Neuroimaging in Parkinson disease: from research setting to clinical practice

Visualizing alpha-synuclein and iron deposition in M83 mouse model of Parkinson's disease in vivo

Abnormal alpha-synuclein (αSyn) and iron accumulation in the brain play an important role in Parkinson's disease (PD). Herein, we aim to visualize αSyn inclusions and iron deposition in the brains of M83 (A53T) mouse models of PD in vivo. The fluorescent pyrimidoindole derivative THK-565 probe was characterized by means of recombinant fibrils and brains from 10- to 11-month-old M83 mice. Concurrent wide-field fluorescence and volumetric multispectral optoacoustic tomography (vMSOT) imaging were subsequently performed in vivo. Structural and susceptibility weighted imaging (SWI) magnetic resonance imaging (MRI) at 9.4 T as well as scanning transmission x-ray microscopy (STXM) were performed to characterize the iron deposits in the perfused brains. Immunofluorescence and Prussian blue staining were further performed on brain slices to validate the detection of αSyn inclusions and iron deposition. THK-565 showed increased fluorescence upon binding to recombinant αSyn fibrils and αSyn inclusions in post-mortem brain slices from patients with PD and M83 mice. Administration of THK-565 in M83 mice showed higher cerebral retention at 20 and 40 min post-intravenous injection by wide-field fluorescence compared to nontransgenic littermate mice, in congruence with the vMSOT findings. SWI/phase images and Prussian blue indicated the accumulation of iron deposits in the brains of M83 mice, presumably in the Fe3+ form, as evinced by the STXM results. In conclusion, we demonstrated in vivo mapping of αSyn by means of noninvasive epifluorescence and vMSOT imaging and validated the results by targeting the THK-565 label and SWI/STXM identification of iron deposits in M83 mouse brains ex vivo.

Preclinical evaluation of [18F]FP-CIT, the radiotracer targeting dopamine transporter for diagnosing Parkinson's disease: pharmacokinetic and efficacy analysis

BACKGROUND

N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane (FP-CIT), the representative cocaine derivative used in dopamine transporter imaging, is a promising biomarker, as it reflects the severity of Parkinson's disease (PD). 123I- and 18F-labeled FP-CIT has been used for PD diagnosis. However, preclinical studies evaluating [18F]FP-CIT as a potential diagnostic biomarker are scarce. Among translational research advancements from bench to bedside, translating preclinical findings into clinical practice is one-directional. The aim of this study is to employ a circular approach, beginning back from the preclinical stage, progressing to the supplementation of [18F]FP-CIT, and subsequently returning to clinical application. We investigated the pharmacokinetic properties of [18F]FP-CIT and its efficacy for PD diagnosis using murine models.

RESULTS

Biodistribution, metabolite and excretion analyses were performed in mice and PD models were induced in rats using 6-hydroxydopamine (6-OHDA). The targeting efficiency of [18F]FP-CIT for the dopamine receptor was assessed through animal PET/CT imaging. Subsequently, correlation analysis was conducted between animal PET/CT imaging results and immunohistochemistry (IHC) targeting tyrosine hydroxylase. Rapid circulation was confirmed after [18F]FP-CIT injection. [18F]FP-CIT reached the highest uptake of 23.50 ± 12.46%ID/g in the striatum 1 min after injection, and it was rapidly excreted within 60 min. The major metabolic organs of [18F]FP-CIT were confirmed to be the intestines, liver, and kidneys. Its uptake in the intestine was approximately 5% ID/g. The uptake in the liver gradually increased, with excretion beginning after reaching a maximum after 60 min. The kidneys exhibited rapid elimination after 10 min. In the excretion study, rapid elimination was verified, with 21.46 ± 9.53% of the compound excreted within a 6 h period. Additionally, the efficacy of [18F]FP-CIT PET was demonstrated in the PD model, with a high correlation with IHC for both the absolute value (R = 0.803, p = 0.0017) and the ratio value (R = 0.973, p = 0.0011).

CONCLUSIONS

This study fills the gap regarding insufficient preclinical studies on [18F]FP-CIT, including its ADME, metabolites, and efficiency. The pharmacological results, including accurate diagnosis, rapid circulation, and [18F]FP-CIT excretion, provide complementary evidence that [18F]FP-CIT can be used safely and efficiently to diagnose PD in clinics, although it is already used in clinics.

Differential diagnosis value of sympathetic skin response and cutaneous silent period on early-stage multiple system atrophy and Parkinson disease

PURPOSE

Early differentiation between Parkinson's disease (PD) and Multiple system atrophy (MSA), particularly the parkinsonian subtypes (MSA-P), is challenging due to similar clinical symptoms. We aimed to evaluate Sympathetic skin response (SSR) and Cutaneous silent period (CSP) parameters in patients with MSA-P and PD to identify possible biomarkers that could distinguish the two groups of patients in early stage.

METHODS

22 individuals with early-stage MSA-P, 29 with early-stage PD, and 28 healthy controls were recruited from Guangdong Provincial People's Hospital. Demographic data was collected for all participants. Their SSR and CSP were evaluated using clinical electromyography equipment. Data were compared between different groups. The diagnostic accuracy of SSR and CSP parameters was calculated using the ROC curve. Logistic regression was used to produce an integration model to enhance diagnostic utility.

RESULTS

Foot amplitude, CSP end latency and duration distinguished MSA-P from PD with the area under the curve (AUC) 0.770, 0.806, and 0.776, respectively. Foot and hand SSR amplitude distinguished PD from HC with the AUC 0.871 and 0.768, respectively. Foot SSR amplitude, hand SSR amplitude, and CSP end latency distinguished MSA-P from HC with the AUC 0.964, 0.872, and 0.812, respectively. The combination of SSR and CSP parameters differentiation between MSA-P and PD, PD and HC with the AUC 0.829 and 0.879, respectively.

CONCLUSIONS

Analysis of SSR and CSP parameters showed excellent diagnostic accuracy in discriminating patients with early-stage MSA-P from HC and good diagnostic accuracy in discriminating patients with MSA-P from PD with early stages.

Serum level of YWHAG as a diagnostic marker of cognitive impairment in Parkinson's disease patients

BACKGROUND

Identifying reliable biomarkers for early detection and prediction of cognitive impairment in Parkinson's disease (PD) is crucial for optimal patient care. This study set out to investigate the potential of YWHAG as a diagnostic biomarker for cognitive impairment in PD.

METHODS

We enrolled a total of 331 PD patients and selected 241 patients that met the criteria for cognitive impairment analysis. The patients were classified into three groups: PD-NC: PD patients with normal cognition, PD-MCI: PD patients with mild cognitive impairment, and PD-D: PD patients with dementia. ELISA was employed to assess YWHAG expression, as well as the neurofilament light chain (NfL). Additionally, cognitive impairment was evaluated using MoCA scores. Correlation analysis and receiver operating curve analysis (ROC) were performed to clarify the relationship between YWHAG expression and cognitive impairment.

RESULTS

Our findings revealed a significant upregulation of YWHAG expression in both the PD-MCI and PD-D groups compared to the PD-NC group. This observation aligned with the elevated expression of NfL in the PD-MCI and PD-D groups. YWHAG and NfL expression levels displayed negative correlations with MoCA scores and positive associations with age. Furthermore, ROC curve analysis demonstrated the diagnostic efficacy of YWHAG expression in distinguishing individuals with PD-NC, PD-MCI, and PD-D.

CONCLUSIONS

Our findings indicate that YWHAG could serve as a promising biomarker for cognitive impairment in PD. The upregulation of YWHAG expression in PD-MCI and PD-D groups, its association with cognitive impairment, and its correlations with MoCA scores and NfL levels support its potential clinical utility.

Predicting the occurrence of mild cognitive impairment in Parkinson's disease using structural MRI data

Introduction

Mild cognitive impairment (MCI) is a common symptom observed in individuals with Parkinson's disease (PD) and a main risk factor for progressing to dementia. Our objective was to identify early anatomical brain changes that precede the transition from healthy cognition to MCI in PD.

Methods

Structural T1-weighted magnetic resonance imaging data of PD patients with healthy cognition at baseline were downloaded from the Parkinson's Progression Markers Initiative database. Patients were divided into two groups based on the annual cognitive assessments over a 5-year time span: (i) PD patients with unstable healthy cognition who developed MCI over a 5-year follow-up (PD-UHC, n = 52), and (ii) PD patients who maintained stable healthy cognitive function over the same period (PD-SHC, n = 52). These 52 PD-SHC were selected among 192 PD-SHC patients using propensity score matching method to have similar demographic and clinical characteristics with PD-UHC at baseline. Seventy-five percent of these were used to train a support vector machine (SVM) algorithm to distinguish between the PD-UHC and PD-SHC groups, and tested on the remaining 25% of individuals. Shapley Additive Explanations (SHAP) feature analysis was utilized to identify the most informative brain regions in SVM classifier.

Results

The average accuracy of classifying PD-UHC vs. PD-SHC was 80.76%, with 82.05% sensitivity and 79.48% specificity using 10-fold cross-validation. The performance was similar in the hold-out test sets with all accuracy, sensitivity, and specificity at 76.92%. SHAP analysis showed that the most influential brain regions in the prediction model were located in the frontal, occipital, and cerebellar regions as well as midbrain.

Discussion

Our machine learning-based analysis yielded promising results in identifying PD individuals who are at risk of cognitive decline from the earliest disease stage and revealed the brain regions which may be linked to the prospective cognitive decline in PD before clinical symptoms emerge.

Distinctive clinical and imaging trajectories in SWEDD and Parkinson's disease patients

A proportion of patients clinically diagnosed with Parkinson's disease (PD) can have a 123I-FP-CIT-SPECT scan without evidence of dopaminergic deficit (SWEDD), generating a debate about the underlying biological mechanisms. This study investigated differences in clinical features, 123I-FP-CIT binding, molecular connectivity, as well as clinical and imaging progression between SWEDD and PD patients. We included 36 SWEDD, 49 de novo idiopathic PD, and 49 healthy controls with 123I-FP-CIT-SPECT from the Parkinson's Progression Markers Initiative. Clinical and imaging 2-year follow-ups were available for 27 SWEDD and 40 PD. Regional-based and voxel-wise analysis assessed dopaminergic integrity in dorsal and ventral striatal, as well as extrastriatal regions, at baseline and follow-up. Molecular connectivity analyses evaluated dopaminergic pathways. Spatial correlation analyses tested whether 123I-FP-CIT-binding alterations would also pertain to the serotoninergic system. SWEDD and PD patients showed comparable symptoms at baseline, except for hyposmia, which was more severe for PD. PD showed significantly lower striatal and extrastriatal 123I-FP-CIT-binding compared to SWEDD and controls. SWEDD exhibited lower binding than controls in striatal regions, insula, and olfactory cortex. Both PD and SWEDD showed extensive altered connectivity of dopaminergic pathways, however, with major impairment in the mesocorticolimbic system for SWEDD. Motor symptoms and dopaminergic deficits worsened after 2 years for PD only. The limited dopaminergic impairment and its stability over time observed for SWEDD, as well as the presence of extrastriatal 123I-FP-CIT binding alterations and prevalent mesocorticolimbic connectivity impairment, suggest other mechanisms contributing to SWEDD pathophysiology.

Ratiometric Fluorescent Probe Promotes Trans-differentiation of Human Mesenchymal Stem Cells to Neurons

Development of multifunctional theranostics is challenging and crucial for deciphering complex biological phenomena and subsequently treating critical disease. In particular, development of theranostics for traumatic brain injury (TBI) and understanding its repair mechanism are challenging and highly complex areas of research. Recently, there have been interesting pieces of research work demonstrated that a small molecule-based neuroregenerative approach using stem cells has potential for future therapeutic lead development for TBI. However, these works demonstrated the application of a mixture of multiple molecules as a "chemical cocktail", which may have serious toxic effects in the differentiated cells. Therefore, development of a single-molecule-based potential differentiating agent for human mesenchymal stem cells (hMSCs) into functional neurons is vital for the upcoming neuro-regenerative therapeutics. This lead could be further extraploted for the design of theranostics for TBI. In this study, we have developed a multifunctional single-molecule-based fluorescent probe, which can image the transdifferentiated neurons as well as promote the differentiation process. We demonstrated a promising class of fluorescent probes (CP-4) that can be employed to convert hMSCs into neurons in the presence of fibroblast growth factor (FGF). This fluorescent probe was used in cellular imaging as its fluorescence intensity remained unaltered for up to 7 days of trans-differentiation. We envision that this imaging probe can have an important application in the study of neuropathological and neurodegenerative studies.

Lifestyle Modulators of Neuroplasticity in Parkinson's Disease: Evidence in Human Neuroimaging Studies

Parkinson's disease (PD) is a neurodegenerative disease characterized by both motor and non-motor symptoms. A progressive neuronal loss and the consequent clinical impairment lead to deleterious effects on daily living and quality of life. Despite effective symptomatic therapeutic approaches, no disease-modifying therapies are currently available. Emerging evidence suggests that adopting a healthy lifestyle can improve the quality of life of PD patients. In addition, modulating lifestyle factors can positively affect the microstructural and macrostructural brain levels, corresponding to clinical improvement. Neuroimaging studies may help to identify the mechanisms through which physical exercise, dietary changes, cognitive enrichment, and exposure to substances modulate neuroprotection. All these factors have been associated with a modified risk of developing PD, with attenuation or exacerbation of motor and non-motor symptomatology, and possibly with structural and molecular changes. In the present work, we review the current knowledge on how lifestyle factors influence PD development and progression and the neuroimaging evidence for the brain structural, functional, and molecular changes induced by the adoption of positive or negative lifestyle behaviours.

Progressive supranuclear palsy: A case report and brief review of the literature

Atypical Parkinsonian syndromes are a subset of progressive neurodegenerative disorders that present with signs of Parkinson's disease. However, due to multisystem degeneration, the atypical Parkinsonian syndromes have additional symptoms that are often referred to as Parkinson-plus syndromes. The most well-studied subsets include progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and Lewy body dementia. Specifically, progressive supranuclear palsy is a tauopathy neurodegenerative disorder that presents with parkinsonism symptoms along with postural instability, vertical saccade, and vertical gaze palsy. Here, we present a case of PSP and provide a brief review of the literature.

Abnormalities of cerebral blood flow and the regional brain function in Parkinson's disease: a systematic review and multimodal neuroimaging meta-analysis

Background

Parkinson's disease (PD) is a neurodegenerative disease with high incidence rate. Resting state functional magnetic resonance imaging (rs-fMRI), as a widely used method for studying neurodegenerative diseases, has not yet been combined with two important indicators, amplitude low-frequency fluctuation (ALFF) and cerebral blood flow (CBF), for standardized analysis of PD.

Methods

In this study, we used seed-based d-mapping and permutation of subject images (SDM-PSI) software to investigate the changes in ALFF and CBF of PD patients. After obtaining the regions of PD with changes in ALFF or CBF, we conducted a multimodal analysis to identify brain regions where ALFF and CBF changed together or could not synchronize.

Results

The final study included 31 eligible trials with 37 data sets. The main analysis results showed that the ALFF of the left striatum and left anterior thalamic projection decreased in PD patients, while the CBF of the right superior frontal gyrus decreased. However, the results of multimodal analysis suggested that there were no statistically significant brain regions. In addition, the decrease of ALFF in the left striatum and the decrease of CBF in the right superior frontal gyrus was correlated with the decrease in clinical cognitive scores.

Conclusion

PD patients had a series of spontaneous brain activity abnormalities, mainly involving brain regions related to the striatum-thalamic-cortex circuit, and related to the clinical manifestations of PD. Among them, the left striatum and right superior frontal gyrus are more closely related to cognition.

Systematic review registration

https://www.crd.york.ac.uk/ PROSPERO (CRD42023390914).

Effects of rasagiline combined with levodopa and benserazide hydrochloride on motor function and homocysteine and IGF-1 levels in elderly patients with Parkinson's disease

BACKGROUND

During the course of their illness, people with Parkinson's disease may see changes in their insulin-like growth factor (IGF-1) and serum homocysteine (Hcy) indices. In this study, patients with intermediate to severe Parkinson's disease were examined for how Resagiline and levodopa and benserazide hydrochloride affected their motor performance, serum levels of homocysteine (Hcy), and insulin-like growth factor (IGF-1).

METHODS

From June 2020 to December 2021, a total of 100+ cases of Parkinson's patients over 60 years old in the middle and late stages of Parkinson's were seen in the outpatient and inpatient departments of the Third People's Hospital of Chengdu City and had a detailed observation record, and according to the inclusion criteria, the patients who met the criteria were randomly grouped into a clinical observation group and a control group. The subjects in the control group received only levodopa and benserazide hydrochloride treatment, while the observation group was treated with Resagiline in combination with the clinical control group. The total treatment observation period was 1 year for both groups, and the motor function and serum Hcy and IGF-1 indexes of both groups were compared after the end of treatment.

RESULTS

We randomly and evenly grouped 64 patients who met the requirements of the inclusion criteria into a clinical observation group and a control group, each with 32 patients, from among 168 patients over 60 years of age with detailed observation records in the middle and late stages of Parkinson's. After the 1-year observation period, we found that the total effective rate after treatment in the clinical observation group (93.75%) and significantly higher than that in the control group (68.75%) (P < 0.05); after 1 year of treatment, the UPDRS score decreased in both groups, and the observation group was significantly lower than the control group (P < 0.05); after treatment, serum Hcy decreased and IGF-1 increased in both groups, and the observation group was higher than the control group mean values (P < 0.05).

CONCLUSIONS

In patients with Parkinson's disease who are in the middle and late stages of the disease, the administration of Resagiline combined with levodopa and benserazide hydrochloride can significantly lower the body's serum Hcy level, significantly raise IGF-1 levels, and significantly improve motor function in patients with Parkinson's disease. It can also have significant therapeutic effects.

Parkinson's disease progression: Increasing expression of an invariant common core subnetwork

Notable success has been achieved in the study of neurodegenerative conditions using reduction techniques such as principal component analysis (PCA) and sparse inverse covariance estimation (SICE) in positron emission tomography (PET) data despite their widely differing approach. In a recent study of SICE applied to metabolic scans from Parkinson's disease (PD) patients, we showed that by using PCA to prespecify disease-related partition layers, we were able to optimize maps of functional metabolic connectivity within the relevant networks. Here, we show the potential of SICE, enhanced by disease-specific subnetwork partitions, to identify key regional hubs and their connections, and track their associations in PD patients with increasing disease duration. This approach enabled the identification of a core zone that included elements of the striatum, pons, cerebellar vermis, and parietal cortex and provided a deeper understanding of progressive changes in their connectivity. This subnetwork constituted a robust invariant disease feature that was unrelated to phenotype. Mean expression levels for this subnetwork increased steadily in a group of 70 PD patients spanning a range of symptom durations between 1 and 21 years. The findings were confirmed in a validation sample of 69 patients with up to 32 years of symptoms. The common core elements represent possible targets for disease modification, while their connections to external regions may be better suited for symptomatic treatment.

Machine learning models for diagnosis and prognosis of Parkinson's disease using brain imaging: general overview, main challenges, and future directions

Parkinson's disease (PD) is a progressive and complex neurodegenerative disorder associated with age that affects motor and cognitive functions. As there is currently no cure, early diagnosis and accurate prognosis are essential to increase the effectiveness of treatment and control its symptoms. Medical imaging, specifically magnetic resonance imaging (MRI), has emerged as a valuable tool for developing support systems to assist in diagnosis and prognosis. The current literature aims to improve understanding of the disease's structural and functional manifestations in the brain. By applying artificial intelligence to neuroimaging, such as deep learning (DL) and other machine learning (ML) techniques, previously unknown relationships and patterns can be revealed in this high-dimensional data. However, several issues must be addressed before these solutions can be safely integrated into clinical practice. This review provides a comprehensive overview of recent ML techniques analyzed for the automatic diagnosis and prognosis of PD in brain MRI. The main challenges in applying ML to medical diagnosis and its implications for PD are also addressed, including current limitations for safe translation into hospitals. These challenges are analyzed at three levels: disease-specific, task-specific, and technology-specific. Finally, potential future directions for each challenge and future perspectives are discussed.

Adaptation strategies and neurophysiological response in early-stage Parkinson's disease: BioVRSea approach

Introduction

There is accumulating evidence that many pathological conditions affecting human balance are consequence of postural control (PC) failure or overstimulation such as in motion sickness. Our research shows the potential of using the response to a complex postural control task to assess patients with early-stage Parkinson's Disease (PD).

Methods

We developed a unique measurement model, where the PC task is triggered by a moving platform in a virtual reality environment while simultaneously recording EEG, EMG and CoP signals. This novel paradigm of assessment is called BioVRSea. We studied the interplay between biosignals and their differences in healthy subjects and with early-stage PD.

Results

Despite the limited number of subjects (29 healthy and nine PD) the results of our work show significant differences in several biosignals features, demonstrating that the combined output of posturography, muscle activation and cortical response is capable of distinguishing healthy from pathological.

Discussion

The differences measured following the end of the platform movement are remarkable, as the induced sway is different between the two groups and triggers statistically relevant cortical activities in α and θ bands. This is a first important step to develop a multi-metric signature able to quantify PC and distinguish healthy from pathological response.

Levodopa-Induced Dyskinesias in Parkinson's Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Since its first introduction, levodopa has become the cornerstone for the treatment of Parkinson's disease and remains the leading therapeutic choice for motor control therapy so far. Unfortunately, the subsequent appearance of abnormal involuntary movements, known as dyskinesias, is a frequent drawback. Despite the deep knowledge of this complication, in terms of clinical phenomenology and the temporal relationship during a levodopa regimen, less is clear about the pathophysiological mechanisms underpinning it. As the disease progresses, specific oscillatory activities of both motor cortical and basal ganglia neurons and variation in levodopa metabolism, in terms of the dopamine receptor stimulation pattern and turnover rate, underlie dyskinesia onset. This review aims to provide a global overview on levodopa-induced dyskinesias, focusing on pathophysiology, clinical manifestations, therapy management strategies and future directions.

Visualizing alpha-synuclein and iron deposition in M83 mouse model of Parkinson's disease in vivo

Background

Abnormal alpha-synuclein and iron accumulation in the brain play an important role in Parkinson's disease (PD). Herein, we aim at visualizing alpha-synuclein inclusions and iron deposition in the brains of M83 (A53T) mouse models of PD in vivo.

Methods

Fluorescently labelled pyrimidoindole-derivative THK-565 was characterized by using recombinant fibrils and brains from 10-11 months old M83 mice, which subsequently underwent in vivo concurrent wide-field fluorescence and volumetric multispectral optoacoustic tomography (vMSOT) imaging. The in vivo results were verified against structural and susceptibility weighted imaging (SWI) magnetic resonance imaging (MRI) at 9.4 Tesla and scanning transmission X-ray microscopy (STXM) of perfused brains. Brain slice immunofluorescence and Prussian blue staining were further performed to validate the detection of alpha-synuclein inclusions and iron deposition in the brain, respectively.

Results

THK-565 showed increased fluorescence upon binding to recombinant alpha-synuclein fibrils and alpha-synuclein inclusions in post-mortem brain slices from patients with Parkinson's disease and M83 mice. i.v. administration of THK-565 in M83 mice showed higher cerebral retention at 20 and 40 minutes post-injection by wide-field fluorescence compared to non-transgenic littermate mice, in congruence with the vMSOT findings. SWI/phase images and Prussian blue indicated the accumulation of iron deposits in the brains of M83 mice, presumably in the Fe3+ form, as evinced by the STXM results.

Conclusion

We demonstrated in vivo mapping of alpha-synuclein by means of non-invasive epifluorescence and vMSOT imaging assisted with a targeted THK-565 label and SWI/STXM identification of iron deposits in M83 mouse brains ex vivo.

Large-scale activation likelihood estimation meta-analysis of parkinsonian disorders

Parkinsonism is a feature of several neurodegenerative disorders, including Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy. Neuroimaging studies have yielded insights into parkinsonian disorders; however, due to variability in results, the brain regions consistently implicated in these disorders remain to be characterized. The aim of this meta-analysis was to identify consistent brain abnormalities in individual parkinsonian disorders (Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy) and to investigate any shared abnormalities across disorders. A total of 44 591 studies were systematically screened following searches of two databases. A series of whole-brain activation likelihood estimation meta-analyses were performed on 132 neuroimaging studies (69 Parkinson's disease; 23 progressive supranuclear palsy; 17 corticobasal syndrome; and 23 multiple system atrophy) utilizing anatomical MRI, perfusion or metabolism PET and single-photon emission computed tomography. Meta-analyses were performed in each parkinsonian disorder within each imaging modality, as well as across all included disorders. Results in progressive supranuclear palsy and multiple system atrophy aligned with current imaging markers for diagnosis, encompassing the midbrain, and brainstem and putamen, respectively. PET imaging studies of patients with Parkinson's disease most consistently reported abnormality of the middle temporal gyrus. No significant clusters were identified in corticobasal syndrome. When examining abnormalities shared across all four disorders, the caudate was consistently reported in MRI studies, whilst the thalamus, inferior frontal gyrus and middle temporal gyri were commonly implicated by PET. To our knowledge, this is the largest meta-analysis of neuroimaging studies in parkinsonian disorders and the first to characterize brain regions implicated across parkinsonian disorders.

Deep learning application for the classification of Alzheimer's disease using 18F-flortaucipir (AV-1451) tau positron emission tomography

The positron emission tomography (PET) with 18F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively unimpaired (CU) individuals. This study aimed to evaluate the utility of 18F-flortaucipir-PET images and multimodal data integration in the differentiation of CU from MCI or AD through DL. We used cross-sectional data (18F-flortaucipir-PET images, demographic and neuropsychological score) from the ADNI. All data for subjects (138 CU, 75 MCI, 63 AD) were acquired at baseline. The 2D convolutional neural network (CNN)-long short-term memory (LSTM) and 3D CNN were conducted. Multimodal learning was conducted by adding the clinical data with imaging data. Transfer learning was performed for classification between CU and MCI. The AUC for AD classification from CU was 0.964 and 0.947 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.947, and 0.976 in multimodal learning. The AUC for MCI classification from CU had 0.840 and 0.923 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.845, and 0.850 in multimodal learning. The 18F-flortaucipir PET is effective for the classification of AD stage. Furthermore, the effect of combination images with clinical data increased the performance of AD classification.

Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography

BACKGROUND

The progression of Alzheimer's dementia (AD) can be classified into three stages: cognitive unimpairment (CU), mild cognitive impairment (MCI), and AD. The purpose of this study was to implement a machine learning (ML) framework for AD stage classification using the standard uptake value ratio (SUVR) extracted from ¹⁸F-flortaucipir positron emission tomography (PET) images. We demonstrate the utility of tau SUVR for AD stage classification. We used clinical variables (age, sex, education, mini-mental state examination scores) and SUVR extracted from PET images scanned at baseline. Four types of ML frameworks, such as logistic regression, support vector machine (SVM), extreme gradient boosting, and multilayer perceptron (MLP), were used and explained by Shapley Additive Explanations (SHAP) to classify the AD stage.

RESULTS

Of a total of 199 participants, 74, 69, and 56 patients were in the CU, MCI, and AD groups, respectively; their mean age was 71.5 years, and 106 (53.3%) were men. In the classification between CU and AD, the effect of clinical and tau SUVR was high in all classification tasks and all models had a mean area under the receiver operating characteristic curve (AUC) > 0.96. In the classification between MCI and AD, the independent effect of tau SUVR in SVM had an AUC of 0.88 (p < 0.05), which was the highest compared to other models. In the classification between MCI and CU, the AUC of each classification model was higher with tau SUVR variables than with clinical variables independently, which yielded an AUC of 0.75(p < 0.05) in MLP, which was the highest. As an explanation by SHAP for the classification between MCI and CU, and AD and CU, the amygdala and entorhinal cortex greatly affected the classification results. In the classification between MCI and AD, the para-hippocampal and temporal cortex affected model performance. Especially entorhinal cortex and amygdala showed a higher effect on model performance than all clinical variables in the classification between MCI and CU.

CONCLUSIONS

The independent effect of tau deposition indicates that it is an effective biomarker in classifying CU and MCI into clinical stages using MLP. It is also very effective in classifying AD stages using SVM with clinical information that can be easily obtained at clinical screening.

Targeting the microbiota-mitochondria crosstalk in neurodegeneration with senotherapeutics

Neurodegenerative diseases are a group of age-related disorders characterized by a chronic and progressive loss of function and/or structure of synapses, neurons, and glial cells. The etiopathogenesis of neurodegenerative diseases is characterized by a complex network of intricately intertwined pathophysiological processes that are still not fully understood. Safe and effective disease-modifying treatments are urgently needed, but still not available. Accumulating evidence suggests that gastrointestinal dyshomeostasis and microbial dysbiosis might play an important role in neurodegeneration by acting as either primary or secondary pathophysiological factors. The research on the role of microbiota in neurodegeneration is in its early phase; however, accumulating evidence suggests that dysbiosis might promote neurodegenerative diseases by disrupting mitochondrial function and inducing mitochondrial dysfunction-associated senescence (MiDAS), possibly due to bidirectional crosstalk based on the common evolutionary origin of mitochondria and bacteria. Cellular senescence is an onco-supressive homeostatic mechanism that results in an irreversible cell cycle arrest upon exposure to noxious stimuli. Senescent cells resist apoptosis via senescent cell anti-apoptotic pathways (SCAPs) and transition into a state known as senescence-associated secretory phenotype (SASP) that generates a cytotoxic proinflammatory microenvironment. Cellular senescence results in the adoption of a detrimental vicious cycle driven by dysbiosis, mitochondrial dysfunction, inflammation, and oxidative stress - a pathophysiological positive feedback loop that results in neuroinflammation and neurodegeneration. Detrimental effects of MiDAS might be prevented and abolished by mitochondria-targeted senotherapeutics, a group of drugs specifically designed to alleviate senescence by inhibiting SCAPs (senolytics), or inhibiting SASP (senomorphics).

Primary motor area-related injury of anterior central gyrus in Parkinson's disease with dyskinesia: a study based on MRS and Q-Space

INTRODUCTION

By using magnetic resonance spectroscopy (MRS) and Q-Space imaging technology, this research analyzes the imaging characteristics of white matter fibers in the primary motor cortex and posterior limbs of the subcortical internal capsule in parkinsonian patients with motor disorders. The correlation among the changes in axonal function and structure in the cerebral cortex and subcortical cortex and motor disorder is further revealed.

METHODS

First, motor function and clinical condition of 20 patients with Parkinson's disease is assessed the third section of the Unified Parkinson's Scale and H&Y Parkinson's Clinical Staging Scale. Magnetic resonance (MR) scanning is performed with 1H-MRS. Secondly, the range maps of N-acetylaspartic acid (NAA), Choline (Cho), and Creatine (Cr) in the region of interest (the primary motor area of anterior central cortex gyrus, i.e. M1 region) are obtained, and the ratios of NAA/Cr and Cho are calculated. Third, Q-Space MR diffusion imaging technique is used to collect Q-Space images, and a Dsi-studio workstation is used to post-process the images. The fraction anisotropic (FA), generalized fraction anisotropic (GFA), and apparent diffusion coefficient (ADC) parameters of Q-Space in the primary motor cortex and the region of interest in the posterior limb of the internal capsule are obtained. Finally, the parameters of MRS and Q-Space in the experimental group and the control group are further analyzed by SPSS statistical software.

RESULTS

After assessing with Parkinson's score scale, there is obvious motor dysfunction in the experimental group. The average clinical stage of H&Y is 3.0±0.31. In the analysis of MRS data, the ratio of NAA/Cr in the primary motor area of the anterior central gyrus in the experimental group is significantly lower than that in the control group (P<0.05). In the ADC map obtained by Q-Space imaging technique, the ADC value in the primary motor area of the anterior central gyrus in the experimental group is higher than that in the control group (P<0.05), and the difference is statistically significant (P<0.05). There is no significant difference between the experimental group and the control group (P>0.05) in FA and GFA values of the posterior limb of capsule to characterize the characteristics of white matter fibers.

CONCLUSIONS

In parkinsonian patients with motor dysfunction, there are apparent functional and structural changes in the primary motor area neurons and peripheral white matter of the anterior central gyrus, and no obvious damage to the axonal structure of the descending fibers in the cortex.

A review of the current research on in vivo and in vitro detection for alpha-synuclein: a biomarker of Parkinson's disease

Parkinson's disease is a health-threatening neurodegenerative disease of the elderly with clinical manifestations of motor and non-motor deficits such as tremor palsy and loss of smell. Alpha-synuclein (α-Syn) is the pathological basis of PD, it can abnormally aggregate into insoluble forms such as oligomers, fibrils, and plaques, causing degeneration of nigrostriatal dopaminergic neurons in the substantia nigra in the patient's brain and the formation of Lewy bodies (LBs) and Lewy neuritis (LN) inclusions. As a result, achieving α-Syn aggregate detection in the early stages of PD can effectively stop or delay the progression of the disease. In this paper, we provide a brief overview and analysis of the molecular structures and α-Syn in vivo and in vitro detection methods, such as mass spectrometry, antigen-antibody recognition, electrochemical sensors, and imaging techniques, intending to provide more technological support for detecting α-Syn early in the disease and intervening in the progression of Parkinson's disease.

Structural and Molecular Imaging for Clinically Uncertain Parkinsonism

Neuroimaging is an important adjunct to the clinical assessment of Parkinson disease (PD). Parkinsonism can be challenging to differentiate, especially in early disease stages, when it mimics other movement disorders or when there is a poor response to dopaminergic therapies. There is also a discrepancy between the phenotypic presentation of degenerative parkinsonism and the pathological outcome. The emergence of more sophisticated and accessible neuroimaging can identify molecular mechanisms of PD, the variation between clinical phenotypes, and the compensatory mechanisms that occur with disease progression. Ultra-high-field imaging techniques have improved spatial resolution and contrast that can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. We highlight the imaging modalities that can be accessed in clinical practice and recommend an approach to the diagnosis of clinically uncertain parkinsonism.

Signaling pathways in Parkinson's disease: molecular mechanisms and therapeutic interventions

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide, and its treatment remains a big challenge. The pathogenesis of PD may be related to environmental and genetic factors, and exposure to toxins and gene mutations may be the beginning of brain lesions. The identified mechanisms of PD include α-synuclein aggregation, oxidative stress, ferroptosis, mitochondrial dysfunction, neuroinflammation, and gut dysbiosis. The interactions among these molecular mechanisms complicate the pathogenesis of PD and pose great challenges to drug development. At the same time, the diagnosis and detection of PD are also one of obstacles to the treatment of PD due to its long latency and complex mechanism. Most conventional therapeutic interventions for PD possess limited effects and have serious side effects, heightening the need to develop novel treatments for this disease. In this review, we systematically summarized the pathogenesis, especially the molecular mechanisms of PD, the classical research models, clinical diagnostic criteria, and the reported drug therapy strategies, as well as the newly reported drug candidates in clinical trials. We also shed light on the components derived from medicinal plants that are newly identified for their effects in PD treatment, with the expectation to provide the summary and outlook for developing the next generation of drugs and preparations for PD therapy.

PET imaging in animal models of Parkinson's disease

Alpha-synucleinopathies, such as Parkinson's disease, dementia with Lewy bodies and multiple system atrophy, are characterized by aberrant accumulation of alpha-synuclein and synaptic dysfunction leading to motor and cognitive deficits. Animal models of alpha-synucleinopathy have greatly facilitated the mechanistic understanding of the disease and the development of therapeutics. Various transgenic, alpha-synuclein fibril-injected, and toxin-injected animal models of Parkinson's disease and multiple system atrophy that recapitulate the disease pathology have been developed and widely used. Recent advances in positron emission tomography have allowed the noninvasive visualization of molecular alterations, underpinning behavioral dysfunctions in the brains of animal models and the longitudinal monitoring of treatment effects. Imaging studies in these disease animal models have employed multi-tracer PET designs to reveal dopaminergic deficits together with other molecular alterations. This review focuses on the development of new positron emission tomography tracers and studies of alpha-synuclein, synaptic vesicle glycoprotein 2A neurotransmitter receptor deficits such as dopaminergic receptor, dopaminergic transporter, serotonergic receptor, vesicular monoamine transporter 2, hypometabolism, neuroinflammation, mitochondrial dysfunction and leucine rich repeat kinase 2 in animal models of Parkinson's disease. The outstanding challenges and emerging applications are outlined, such as investigating the gut-brain-axis by using positron emission tomography in animal models, and provide a future outlook.

Graph-Based Analysis of Brain Connectivity in Multiple Sclerosis Using Functional MRI: A Systematic Review

(1) Background: Multiple sclerosis (MS) is an immune system disease in which myelin in the nervous system is affected. This abnormal immune system mechanism causes physical disabilities and cognitive impairment. Functional magnetic resonance imaging (fMRI) is a common neuroimaging technique used in studying MS. Computational methods have recently been applied for disease detection, notably graph theory, which helps researchers understand the entire brain network and functional connectivity. (2) Methods: Relevant databases were searched to identify articles published since 2000 that applied graph theory to study functional brain connectivity in patients with MS based on fMRI. (3) Results: A total of 24 articles were included in the review. In recent years, the application of graph theory in the MS field received increased attention from computational scientists. The graph-theoretical approach was frequently combined with fMRI in studies of functional brain connectivity in MS. Lower EDSSs of MS stage were the criteria for most of the studies (4) Conclusions: This review provides insights into the role of graph theory as a computational method for studying functional brain connectivity in MS. Graph theory is useful in the detection and prediction of MS and can play a significant role in identifying cognitive impairment associated with MS.

Metabolic assessment of cerebral palsy with normal clinical MRI using 18F-FDG PET imaging: A preliminary report

To explore the cerebral metabolic patterns of cerebral palsy (CP) patients without structural abnormalities by brain magnetic resonance imaging (MRI) scans, we evaluated ¹⁸F-fluoro-deoxyglucose positron emission tomography (¹⁸F-FDG PET) imaging features in patients. Thirty-one children with CP [Gross Motor Function Classification System (GMFCS) levels II-V] showing no structural abnormalities by MRI were enrolled in this study. Regional glucose metabolic activity values were calculated using Scenium software and compared between the right and left cerebral hemispheres. These comparisons revealed asymmetric metabolic reductions in the central region, cerebellum, frontal lobe, and parietal lobe (p < 0.01). We next determined whether averaged brain metabolic activity values in different brain regions correlated with GMFCS levels. The metabolic activity values of basal ganglia, left temporal lobe, and cerebellum correlated negatively with GMFCS scores (all p < 0.05). This method was applied to the left cerebellum, which showed higher metabolic activity values than those in the right cerebellum in most patients (83.8%), and these values also correlated negatively with GMFCS scores (Spearman's r = −0.36, p = 0.01). Differential cortical glucose metabolism by ¹⁸F-FDG PET, may help to distinguish between different CP diagnoses that are not detected by MRI.

Spatially-directed magnetic molecularly imprinted polymers with good anti-interference for simultaneous enrichment and detection of dual disease-related bio-indicators

As the changes of biomarkers directly reflect the occurrence of degenerative diseases, accurate detection of biomarkers is of great significance for disease diagnosis and control. However, single index detection has high uncertainties to accurately reflect the pathological characteristics because of the complexity of the human internal environment and the extremely trace concentration of indicators. To this end, a method for simultaneous detection of dual-biomarkers based on anti-interference magnetic molecularly imprinted polymers (D-mag-MIPs) is thereby proposed, and successfully applied in human urine analysis for the detection of Parkinson's disease bio-indicators 4-dihydroxyphenylacetic acid (DOPAC) and dopamine (DA). In this work, carboxyl functionalized ferric oxide served as a magnetic core, laying a solid foundation for batch detection. Hyperbranched polyethylenimine, whose abundant amino groups can provide multiple interaction forces to templates with high affinity, is employed as a functional monomer. Relative to single-template MIPs, D-mag-MIPs achieve the detection of dual bio-indicators in a one-time test, reducing the false positive result probability and enhancing the detection accuracy. The proposed methodology has been evaluated to exhibit good anti-interference, satisfactory precision, low detection limits, wide linear ranges and fast batch detection for DA and DOPAC. This work thus offers an alternative and efficient pathway for convenient batch detection of dual bio-indicators from biofluids at once.

Increased Expression of Alpha-, Beta-, and Gamma-Synucleins in Brainstem Regions of a Non-Human Primate Model of Parkinson’s Disease

Parkinson’s disease (PD) is characterized by cell loss in the substantia nigra and the presence of alpha-synuclein (α-syn)-containing neuronal Lewy bodies. While α-syn has received major interest in the pathogenesis of PD, the function of beta- and gamma-synucleins (β-syn and γ-syn, respectively) is not really known. Yet, these proteins are members of the same family and also concentrated in neuronal terminals. The current preclinical study investigated the expression levels of α-, β-, and γ-synucleins in brainstem regions involved in PD physiopathology. We analyzed synuclein expression in the substantia nigra, raphe nuclei, pedunculopontine nucleus, and locus coeruleus from control and parkinsonian (by MPTP) macaques. MPTP-intoxicated monkeys developed a more or less severe parkinsonian score and were sacrificed after a variable post-MPTP period ranging from 1 to 20 months. The expression of the three synucleins was increased in the substantia nigra after MPTP, and this increase correlates positively, although not very strongly, with cell loss and motor score and not with the time elapsed after intoxication. In the dorsal raphe nucleus, the expression of the three synucleins was also increased, but only α- and γ-Syn are linked to the motor score and associated cell loss. Finally, although no change in synuclein expression was demonstrated in the locus coeruleus after MPTP, we found increased expression levels of γ-Syn, which are only correlated with cell loss in the pedunculopontine nucleus. Altogether, our data suggest that these proteins may play a key role in brainstem regions and mesencephalic tegmentum. Given the involvement of these brain regions in non-motor symptoms of PD, these data also strengthen the relevance of the MPTP macaque model of PD, which exhibits pathological changes beyond nigral DA cell loss and α-synucleinopathy.

Mapping microstructural gradients of the human striatum in normal aging and Parkinson's disease

Mapping structural spatial change (i.e., gradients) in the striatum is essential for understanding the function of the basal ganglia in both health and disease. We developed a method to identify and quantify gradients of microstructure in the single human brain in vivo. We found spatial gradients in the putamen and caudate nucleus of the striatum that were robust across individuals, clinical conditions, and datasets. By exploiting multiparametric quantitative MRI, we found distinct, spatially dependent, aging-related alterations in water content and iron concentration. Furthermore, we found cortico-striatal microstructural covariation, showing relations between striatal structural gradients and cortical hierarchy. In Parkinson's disease (PD) patients, we found abnormal gradients in the putamen, revealing changes in the posterior putamen that explain patients' dopaminergic loss and motor dysfunction. Our work provides a noninvasive approach for studying the spatially varying, structure-function relationship in the striatum in vivo, in normal aging and PD.

Combined assessment by transcranial sonography and Sniffin' Sticks test has a similar diagnostic accuracy compared to brain SPECT for Parkinson's disease diagnosis

OBJECTIVES

This study aimed to investigate the accuracy of TCS combined with the Sniffin' sticks olfactory test (SST-16) for differentiation between idiopathic PD patients and healthy controls compared to that of ^99 mTc-TRODAT-1 SPECT (TRODAT).

METHODS

A cross-sectional study included PD patients diagnosed in accordance with United Kingdom PD Society Brain Bank criteria and a control group of age and sex- matched healthy subjects. All patients were examined by a movement disorder specialist and underwent brain SPECT using TRODAT, TCS examination and SST-16 test. Receiver Operating Characteristic (ROC) curves were used to calculate cut-off points for TCS, striatal TRODAT binding potentials and SST-16. The area under the ROC curve determined the diagnostic accuracy of the method.

RESULTS

Twenty patients with PD (13 males and 7 females) and nine healthy subjects were included. Median age of PD onset was 56.5 years with median disease duration of 5 years. A larger substantia nigra (SN) echogenic area was observed in the PD group (p = 0.013). SN echogenic area cut-off point of 0.22 cm² was obtained from a ROC curve for PD diagnosis. Considering this cut-off point, TCS diagnostic accuracy was estimated at 79.2% for PD diagnosis. The cut-off value of 0.90 for striatal TRODAT binding was associated with 99% diagnostic accuracy for the diagnosis of PD. SST-16 values equal or less than 9 points showed an 85.8% diagnostic accuracy for PD diagnosis. Combination of both SST-16 and TCS improved the diagnostic accuracy to 95% for PD diagnosis.

CONCLUSION

Combined SST-16 and TCS assessment was indicated as accurate for distinguishing PD patients from healthy controls. The diagnostic accuracy of TCS combined with SST-16 for differentiation between idiopathic PD patients and healthy controls is similar to that of SPECT TRODAT.

Predictors of RBD progression and conversion to synucleinopathies

Purpose of review

Rapid eye movement (REM) sleep behaviour disorder (RBD) is considered the expression of the initial neurodegenerative process underlying synucleinopathies and constitutes the most important marker of their prodromal phase. This article reviews recent research from longitudinal research studies in isolated RBD (iRBD) aiming to describe the most promising progression biomarkers of iRBD and to delineate the current knowledge on the level of prediction of future outcome in iRBD patients at diagnosis.

Recent findings

Longitudinal studies revealed the potential value of a variety of biomarkers, including clinical markers of motor, autonomic, cognitive, and olfactory symptoms, neurophysiological markers such as REM sleep without atonia and electroencephalography, genetic and epigenetic markers, cerebrospinal fluid and serum markers, and neuroimaging markers to track the progression and predict phenoconversion. To-date the most promising neuroimaging biomarker in iRBD to aid the prediction of phenoconversion is striatal presynaptic striatal dopaminergic dysfunction.

Summary

There is a variety of potential biomarkers for monitoring disease progression and predicting iRBD conversion into synucleinopathies. A combined multimodal biomarker model could offer a more sensitive and specific tool. Further longitudinal studies are warranted to iRBD as a high-risk population for early neuroprotective interventions and disease-modifying therapies.

Biosensor approaches on the diagnosis of neurodegenerative diseases: Sensing the past to the future

Early diagnosis of neurodegeneration-oriented diseases that develop with the aging world is essential for improving the patient's living conditions as well as the treatment of the disease. Alzheimer's and Parkinson's diseases are prominent examples of neurodegeneration characterized by dementia leading to the death of nerve cells. The clinical diagnosis of these diseases only after the symptoms appear, delays the treatment process. Detection of biomarkers, which are distinctive molecules in biological fluids, involved in neurodegeneration processes, has the potential to allow early diagnosis of neurodegenerative diseases. Studies on biosensors, whose main responsibility is to detect the target analyte with high specificity, has gained momentum in recent years with the aim of high detection of potential biomarkers of neurodegeneration process. This study aims to provide an overview of neuro-biosensors developed on the basis of biomarkers identified in biological fluids for the diagnosis of neurodegenerative diseases such as Alzheimer's disease (AD), and Parkinson's disease (PD), and to provide an overview of the urgent needs in this field, emphasizing the importance of early diagnosis in the general lines of the neurodegeneration pathway. In this review, biosensor systems developed for the detection of biomarkers of neurodegenerative diseases, especially in the last 5 years, are discussed.

60 Years of Achievements by KSNM in Neuroimaging Research

Nuclear medicine neuroimaging is able to show functional and molecular biologic abnormalities in various neuropsychiatric diseases. Therefore, it has played important roles in the clinical diagnosis and in research on the normal and pathological states of the brain. More than 400 outstanding studies have been conducted by Korean researchers over the past 60 years. In the 1990s, when multiheaded single-photon emission computed tomography (SPECT) scanners were first introduced in South Korea, stroke research using brain perfusion SPECT was conducted. With the spread of positron emission tomography (PET) scanners in the 2000s, research on the clinical usefulness of PET and the evaluation of pathophysiology in various diseases such as epilepsy, brain tumors, degenerative brain diseases, and other neuropsychiatric diseases were actively conducted using [¹⁸F]FDG and various neuroreceptor tracers. In the 2010s, with the clinical application of new radiopharmaceuticals for amyloid and tau imaging, research demonstrating the clinical usefulness of PET imaging and the pathophysiology of dementia has increased rapidly. It is expected that the role of nuclear medicine will expand with the development of new radiopharmaceuticals and analysis technologies, along with the application of artificial intelligence for early and differential diagnosis, and the development of therapeutic agents for degenerative brain diseases.

HDAC Inhibitors: Innovative Strategies for Their Design and Applications

Histone deacetylases (HDACs) are a large family of epigenetic metalloenzymes that are involved in gene transcription and regulation, cell proliferation, differentiation, migration, and death, as well as angiogenesis. Particularly, disorders of the HDACs expression are linked to the development of many types of cancer and neurodegenerative diseases, making them interesting molecular targets for the design of new efficient drugs and imaging agents that facilitate an early diagnosis of these diseases. Thus, their selective inhibition or degradation are the basis for new therapies. This is supported by the fact that many HDAC inhibitors (HDACis) are currently under clinical research for cancer therapy, and the Food and Drug Administration (FDA) has already approved some of them. In this review, we will focus on the recent advances and latest discoveries of innovative strategies in the development and applications of compounds that demonstrate inhibitory or degradation activity against HDACs, such as PROteolysis-TArgeting Chimeras (PROTACs), tumor-targeted HDACis (e.g., folate conjugates and nanoparticles), and imaging probes (positron emission tomography (PET) and fluorescent ligands).

Recent Developments in Positron Emission Tomography Tracers for Proteinopathies Imaging in Dementia

An early detection and intervention for dementia represent tremendous unmet clinical needs and priorities in society. A shared feature of neurodegenerative diseases causing dementia is the abnormal accumulation and spreading of pathological protein aggregates, which affect the selective vulnerable circuit in a disease-specific pattern. The advancement in positron emission tomography (PET) biomarkers has accelerated the understanding of the disease mechanism and development of therapeutics for Alzheimer's disease and Parkinson's disease. The clinical utility of amyloid-β PET and the clinical validity of tau PET as diagnostic biomarker for Alzheimer's disease continuum have been demonstrated. The inclusion of biomarkers in the diagnostic criteria has introduced a paradigm shift that facilitated the early and differential disease diagnosis and impacted on the clinical management. Application of disease-modifying therapy likely requires screening of patients with molecular evidence of pathological accumulation and monitoring of treatment effect assisted with biomarkers. There is currently still a gap in specific 4-repeat tau imaging probes for 4-repeat tauopathies and α-synuclein imaging probes for Parkinson's disease and dementia with Lewy body. In this review, we focused on recent development in molecular imaging biomarkers for assisting the early diagnosis of proteinopathies (i.e., amyloid-β, tau, and α-synuclein) in dementia and discussed future perspectives.

Identification of blood-based biomarkers for diagnosis and prognosis of Parkinson's disease: A systematic review of proteomics studies

Parkinson's Disease (PD), a neurodegenerative disorder, is characterised by the loss of motor function and dopamine neurons. Therapeutic avenues remain a challenge due to lack of accuracy in early diagnosis, monitoring of disease progression and limited therapeutic options. Proteomic platforms have been utilised to discover biomarkers for numerous diseases, a tool that may benefit the diagnosis and monitoring of disease progression in PD patients. Therefore, this systematic review focuses on analysing blood-based candidate biomarkers (CB) identified via proteomics platforms for PD. This study systematically reviewed articles across six databases (EMBASE, Cochrane, Ovid Medline, Scopus, Science Direct and PubMed) published between 2010 and 2020. Of the 504 articles identified, 12 controlled-PD studies were selected for further analysis. A total of 115 candidate biomarkers (CB) were identified across selected 12-controlled studies, of which 23 CB were found to be replicable in more than two cohorts. Using the PANTHER Go-Slim classification system and STRING network, the gene function and protein interactions between biomarkers were analysed. Our analysis highlights Apolipoprotein A-I (ApoA-I), which is essential in lipid metabolism, oxidative stress, and neuroprotection demonstrates high replicability across five cohorts with consistent downregulation across four cohorts. Since ApoA-I was highly replicable across blood fractions, proteomic platforms and continents, its relationship with cholesterol, statin and oxidative stress as PD biomarker, its role in the pathogenesis of PD is discussed in this paper. The present study identified ApoA-I as a potential biomarker via proteomics analysis of PD for the early diagnosis and prediction of disease progression.

Advances in clinical basic research: Performance, treatments, and mechanisms of Parkinson disease

The loss of neuronal in the substantia nigra of the elderly contributes to striatal damage and plays a critical part in the common forms of neurodegenerative diseases such as Parkinson disease (PD). The deficit of dopamine is one of the most familiar neuropathological features of PD as well as α-Synuclein aggregation. The peripheral autonomic nervous system is also affected negatively during the course of the disease, although the subsistent of dyskinesias and else major motor characteristic deficits take significant role in the diagnostic methods during clinical practice, which is related to a number of non-motor symptoms that might increase aggregate risks. Multiple pathways and mechanisms are involved in the molecular pathogenesis: α-Synuclein, neuronal homeostasis, mitochondrial function, oxidative stress, as well as neuroinflammation. Investigations in the last few years for diagnostic biomarkers used neuroimaging, including single photon emission computed tomography  as well as cutting-edge magnetic resonance imaging techniques, which has been presented to facilitate discrepant diagnosis. Pharmacological treatment is also important and efficient in equal measure. In addition to reliance on striatal dopamine replacement therapy, many solutions that are used for motor or nonmotor symptoms in these patients are available.

A multi-scanner neuroimaging data harmonization using RAVEL and ComBat

Modern neuroimaging studies frequently combine data collected from multiple scanners and experimental conditions. Such data often contain substantial technical variability associated with image intensity scale (image intensity scales are not the same in different images) and scanner effects (images obtained from different scanners contain substantial technical biases). Here we evaluate and compare results of data analysis methods without any data transformation (RAW), with intensity normalization using RAVEL, with regional harmonization methods using ComBat, and a combination of RAVEL and ComBat. Methods are evaluated on a unique sample of 16 study participants who were scanned on both 1.5T and 3T scanners a few months apart. Neuroradiological evaluation was conducted for 7 different regions of interest (ROI’s) pertinent to Alzheimer’s disease (AD). Cortical measures and results indicate that: (1) RAVEL substantially improved the reproducibility of image intensities; (2) ComBat is preferred over RAVEL and the RAVEL-ComBat combination in terms of regional level harmonization due to more consistent harmonization across subjects and image-derived measures; (3) RAVEL and ComBat substantially reduced bias compared to analysis of RAW images, but RAVEL also resulted in larger variance; and (4) the larger root mean square deviation (RMSD) of RAVEL compared to ComBat is due mainly to its larger variance.

Enantiomeric purity deviations of radiolabelled amino acids obtained from chiral columns

Enantiomeric purity (EP) is an important value which denotes the relative percentage of the L-isomer with respect to the D-isomer. For 11C and 18F-labelled amino acid (AA) radiopharmaceutical (RP) production, EP represents a quality control parameter specified in European and national monographs for particular RPs. In most instances, EP value of greater then 90 or 95% (depending on AA type) is required as part of the quality control (QC) value of a RP following radiosynthesis. In common practice, two chromatographic columns are used for the EP determination of RPs: Crownpak CR(+) (Daicel), which contains a crown ether stationary phase or Chirobiotic T (Astec), which contains silica-bound glycoproteins as the stationary phase. The application of column Crownpak CR(+) requires that only perchloric acid solution (with pH 1–2) may be used, as the retention capability of the stationary phase is greatly reduced using organic solvents. This work intends to identify which chromatographic system is more accurate and reliable for EP determination as part of QC. We performed a series of parallel injections of the same batch of the widely used AA RPs [11C]MET and [18F]FET on the two aforementioned columns. The EP determination using column Crownpak CR(+) consistently provided a lower EP value compared to the Chirobiotic T column; the EP deviation between the respective columns was found to range from 2.4–4.0% for the same RP sample. Furthermore, the EP value was influenced by a sample’s dilution factor, e.g. the EP was observed to increase up to 1.5% when the radioactive sample had a fivefold dilution factor. This phenomenon was consistent for both Crownpak CR(+) and Chirobiotic T columns. Finally, a series of standard solutions of non-radioactive methionine with various ratios of L-and D-isomers was analyzed. The data obtained for non-radioactive methionine confirmed that column Crownpak CR(+) incorrectly provided a higher D-enantiomer concentration, whereas Chirobiotic T was found to provide a lower D-enantiomer concentration of the same sample. The deviation from the theoretical EP value was between 0.67 and 1.92%.

Cortical Serotonergic and Catecholaminergic Denervation in MPTP-Treated Parkinsonian Monkeys

Decreased cortical serotonergic and catecholaminergic innervation of the frontal cortex has been reported at early stages of Parkinson's disease (PD). However, the limited availability of animal models that exhibit these pathological features has hampered our understanding of the functional significance of these changes during the course of the disease. In the present study, we assessed longitudinal changes in cortical serotonin and catecholamine innervation in motor-symptomatic and asymptomatic monkeys chronically treated with low doses of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Densitometry and unbiased stereological techniques were used to quantify changes in serotonin and tyrosine hydroxylase (TH) immunoreactivity in frontal cortices of 3 control monkeys and 3 groups of MPTP-treated monkeys (motor-asymptomatic [N = 2], mild parkinsonian [N = 3], and moderate parkinsonian [N = 3]). Our findings revealed a significant decrease (P < 0.001) in serotonin innervation of motor (Areas 4 and 6), dorsolateral prefrontal (Areas 9 and 46), and limbic (Areas 24 and 25) cortical areas in motor-asymptomatic MPTP-treated monkeys. Both groups of symptomatic MPTP-treated animals displayed further serotonin denervation in these cortical regions (P < 0.0001). A significant loss of serotonin-positive dorsal raphe neurons was found in the moderate parkinsonian group. On the other hand, the intensity of cortical TH immunostaining was not significantly affected in motor asymptomatic MPTP-treated monkeys, but underwent a significant reduction in the moderate symptomatic group (P < 0.05). Our results indicate that chronic intoxication with MPTP induces early pathology in the corticopetal serotonergic system, which may contribute to early non-motor symptoms in PD.

In-flow electrochemical detection of chemicals in droplets with pyrolysed photoresist electrodes: application as a module for quantification of microsampled dopamine

The electrochemical quantification of analytes in droplets of PBS separated by a fluorinated phase was investigated. PDMS-fused silica chips with pyrolysed photoresist electrodes were prepared using a simple fabrication technique and used to analyze droplets in flow. Potentiostatic chronoamperometry provided current readouts consistent with mass transport and the concentration inside the droplets. This paper highlights measurements of dopamine in droplets in T-junction microfluidic chips at unprecedently low concentrations, with a limit of detection of 207 nM and a linear range of 0.21-20 μM, giving results similar to continuous flow electrochemistry and allowing the analysis in the striatal extracellular range (<1 μM). The system was applied to the quick and reliable on-line detection of dopamine concentration steps in droplets collected with a microsampling probe in vitro, demonstrating the usefulness of the electrochemical device as a quantification module for microsampled chemicals in droplets.

The translocator protein (TSPO) is prodromal to mitophagy loss in neurotoxicity

Dysfunctional mitochondria characterise Parkinson's Disease (PD). Uncovering etiological molecules, which harm the homeostasis of mitochondria in response to pathological cues, is therefore pivotal to inform early diagnosis and therapy in the condition, especially in its idiopathic forms. This study proposes the 18 kDa Translocator Protein (TSPO) to be one of those. Both in vitro and in vivo data show that neurotoxins, which phenotypically mimic PD, increase TSPO to enhance cellular redox-stress, susceptibility to dopamine-induced cell death, and repression of ubiquitin-dependent mitophagy. TSPO amplifies the extracellular signal-regulated protein kinase 1 and 2 (ERK1/2) signalling, forming positive feedback, which represses the transcription factor EB (TFEB) and the controlled production of lysosomes. Finally, genetic variances in the transcriptome confirm that TSPO is required to alter the autophagy-lysosomal pathway during neurotoxicity.

Nanomedicine against Alzheimer's and Parkinson's Disease

Alzheimer's and Parkinson's are the two most rampant neurodegenerative disorders worldwide. Existing treatments have a limited effect on the pathophysiology but are unable to fully arrest the progression of the disease. This is due to the inability of these therapeutic molecules to efficiently cross the blood-brain barrier. We discuss how nanotechnology has enabled researchers to develop novel and efficient nano-therapeutics against these diseases. The development of nanotized drug delivery systems has permitted an efficient, site-targeted, and controlled release of drugs in the brain, thereby presenting a revolutionary therapeutic approach. Nanoparticles are also being thoroughly studied and exploited for their role in the efficient and precise diagnosis of neurodegenerative conditions. We summarize the role of different nano-carriers and RNAi-conjugated nanoparticle-based therapeutics for their efficacy in pre-clinical studies. We also discuss the challenges underlying the use of nanomedicine with a focus on their route of administration, concentration, metabolism, and any toxic effects for successful therapeutics in these diseases.

Novel targeted therapies for Parkinson's disease

Parkinson’s disease (PD) is the second more common neurodegenerative disease with increasing incidence worldwide associated to the population ageing. Despite increasing awareness and significant research advancements, treatment options comprise dopamine repleting, symptomatic therapies that have significantly increased quality of life and life expectancy, but no therapies that halt or reverse disease progression, which remain a great, unmet goal in PD research. Large biomarker development programs are undertaken to identify disease signatures that will improve patient selection and outcome measures in clinical trials. In this review, we summarize PD-related mechanisms that can serve as targets of therapeutic interventions aiming to slow or modify disease progression, as well as previous and ongoing clinical trials in each field, and discuss future perspectives.

A Role of PET/MR Imaging in Dementia?

Since many years, magnetic resonance imaging (MRI) and positron emission tomography (PET) have a prominent role in neurodegenerative disorders and dementia, not only in a research setting but also in a clinical setting. For several decades, information from both modalities is combined ranging from individual visual assessments to fully integrating all images. Several tools are available to coregister images from MRI and PET and to covisualize these images. When studying neurodegenerative disorders with PET it is important to perform a partial volume correction and this can be done using the structural information obtained by MRI. With the advent of PET/MR, the question arises in how far this hybrid imaging modality is an added value compared to combining PET and MRI data from two separate modalities. One issue in PET/MR is still not yet completely settled, that is, the attenuation correction. This is of less importance for visual assessments but it can become an issue when combining data from PET/CT and PET/MR scanners in multicenter studies or when using cut-off values to classify patients. Simultaneous imaging has clearly some advantages: for the patient it is beneficial to have only one scan session instead of two but also in cases in which PET data are related to functional of physiological data acquired with MRI (such as functional MRI or arterial spin labeling). However, the most important benefit is currently the more integrated use of PET and MRI. This is also possible with separate measurements but requires more streamlining of the whole process. In that case coregistration of images is mandatory. It needs to be determined in which cases simultaneous PET/MRI leads to new insights or improved diagnosis compared to multimodal imaging using dedicated scanners.