insomnia, migraine, and comorbid migraine and insomnia, respectively, and healthy controls (HC). Direct group comparisons with HC followed by conjunction analyses identified shared regional gray matter volume (GMV) alterations between the disorders. To further examine large-scale anatomical network changes, a seed-based structural covariance network (SCN) analysis was applied. Conjunction analyses also identified common SCN alterations in two disease groups, and we further evaluated these shared regional and global neuroanatomical signatures in the comorbid group.

RESULTS

Compared with controls, patients with migraine and insomnia showed GMV changes in the cerebellum and the lingual, precentral, and postcentral gyri (PCG). The bilateral PCG were common GMV alteration sites in both groups, with decreased structural covariance integrity observed in the cerebellum. In patients with comorbid migraine and insomnia, shared regional GMV and global SCN changes were consistently observed. The GMV of the right PCG also correlated with sleep quality in these patients.

CONCLUSION

These findings highlight the specific role of the PCG in the shared pathophysiology of insomnia and migraine from a regional and global brain network perspective. These multilevel neuroanatomical changes could be used as potential image markers to decipher the comorbidity of the two disorders.

Disrupted morphological grey matter networks in early-stage Parkinson's disease

While previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.

Differences in Brain Structural Covariance Network Characteristics in Children and Adults With Autism Spectrum Disorder

Systematically describing the structural topological configuration of human brain during development is an essential task. Autism spectrum disorder (ASD) represents a powerful challenge for psychiatry and neuroscience researchers. In this study, we investigated variations in the structural covariance network properties of 441 patients with ASD ranging in age from 7 to 45 years and in 426 age-matched healthy controls (HCs) using structural magnetic resonance neuroimaging from the ABIDE database. We applied a sliding window approach to study topological variation during development using comprehensive graph theoretical analysis. The main findings are as follows: (1) Cross-sectional trajectories of the network characteristics exhibited inverted U-shapes in both HCs and participants with ASD, with the latter exhibiting a 7-year delay in reaching the maximum value, (2) network resilience to targeted attacks peaked at 18' and 19' in the HCs and at 25' in the participants with ASD, and the weakest resilience occurred at age 7', (3) the HCs and participants with ASD exhibited normalized mean degree differences in the right amygdala, and (4) significant differences in the network characteristics were observed in the 18' age group at most of the densities analyzed. We used cross-sectional analysis to infer distinct neurodevelopmental trajectories in ASD in the brain structural connectome. Our findings are consistent with the notion that adolescence is a sensitive period of brain development with strong potential for brain plasticity, offering opportunities for environmental adaptation and social integration and for increasing vulnerability. ASD may be a product of susceptibility. LAY SUMMARY: We used cross-sectional analysis to preliminarily infer distinct neurodevelopmental trajectories in ASD in the brain structural connectome. The main findings are as follows: (1) Cross-sectional trajectories of the network characteristics exhibited inverted U-shapes in both HCs and participants with ASD, with the latter exhibiting a 7-year delay in reaching the maximum value, (2) Network resilience to targeted attacks peaked at 18' and 19' in the HCs and at 25' in the participants with ASD, and the weakest resilience occurred at age 7', (3) The HCs and participants with ASD exhibited normalized mean degree differences in the right amygdala, and (4) significant differences in the network characteristics were observed in the 18' age group at most of the densities analyzed.

Cortico-striato-thalamo-cerebellar networks of structural covariance underlying different epilepsy syndromes associated with generalized tonic-clonic seizures

Generalized tonic-clonic seizures (GTCS) are the severest and most remarkable clinical expressions of human epilepsy. Cortical, subcortical, and cerebellar structures, organized with different network patterns, underlying the pathophysiological substrates of genetic associated epilepsy with GTCS (GE-GTCS) and focal epilepsy associated with focal to bilateral tonic-clonic seizure (FE-FBTS). Structural covariance analysis can delineate the features of epilepsy network related with long-term effects from seizure. Morphometric MRI data of 111 patients with GE-GTCS, 111 patients with FE-FBTS and 111 healthy controls were studied. Cortico-striato-thalao-cerebellar networks of structural covariance within the gray matter were constructed using a Winner-take-all strategy with five cortical parcellations. Comparisons of structural covariance networks were conducted using permutation tests, and module effects of disease duration on networks were conducted using GLM model. Both patient groups showed increased connectivity of structural covariance relative to controls, mainly within the striatum and thalamus, and mostly correlated with the frontal, motor, and somatosensory cortices. Connectivity changes increased as a function of epilepsy durations. FE-FBTS showed more intensive and extensive gray matter changes with volumetric loss and connectivity increment than GE-GTCS. Our findings implicated cortico-striato-thalamo-cerebellar network changes at a large temporal scale in GTCS, with FE-FBTS showing more severe network disruption. The study contributed novel imaging evidence for understanding the different epilepsy syndromes associated with generalized seizures.

The cerebellum is associated with 2-year prognosis in patients with high-frequency migraine

Background

The increase of headache frequency is associated with higher headache related disability and lower quality of life in patients with migraine. However, the pathophysiology of migraine progression, persistence, or remission is elusive. The purpose of this study is to identify the brain signatures that are predictive of the long-term outcomes among patients with high-frequency migraine (HFM: 10–30 headache days/month).

Methods

We prospectively enrolled patients with HFM and healthy controls and collected their baseline clinical profiles and brain-MRI data at first visit. We longitudinally followed the patients and determined their outcomes at 2-year follow-up. Good outcome was defined as ≥50% reduction of baseline headache days and poor outcome was defined as reduction < 50% or frequency increase. Voxel-based morphometry was used to study gray matter volume (GMV), and structural covariance was used to investigate structural connectivity.

Results

Among 56 patients with HFM, 37 had good outcome and 19 poor outcome. Compared to the healthy controls (n = 37), patients with poor outcome had decreased GMV over the left posterior cingulate gyrus, and increased GMV over the bilateral cerebellum and the right precentral gyrus. Further, patients with poor outcome had greater GMV over the right and the left cerebella compared to patients with good outcome, and the GMVs of the cerebella were correlated to 2-year headache frequencies (right: r = 0.38, P = 0.005; left: r = 0.35, P = 0.009). Structural connectivity were increased between the cerebellum and the cuneus, the calcarine cortex, and the temporal lobe, respectively, in patients with poor outcome, and was decreased between the cerebellum and the prefrontal cortex in patients with poor outcome. The structural covariance integrities between the right cerebellum and the right cuneus were correlated to 2-year headache frequencies (r = 0.36, P = 0.008).

Conclusions

Structural volume and connectivity changes of the cerebellum may underlie headache persistence in patients with HFM.

Phenotype Network and Brain Structural Covariance Network of Anxiety

Network-based approach for psychological phenotypes assumes the dynamical interactions among the psychiatric symptoms, psychological characteristics, and neurocognitive performances arise, as they coexist, propagate, and inhibit other components within the network of mental phenomena. For differential types of dataset from which the phenotype network is to be estimated, a Gaussian graphical model, an Ising model, a directed acyclic graph, or an intraindividual covariance network could be used. Accordingly, these network-based approaches for anxiety-related psychological phenomena have been helpful in quantitative and pictorial understanding of qualitative dynamics among the diverse psychological phenomena as well as mind-environment interactions. Brain structural covariance refers to the correlative patterns of diverse brain morphological features among differential brain regions comprising the brain, as calculated per participant or across the participants. These covarying patterns of brain morphology partly overlap with longitudinal patterns of brain cortical maturation and also with propagating pattern of brain morphological changes such as cortical thinning and brain volume reduction in patients diagnosed with neurologic or psychiatric disorders along the trajectory of disease progression. Previous studies that used the brain structural covariance network could show neural correlates of specific anxiety disorder such as panic disorder and also elucidate the neural underpinning of anxiety symptom severity in diverse psychiatric and neurologic disorder patients.

The Combination of DAT-SPECT, Structural and Diffusion MRI Predicts Clinical Progression in Parkinson's Disease

There is an increasing interest in identifying non-invasive biomarkers of disease severity and prognosis in idiopathic Parkinson’s disease (PD). Dopamine-transporter SPECT (DAT-SPECT), diffusion tensor imaging (DTI), and structural magnetic resonance imaging (sMRI) provide unique information about the brain’s neurotransmitter and microstructural properties. In this study, we evaluate the relative and combined capability of these imaging modalities to predict symptom severity and clinical progression in de novo PD patients. To this end, we used MRI, SPECT, and clinical data of de novo drug-naïve PD patients (n = 205, mean age 61 ± 10) and age-, sex-matched healthy controls (n = 105, mean age 58 ± 12) acquired at baseline. Moreover, we employed clinical data acquired at 1 year follow-up for PD patients with or without L-Dopa treatment in order to predict the progression symptoms severity. Voxel-based group comparisons and covariance analyses were applied to characterize baseline disease-related alterations for DAT-SPECT, DTI, and sMRI. Cortical and subcortical alterations in de novo PD patients were found in all evaluated imaging modalities, in line with previously reported midbrain-striato-cortical network alterations. The combination of these imaging alterations was reliably linked to clinical severity and disease progression at 1 year follow-up in this patient population, providing evidence for the potential use of these modalities as imaging biomarkers for disease severity and prognosis that can be integrated into clinical trials.

Decreased cerebral blood flow and improved cognitive function in patients with end-stage renal disease after peritoneal dialysis: An arterial spin-labelling study

OBJECTIVES

The aim of this study was to evaluate the relationship between cognitive impairment and brain perfusion using arterial spin labelling (ASL) in end-stage renal disease (ESRD) patients undergoing PD.

METHODS

ESRD patients undergoing PD were recruited. Laboratory screening, neuropsychological tests and ASL magnetic resonance imaging (MRI) were conducted prior to and after 6 months of PD. Age- and sex-matched normal subjects without ESRD served as the control group. Comparisons of regional CBF between ESRD patients before or after undergoing PD and normal controls were performed. Correlations between biochemical, neuropsychological and CBF data were also conducted to evaluate the relationships.

RESULTS

ESRD patients showed poor performance in many of the neuropsychological tests; PD improved cognition in some domains. Pre-PD patients had higher mean CBF than post-PD patients and normal controls, but no significant difference was found between the normal controls and post-PD patients. Negative correlations were observed pre-PD (regional CBF in left hippocampus vs. perseverative responses, r = -0.662, p = 0.014), post-PD (mean CBF vs. haemoglobin level, r = -0.766, p = 0.002), and before and after PD (change in CBF in the left putamen vs. change in haematocrit percentage, r = -0.808, p = 0.001).

CONCLUSION

Before PD, ESRD patients had increased cerebral perfusion that was related to poorer executive function, especially in the left hippocampus. Post-PD patients performed better in some cognitive test domains than pre-PD patients. The degree of anaemia, i.e., haemoglobin level or haematocrit percentage, might predict cognitive impairment in PD patients.

KEY POINTS

• In this study, ESRD patients before PD had cerebral hyperperfusion that was related to poorer executive function. • Post-PD patients performed better in some cognitive test domains than pre-PD patients did. • The degree of anaemia might predict cognitive impairment in PD patients.

Anxiety in Parkinson's disease is associated with reduced structural covariance of the striatum

BACKGROUND

Anxiety is highly prevalent in Parkinson's disease (PD) and has great negative impact on quality of life. Functional and structural neuroimaging studies have contributed to our understanding of the symptomatology of PD but still little is known about the pathophysiology of PD-related anxiety.

METHODS

We used seed-based structural covariance analysis to study the anatomical network correlates of anxiety in PD. Structural covariance analysis is based on the statistical correlation between regional brain volumes measured on T1-weighted magnetic resonance images. We investigated the association between anxiety symptoms, as measured by the Beck Anxiety Inventory (BAI), and seed-to-whole-brain structural covariance networks in 115 patients with idiopathic PD using five bilateral seeds: basolateral amygdala, centromedial-superficial amygdala, dorsal caudate nucleus, dorsal-caudal putamen, and nucleus accumbens.

RESULTS

Severity of anxiety correlated negatively with structural covariance between the left striatal sub-regions and the contralateral caudate nucleus. Moreover, severity of anxiety was associated with reduced structural covariance between the right dorsal caudate nucleus and ipsilateral ventrolateral prefrontal cortex and between the left nucleus accumbens and ipsilateral dorsolateral prefrontal cortex. Structural covariance of the amygdalar seeds did not correlate with anxiety.

CONCLUSIONS

We interpret these findings as a reduced interhemispheric cooperation between the left and right striatum and reduced prefrontal-striatal connectivity, possibly related to impaired 'top-down' regulation of emotions. These findings shed more light on the pathophysiology of PD-related anxiety LIMITATIONS: This study did not include PD patients with an anxiety disorder.

Altered amygdala-related structural covariance and resting-state functional connectivity in end-stage renal disease patients

Depression and cognitive control deficits were frequently reported in concurrent end-stage renal disease (ESRD) patients. Neuroimaging studies indicated depression could be a risk factor for cognitive control deficits, and amygdala-related circuitry may play a critical role in this abnormal interaction. To investigate the potential relationship between depressive symptoms and cognitive control reduction in ESRD patients, T1-weighted and resting fMRI images were obtained in 29 ESRD patients and 29 healthy controls. Voxel-based morphometry (VBM), structural covariance (SC) analysis based on grey matter volume (GMV), and functional connectivity (FC) analysis were adopted. All subjects performed the Beck Depression Inventory (BDI) assessment and Stroop test. The patients also underwent blood biochemistry tests (urea, creatinine, phosphate, Ca2⁺, hematocrit, cystatin, hemoglobin). Compared with controls, GMV reductions were found mainly in the anterior cingulate cortex (ACC) and bilateral amygdala, and decreased SC was found between the amygdala and ACC in ESRD patients. This indicated that structural changes in the amygdala may be related to the GMV alterations in the ACC. Additionally, decreased FC between the amygdala and ACC was revealed in ESRD patients. Negative correlation was found between the FC of the amygdala-ACC and reaction delay during the Stroop test, but this correlation disappeared after controlling BDI. Stepwise regression analysis showed that the low level of hemoglobin was contributed to the reduced FC of the amygdala-ACC in ESRD patients. Our results demonstrated the abnormal interaction between depressive mood and cognitive control deficits in ESRD patients.

Cerebellar atrophy in different subtypes of Parkinson's disease

BACKGROUND

To investigate, using Magnetic Resonance Imaging (MRI) and voxel-based morphometry (VBM), morphometric changes of cerebellum in Parkinson's disease with different motor and affective subtypes.

METHODS

Fifty-four patients with idiopathic Parkinson's disease (PD) were classified into tremor-predominant-PD (PDT) (n = 37) and akinetic/rigidity-predominant-PD (PDAR) (n = 17). Moreover, PD groups were divided into four affective subtypes, including depressive but not anxious PD (dPD, n = 5), anxious but not depressive PD (aPD, n = 8), comorbid depressive and anxious PD (coPD, n = 8), and PD patients without depressive or anxious symptoms (nPD, n = 33). They were additionally compared at a group level with thirty-nine normal controls (NCs). An analysis of covariance followed by post hoc tests was performed to examine the alterations of cerebellar grey matter volume (GMV) in different groups of PD.

RESULTS

Compared with NCs, PD showed grey matter (GM) atrophy in the right Crus II, pyramis, culmen, the right lobules IV, and V, and the left lobule VI. PDT, PDAR and NCs did not differ in the volume of the cerebellum. Relative to nPD group, dPD group exhibited GMV reduction in the left Crus I, while aPD group showed GMV reduction in the tonsil and the right lobule VIII. The GM atrophy was also found in the coPD group compared to NCs, including the tonsil, the left lobule VIII, the right lobule VI, the left Crus I, and vermis IV, and V. There was a significant negative correlation between the Hamilton Rating Scale for Depression (HAMD) score and the right lobule IX volume, and a significant negative correlation between the Hamilton Rating Scale for Anxiety (HAMA) score and the right lobule VIII volume.

CONCLUSIONS

These findings suggest that cerebellar changes are involved in PD. It also supports a possible role of the cerebellum in the depressive and anxious symptoms in PD.

Method for retrospective estimation of natural head movement during structural MRI

BACKGROUND

Head motion during brain structural MRI scans biases brain morphometry measurements but quantitative retrospective methods estimating head motion from structural MRI have not been evaluated.

PURPOSE

To verify the hypothesis that two metrics retrospectively computed from MR images: 1) average edge strength (AES, reduced with image blurring) and 2) entropy (ENT, increased with blurring and ringing artifacts) could be sensitive to in-scanner head motion during acquisition of T₁ -weighted MR images.

STUDY TYPE

Retrospective.

POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL

In all, 83 healthy control (HC) and 120 Parkinson's disease (PD) patients.

FIELD STRENGTH/SEQUENCE

3D magnetization-prepared rapid gradient-echo (MPRAGE) images at 3T.

ASSESSMENT

We 1) compared AES and ENT distribution between HC and PD; 2) evaluated the correlation between tremor score (TS) and AES (or ENT) in PD; and 3) investigated cortical regions showing an association between AES (or ENT) and local and network-level covariance measures of cortical thickness (CT), gray to white matter contrast (GWC) and gray matter density maps (GMx).

STATISTICAL TESTS

1) Student's t-test. 2) Spearman's rank correlation. 3) General linear model and partial least square analysis.

RESULTS

AES, but not ENT, differentiated HC and PD (P = 0.02, HC median AES = 39.8, interquartile range = 9.8, PD median AES = 37.6, interquartile range = 8.1). In PD, AES correlated negatively with TS (ρ = -0.21, P = 0.02) and showed a significant relationship (|Z| >3, P < 0.001) with structural covariance of CT and GWC in 54 out of 68 cortical regions.

DATA CONCLUSION

In clinical populations prone to head motion, AES can provide a reliable retrospective index of motion during structural scans, identifying brain areas whose morphometric measures covary with motion.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:927-937.

Striatal adenosine A2A receptor neurons control active-period sleep via parvalbumin neurons in external globus pallidus

Dysfunction of the striatum is frequently associated with sleep disturbances. However, its role in sleep-wake regulation has been paid little attention even though the striatum densely expresses adenosine A_2A receptors (A_2ARs), which are essential for adenosine-induced sleep. Here we showed that chemogenetic activation of A_2AR neurons in specific subregions of the striatum induced a remarkable increase in non-rapid eye movement (NREM) sleep. Anatomical mapping and immunoelectron microscopy revealed that striatal A_2AR neurons innervated the external globus pallidus (GPe) in a topographically organized manner and preferentially formed inhibitory synapses with GPe parvalbumin (PV) neurons. Moreover, lesions of GPe PV neurons abolished the sleep-promoting effect of striatal A_2AR neurons. In addition, chemogenetic inhibition of striatal A_2AR neurons led to a significant decrease of NREM sleep at active period, but not inactive period of mice. These findings reveal a prominent contribution of striatal A_2AR neuron/GPe PV neuron circuit in sleep control.

Correlation between Dopamine Transporter Degradation and Striatocortical Network Alteration in Parkinson's Disease

The association between dopamine neuron loss and functional change in the striatocortical network was analyzed in 31 patients with Parkinson's disease (PD) [mean disease duration 4.03 ± 4.20 years; Hoehn and Yahr (HY) stage 2.2 ± 1.2] and 37 age-matched normal control subjects. We performed ^99mTc-TRODAT-1 SPECT/CT imaging to detect neuron losses and resting-state functional magnetic resonance imaging to detect functional changes. Mean striatal dopamine transporter binding ratios were determined by region of interest analysis. The functional connectivity correlation coefficient (fc-cc) was determined in six striatal subregions, and interactions between these binding ratios and the striatocortical fc-cc values were analyzed. The PD patients had significant functional network alterations in all striatal subregions. Lower striatal dopamine transporter binding correlated significantly with lower fc-cc values in the superior medial frontal (SMF) lobe and superior frontal lobe and higher fc-cc values in the cerebellum and parahippocampus. The difference in fc-cc between the ventral inferior striatum and SMF lobe was significantly correlated with increased disease duration (r = -0.533, P = 0.004), higher HY stage (r = -0.431, P = 0.020), and lower activities of daily living score (r = 0.369, P = 0.049). The correlation of frontostriatal network changes with clinical manifestations suggests that fc-cc may serve as a surrogate marker of disease progression.

Autonomic Function Impairment and Brain Perfusion Deficit in Parkinson's Disease

INTRODUCTION

Autonomic disorders have been recognized as important Parkinson's disease (PD) components. Some vulnerable structures are related to the central autonomic network and have also been linked to autonomic function alterations. The aims of the study are to evaluate the severity of the autonomic dysfunction and the cortical hypoperfusion using arterial spin labeling (ASL) MRI. And then, possible relationships of significant between-group differences in perfusion pattern to clinical variables and autonomic functions were examined to determine the pharmaceutical effects of dopaminergic treatment on cerebral blood flow (CBF) in patients with PD.

METHODS

Brain ASL MRI was carried out in 20 patients with PD (6 men and 14 women, mean age: 63.3 ± 6.4 years) and 22 sex- and age-matched healthy volunteers to assess whole-brain CBF and the effects of dopaminergic therapy on perfusion. All subjects underwent a standardized evaluation of cardiovagal and adrenergic function including a deep breathing, Valsalva maneuver, and 5-min head-up tilt test. Perfusion MRI data were acquired on a 3.0 T scanner with a pulsed continuous ASL technique. The CBF, autonomic parameters, and clinical data were analyzed after adjusting for age and sex.

RESULTS

Patients exhibited a decline in autonomic function (rapid heart rate in response to deep breathing, low baroreflex sensitivity, high systolic and diastolic pressure, and altered tilting test response), widespread low CBF, and robust response to dopaminergic therapy. Lower perfusion in the middle frontal gyrus was associated with increased clinical disease severity (Unified Parkinson's Disease Rating Scale I score, P < 0.001). Lower perfusion in autonomic control areas, such as the frontal lobe and insula, were significantly associated with autonomic impairment (P < 0.001).

CONCLUSIONS

Our study indicates that PD is a progressive neurodegenerative disorder that changes the perfusion of central nervous system and is associated with variable autonomic dysfunctions. Neuronal loss and sympathetic activation may explain the interaction between cortical autonomic region perfusion and cardiovascular autonomic function.

Limbic grey matter changes in early Parkinson's disease

The purpose of this study was to investigate local and network‐related changes of limbic grey matter in early Parkinson's disease (PD) and their inter‐relation with non‐motor symptom severity. We applied voxel‐based morphometric methods in 538 T1 MRI images retrieved from the Parkinson's Progression Markers Initiative website. Grey matter densities and cross‐sectional estimates of age‐related grey matter change were compared between subjects with early PD (n = 366) and age‐matched healthy controls (n = 172) within a regression model, and associations of grey matter density with symptoms were investigated. Structural brain networks were obtained using covariance analysis seeded in regions showing grey matter abnormalities in PD subject group. Patients displayed focally reduced grey matter density in the right amygdala, which was present from the earliest stages of the disease without further advance in mild‐moderate disease stages. Right amygdala grey matter density showed negative correlation with autonomic dysfunction and positive with cognitive performance in patients, but no significant interrelations were found with anxiety scores. Patients with PD also demonstrated right amygdala structural disconnection with less structural connectivity of the right amygdala with the cerebellum and thalamus but increased covariance with bilateral temporal cortices compared with controls. Age‐related grey matter change was also increased in PD preferentially in the limbic system. In conclusion, detailed brain morphometry in a large group of early PD highlights predominant limbic grey matter deficits with stronger age associations compared with controls and associated altered structural connectivity pattern. This provides in vivo evidence for early limbic grey matter pathology and structural network changes that may reflect extranigral disease spread in PD. Hum Brain Mapp 38:3566–3578, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Parkinson's disease: diagnostic utility of volumetric imaging

PURPOSE

This paper aims to examine the effectiveness of structural imaging as an aid in the diagnosis of Parkinson's disease (PD).

METHODS

High-resolution T ₁-weighted magnetic resonance imaging was performed in 72 patients with idiopathic PD (mean age, 61.08 years) and 73 healthy subjects (mean age, 58.96 years). The whole brain was parcellated into 95 regions of interest using composite anatomical atlases, and region volumes were calculated. Three diagnostic classifiers were constructed using binary multiple logistic regression modeling: the (i) basal ganglion prior classifier, (ii) data-driven classifier, and (iii) basal ganglion prior/data-driven hybrid classifier. Leave-one-out cross validation was used to unbiasedly evaluate the predictive accuracy of imaging features. Pearson's correlation analysis was further performed to correlate outcome measurement using the best PD classifier with disease severity.

RESULTS

Smaller volume in susceptible regions is diagnostic for Parkinson's disease. Compared with the other two classifiers, the basal ganglion prior/data-driven hybrid classifier had the highest diagnostic reliability with a sensitivity of 74%, specificity of 75%, and accuracy of 74%. Furthermore, outcome measurement using this classifier was associated with disease severity.

CONCLUSIONS

Brain structural volumetric analysis with multiple logistic regression modeling can be a complementary tool for diagnosing PD.

Associations among Cognitive Functions, Plasma DNA, and White Matter Integrity in Patients with Early-Onset Parkinson's Disease

Early-onset Parkinson's disease (EOPD) patients are symptomatic at a relatively young age, and the impacts of the disease on both the patients and their caregivers are dramatic. Few studies have reported on the cognitive impairments seen in EOPD, and the results of these studies have been diverse. Furthermore, it is still unclear what microstructural white matter (WM) changes are present in EOPD patients. As such, we conducted this study to investigate the microstructural WM changes experienced by EOPD patients and their association with cognitive function and plasma DNA levels. We enrolled 24 EOPD patients and 33 sex- and age-matched healthy volunteers who underwent complete neuro-psychological testing (NPT) to evaluate their cognitive function and diffusion tensor imaging (DTI) scanning to determine their fiber integrity. The plasma DNA measurements included measurements of nuclear and mitochondrial DNA levels. Fractional anisotropy (FA) maps were compared using voxel-based statistics to determine differences between the two groups. The differences in DTI indices and NPT scores were correlated after adjusting for age, sex, and education. Our results demonstrate that patients with EOPD have elevated nuclear DNA levels and wide spectrums of impairments in NPT, especially in the executive function and visuospatial function domains. Exploratory group-wise comparisons of the DTI indices revealed that the patients with EOPD exhibited lower DTI parameters in several brain locations. These poorer DTI parameters were associated with worse cognitive performances and elevated plasma nuclear DNA levels, especially in the anterior thalamic radiation region. Our findings suggest that the thalamus and its adjacent anterior thalamic radiation may be important in the pathogenesis of EOPD, as they appear to become involved in the disease process at an early stage.

Hippocampus and amygdala volume in relation to migraine frequency and prognosis

Objectives To investigate the structural changes of hippocampus and amygdala and their relationships with migraine frequency and prognosis. Methods Hippocampus and amygdala volumes were measured by 3-T brain magnetic resonance imaging (MRI) in 31 controls and 122 migraine patients who were categorized into eight groups by headache frequency: group 1 (1-2 headache days/month), 2 (3-4), 3 (5-7), 4 (8-10), 5 (11-14), 6 (15-19), 7 (20-24), and 8 (25-30). Headache frequency was reassessed 2 years later and a frequency reduction ≥50% was regarded a good outcome. Results Hippocampus and amygdala volumes fluctuated in patient groups but did not differ from the controls. In migraine patients, the bilateral hippocampus volumes peaked in group 3. The volumes and headache frequencies correlated positively in groups 2-3 on bilateral sides (L: r = 0.44, p = 0.007; R: r = 0.35, p = 0.037), and negatively in groups 3-7 on the left side (5-24 days/month; L: r = -0.31, p = 0.004) and groups 3-8 on the right side ( r = -0.31, p = 0.002). The left amygdala volume also peaked in group 3, and correlated with headache frequency in groups 1-3 ( r = 0.34, p = 0.020) and groups 3-6 ( r = -0.30, p = 0.012). The volumetric changes of the right amygdala with headache frequency did not reach statistical significance. At 2-year follow-up, the right hippocampus volume was positively associated with a good migraine outcome after adjustment of headache frequency (OR 4.72, p = 0.024). Conclusions Hippocampus and amygdala display a structural plasticity linked to both headache frequency and clinical outcome of migraine.

Longitudinal brain structural alterations and systemic inflammation in obstructive sleep apnea before and after surgical treatment

Background

Systemic inflammation, neurocognitive impairments, and morphologic brain changes are associated with obstructive sleep apnea (OSA). Understanding their longitudinal evolution and interactions after surgical treatment provides clues to the pathogenesis of cognitive impairment and its reversibility. In the present study, we investigate clinical disease severity, systemic inflammation, cognitive deficits, and corresponding gray matter volume (GMV) changes in OSA, and the modifications following surgery.

Methods

Twenty-one patients with OSA (apnea-hypopnea index, AHI > 5) and 15 healthy volunteers (AHI < 5) underwent serial evaluation, including polysomnography, flow cytometry for leukocyte apoptosis categorization, cognitive function evaluation, and high-resolution brain scan. Disease severity, leukocyte apoptosis, cognitive function, and imaging data were collected to assess therapeutic efficacy 3 months after surgery.

Results

Pre-operatively, patients presented with worse cognitive function, worse polysomnography scores, and higher early leukocyte apoptosis associated with increased insular GMV. There was reduced GMV in the anterior cingulate gyrus before and after surgery in the cases compared to that in controls, suggesting an irreversible structural deficit. Post-operatively, there were significant improvements in different cognitive domains, including attention, executive and visuospatial function, and depression, and in early leukocyte apoptosis. There was also a significant decrease in GMVs after treatment, suggesting recovery from vasogenic edema in the precuneus, insula, and cerebellum. Improvement in early leukocyte apoptosis post-surgery predicted better recovery of precuneus GMV.

Conclusions

In OSA, increased disease severity and systemic inflammation can alter GMV in vulnerable regions. Surgical treatment may improve disease severity and systemic inflammation, with subsequent recovery in brain structures and functions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-0887-8) contains supplementary material, which is available to authorized users.

Dopaminergic Therapy Modulates Cortical Perfusion in Parkinson Disease With and Without Dementia According to Arterial Spin Labeled Perfusion Magnetic Resonance Imaging

Arterial spin labeling (ASL) magnetic resonance imaging analyses allow for the quantification of altered cerebral blood flow, and provide a novel means of examining the impact of dopaminergic treatments. The authors examined the cerebral perfusion differences among 17 Parkinson disease (PD) patients, 17 PD with dementia (PDD) patients, and 17 healthy controls and used ASL-MRI to assess the effects of dopaminergic therapies on perfusion in the patients. The authors demonstrated progressive widespread cortical hypoperfusion in PD and PDD and robust effects for the dopaminergic therapies. Specifically, dopaminergic medications further decreased frontal lobe and cerebellum perfusion in the PD and PDD groups, respectively. These patterns of hypoperfusion could be related to cognitive dysfunctions and disease severity. Furthermore, desensitization to dopaminergic therapies in terms of cortical perfusion was found as the disease progressed, supporting the concept that long-term therapies are associated with the therapeutic window narrowing. The highly sensitive pharmaceutical response of ASL allows clinicians and researchers to easily and effectively quantify the absolute perfusion status, which might prove helpful for therapeutic planning.

Cerebellar atrophy in Parkinson's disease and its implication for network connectivity

Pathophysiological and atrophic changes in the cerebellum are documented in Parkinson's disease. Without compensatory activity, such abnormalities could potentially have more widespread effects on both motor and non-motor symptoms. We examined how atrophic change in the cerebellum impacts functional connectivity patterns within the cerebellum and between cerebellar-cortical networks in 42 patients with Parkinson's disease and 29 control subjects. Voxel-based morphometry confirmed grey matter loss across the motor and cognitive cerebellar territories in the patient cohort. The extent of cerebellar atrophy correlated with decreased resting-state connectivity between the cerebellum and large-scale cortical networks, including the sensorimotor, dorsal attention and default networks, but with increased connectivity between the cerebellum and frontoparietal networks. The severity of patients' motor impairment was predicted by a combination of cerebellar atrophy and decreased cerebellar-sensorimotor connectivity. These findings demonstrate that cerebellar atrophy is related to both increases and decreases in cerebellar-cortical connectivity in Parkinson's disease, identifying potential cerebellar driven functional changes associated with sensorimotor deficits. A post hoc analysis exploring the effect of atrophy in the subthalamic nucleus, a cerebellar input source, confirmed that a significant negative relationship between grey matter volume and intrinsic cerebellar connectivity seen in controls was absent in the patients. This suggests that the modulatory relationship of the subthalamic nucleus on intracerebellar connectivity is lost in Parkinson's disease, which may contribute to pathological activation within the cerebellum. The results confirm significant changes in cerebellar network activity in Parkinson's disease and reveal that such changes occur in association with atrophy of the cerebellum.

Brain mediators of systemic oxidative stress on perceptual impairments in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is well documented to be associated with elevated systemic oxidative stress and perceptual impairments. Furthermore, the striatum and extrastriatal cortical areas, which are involved in the coordination of perceptual functions, are impaired at an early stage of the disease. However, the possible pathophysiology involved in perceptual impairments remains unclear. This raises the possibility that structural abnormalities might mediate the relationship between oxidative stress and perceptual impairments.

METHODS

We explored the differences between 27 patients with PD and 25 healthy controls in terms of serum oxidative stress, perceptual functions, and regional gray matter. A single-level three-variable mediation model was used to investigate the possible relationships between serum oxidative stress, regional gray matter volume, and different domains of perceptual functioning.

RESULTS

The results demonstrate that increased serum oxidative stress (as indicated by thiobarbituric acid reactive substances) was associated with declined perceptual functioning in PD patients. We further explored significant gray matter volume reductions in the bilateral temporal gyri (middle temporal gyrus and fusiform gyrus), bilateral frontal gyri, limbic lobe (hippocampus and uncus), left inferior parietal lobule, right caudate nucleus, and insula in PD. Further mediation analysis showed that gray matter volumes in the middle temporal gyrus, inferior parietal lobule, hippocampus, and insula served as brain mediators between elevated serum oxidative stress and perceptual impairments.

CONCLUSIONS

These results suggest that higher oxidative stress levels adversely impact perceptual functions by causing temporal and mesolimbic abnormalities.