The importance of preclinical diagnostics in Parkinson disease

Role of Peroxynitrite in the Pathogenesis of Parkinson's Disease and Its Fluorescence Imaging-Based Detection

Parkinson's disease (PD) is the second most common neurodegenerative disorder, affecting the lives of millions of people worldwide. Although the mechanism underlying PD pathogenesis is largely undefined, increasing evidence indicates that oxidative and nitrosative stresses play a crucial role in PD occurrence and development. Among them, the role of oxidative stress has been widely acknowledged, but there is relatively less attention given to nitrosative stress, which is mainly derived from peroxynitrite. In the present review, after briefly introducing the background of PD, we discuss the physiopathological function of peroxynitrite and especially highlight how overloaded peroxynitrite is involved in PD pathogenesis. Then, we summarize the currently reported fluorescence imaging-based peroxynitrite detection probes. Moreover, we specifically emphasize the probes that have been applied in PD research. Finally, we propose perspectives on how to develop a more applicable peroxynitrite probe and leverage it for PD theranostics. Conclusively, the present review broadens the knowledge on the pathological role of peroxynitrite in the context of PD and sheds light on how to develop and utilize fluorescence imaging-based strategies for peroxynitrite detection.

PD-ARnet: a deep learning approach for Parkinson's disease diagnosis from resting-state fMRI

Objective. The clinical diagnosis of Parkinson's disease (PD) relying on medical history, clinical symptoms, and signs is subjective and lacks sensitivity. Resting-state fMRI (rs-fMRI) has been demonstrated to be an effective biomarker for diagnosing PD.Approach.This study proposes a deep learning approach for the automatic diagnosis of PD using rs-fMRI, named PD-ARnet. Specifically, PD-ARnet utilizes Amplitude of Low Frequency Fluctuations and Regional Homogeneity extracted from rs-fMRI as inputs. The inputs are then processed through a developed dual-branch 3D feature extractor to perform advanced feature extraction. During this process, a Correlation-Driven weighting module is applied to capture complementary information from both features. Subsequently, the Attention-Enhanced fusion module is developed to effectively merge two types of features, and the fused features are input into a fully connected layer for automatic diagnosis classification.Main results.Using 145 samples from the PPMI dataset to evaluate the detection performance of PD-ARnet, the results indicated an average classification accuracy of 91.6% (95% confidence interval [CI]: 90.9%, 92.4%), precision of 94.7% (95% CI: 94.2%, 95.1%), recall of 86.2% (95% CI: 84.9%, 87.4%), F1 score of 90.2% (95% CI: 89.3%, 91.1%), and AUC of 92.8% (95% CI: 91.1%, 95.0%).Significance.The proposed method has the potential to become a clinical auxiliary diagnostic tool for PD, reducing subjectivity in the diagnostic process, and enhancing diagnostic efficiency and consistency.

Sleep deprivation induces late deleterious effects in a pharmacological model of Parkinsonism

Parkinson's disease is a degenerative, chronic and progressive disease, characterized by motor dysfunctions. Patients also exhibit non-motor symptoms, such as affective and sleep disorders. Sleep disorders can potentiate clinical and neuropathological features and lead to worse prognosis. The goal of this study was to evaluate the effects of sleep deprivation (SD) in mice submitted to a progressive pharmacological model of Parkinsonism (chronic administration with a low dose of reserpine). Male Swiss mice received 20 injections of reserpine (0.1 mg/kg) or vehicle, on alternate days. SD was applied before or during reserpine treatment and was performed by gentle handling for 6 h per day for 10 consecutive days. Animals were submitted to motor and non-motor behavioral assessments and neurochemical evaluations. Locomotion was increased by SD and decreased by reserpine treatment. SD during treatment delayed the onset of catalepsy, but SD prior to treatment potentiated reserpine-induced catalepsy. Thus, although SD induced an apparent beneficial effect on motor parameters, a delayed deleterious effect on alterations induced by reserpine was found. In the object recognition test, both SD and reserpine treatment produced cognitive deficits. In addition, the association between SD and reserpine induced anhedonic-like behavior. Finally, an increase in oxidative stress was found in hippocampus of mice subjected to SD, and tyrosine hydroxylase immunoreactivity was reduced in substantia nigra of reserpine-treated animals. Results point to a possible late effect of SD, aggravating the deficits in mice submitted to the reserpine progressive model of PD.

Parkinson's severity diagnosis explainable model based on 3D multi-head attention residual network

The severity evaluation of Parkinson's disease (PD) is of great significance for the treatment of PD. However, existing methods either have limitations based on prior knowledge or are invasive methods. To propose a more generalized severity evaluation model, this paper proposes an explainable 3D multi-head attention residual convolution network. First, we introduce the 3D attention-based convolution layer to extract video features. Second, features will be fed into LSTM and residual backbone networks, which can be used to capture the contextual information of the video. Finally, we design a feature compression module to condense the learned contextual features. We develop some interpretable experiments to better explain this black-box model so that it can be better generalized. Experiments show that our model can achieve state-of-the-art diagnosis performance. The proposed lightweight but effective model is expected to serve as a suitable end-to-end deep learning baseline in future research on PD video-based severity evaluation and has the potential for large-scale application in PD telemedicine. The source code is available at https://github.com/JackAILab/MARNet.

The pyroptosis mediated biomarker pattern: an emerging diagnostic approach for Parkinson's disease

BACKGROUND

Parkinson's disease (PD) affects 1% of people over 60, and long-term levodopa treatment can cause side effects. Early diagnosis is of great significance in slowing down the pathological process of PD. Multiple pieces of evidence showed that non-coding RNAs (ncRNAs) could participate in the progression of PD pathology. Pyroptosis is known to be regulated by ncRNAs as a key pathological feature of PD. Therefore, evaluating ncRNAs and pyroptosis-related proteins in serum could be worthy biomarkers for early diagnosis of PD.

METHODS

NcRNAs and pyroptosis/inflammation mRNA levels were measured with reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). Luciferase assays were performed to confirm GSDME as a target of miR-675-5p and HMGB1 as a target of miR-1247-5p. In the serum of healthy controls (n = 106) and PD patients (n = 104), RT-qPCR was utilized to assess miR-675-5p, miR-1247-5p, and two related ncRNAs (circSLC8A1and lncH19) levels. The enzyme-linked immunosorbent assay measured serum levels of pyroptosis-related proteins in controls (n = 54) and PD patients (n = 70).

RESULTS

Our data demonstrated that miR-675-5p and miR-1247-5p significantly changed in PD neuron and animal models. Overexpressed miR-675-5p or downregulated miR-1247-5p could regulate pyroptosis and inflammation in PD neuron models. Using the random forest algorithm, we constructed a classifier based on PD neuron-pyroptosis pathology (four ncRNAs and six proteins) having better predictive power than single biomarkers (AUC = 92%). Additionally, we verified the performance of the classifier in early-stage PD patients (AUC ≥ 88%).

CONCLUSION

Serum pyroptosis-related ncRNAs and proteins could serve as reliable, inexpensive, and non-invasive diagnostic biomarkers for PD.

LIMITATIONS

All participants were from the same region. Additionally, longitudinal studies in the aged population are required to explore the practical application value of the classifier.

Automated Capillary Electrophoresis Immunoblot for the Detection of Alpha-Synuclein in Mouse Tissue

Background

Alpha-synuclein (aSyn) is a key player in neurodegenerative diseases such as Parkinson's disease (PD), dementia with Lewy bodies, or multiple system atrophy. aSyn is expressed throughout the brain, and can also be detected in various peripheral tissues. In fact, initial symptoms of PD are non-motoric and include autonomic dysfunction, suggesting that the periphery might play an important role in early development of the disease. aSyn is expressed at relatively low levels in non-central tissues, which brings challenges for its detection and quantification in different tissues.

Objective

Our goal was to assess the sensitivity of aSyn detection in central and peripheral mouse tissues through capillary electrophoresis (CE) immunoblot, considering the traditional SDS-PAGE immunoblot as the current standard.

Methods

Tissues from central and non-central origin from wild type mice were extracted, and included midbrain, inner ear, and esophagus/stomach. aSyn detection was assessed through immunoblotting using Simple Western size-based CE and SDS-PAGE.

Results

CE immunoblots show a consistent detection of aSyn in central and peripheral tissues. Through SDS-PAGE, immunoblots revealed a reliable signal corresponding to aSyn, particularly following membrane fixation.

Conclusion

Our results suggest a reliable detection of aSyn in central and peripheral tissues using the CE Simple Western immunoblot system. These observations can serve as preliminary datasets when aiming to formally compare CE with SDS-PAGE, as well as for further characterization of aSyn using this technique.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Developing a Staging Scheme for Essential Tremor: A Discussion of Organizing Principles

Essential tremor (ET) is a chronic, progressive neurological disease that may negatively affect patients' lives. While there has been considerable progress in ET research, some fundamental issues remain unaddressed. One such issue is disease staging. Staging schemes have inherent value and are part of the dialogue that clinicians have with other movement disorders patients. We highlight the value of and challenges with developing a staging system for ET and organize a discussion around the potential steps in developing such a system. Diseases for which there are staging schemes generally have a number of shared characteristics. ET has numerous features that would lend themselves to a staging scheme: emerging evidence supporting the existence of a premotor phase of disease, insidious onset, progressive worsening of arm tremor, spread of tremor to other body regions, the observation that patients seem to be at increased risk for other conditions within the same organ (i.e., emergence of Parkinson's disease and Alzheimer's disease in excessive numbers of ET patients), pathological changes in the cerebellum whose evolution can be ordered from (i) those that compromise the physical integrity and physiological function of Purkinje cells, (ii) subsequent changes that are reparative and regenerative, and (iii) eventual cell death. Challenges to formulating a staging scheme are the absence of both a biological marker and an "end stage" of disease. The sum of combined evidence suggests that a staging scheme would be of value. We provide initial thoughts as to how to begin to structure such a staging scheme.

Cardiac 123I-Metaiodobenzylguanidine (MIBG) Scintigraphy in Parkinson's Disease: A Comprehensive Review

Cardiac sympathetic denervation, as documented on 123I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy, is relatively sensitive and specific for distinguishing Parkinson's disease (PD) from other neurodegenerative causes of parkinsonism. The present study aims to comprehensively review the literature regarding the use of cardiac MIBG in PD. MIBG is an analog to norepinephrine. They share the same uptake, storage, and release mechanisms. An abnormal result in the cardiac MIBG uptake in individuals with parkinsonism can be an additional criterion for diagnosing PD. However, a normal result of cardiac MIBG in individuals with suspicious parkinsonian syndrome does not exclude the diagnosis of PD. The findings of cardiac MIBG studies contributed to elucidating the pathophysiology of PD. We investigated the sensitivity and specificity of cardiac MIBG scintigraphy in PD. A total of 54 studies with 3114 individuals diagnosed with PD were included. The data were described as means with a Hoehn and Yahr stage of 2.5 and early and delayed registration H/M ratios of 1.70 and 1.51, respectively. The mean cutoff for the early and delayed phases were 1.89 and 1.86. The sensitivity for the early and delayed phases was 0.81 and 0.83, respectively. The specificity for the early and delayed phases were 0.86 and 0.80, respectively.

An investigation of neuromelanin distribution in substantia nigra and locus coeruleus in patients with Parkinson's disease using neuromelanin-sensitive MRI

Loss of neuromelanin in the midbrain is known in Parkinson's disease(PD), which can now be directly detected by neuromelanin-sensitive MRI(NM-MRI). This case-control study was to investigate the distribution of neuromelanin in the substantia nigra(SN) and the locus coeruleus(LC) using NM-MRI technique and evaluate its potential as a diagnostic marker for PD. 10 early PD patients(H&Y stage I, II), 11 progressive PD patients(H&Y stage III-V), and 10 healthy controls matched in age and gender were recruited. All participants completed clinical and psychometric assessments as well as NM-MRI scans. Neuromelanin signal intensities in SN and LC were measured by contrast-to-noise ratios(CNRs) derived from NM-MRI scans. There were significant decreases of CNRs in SNpc(including anterior, central, and posterior) and LC in PD patients compared to controls. There were also significant differences of CNR between the left and right sides. CNR in LC had a negative correlation with the Non-Motor Symptoms Scale(NMSS) score in PD patients(|R|=0.49), whereas CNR in SNpc did not correlate with Unified Parkinson Disease Rating Scale(UPDRS) score(|R|<0.3). The receiver operating characteristic(ROC) curves revealed that the CNR in LC had a high diagnostic specificity of 90.1% in progressive patients. This study provides new evidence for the asymmetric distribution of neuromelanin in SN and the LC of patients with PD. The neuromelanin loss is bilateral and more predominately in LC than that in SN. This distinct neuromelanin distribution pattern may offer a potential diagnostic marker and a potential neuropharmacological intervention target for PD patients.

Early approaches of YKL-40 as a biomarker and therapeutic target for Parkinson's disease

Aim: To investigate whether the estimation of cerebrospinal fluid (CSF) and brain YKL-40 levels may be used as an efficient biomarker for Parkinson's disease (PD). Methods: Lipopolysaccharides (LPS) was injected into the right substantia nigra pars compacta (SNpc). Rats were divided into: control group, early LPS-induced PD group (14 days), and advanced LPS-induced PD group (28 days). YKL-40 and other related factors were detected in CSF and brain tissue. Results: Increased expression of YKL-40 was observed in brain tissue and CSF of PD-induced rats associated with triggered inflammatory cytokine release. Conclusion: The current study was limited to detecting YKL-40 and other inflammatory factors in brain and CSF. YKL-40 may be considered as an early biomarker and therapeutic target for PD.

Multilingual evaluation of interpretable biomarkers to represent language and speech patterns in Parkinson's disease

Motor impairments are only one aspect of Parkinson's disease (PD), which also include cognitive and linguistic impairments. Speech-derived interpretable biomarkers may help clinicians diagnose PD at earlier stages and monitor the disorder's evolution over time. This study focuses on the multilingual evaluation of a composite array of biomarkers that facilitate PD evaluation from speech. Hypokinetic dysarthria, a motor speech disorder associated with PD, has been extensively analyzed in previously published studies on automatic PD evaluation, with a relative lack of inquiry into language and task variability. In this study, we explore certain acoustic, linguistic, and cognitive information encoded within the speech of several cohorts with PD. A total of 24 biomarkers were analyzed from American English, Italian, Castilian Spanish, Colombian Spanish, German, and Czech by conducting a statistical analysis to evaluate which biomarkers best differentiate people with PD from healthy participants. The study leverages conceptual robustness as a criterion in which a biomarker behaves the same, independent of the language. Hence, we propose a set of speech-based biomarkers that can effectively help evaluate PD while being language-independent. In short, the best acoustic and cognitive biomarkers permitting discrimination between experimental groups across languages were fundamental frequency standard deviation, pause time, pause percentage, silence duration, and speech rhythm standard deviation. Linguistic biomarkers representing the length of the narratives and the number of nouns and auxiliaries also provided discrimination between groups. Altogether, in addition to being significant, these biomarkers satisfied the robustness requirements.

Proof of Concept in Artificial-Intelligence-Based Wearable Gait Monitoring for Parkinson's Disease Management Optimization

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder, affecting 6.2 million patients and causing disability and decreased quality of life. The research is oriented nowadays toward artificial intelligence (AI)-based wearables for early diagnosis and long-term PD monitoring. Our primary objective is the monitoring and assessment of gait in PD patients. We propose a wearable physiograph for qualitative and quantitative gait assessment, which performs bilateral tracking of the foot biomechanics and unilateral tracking of arm balance. Gait patterns are assessed by means of correlation. The surface plot of a correlation coefficient matrix, generated from the recorded signals, is classified using convolutional neural networks into physiological or PD-specific gait. The novelty is given by the proposed AI-based decisional support procedure for gait assessment. A proof of concept of the proposed physiograph is validated in a clinical environment on five patients and five healthy controls, proving to be a feasible solution for ubiquitous gait monitoring and assessment in PD. PD management demonstrates the complexity of the human body. A platform empowering multidisciplinary, AI-evidence-based decision support assessments for optimal dosing between drug and non-drug therapy could lay the foundation for affordable precision medicine.

The Disease Modification Conundrum in Parkinson’s Disease: Failures and Hopes

In the last half-century, Parkinson’s disease (PD) has played a historical role in demonstrating our ability to translate preclinical scientific advances in pathology and pharmacology into highly effective clinical therapies. Yet, as highly efficacious symptomatic treatments were successfully developed and adopted in clinical practice, PD remained a progressive disease without a cure. In contrast with the success story of symptomatic therapies, the lack of translation of disease-modifying interventions effective in preclinical models into clinical success has continued to accumulate failures in the past two decades. The ability to stop, prevent or mitigate progression in PD remains the “holy grail” in PD science at the present time. The large number of high-quality disease modification clinical trials in the past two decades with its lessons learned, as well as the growing knowledge of PD molecular pathology should enable us to have a deeper understanding of the reasons for past failures and what we need to do to reach better outcomes. Periodic reviews and mini-reviews of the unsolved disease modification conundrum in PD are important, considering how this field is rapidly evolving along with our views and understanding of the possible explanations.

Wrist-based accelerometer cut-points for quantifying moderate-to-vigorous intensity physical activity in Parkinson's disease

BACKGROUND

Persons with Parkinson's disease (PD) participate in low levels of physical activity. This has prompted interest in developing interventions targeting physical activity behavior in PD. However, the current cut-points to quantify moderate-to-vigorous physical activity (MVPA) developed for PD have been derived from a single, vertical axis using hip-worn accelerometers, and this cut-point may not be applicable for wrist-worn devices. Wrist-worn devices might improve accessibility and compliance with physical activity monitoring in PD.

RESEARCH QUESTION

What is the relationship between wrist-based activity counts and energy expenditure during treadmill walking in persons with PD? Do cut-points for quantifying time spent in MVPA differ between persons with PD and controls matched by age and sex?

METHODS

The sample included 26 persons with mild-to-moderate PD (Hoehn and Yahr stages 2-3) and 27 age- and sex-matched controls. Participants completed three, 6-minute bouts of walking on a treadmill at three increasing speeds. Vector magnitude was measured using ActiGraph GT3X+ accelerometer worn on the more affected side for persons with PD and the non-dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system.

RESULTS

Our results indicated a strong association between activity counts and energy expenditure for persons with PD and controls with R2 values of 0.94(0.07) and 0.95(0.06), respectively. Persons with PD had a cut-point of 2883(871) counts·min-1; this was significantly lower than the cut-point of 4389(1844) counts·min-1 for controls.

CONCLUSION

We generated a PD-specific cut-point for wrist-worn ActiGraph accelerometers among persons with PD, and this was lower than controls. This disease-specific cut-point may provide more accurate measurements of time spent in MVPA in PD.

Comprehensive Serum Lipidomics for Detecting Incipient Dementia in Parkinson's Disease

While a number of methods are available for analyzing lipids, unbiased untargeted lipidomics with high coverage remains a challenge. In this work, we report a study of isotope-standard-assisted liquid chromatography mass spectrometry lipidomics of serum for biomarker discovery. We focus on Parkinson's disease (PD), a neurodegenerative disorder that often progresses to dementia. Currently, the diagnosis of PD is purely clinical and there is limited ability to predict which PD patients will transition to dementia, hampering early interventions. We studied serum samples from healthy controls and PD patients with no clinical signs of dementia. A follow-up 3 years later revealed that a subset of PD patients had transitioned to dementia. Using the baseline samples, we constructed two biomarker panels to differentiate (1) PD patients from healthy controls and (2) PD patients that remained cognitively stable from PD patients with incipient dementia (diagnosed 3 years after sample collection). The proposed biomarker panels displayed excellent performance and may be useful for detecting prodromal PD dementia, allowing early interventions and prevention efforts. The biochemistry of significantly changed lipids is also discussed within the current knowledge of neurological pathologies. Our results are promising and future work using a larger cohort of samples is warranted.

Probing the Pre-diagnostic Phase of Parkinson's Disease in Population-Based Studies

Parkinson's disease covers a wide spectrum of symptoms, ranging from early non-motor symptoms to the characteristic bradykinesia, tremor and rigidity. Although differences in the symptomatology of Parkinson's disease are increasingly recognized, there is still a lack of insight into the heterogeneity of the pre-diagnostic phase of Parkinson's disease. In this perspective, we highlight three aspects regarding the role of population-based studies in providing new insights into the heterogeneity of pre-diagnostic Parkinson's disease. First we describe several specific advantages of population-based cohort studies, including the design which overcomes some common biases, the broad data collection and the high external validity. Second, we draw a parallel with the field of Alzheimer's disease to provide future directions to uncover the heterogeneity of pre-diagnostic Parkinson's disease. Finally, we anticipate on the emergence of prevention and disease-modification trials and the potential role of population-based studies herein. In the coming years, bridging gaps between study designs will be essential to make vital advances in elucidating the heterogeneity of pre-diagnostic Parkinson's disease.

Self-reported parkinsonism features in older autistic adults: A descriptive study

LAY ABSTRACT

Autistic adults without a suspected intellectual disability reported several motor features such as having tremors, and stiffness in one's legs which are considered to be part of a complex of motor features called parkinsonism. This so-called parkinsonism was remarkably prevalent in middle-aged and older autistic adults in two independent studies (Dutch study: 50-81 years, 183 males, 113 females, all adulthood diagnoses; the USA study: 50-83 years, 110 females, 109 males, majority adulthood diagnosis). Parkinsonism can be part of the progressive motor disease-Parkinson's disease. Therefore, it is important that future studies, including in-person neurological assessment, determine if (and if so, why) autistic adults who report these motor features are at increased risk for developing Parkinson's disease.

Heart Matters: Cardiac Dysfunction and Other Autonomic Changes in Parkinson's Disease

It has been more than 200 years since James Parkinson made the first descriptions of the disease that bears his name. Since then, knowledge about Parkinson's disease has been improved, and its pathophysiology, diagnosis, and treatments are well described in the scientific and medical literature. However, there is no way to prevent the disease from its progressive nature yet and only its symptoms can be minimized. It is known that the process of neurodegeneration begins before the onset of motor signs and symptoms of the disease, when diagnosis is usually made. Therefore, recognizing manifested non-motor symptoms can make an early diagnosis possible and lead to a better understanding of the disease. Autonomic dysfunctions are important non-motor manifestations of Parkinson's disease and affect the majority of patients. Importantly, heart failure is the third leading cause of death in people suffering from Parkinson's disease. Several evidences have shown the correlation between Parkinson's disease and the preexistence of cardiovascular diseases. Therefore, cardiovascular monitoring and identification of its dysfunctions can have a prodromal role for Parkinson's disease. This review presents studies of the literature that can lead to a better understanding of Parkinson's disease with special attention to its relation to heart and cardiovascular parameters.

Inflammatory Mechanisms in Parkinson's Disease: From Pathogenesis to Targeted Therapies

Inflammation is a critical factor contributing to the progressive neurodegenerative process observed in Parkinson's disease (PD). Microglia, the immune cells of the central nervous system, are activated early in PD pathogenesis and can both trigger and propagate early disease processes via innate and adaptive immune mechanisms such as upregulated immune cells and antibody-mediated inflammation. Downstream cytokines and gene regulators such as microRNA (miRNA) coordinate later disease course and mediate disease progression. Biomarkers signifying the inflammatory and neurodegenerative processes at play within the central nervous system are of increasing interest to clinical teams. To be effective, such biomarkers must achieve the highest sensitivity and specificity for predicting PD risk, confirming diagnosis, or monitoring disease severity. The aim of this review was to summarize the current preclinical and clinical evidence that suggests that inflammatory processes contribute to the initiation and progression of neurodegenerative processes in PD. In this article, we further summarize the data about main inflammatory biomarkers described in PD to date and their potential for regulation as a novel target for disease-modifying pharmacological strategies.

Comparison of Three Motor Subtype Classifications in de novo Parkinson's Disease Patients

Objective: The aims of this study were to compare the characteristics of three motor subtype classifications in patients with de novo Parkinson's disease (PD) and to find the most suitable motor subtype classification for identifying non-motor symptoms (NMSs).

Methods: According to previous studies, a total of 256 patients with de novo PD were classified using the tremor-dominant/mixed/akinetic-rigid (TD/mixed/AR), TD/indeterminate/postural instability and gait disturbance (PIGD), and predominantly TD/predominantly PIGD (p-TD/p-PIGD) classification systems.

Results: Among the TD/mixed/AR subgroups, the patients with the AR subtype obtained more severe motor scores than the patients with the TD subtype. Among the TD/indeterminate/PIGD subgroups and between the p-TD and p-PIGD subgroups, the patients with the PIGD/p-PIGD subtype obtained more severe scores related to activities of daily living (ADL), motor and non-motor symptoms, including depression, anxiety, and sleep impairment, than the patients with the TD/p-TD subtype. Furthermore, symptoms in the cardiovascular, gastrointestinal, and miscellaneous domains of the Non-motor Questionnaire (NMSQuest) were more prevalent in the patients with the PIGD/p-PIGD subtypes than the patients with the TD/p-TD subtypes.

Conclusions: The PIGD/p-PIGD subtypes had more severe ADL, motor and non-motor symptoms than the TD/p-TD subtypes. We disclosed for the first time that the TD/indeterminate/PIGD classification seems to be the most suitable classification among the three motor subtype classifications for identifying NMSs in PD.

Patterns of olfactory dysfunctions in patients with Parkinson disease

Background

Olfactory dysfunction (OD) is a well-established nonmotor manifestations (NMM) of Parkinson disease (PD) which needs objective assessment for better understanding of the disease pathogenesis. The aim of this work was quantitative and qualitative assessment of olfactory performance in newly diagnosed PD patients.

Methods

This study was performed on 32 recently diagnosed PD patients and 24 healthy controls subjects (HCS) submitted to unified Parkinson’s disease rating scale–III (UPDRS–III), extended n-butanol Sniffin’ Sticks test (SST) and olfactory bulbs volumetry (OBV).

Results

There were significant decreases in SST threshold, discrimination, identification, and TDI variables as well as OBV in PD patients compared to HCS. The olfactory performance was negatively correlated with disease duration but had no relation with PD severity as well as motor subtype.

Conclusion

OD is highly prevalent during the early stages of PD which is both measurable and specific with identification and discrimination impairments to certain odors which makes smell performance testing an important step in PD patients’ evaluation.

Olfactory dysfunction in essential tremor versus tremor dominant Parkinson disease

BACKGROUND

Essential tremor (ET) and tremor dominant Parkinson disease (TDPD) variant constitute the main causes of geriatric tremor which differentiation is not always an easy mission. The objective of this work was to study the olfactory performance in ET and PD patients for possible consideration as a differentiating biomarker.

METHODS

This study was performed on 36ET, 22 TDPD variant and 24 healthy controls subjects (HCS) submitted to extended n-butanol Sniffin' Sticks test (SST) and olfactory bulbs volumetry (OBV).

RESULTS

There were significant decreases in SST threshold, discrimination, identification and TDI variables in TDPD patients compared to ET and HCS. ET patients showed significant decrease in the same variables compared to HCS. Regarding OBV, there were significant decreases in TDPD patients compared to ET and HCS with nonsignificant difference between the 2-latter groups. Our results showed that TDI score of 25 can differentiate between TDPD and ET patients with sensitivity and specificity (94 %, 91 %) respectively.

CONCLUSION

Olfactory assessment is a rapid, safe, and easily applicable biomarker that could differentiate TDPD from ET in doubtful cases.

Changes in Day/Night Activity in the 6-OHDA-Induced Experimental Model of Parkinson's Disease: Exploring Prodromal Biomarkers

The search for experimental models mimicking an early stage of Parkinson's disease (PD) before motor manifestations is fundamental in order to explore early signs and get a better prognosis. Interestingly, our previous studies have indicated that 6-hydroxydopamine (6-OHDA) is a suitable model to induce an early degeneration of the nigrostriatal system without any gross motor impairment. Considering our previous findings, we aim to implement a novel system to monitor rats after intrastriatal injection of 6-OHDA to detect and analyze physiological changes underlying prodromal PD. Twenty male Sprague-Dawley rats were unilaterally injected with 6-OHDA (n = 10) or saline solution (n = 10) into the right striatum and placed in enriched environment cages where the activity was monitored. After 2 weeks, the amphetamine test was performed before the sacrifice. Immunohistochemistry was developed for the morphological evaluation and western blot analysis to assess molecular changes. Home-cage monitoring revealed behavioral changes in response to 6-OHDA administration including significant hyperactivity and hypoactivity during the light and dark phase, respectively, turning out in a change of the circadian timing. A preclinical stage of PD was functionally confirmed with the amphetamine test. Moreover, the loss of tyrosine hydroxylase expression was significantly correlated with the motor results, and 6-OHDA induced early proapoptotic events. Our findings provide evidence for a novel prodromal 6-OHDA model following a customized monitoring system that could give insights to detect non-motor deficits and molecular targets to test neuroprotective/neurorestorative agents.

Calcium, Bioenergetics, and Parkinson's Disease

Degeneration of substantia nigra (SN) dopaminergic (DAergic) neurons is responsible for the core motor deficits of Parkinson’s disease (PD). These neurons are autonomous pacemakers that have large cytosolic Ca²⁺ oscillations that have been linked to basal mitochondrial oxidant stress and turnover. This review explores the origin of Ca²⁺ oscillations and their role in the control of mitochondrial respiration, bioenergetics, and mitochondrial oxidant stress.

Late-life falling and depressive symptoms associated with the risk of Parkinson's disease: a nationwide cohort data analysis

BACKGROUND

This study aimed to evaluate the relationship between the history of late-life falling and the development of Parkinson's disease (PD) and investigate whether depressive symptoms interact with falling to increase PD risk.

METHODS

We identified 1,223,726 subjects without PD who underwent the National Screening Program for Transitional Age at 66 years between 2009 and 2013 using the National Health Cohort database. In this program, every participant was assessed whether they experienced falling for the past six months. Depressive symptoms were evaluated with a three-item questionnaire extracted from the Geriatric Depression Scale. Incident PD was traced for a mean 4.23 ± 1.50 years. Cox proportional hazard regression models were used to assess the risk of PD by falling history with and without depressive symptoms after adjusting for other confounding variables.

RESULTS

In this cohort, the PD incidence rate was 1.30 and 1.03 cases per 1000 person-years in groups with and without falling and 1.34 and 1.00 cases per 1000 person-years in groups with and without depressive symptoms. The predictive risk of PD was increased by either a history of falling (HR = 1.24; 95% CI 1.11-1.40) or the presence of depressive symptoms (HR = 1.31; 95% CI 1.21-1.42) after adjusting for possible confounding variables. For individuals with both falling and depressive symptoms, PD risk increased further (HR = 1.66; 95% CI 1.40-1.97), but with sex-differences. The two factors increased PD risk in a sub-additive manner in men, whereas synergistically in women.

CONCLUSIONS

This national cohort database shows that late-life depressive symptoms accompanied by a falling event pose an increase in the risk of PD in older adults.

Step-rate threshold for physical activity intensity in Parkinson's disease

OBJECTIVES

To examine the relationship between step-rate and energy expenditure during treadmill walking in persons with PD and then further develop a step-rate cut-point for moderate-to-vigorous physical activity (MVPA) for persons with PD.

MATERIALS AND METHODS

The sample consisted of 30 persons with mild-to-moderate PD and 30 controls matched by age and sex. Participants performed a 6-minute bout of over-ground walking at comfortable speed, and then completed three, 6-minute bouts of treadmill walking at 13.4 m/min slower, comfortable, and 13.4 m/min faster than comfortable speeds. The three treadmill speeds were based on the initial over-ground walking speed. The total number of steps per treadmill walking bout was recorded using a hand-tally counter, and energy expenditure was measured using a portable, indirect spirometry system.

RESULTS

The results indicated a strong association between step-rate and energy expenditure for persons with PD (R²  = .92) and controls (R²  = .92). The analyses further indicated a steeper slope of the association for persons with PD compared with controls (t(58) = -1.87, P < .05), resulting in a lower step-rate threshold (t(58) = 2.19, P < .05) for persons with PD (~80 steps·per minutes) than controls (~93 steps·per minutes).

CONCLUSION

Collectively, these results support the application of this disease-specific step-rate threshold for MVPA among persons with PD. This has important implications for physical activity promotion, prescription, and monitoring using accelerometers and pedometers for persons with PD to manage health and symptoms of PD.

Parkinson's disease: etiopathogenesis and treatment

The concept of 'idiopathic' Parkinson's disease (PD) as a single entity has been challenged with the identification of several clinical subtypes, pathogenic genes and putative causative environmental agents. In addition to classic motor symptoms, non-motor manifestations (such as rapid eye movement sleep disorder, anosmia, constipation and depression) appear at prodromic/premotor stage and evolve, along with cognitive impairment and dysautonomia, as the disease progresses, often dominating the advanced stages of the disease. The key molecular pathogenic mechanisms include α-synuclein misfolding and aggregation, mitochondrial dysfunction, impairment of protein clearance (associated with deficient ubiquitin-proteasome and autophagy-lysosomal systems), neuroinflammation and oxidative stress. The involvement of dopaminergic as well as noradrenergic, glutamatergic, serotonergic and adenosine pathways provide insights into the rich and variable clinical phenomenology associated with PD and the possibility of alternative therapeutic approaches beyond traditional dopamine replacement therapies.One of the biggest challenges in the development of potential neuroprotective therapies has been the lack of reliable and sensitive biomarkers of progression. Immunotherapies such as the use of vaccination or monoclonal antibodies directed against aggregated, toxic α-synuclein.as well as anti-aggregation or protein clearance strategies are currently investigated in clinical trials. The application of glucagon-like peptide one receptor agonists, specific PD gene target agents (such as GBA or LRRK2 modifiers) and other potential disease modifying drugs provide cautious optimism that more effective therapies are on the horizon. Emerging therapies, such as new symptomatic drugs, innovative drug delivery systems and novel surgical interventions give hope to patients with PD about their future outcomes and prognosis.

Future Perspectives on the Relevance of Auditory Markers in Prodromal Parkinson's Disease

Research on auditory processing in Parkinson's disease (PD) has recently made substantial progress. At present, evidence has been found for altered auditory processing in the clinical stage of PD. The auditory alterations in PD have been demonstrated with low-cost and non-invasive assessments that are already used in routine clinical practice. Since auditory alterations have been reported early in disease progression, it would be highly relevant to investigate whether auditory markers could be provided in the prodromal stage of PD. In addition, auditory alterations in early stage PD might be modulated by dopaminergic medication. Therefore, the aim of this review is (1) to summarize the literature on auditory processing in PD with a specific focus on the early disease stages, (2) to give future perspectives on which audiological and electrophysiological measurements could be useful in the prodromal stage of PD and (3) to assess the effect of dopaminergic medication on potential auditory markers in the prodromal stage of PD.

Development of early diagnosis of Parkinson's disease: Illusion or reality?

The fight against neurodegenerative diseases, Alzheimer disease and Parkinson's disease (PD), is a challenge of the 21st century. The low efficacy of treating patients is due to the late diagnosis and start of therapy, after the degeneration of most specific neurons and depletion of neuroplasticity. It is believed that the development of early diagnosis (ED) and preventive treatment will delay the onset of specific symptoms. This review evaluates methodologies for developing ED of PD. Since PD is a systemic disease, and the degeneration of certain neurons precedes that of nigrostriatal dopaminergic neurons that control motor function, the current methodology is based on searching biomarkers, such as premotor symptoms and changes in body fluids (BF) in patients. However, all attempts to develop ED were unsuccessful. Therefore, it is proposed to enhance the current methodology by (i) selecting among biomarkers found in BF in patients at the clinical stage those that are characteristics of animal models of the preclinical stage, (ii) searching biomarkers in BF in subjects at the prodromal stage, selected by detecting premotor symptoms and failure of the nigrostriatal dopaminergic system. Moreover, a new methodology was proposed for the development of ED of PD using a provocative test, which is successfully used in internal medicine.

Pyrrolylquinoxaline-2-One Derivative as a Potent Therapeutic Factor for Brain Trauma Rehabilitation

Traumatic brain injury (TBI) often causes massive brain cell death accompanied by the accumulation of toxic factors in interstitial and cerebrospinal fluids. The persistence of the damaged brain area is not transient and may occur within days and weeks. Chaperone Hsp70 is known for its cytoprotective and antiapoptotic activity, and thus, a therapeutic approach based on chemically induced Hsp70 expression may become a promising approach to lower post-traumatic complications. To simulate the processes of secondary damage, we used an animal model of TBI and a cell model based on the cultivation of target cells in the presence of cerebrospinal fluid (CSF) from injured rats. Here we present a novel low molecular weight substance, PQ-29, which induces the synthesis of Hsp70 and empowers the resistance of rat C6 glioma cells to the cytotoxic effect of rat cerebrospinal fluid taken from rats subjected to TBI. In an animal model of TBI, PQ-29 elevated the Hsp70 level in brain cells and significantly slowed the process of the apoptosis in acceptor cells in response to cerebrospinal fluid action. The compound was also shown to rescue the motor function of traumatized rats, thus proving its potential application in rehabilitation therapy after TBI.

An Electrochemical Immunosensor Based on a Self-Assembled Monolayer Modified Electrode for Label-Free Detection of α-Synuclein

This research demonstrated the development of a simple, cost-effective, and label-free immunosensor for the detection of α-synuclein (α-Syn) based on a cystamine (CYS) self-assembled monolayer (SAM) decorated fluorine-doped tin oxide (FTO) electrode. CYS-SAM was formed onto the FTO electrode by the adsorption of CYS molecules through the head sulfur groups. The free amine (–NH₂) groups at the tail of the CYS-SAM enabled the immobilization of anti-α-Syn-antibody, which concurrently allowed the formation of immunocomplex by covalent bonding with α-Syn-antigen. The variation of the concentrations of the attached α-Syn at the immunosensor probe induced the alternation of the current and the charge transfer resistance (R_ct) for the redox response of [Fe(CN)₆]^3−/4−, which displayed a linear dynamic range from 10 to 1000 ng/mL with a low detection limit (S/N = 3) of ca. 3.62 and 1.13 ng/mL in differential pulse voltammetry (DPV) and electrochemical impedance spectra (EIS) measurements, respectively. The immunosensor displayed good reproducibility, anti-interference ability, and good recoveries of α-Syn detection in diluted human serum samples. The proposed immunosensor is a promising platform to detect α-Syn for the early diagnose of Parkinson’s disease, which can be extended for the determination of other biologically important biomarkers.

Non-Motor Symptoms of the Postural Instability and Gait Difficulty Subtype in De Novo Parkinson's Disease Patients: A Cross-Sectional Study in a Single Center

BACKGROUND AND PURPOSE

Little is known about non-motor symptoms (NMSs) associated with the postural instability and gait difficulty (PIGD) phenotype, especially in de novo Parkinson's disease (PD) patients. The aims of this study were to compare NMSs between the tremor dominant (TD) and PIGD phenotypes in de novo PD patients and to determine factors that are associated with the PIGD subtype.

PATIENTS AND METHODS

In a cross-sectional study conducted at our single center, 226 de novo PD patients with a median disease duration of 2 years were recruited. Data, including comprehensive demographics, motor subtypes and NMSs were obtained. Motor subtypes were classified as PIGD and non-PIGD (TD and indeterminate) by Jankovic's method. NMSs were evaluated by the non-motor symptoms questionnaire (NMSQuest).

RESULTS

We identified 73 (32.3%), 34 (15.0%) and 119 (52.7%) patients with TD, intermediate and PIGD subtypes, respectively. Patients with the PIGD subtype had poorer ADL, motor, depression, anxiety, sleep, and non-motor scores compared with those with the TD subtype. In the NMSQuest, the prevalence of cardiovascular, sleep, mood/cognitive and miscellaneous domains was increased in patients with the PIGD subtype compared with patients with the TD subtype. Multivariable forward stepwise logistic regression revealed that the Hamilton Depression Scale (HAMD) [odds ratio (OR), 1.059; 95% confidence interval (CI), 1.016-1.104, p = 0.007] and pain (OR, 3.175; 95% CI, 1.695-5.947, p < 0.001) exhibit significant discriminative power in differentiating PIGD and non-PIGD groups.

CONCLUSION

The PIGD group had more severe cardiovascular symptoms, sleep impairments, mood disturbances and pain. We demonstrated for the first time that pain was associated with the PIGD phenotype. Prompt detection and early treatment of NMSs related to the PIGD phenotype may improve patient outcomes.