Reproducible metabolic topographies associated with multiple system atrophy: Network and regional analyses in Chinese and American patient cohorts.
ABSTRACT: Multiple system atrophy (MSA) is an atypical parkinsonian syndrome and often difficult to discriminate clinically from progressive supranuclear palsy (PSP) and Parkinson's disease (PD) in early stages. Although a characteristic metabolic brain network has been reported for MSA, it is unknown whether this network can provide a clinically useful biomarker in different centers. This study was aimed to identify and cross-validate MSA-related brain network and assess its ability for differential diagnosis and clinical correlations in Chinese and American patient cohorts. We included 18F-FDG PET scans retrospectively from 128 clinically diagnosed parkinsonian patients (34 MSA, 34 PSP and 60 PD) and 40 normal subjects in China and in the USA. Using PET images from 20 moderate-stage MSA patients of parkinsonian subtype and 20 normal subjects in both centers, we reproduced MSA-related pattern (MSAPRP) of spatial covariance and estimated its reliability. MSAPRP scores were evaluated in assessing differential diagnosis among moderate- and early-stage MSA, PSP or PD patients and clinical correlations with disease severity. Regional metabolic differences were detected using statistical parameter mapping analysis. MSA-related network and regional topographies of metabolic abnormality were cross-validated between the Chinese and American cohorts. We generated a highly reliable MSAPRP characterized by decreased loading in inferior frontal cortex, striatum and cerebellum, and increased loading in sensorimotor, parietal and occipital cortices. MSAPRP scores discriminated between normal, MSA, PSP and PD subjects and correlated with standardized ratings of clinical stages and motor symptoms in MSA. High similarities in MSAPRPs, network scores and corresponding maps of metabolic abnormality were observed between two different cohorts. We have demonstrated reproducible metabolic topographies associated with MSA at both network and regional levels in two independent patient cohorts. Moreover, MSAPRP scores are sensitive for evaluating disease discrimination and clinical correlates. This study supports differential diagnosis of MSA regardless of different patient populations, PET scanners and imaging protocols.
Project description:Progressive supranuclear palsy (PSP) is a rare movement disorder and often difficult to distinguish clinically from Parkinson's disease (PD) and multiple system atrophy (MSA) in early phases. In this study, we report reproducible disease-related topographies of brain network and regional glucose metabolism associated with PSP in clinically-confirmed independent cohorts of PSP, MSA, and PD patients and healthy controls in the USA and China. Using 18 F-FDG PET images from PSP and healthy subjects, we applied spatial covariance analysis with bootstrapping to identify a PSP-related pattern (PSPRP) and estimate its reliability, and evaluated the ability of network scores for differential diagnosis. We also detected regional metabolic differences using statistical parametric mapping analysis. We produced a highly reliable PSPRP characterized by relative metabolic decreases in the middle prefrontal cortex/cingulate, ventrolateral prefrontal cortex, striatum, thalamus and midbrain, covarying with relative metabolic increases in the hippocampus, insula and parieto-temporal regions. PSPRP network scores correlated positively with PSP duration and accurately discriminated between healthy, PSP, MSA and PD groups in two separate cohorts of parkinsonian patients at both early and advanced stages. Moreover, PSP patients shared many overlapping areas with abnormal metabolism in the same cortical and subcortical regions as in the PSPRP. With rigorous cross-validation, this study demonstrated highly comparable and reproducible PSP-related metabolic topographies at network and regional levels across different patient populations and PET scanners. Metabolic brain network activity may serve as a reliable and objective marker of PSP, although cross-validation applying recent diagnostic criteria and classification is warranted.
Project description:Little is known of the precise relationship between the expression of disease-related metabolic patterns and nigrostriatal dopaminergic dysfunction in parkinsonism. We studied 51 subjects with Parkinson's disease (PD) (18 non-demented, 24 demented, and 9 dementia with Lewy bodies) and 127 with atypical parkinsonian syndromes (47 multiple system atrophy (MSA), 38 progressive supranuclear palsy (PSP), and 42 corticobasal syndrome (CBS)) with 18F-fluorodeoxyglucose PET to quantify the expression of previously validated disease-related patterns for PD, MSA, PSP, and CBS and 18F-fluoropropyl-?-CIT PET to quantify caudate and putamen dopamine transporter (DAT) binding. The patients in each group exhibited significant elevations in the expression of the corresponding disease-related pattern ( p?<?0.001), relative to 16 healthy subjects. With the exception of cerebellar MSA (MSA-C), all groups displayed significant reductions in putamen DAT binding relative to healthy subjects ( p?<?0.05). Correlations between the dopaminergic and metabolic measures were significant in PD and CBS but not in MSA and PSP. In all patient groups with the exception of MSA-C and CBS, pattern expression values and DAT binding correlated with disease duration and severity measures. The findings suggest that in these parkinsonian disorders, metabolic network expression and DAT binding provide complementary information regarding the underlying disease process.
Project description:To determine if blood neurofilament light chain (NfL) protein can discriminate between Parkinson disease (PD) and atypical parkinsonian disorders (APD) with equally high diagnostic accuracy as CSF NfL, and can therefore improve the diagnostic workup of parkinsonian disorders.The study included 3 independent prospective cohorts: the Lund (n = 278) and London (n = 117) cohorts, comprising healthy controls and patients with PD, progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and multiple system atrophy (MSA), as well as an early disease cohort (n = 109) of patients with PD, PSP, MSA, or CBS with disease duration ?3 years. Blood NfL concentration was measured using an ultrasensitive single molecule array (Simoa) method, and the diagnostic accuracy to distinguish PD from APD was investigated.We found strong correlations between blood and CSF concentrations of NfL (? ? 0.73-0.84, p ? 0.001). Blood NfL was increased in patients with MSA, PSP, and CBS (i.e., all APD groups) when compared to patients with PD as well as healthy controls in all cohorts (p < 0.001). Furthermore, in the Lund cohort, blood NfL could accurately distinguish PD from APD (area under the curve [AUC] 0.91) with similar results in both the London cohort (AUC 0.85) and the early disease cohort (AUC 0.81).Quantification of blood NfL concentration can be used to distinguish PD from APD. Blood-based NfL might consequently be included in the diagnostic workup of patients with parkinsonian symptoms in both primary care and specialized clinics.This study provides Class III evidence that blood NfL levels discriminate between PD and APD.
Project description:Background:There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes. Methods:We used dMRI from 1002 subjects, along with the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III), to develop and validate disease-specific machine learning comparisons using 60 template regions and tracts of interest in Montreal Neurological Institute (MNI) space between Parkinson's disease (PD) and Atypical Parkinsonism (multiple system atrophy - MSA, progressive supranuclear palsy - PSP), as well as between MSA and PSP. For each comparison, models were developed on a training/validation cohort and evaluated in a test cohort by quantifying the area under the curve (AUC) of receiving operating characteristic (ROC) curves. Findings:In the test cohort for both disease-specific comparisons, AUCs were high in the dMRI + MDS-UPDRS (PD vs. Atypical Parkinsonism: 0·962; MSA vs. PSP: 0·897) and dMRI Only (PD vs. Atypical Parkinsonism: 0·955; MSA vs. PSP: 0·926) models, whereas the MDS-UPDRS III Only models had significantly lower AUCs (PD vs. Atypical Parkinsonism: 0·775; MSA vs. PSP: 0·582). Interpretations:This study provides an objective, validated, and generalizable imaging approach to distinguish different forms of Parkinsonian syndromes using multi-site dMRI cohorts. The dMRI method does not involve radioactive tracers, is completely automated, and can be collected in less than 12 minutes across 3T scanners worldwide. The use of this test could thus positively impact the clinical care of patients with Parkinson's disease and Parkinsonism as well as reduce the number of misdiagnosed cases in clinical trials.
Project description:Parkinson's disease (PD) is associated with a characteristic regional metabolic covariance pattern that is modulated by treatment. To determine whether a homologous metabolic pattern is also present in nonhuman primate models of parkinsonism, 11 adult macaque monkeys with parkinsonism secondary to chronic systemic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and 12 age-matched healthy animals were scanned with [(18)F]fluorodeoxyglucose (FDG) positron emission tomography (PET). A subgroup comprising five parkinsonian and six control animals was used to identify a parkinsonism-related pattern (PRP). For validation, analogous topographies were derived from other subsets of parkinsonian and control animals. The PRP topography was characterized by metabolic increases in putamen/pallidum, thalamus, pons, and sensorimotor cortex, as well as reductions in the posterior parietal-occipital region. Pattern expression was significantly elevated in parkinsonian relative to healthy animals (P<0.00001). Parkinsonism-related topographies identified in the other derivation sets were very similar, with significant pairwise correlations of region weights (r>0.88; P<0.0001) and subject scores (r>0.74; P<0.01). Moreover, pattern expression in parkinsonian animals correlated with motor ratings (r>0.71; P<0.05). Thus, homologous parkinsonism-related metabolic networks are demonstrable in PD patients and in monkeys with experimental parkinsonism. Network quantification may provide a useful biomarker for the evaluation of new therapeutic agents in preclinical models of PD.
Project description:Background: Microarray technology may offer a new opportunity to gain insight into disease-specific global protein expression profiles. The present study was performed to apply a serum cytokine-array to screen for potential molecular biomarkers for Parkinson's disease (PD), multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). Methodology/Principal Findings: Serum samples were obtained from patients with clinical diagnoses of PD (n=117), MSA (n=31) and PSP/CBS (n=38) and 99 controls. Cytokine profiles of sera of patients and controls were analyzed with a semiquantitative human cytokine antibody array. In a next step, significantly altered cytokines were individually validated by immunoassays. The cytokine array revealed a significantly altered expression of 12 cytokines. Immunoassay validation confirmed a significant increase of PDGF-BB in PSP/CBS, MSA and PD and a decrease of Prolactin in PD (Kruskal-Wallis p<0.05). A multivariate analysis taking into account diagnoses anti-Parkinsonian treatment, sex and age revealed that PDGF-BB levels were influenced only by the diagnoses (p<0.001), whereas Prolactin levels were influenced only by anti-Parkinsonian treatment (p<0.001). These findings could be corroborated by a subgroup analysis in untreated patients. Conclusions/Significance: In our unbiased cytokine array screening approach we found PDGF-BB to be elevated in PSP/CBS, MSA and PD. Increased PDGF-BB levels might be of relevance in a model of molecular biomarkers for Parkinsonian syndromes. Overall design: Screen serum samples from patients with Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome, multisystem atrophy and controls for deregulation of serum proteins using a cytokine-array detecting 174 secreted signaling proteins.
Project description:Decreased blood-brain barrier (BBB) efflux function of the P-glycoprotein (P-gp) transport system could facilitate the accumulation of toxic compounds in the brain, increasing the risk of neurodegenerative pathology such as Parkinson's disease (PD). This study investigated in vivo BBB P-gp function in patients with parkinsonian neurodegenerative syndromes, using [11C]-verapamil PET in PD, PSP and MSA patients. Regional differences in distribution volume were studied using SPM with higher uptake interpreted as reduced P-gp function. Advanced PD patients and PSP patients had increased [11C]-verapamil uptake in frontal white matter regions compared to controls; while de novo PD patients showed lower uptake in midbrain and frontal regions. PSP and MSA patients had increased uptake in the basal ganglia. Decreased BBB P-gp function seems a late event in neurodegenerative disorders, and could enhance continuous neurodegeneration. Lower [11C]-verapamil uptake in midbrain and frontal regions of de novo PD patients could indicate a regional up-regulation of P-gp function.
Project description:Most available pattern recognition methods in neuroimaging address binary classification problems. Here, we used relevance vector machine (RVM) in combination with booststrap resampling ('bagging') for non-hierarchical multiclass classification. The method was tested on 120 cerebral (18)fluorodeoxyglucose (FDG) positron emission tomography (PET) scans performed in patients who exhibited parkinsonian clinical features for 3.5 years on average but that were outside the prevailing perception for Parkinson's disease (PD). A radiological diagnosis of PD was suggested for 30 patients at the time of PET imaging. However, at follow-up several years after PET imaging, 42 of them finally received a clinical diagnosis of PD. The remaining 78 APS patients were diagnosed with multiple system atrophy (MSA, N = 31), progressive supranuclear palsy (PSP, N = 26) and corticobasal syndrome (CBS, N = 21), respectively. With respect to this standard of truth, classification sensitivity, specificity, positive and negative predictive values for PD were 93% 83% 75% and 96%, respectively using binary RVM (PD vs. APS) and 90%, 87%, 79% and 94%, respectively, using multiclass RVM (PD vs. MSA vs. PSP vs. CBS). Multiclass RVM achieved 45%, 55% and 62% classification accuracy for, MSA, PSP and CBS, respectively. Finally, a majority confidence ratio was computed for each scan on the basis of class pairs that were the most frequently assigned by RVM. Altogether, the results suggest that automatic multiclass RVM classification of FDG PET scans achieves adequate performance for the early differentiation between PD and APS on the basis of cerebral FDG uptake patterns when the clinical diagnosis is felt uncertain. This approach cannot be recommended yet as an aid for distinction between the three APS classes under consideration.
Project description:Phosphorylated ?-synuclein (PS-129), a protein implicated in the pathogenesis of Parkinson's disease (PD), was identified by mass spectrometry in human cerebrospinal fluid (CSF). A highly sensitive and specific assay was established and used to measure PS-129 together with total ?-synuclein in the CSF of patients with PD, other parkinsonian disorders such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), and healthy individuals (a total of ~600 samples). PS-129 CSF concentrations correlated weakly with PD severity and, when combined with total ?-synuclein concentrations in CSF, contributed to distinguishing PD from MSA and PSP. Further rigorous validation in independent cohorts of patients, especially those where samples have been collected longitudinally, will determine whether the concentration of PS-129 in CSF will be useful for diagnosing PD and for monitoring PD severity and progression.