Shared functional neural substrates in Parkinson's disease and drug-induced parkinsonism: association with dopaminergic depletion

Neurovascular coupling alteration in drug-naïve Parkinson's disease: The underlying molecular mechanisms and levodopa's restoration effects

BACKGROUND

Parkinson's disease (PD) patients exhibit an imbalance between neuronal activity and perfusion, referred to as abnormal neurovascular coupling (NVC). Nevertheless, the underlying molecular mechanism and how levodopa, the standard treatment in PD, regulates NVC is largely unknown.

MATERIAL AND METHODS

A total of 52 drug-naïve PD patients and 49 normal controls (NCs) were enrolled. NVC was characterized in vivo by relating cerebral blood flow (CBF) and amplitude of low-frequency fluctuations (ALFF). Motor assessments and MRI scanning were conducted on drug-naïve patients before and after levodopa therapy (OFF/ON state). Regional NVC differences between patients and NCs were identified, followed by an assessment of the associated receptors/transporters. The influence of levodopa on NVC, CBF, and ALFF within these abnormal regions was analyzed.

RESULTS

Compared to NCs, OFF-state patients showed NVC dysfunction in significantly lower NVC in left precentral, postcentral, superior parietal cortex, and precuneus, along with higher NVC in left anterior cingulate cortex, right olfactory cortex, thalamus, caudate, and putamen (P-value <0.0006). The distribution of NVC differences correlated with the density of dopaminergic, serotonin, MU-opioid, and cholinergic receptors/transporters. Additionally, levodopa ameliorated abnormal NVC in most of these regions, where there were primarily ALFF changes with limited CBF modifications.

CONCLUSION

Patients exhibited NVC dysfunction primarily in the striato-thalamo-cortical circuit and motor control regions, which could be driven by dopaminergic and nondopaminergic systems, and levodopa therapy mainly restored abnormal NVC by modulating neuronal activity.

Linking the cerebellum to Parkinson disease: an update

Parkinson disease (PD) is characterized by heterogeneous motor and non-motor symptoms, resulting from neurodegeneration involving various parts of the central nervous system. Although PD pathology predominantly involves the nigral-striatal system, growing evidence suggests that pathological changes extend beyond the basal ganglia into other parts of the brain, including the cerebellum. In addition to a primary involvement in motor control, the cerebellum is now known to also have an important role in cognitive, sleep and affective processes. Over the past decade, an accumulating body of research has provided clinical, pathological, neurophysiological, structural and functional neuroimaging findings that clearly establish a link between the cerebellum and PD. This Review presents an overview and update on the involvement of the cerebellum in the clinical features and pathogenesis of PD, which could provide a novel framework for a better understanding the heterogeneity of the disease.

Multimodal imaging study of the 5-HT1A receptor biased agonist, NLX-112, in a model of L-DOPA-induced dyskinesia

INTRODUCTION

The leading treatment for motor signs of Parkinson's disease is L-DOPA, but, upon extended use, it can lead to levodopa-induced dyskinesia (LID). Serotonergic neurons are involved in LID etiology and previous pre-clinical studies have shown that NLX-112, a 5-HT1A biased agonist, has robust antidyskinetic effects. Here, we investigated its effects in hemiparkinsonian (HPK) rats with a unilateral nigrostriatal 6-OHDA lesion.

METHODS

We compared HPK rats with LID (i.e., sensitized to the dyskinetic effects of chronic L-DOPA) and without LID (HPK-non-LID), using [18F]FDG PET imaging and fMRI functional connectivity following systemic treatment with saline, L-DOPA, NLX-112 or L-DOPA + NLX-112.

RESULTS

In HPK-non-LID rats, [18F]FDG PET experiments showed that L-DOPA led to hypermetabolism in motor areas (cerebellum, brainstem, and mesencephalic locomotor region) and to hypometabolism in cortical regions. L-DOPA effects were also observed in HPK-LID rats, with the additional emergence of hypermetabolism in raphe nuclei and hypometabolism in hippocampus and striatum. NLX-112 attenuated L-DOPA-induced raphe hypermetabolism and cingulate cortex hypometabolism in HPK-LID rats. Moreover, in fMRI experiments NLX-112 partially corrected the altered neural circuit connectivity profile in HPK-LID rats, through activity in regions rich in 5-HT1A receptors.

CONCLUSION

This neuroimaging study sheds light for the first time on the brain activation patterns of HPK-LID rats. The 5-HT1A receptor agonist, NLX-112, prevents occurrence of LID, likely by activating pre-synaptic autoreceptors in the raphe nuclei, resulting in a partial restoration of brain metabolic and connectivity profiles. In addition, NLX-112 also rescues L-DOPA-induced deficits in cortical activation, suggesting potential benefit against non-motor symptoms of Parkinson's disease.

Parkinson's Disease-Related Brain Metabolic Pattern Is Expressed in Schizophrenia Patients during Neuroleptic Drug-Induced Parkinsonism

Drug-induced parkinsonism (DIP) is a frequent parkinsonian syndrome that appears as a result of pharmacotherapy for the management of psychosis. It could substantially hamper treatment and therefore its diagnosis has a direct influence on treatment effectiveness. Although of such high importance, there is a lack of systematic research for developing neuroimaging-based criteria for DIP diagnostics for such patients. Therefore, the current study was aimed at applying a metabolic brain imaging approach using the 18F-FDG positron emission tomography and spatial covariance analysis to reveal possible candidates for DIP markers. As a result, we demonstrated, to our knowledge, the first attempt at the application of the Parkinson's Disease-Related Pattern (PDRP) as a metabolic signature of parkinsonism for the assessment of PDRP expression for schizophrenia patients with DIP. As a result, we observed significant differences in PDRP expression between the control group and the groups with PD and DIP patients. Similar differences in PDRP expression were also found when the non-DIP schizophrenia patients were compared with the PD group. Therefore, our findings made it possible to conclude that PDRP is a promising tool for the development of clinically relevant criteria for the estimation of the risk of developing DIP.

Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI

This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of dopamine transporter SPECT with ¹²³I-FP-CIT in parkinsonian syndromes. A total of 1306 ¹²³I-FP-CIT-SPECT were included retrospectively. Binary classification as ‘reduced’ or ‘normal’ striatal ¹²³I-FP-CIT uptake by an experienced reader served as standard-of-truth. A custom-made 3-dimensional convolutional neural network (CNN) was trained for classification of the SPECT images with 1006 randomly selected images in three different settings: “full image”, “striatum only” (3-dimensional region covering the striata cropped from the full image), “without striatum” (full image with striatal region removed). The remaining 300 SPECT images were used to test the CNN classification performance. Layer-wise relevance propagation (LRP) was used for voxelwise quantification of the relevance for the CNN-based classification in this test set. Overall accuracy of CNN-based classification was 97.0%, 95.7%, and 69.3% in the “full image”, “striatum only”, and “without striatum” setting. Prominent contributions in the LRP-based relevance maps beyond the striatal signal were detected in insula, amygdala, ventromedial prefrontal cortex, thalamus, anterior temporal cortex, superior frontal lobe, and pons, suggesting that ¹²³I-FP-CIT uptake in these brain regions provides clinically useful information for the differentiation of neurodegenerative and non-neurodegenerative parkinsonian syndromes.