Dopaminergic Correlates of Regional Cerebral Blood Flow in Parkinsonian Disorders

Relationships between PET and blood plasma biomarkers in corticobasal syndrome

INTRODUCTION

Corticobasal syndrome (CBS) can result from underlying Alzheimer's disease (AD) pathologies. Little is known about the utility of blood plasma metrics to predict positron emission tomography (PET) biomarker-confirmed AD in CBS.

METHODS

A cohort of eighteen CBS patients (8 amyloid beta [Aβ]+; 10 Aβ-) and 8 cognitively unimpaired (CU) individuals underwent PET imaging and plasma analysis. Plasma concentrations were compared using a Kruskal-Wallis test. Spearman correlations assessed relationships between plasma concentrations and PET uptake.

RESULTS

CBS Aβ+ group showed a reduced Aβ42/40 ratio, with elevated phosphorylated tau (p-tau)181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) concentrations, while CBS Aβ- group only showed elevated NfL concentration compared to CU. Both p-tau181 and GFAP were able to differentiate CBS Aβ- from CBS Aβ+ and showed positive associations with Aβ and tau PET uptake.

DISCUSSION

This study supports use of plasma p-tau181 and GFAP to detect AD in CBS. NfL shows potential as a non-specific disease biomarker of CBS regardless of underlying pathology.

HIGHLIGHTS

Plasma phosphorylated tau (p-tau)181 and glial fibrillary acidic protein (GFAP) concentrations differentiate corticobasal syndrome (CBS) amyloid beta (Aβ)- from CBS Aβ+. Plasma neurofilament light concentrations are elevated in CBS Aβ- and Aβ+ compared to controls. Plasma p-tau181 and GFAP concentrations were associated with Aβ and tau positron emission tomography (PET) uptake. Aβ42/40 ratio showed a negative correlation with Aβ PET uptake.

The Role of Dual-Phase 18 F-FP-CIT PET to Early Diagnosis of Corticobasal Syndrome

BACKGROUND

Corticobasal syndrome (CBS) is a neurodegeneration characterized by asymmetric parkinsonism, dystonia, myoclonus, and apraxia. In the early stage, CBS presents with asymmetric parkinsonism and cortical symptoms (apraxia and alien hand), and neuroimaging finding is often vague, making early clinical differentiation from idiopathic Parkinson disease (IPD) challenging. This study was performed to delineate the specific patterns of cortical hypoperfusion, dopamine transporter (DAT) uptake using dual-phase FP-CIT PET in discriminating between CBS and IPD at early stage.

PATIENTS AND METHODS

The study enrolled clinically diagnosed CBS (n = 11) and IPD (n = 22) patients (age and sex matched). All participants underwent dual-phase 18 F-FP-CIT PET, and regional SUV ratio (SUVR) was obtained by semiquantitative analysis. The early perfusion imaging and DAT imaging were compared between groups.

RESULTS

The regional SUVRs (early phase) of the frontal lobe, thalamus, cingulate, and caudate were significantly lower in patients with CBS, whereas the SUVR of occipital lobe was lower in the IPD group. The CBS group exhibited more prominent asymmetry than the IPD group, particularly in the perirolandic area, superior frontal gyrus, and anterior parietal lobe in early phase PET. Striatal DAT uptake (delayed phase) revealed that the caudate showed lower SUVR and prominent asymmetry in the CBS group, and the caudate-to-putamen ratio (CP ratio) was significantly lower in CBS patients ( P < 0.001). Among the parameters (early and delayed), the CP ratio in DAT exhibited the most powerful discriminative power from receiver operating characteristic curve comparison (area under curve = 0.983).

CONCLUSIONS

This study demonstrated that the dual-phase FP-CIT PET is useful in differentiating CBS and IPD in the early stage of the disease, and a lower CP ratio of DAT imaging is highly informative for distinguishing between corticobasal degeneration and IPD.

Predictability of inter-regional cerebral perfusion similarity on dopamine responsiveness and the moderation role of cognition in PD patients

BACKGROUND

Large heterogeneity can be found in dopamine responsiveness of patients with Parkinson's disease (PD). Instantly and objectively understanding dopamine responsiveness of patients may help clinical practice.

PURPOSE

This PD study explored the predictability of off-state inter-regional cerebral blood flow (CBF) perfusion similarity on patient's dopamine responsiveness and tested whether the predictive power could be moderated by patient's cognitive status.

MATERIALS AND METHOD

The PD cohort with 192 patients (containing off state and on state (PD-off and PD-on)) and the normal control (NC) cohort with 92 subjects were included. The intra-individual CBF relative variation networks were constructed and compared between PD-off and PD-on, PD-off and NC to identify the alterations caused by dopamine depletion. Based on that, regression analysis of off-state inter-regional CBF perfusion similarity on patient's dopamine responsiveness was performed. Finally, moderation analysis was conducted to test the moderation role of cognition on the regression model.

RESULTS

In the PD-off cohort, a total of 82 edges in the network were identified that affected by dopamine depletion. Off-state inter-regional CBF perfusion similarity was found that had a significant influence on patient's dopamine responsiveness. Cognitive status was validated that positively moderated the relationship between off-state inter-regional CBF perfusion similarity and dopamine responsiveness.

CONCLUSION

Dopamine responsiveness of PD patient could be predicted by off-state inter-regional CBF perfusion similarity. Patient's cognitive status might have a positive moderation effect on his/her dopamine responsiveness.

Chronic Cerebral Hypoperfusion Aggravates Parkinson’s Disease Dementia-Like Symptoms and Pathology in 6-OHDA-Lesioned Rat through Interfering with Sphingolipid Metabolism

Chronic cerebral hypoperfusion (CCH) is a cardinal risk factor for Parkinson's disease dementia (PDD), but this potential causality lacks mechanistic evidence. We selected bilateral common carotid artery occlusion (BCCAO) to simulate chronic cerebral hypoperfusion in the rat model of PD induced by typical neurotoxin 6-hydroxy dopamine (6-OHDA). Four weeks after unilateral injection of 6-OHDA into the medial forebrain bundle, rats underwent BCCAO. Male Sprague-Dawley rats were divided into five groups of ten, including sham, PD+BCCAO 2 weeks, PD+BCCAO 1 week, PD, and BCCAO 2 weeks. Then, open field test (OFT) and Morris water maze test (MWM) were used to assess the PDD-like symptoms in rats. Also, the pathological manifestations and mechanisms of BCCAO impairing cognitive functions have been explored via hematoxylin-eosin staining, Nissl staining, immunohistochemistry, immunofluorescence, RNA sequencing analysis, lipidomics, and quantitative real-time polymerase chain reaction. In this study, we found that CCH could aggravate PDD-like cognitive symptoms (i.e., learning memory and spatial cognition) and PDD-like pathology (higher expression of α-Syn and Aβ in prefrontal cortex and striatum). Moreover, a potential relationship between differentially expressed mRNAs and lipid metabolism was revealed by RNA sequencing analysis. Lipidomics showed that CCH could affect the intensity of 5 lipids, including sphingomyelin (SM 9:0;2O/26:2; SM 8:1;2O/25:0; and SM 8:0;2O/28:4), cardiolipin, lysophosphatidylcholine, cholesteryl ester, and triacylglycerol. Interestingly, the KEGG pathway analysis of both RNA sequencing analysis and lipidomics suggested that CCH leaded to learning impairment by affecting sphingolipid metabolism. Finally, we found that CCH disrupts the sphingolipid metabolism by affecting the mRNA expression of SMPD1 and SMS2, leading to the accumulation of sphingomyelin in the prefrontal cortex. In summary, CCH, an independent exacerbating reason for impairment in learning and memory within the pathopoiesis of PD, aggravates Parkinson's disease dementia-like symptoms and pathology in 6-OHDA-lesioned rat through interfering with sphingolipid metabolism.

Classification of Parkinson's disease using a region-of-interest- and resting-state functional magnetic resonance imaging-based radiomics approach

To investigate the value of combining amplitude of low-frequency fluctuations-based radiomics and the support vector machine classifier method in distinguishing patients with Parkinson's disease from healthy controls. A total of 123 patients with Parkinson's disease and 90 healthy controls from three centers with functional and structural MRI images were included in this study. We extracted radiomics features using the Brainnetome 246 atlas from the mean amplitude of low-frequency fluctuations maps. Two-sample t-tests and recursive feature elimination combined with support vector machine method were applied for feature selection and dimensionality reduction. We used support vector machine classifier to construct model and identify the discriminative features. The automated anatomical labeling 90 atlas and fivefold cross-validation were used to evaluate the robustness and generalization of the classifier. We found our model obtained a high classification performance with an accuracy of 78.07%, and AUC, sensitivity, and specificity of 0.8597, 78.80%, and 76.08%, respectively. We detected 7 discriminative brain subregions. The fivefold cross-validation and automated anatomical labeling 90 atlas also got high classification accuracy, and we found Brainnetome 246 atlas achieved a higher classification performance than the automated anatomical labeling 90 atlas both with tenfold and fivefold cross-validation. Our findings may help the early diagnosis of Parkinson's disease and provide support for research on Parkinson's disease mechanisms and clinical evaluation.