Decrease in Aβ42 predicts dopa-resistant gait progression in early Parkinson disease

Improvements in clinical signs and symptoms of Parkinson's disease using photobiomodulation: a five-year follow-up

BACKGROUND

Parkinson's disease is a progressive neurodegenerative disease characterized by clinical motor signs and non-motor symptoms that severely impact quality of life. There is an urgent need for therapies that might slow, halt or even reverse the progression of existing symptoms or delay the onset of new symptoms. Photobiomodulation is a therapy that has shown potential to alleviate some symptoms of Parkinson's disease in animal studies and in small clinical trials.

OBJECTIVE

To assess long-term effectiveness of photobiomodulation therapy in a cohort of Parkinson's disease individuals after five years of continuing therapy.

METHODS

Eight participants of the initial 12 in a previously published study agreed to be reassessed after five years. Seven of these participants had continued home-based, self-applied photobiomodulation therapy three times per week for five years. One participant had discontinued treatment after one year. Participants were assessed for a range of clinical motor signs, including MDS-UPDRS-III, measures of mobility and balance. Cognition was assessed objectively, and quality of life and sleep quality were assessed using self-reported questionnaires. A Wilcoxon Signed Ranks test was used to evaluate change in outcome measures between baseline (before treatment) and after five years, with the alpha value set to 0.05.

RESULTS

Of the seven participants who had continued photobiomodulation therapy, one had a preliminary diagnosis of multisystem atrophy and was excluded from the group analysis. For the remaining six participants, there was a significant improvement in walk speed, stride length, timed up-and-go tests, tests of dynamic balance, and cognition compared to baseline and nonsignificant improvements in all other measures, apart from MDS-UPDRS-III, which was unchanged and one measure of static balance (single leg stance, standing on the unaffected leg with eyes open) which declined. Five of six participants either improved or showed no decline in MDS-UPDRS-III score and most participants showed improvement or no decline in all other outcome measures. No adverse effects of the photobiomodulation therapy were reported.

CONCLUSIONS

This study provides a signal that photobiomodulation therapy might safely reduce important clinical motor signs and non-motor symptoms in some Parkinson's disease patients, with improvements maintained over several years. Home-based photobiomodulation therapy has the potential to complement standard therapies to manage symptoms and potentially delay Parkinson's symptom progression.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry, registration number ACTRN12618000038291p, registered on 12/01/2018.

Interplay between the glymphatic system and neurotoxic proteins in Parkinson's disease and related disorders: current knowledge and future directions

Parkinson's disease is a common neurodegenerative disorder that is associated with abnormal aggregation and accumulation of neurotoxic proteins, including α-synuclein, amyloid-β, and tau, in addition to the impaired elimination of these neurotoxic protein. Atypical parkinsonism, which has the same clinical presentation and neuropathology as Parkinson's disease, expands the disease landscape within the continuum of Parkinson's disease and related disorders. The glymphatic system is a waste clearance system in the brain, which is responsible for eliminating the neurotoxic proteins from the interstitial fluid. Impairment of the glymphatic system has been proposed as a significant contributor to the development and progression of neurodegenerative disease, as it exacerbates the aggregation of neurotoxic proteins and deteriorates neuronal damage. Therefore, impairment of the glymphatic system could be considered as the final common pathway to neurodegeneration. Previous evidence has provided initial insights into the potential effect of the impaired glymphatic system on Parkinson's disease and related disorders; however, many unanswered questions remain. This review aims to provide a comprehensive summary of the growing literature on the glymphatic system in Parkinson's disease and related disorders. The focus of this review is on identifying the manifestations and mechanisms of interplay between the glymphatic system and neurotoxic proteins, including loss of polarization of aquaporin-4 in astrocytic endfeet, sleep and circadian rhythms, neuroinflammation, astrogliosis, and gliosis. This review further delves into the underlying pathophysiology of the glymphatic system in Parkinson's disease and related disorders, and the potential implications of targeting the glymphatic system as a novel and promising therapeutic strategy.

Motor progression trajectories and risk of mild cognitive impairment in Parkinson's disease: A latent class trajectory model from PPMI cohort

AIMS

Rare studies have investigated the association between heterogeneity of motor progression and risk of early cognitive impairment in Parkinson's disease (PD). In this study, we aim to identify distinct trajectories of motor progression longitudinally and investigate their impact on predicting mild cognitive impairment (MCI).

METHODS

A 5-year cohort including 415 PD patients at baseline was collected from the Parkinson's Progression Markers Initiative. The severity of motor symptoms was evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale part III. The latent class trajectory model and nonlinear mixed-effects model were used to analyze and delineate the longitudinal changes in motor symptoms. Propensity score matching (PSM) was used to minimize the impact of potential confounders. Cox proportional hazard models were applied to calculate hazard ratios for MCI, and a Kaplan-Meier curve was generated using the occurrence of MCI during the follow-up as the time-to-event.

RESULTS

Two latent trajectories were identified: a mild and remitting motor symptoms class (Class 1, 33.01%) and a severe and progressive motor symptom class (Class 2, 66.99%). Patients in Class 2 initially exhibited severe motor symptoms that worsened progressively despite receiving anti-PD medications. In comparison, patients in Class 1 exhibited milder symptoms that improved following drug therapy and a slower progression. During a 5-year follow-up, patients in Class 2 showed a higher risk of developing MCI compared to those in Class 1 before PSM (Log-Rank 28.58, p < 0.001) and after PSM (Log-Rank 8.20, p = 0.004).

CONCLUSIONS

PD patients with severe and progressive motor symptoms are more likely to develop MCI than those with mild and stable motor symptoms.

Early detection of diseases causing dementia using digital navigation and gait measures: A systematic review of evidence

Wearable digital technologies capable of measuring everyday behaviors could improve the early detection of dementia-causing diseases. We conducted two systematic reviews following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to establish the evidence base for measuring navigation and gait, two everyday behaviors affected early in AD and non-AD disorders and not adequately measured in current practice. PubMed and Web of Science databases were searched for studies on asymptomatic and early-stage symptomatic individuals at risk of dementia, with the Newcastle-Ottawa Scale used to assess bias and evaluate methodological quality. Of 316 navigation and 2086 gait records identified, 27 and 83, respectively, were included in the final sample. We highlight several measures that may identify at-risk individuals, whose quantifiability with different devices mitigates the risk of future technological obsolescence. Beyond navigation and gait, this review also provides the framework for evaluating the evidence base for future digital measures of behaviors considered for early disease detection.

Exercise and gait/movement analyses in treatment and diagnosis of Parkinson's Disease

Cardinal motor symptoms in Parkinson's disease (PD) include bradykinesia, rest tremor and/or rigidity. This symptomatology can additionally encompass abnormal gait, balance and postural patterns at advanced stages of the disease. Besides pharmacological and surgical therapies, physical exercise represents an important strategy for the management of these advanced impairments. Traditionally, diagnosis and classification of such abnormalities have relied on partially subjective evaluations performed by neurologists during short and temporally scattered hospital appointments. Emerging sports medical methods, including wearable sensor-based movement assessment and computational-statistical analysis, are paving the way for more objective and systematic diagnoses in everyday life conditions. These approaches hold promise to facilitate customizing clinical trials to specific PD groups, as well as personalizing neuromodulation therapies and exercise prescriptions for each individual, remotely and regularly, according to disease progression or specific motor symptoms. We aim to summarize exercise benefits for PD with a specific emphasis on gait and balance deficits, and to provide an overview of recent advances in movement analysis approaches, notably from the sports science community, with value for diagnosis and prognosis. Although such techniques are becoming increasingly available, their standardization and optimization for clinical purposes is critically missing, especially in their translation to complex neurodegenerative disorders such as PD. We highlight the importance of integrating state-of-the-art gait and movement analysis approaches, in combination with other motor, electrophysiological or neural biomarkers, to improve the understanding of the diversity of PD phenotypes, their response to therapies and the dynamics of their disease progression.

Transcutaneous auricular vagus nerve stimulation improves gait and cortical activity in Parkinson's disease: A pilot randomized study

OBJECTIVE

In this randomized, double-blind, sham-controlled trial, we explored the effect of 20 Hz transcutaneous auricular vagus nerve stimulation (taVNS) on gait impairments in Parkinson's disease (PD) patients and investigated the underlying neural mechanism.

METHODS

In total, 22 PD patients and 14 healthy controls were enrolled. PD patients were randomized (1:1) to receive active or sham taVNS (same position as active taVNS group but without releasing current) twice a day for 1 week. Meanwhile, all subjects were measured activation in the bilateral frontal and sensorimotor cortex during usual walking by functional near-infrared spectroscopy.

RESULTS

PD patients showed instable gait with insufficient range of motion during usual walking. Active taVNS improved gait characteristics including step length, stride velocity, stride length, and step length variability compared with sham taVNS after completion of the 7-day therapy. No difference was found in the Unified Parkinson's Disease Rating Scale III, Timed Up and Go, Tinetti Balance, and Gait scores. Moreover, PD patients had higher relative change of oxyhemoglobin in the left dorsolateral prefrontal cortex, pre-motor area, supplementary motor area, primary motor cortex, and primary somatosensory cortex than HCs group during usual walking. Hemodynamic responses in the left primary somatosensory cortex were significantly decreased after taVNS therapy.

CONCLUSION

taVNS can relieve gait impairments and remodel sensorimotor integration in PD patients.

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design

BACKGROUND

In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.

OBJECTIVES

To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.

METHODS

Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.

RESULTS

On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.

CONCLUSIONS

It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Gait and balance in apolipoprotein Ɛ4 allele carriers in older adults and Parkinson's disease

Background

Gait and balance impairments are among the most troublesome and heterogeneous in Parkinson's disease (PD). This heterogeneity may, in part, reflect genetic variation. The apolipoprotein E (APOE) gene has three major allelic variants (ε2, ε3 and ε4). Previous work has demonstrated that older adult (OA) APOE ε4 carriers demonstrate gait deficits. This study compared gait and balance measures between APOE ε4 carriers and non-carriers in both OA and PD.

Methods

334 people with PD (81 APOE ε4 carriers and 253 non-carriers) and 144 OA (41 carriers and 103 non-carriers) were recruited. Gait and balance were assessed using body-worn inertial sensors. Two-way analyses of covariance (ANCOVA) compared gait and balance characteristics between APOE ε4 carriers and non-carriers in people with PD and OA, controlling for age, gender, and testing site.

Results

Gait and balance were worse in people with PD compared to OA. However, there were no differences between APOE ε4 carriers and non-carriers in either the OA or PD group. In addition, there were no significant group (OA/PD) by APOE ε4 status (carrier/non-carrier) interaction effects for any measures of gait or balance.

Conclusions

Although we found expected impairments in gait and balance in PD compared to OA, gait and balance characteristics did not differ between APOE ε4 carriers and non-carriers in either group. While APOE status did not impact gait and balance in this cross-sectional study, future work is needed to determine whether progression of gait and balance deficits is faster in PD APOE Ɛ4 carriers.

Cholinergic basal forebrain atrophy in Parkinson's disease with freezing of gait

BACKGROUND

Mounting research support that cholinergic dysfunction plays a prominent role in freezing of gait (FOG), which commonly occurs in Parkinson's disease (PD). Basal forebrain (BF), especially the cholinergic nuclei 4 (Ch4), provides the primary source of the brain cholinergic input. However, whether the degeneration of BF and its innervated cortex contribute to the pathogenesis of FOG is unknown.

OBJECTIVE

To explore the role of structural alterations of BF and its innervated cortical brain regions in the pathogenesis of PD patients with freezing.

METHODS

Magnetic resonance imaging assessments and neurological assessments were performed on 20 PD patients with FOG (PD-FOG), 20 without FOG (PD-NFOG), and 21 healthy participants. Subregion volumes of the BF were compared among groups. Local gyrification index (LGI) was computed to reveal the cortical alternations. Relationships among subregional BF volumes, LGI, and the severity of FOG were evaluated by multiple linear regression.

RESULTS

Our study discovered that, compared to PD-NFOG, PD-FOG exhibited significant Ch4 atrophy (p = 4.6 × 10^-5 ), accompanied by decreased LGI values in the left entorhinal cortex (p = 3.00 × 10^-5 ) and parahippocampal gyrus (p = 2.90 × 10^-5 ). Based on the regression analysis, Ch4 volume was negatively associated with FOG severity in PD-FOG group (β = -12.224, T = -2.556, p = 0.031).

INTERPRETATION

Our results imply that Ch4 degeneration and microstructural disorganization of its innervated cortical brain regions may play important roles in PD-FOG.

Mixed pathology as a rule, not exception: Time to reconsider disease nosology

Parkinson's disease is a progressive neurodegenerative disorder that is associated with motor and nonmotor symptoms. Accumulation of misfolded α-synuclein is considered a key pathological feature during disease initiation and progression. While clearly deemed a synucleinopathy, the development of amyloid-β plaques, tau-containing neurofibrillary tangles, and even TDP-43 protein inclusions occur within the nigrostriatal system and in other brain regions. In addition, inflammatory responses, manifested by glial reactivity, T-cell infiltration, and increased expression of inflammatory cytokines, plus other toxic mediators derived from activated glial cells, are currently recognized as prominent drivers of Parkinson's disease pathology. However, copathologies have increasingly been recognized as the rule (>90%) and not the exception, with Parkinson's disease cases on average exhibiting three different copathologies. While microinfarcts, atherosclerosis, arteriolosclerosis, and cerebral amyloid angiopathy may have an impact on disease progression, α-synuclein, amyloid-β, and TDP-43 pathology do not seem to contribute to progression.

Safety and tolerability of adjunct non-invasive vagus nerve stimulation in people with parkinson's: a study protocol

BACKGROUND

Parkinson's disease (PD) is the fastest growing neurological condition worldwide. Recent theories suggest that symptoms of PD may arise due to spread of Lewy-body pathology where the process begins in the gut and propagate transynaptically via the vagus nerve to the central nervous system. In PD, gait impairments are common motor manifestations that are progressive and can appear early in the disease course. As therapies to mitigate gait impairments are limited, novel interventions targeting these and their consequences, i.e., reducing the risk of falls, are urgently needed. Non-invasive vagus nerve stimulation (nVNS) is a neuromodulation technique targeting the vagus nerve. We recently showed in a small pilot trial that a single dose of nVNS improved (decreased) discrete gait variability characteristics in those receiving active stimulation relative to those receiving sham stimulation. Further multi-dose, multi-session studies are needed to assess the safety and tolerability of the stimulation and if improvement in gait is sustained over time.

DESIGN

This will be an investigator-initiated, single-site, proof-of-concept, double-blind sham-controlled randomised pilot trial in 40 people with PD. Participants will be randomly assigned on a 1:1 ratio to receive either active or sham transcutaneous cervical VNS. All participants will undergo comprehensive cognitive, autonomic and gait assessments during three sessions over 24 weeks, in addition to remote monitoring of ambulatory activity and falls, and exploratory analyses of cholinergic peripheral plasma markers. The primary outcome measure is the safety and tolerability of multi-dose nVNS in PD. Secondary outcomes include improvements in gait, cognition and autonomic function that will be summarised using descriptive statistics.

DISCUSSION

This study will report on the proportion of eligible and enrolled patients, rates of eligibility and reasons for ineligibility. Adverse events will be recorded informing on the safety and device tolerability in PD. This study will additionally provide us with information for sample size calculations for future studies and evidence whether improvement in gait control is enhanced when nVNS is delivered repeatedly and sustained over time.

TRIAL REGISTRATION

This trial is prospectively registered at www.isrctn.com/ISRCTN19394828 . Registered August 23, 2021.

Gait Declines Differentially in, and Improves Prediction of, People with Parkinson's Disease Converting to a Freezing of Gait Phenotype

BACKGROUND

Freezing of gait (FOG) is a debilitating, variably expressed motor symptom in people with Parkinson's disease (PwPD) with limited treatments.

OBJECTIVE

To determine if the rate of progression in spatiotemporal gait parameters in people converting from a noFOG to a FOG phenotype (FOGConv) was faster than non-convertors, and determine if gait parameters can help predict this conversion.

METHODS

PwPD were objectively monitored longitudinally, approximately every 6 months. Non-motor assessments were performed at the initial visit. Steady-state gait in the levodopa ON-state was collected using a gait mat (Protokinetics) at each visit. The rate of progression in 8 spatiotemporal gait parameters was calculated. FOG convertors (FOGConv) were classified if they did not have FOG at initial visit and developed FOG at a subsequent visit.

RESULTS

Thirty freezers (FOG) and 30 non-freezers were monitored an average of 3.5 years, with 10 non-freezers developing FOG (FOGConv). FOGConv and FOG had faster decline in mean stride-length, swing-phase-percent, and increase in mean total-double-support percent, coefficient of variability (CV) foot-strike-length and CV swing-phase-percent than the remaining non-freezers (noFOG). On univariate modeling, progression rates of mean stride-length, stride-velocity, swing-phase-percent, total-double-support-percent and of CV swing-phase-percent had high discriminative power (AUC > 0.83) for classification of the FOGConv and noFOG groups.

CONCLUSION

FOGConv had a faster temporal decline in objectively quantified gait than noFOG, and progression rates of spatiotemporal gait parameters were more predictive of FOG phenotype conversion than initial (static) parameters Objectively monitoring gait in disease prediction models may help define FOG prone groups for testing putative treatments.

A meta-analysis of the diagnostic utility of biomarkers in cerebrospinal fluid in Parkinson's disease

Biomarkers play important roles in the diagnosis and differential diagnosis of Parkinson's disease (PD). Thus, we carried out a systematic review and meta-analysis evaluating the diagnostic utility of cerebrospinal fluid (CSF) biomarkers to distinguish PD from atypical parkinsonian syndromes (APSs) and controls. Data for PD and APS and controls were extracted from 123 studies that reported the concentration of CSF biomarkers. Comparisons were presented using pooled Hedges' g. Sources of heterogeneity were evaluated using meta-regression, and subgroup and sensitivity analyses. We found that compared with controls, PD patients had lower levels of amyloid beta 1-42, phosphorylated tau, total tau, total α-synuclein, Zn, DJ-1, and YKL-40, and higher levels of oligomeric and phosphorylated α-synuclein. Moreover, lower CSF levels of neurofilament light chain, t-tau, YKL-40, and C-reactive protein were found in PD patients compared to those with multiple system atrophy. PD patients also had lower levels of NFL and higher levels of Aβ42 compared with patients with progressive supranuclear palsy. Reduced levels of p-tau and t-tau and higher Aβ42 levels were found in PD patients compared with patients with dementia with Lewy bodies. Finally, reduced NFL levels were found in patients with PD compared with patients with cortical basal degeneration. Therefore, we believe that the combinations of t-α-syn, Aβ42, and NFL could be promising biomarkers for the differential diagnosis of PD and APSs.

Gait alterations in Parkinson’s disease at the stage of hemiparkinsonism—A longitudinal study

Background

Progressive gait impairment in Parkinson’s disease (PD) leads to significant disability. Quantitative gait parameters analysis provides valuable information about fine gait alterations.

Objectives

To analyse change of gait parameters in patients with early PD at the stage of hemiparkinsonism and after 1 year of follow up, taking into account clinical asymmetry.

Methods

Consecutive early PD outpatients with strictly unilateral motor features underwent clinical and neuropsychological assessment at the study entry and after 1 year of follow up. Gait was assessed with GAITRite walkway using dual-task methodology. Spatiotemporal gait parameters (step time and length, swing time and double support time) and their coefficients of variation (CV), gait velocity and heel-to-heel base support were evaluated.

Results

We included 42 PD patients with disease duration of 1.3 years (±1.13). Progression of motor and non-motor symptoms, without significant cognitive worsening, was observed after 1 year of follow up. Significant shortening of the swing time, prolongation of the double support and increase of their CVs were observed during all task conditions similarly for most parameters on symptomatic and asymptomatic bodysides, except for CV for the swing time under the combined task.

Conclusion

Alterations of the swing time and double support time are already present even at the asymptomatic body side, and progress similarly, or even at faster pace, at this side, despite dopaminergic treatment These parameters deserve further investigation in larger, prospective studies to address their potential to serve as markers of progression in interventional disease modifying trials with early PD patients.

Electrochemical Aptasensors for Parkinson's Disease Biomarkers Detection

BACKGROUND

Biomarkers are characteristic molecules that can be measured as indicators of biological process status or condition, exhibiting special relevance in Parkinson's Disease (PD). This disease is a chronic neurodegenerative disorder very difficult to study given the site of pathology and due to a clinical phenotype that fluctuates over time. Currently there is no definitive diagnostic test, thus clinicians hope that the detection of crucial biomarkers will help to the symptomatic and presymptomatic diagnostics and providing surrogate endpoints to demonstrate the clinical efficacy of new treatments.

METHODS

Electrochemical aptasensors are excellent analytical tools that are used in the detection of PD biomarkers, as they are portable, easy to use, and perform real-time analysis.

RESULTS

In this review, we discuss the most important clinical biomarkers for PD, highlighting their physiological role and function in the disease. Herein, we review for the first time innovative aptasensors for the detection of current potential PD biomarkers based on electrochemical techniques and discuss future alternatives, including ideal analytical platforms for point-of-care diagnostics.

CONCLUSION

These new tools will be critical not only in the discovery of sensitive, specific, and reliable biomarkers of preclinical PD, but also in the development of tests that can assist in the early detection and differential diagnosis of parkinsonian disorders and in monitoring disease progression. Various methods for fixing aptamers onto the sensor surfaces, enabling quantitative and specific PD biomarker detection present in synthetic and clinical samples, will also be discussed.

Parkinson's Disease Symptoms Associated with Developing On-State Axial Symptoms Early after Subthalamic Deep Brain Stimulation

Background: The relationship between axial symptoms in Parkinson’s disease (PD) and subthalamic deep brain stimulation (STN-DBS) is still unclear. Purpose: We searched for particular clinical characteristics before STN-DBS linked to on-state axial problems after surgery. Methods: We retrospectively analyzed baseline motor, emotional and cognitive features from PD patients with early axial symptoms (within 4 years after STN-DBS) and late axial symptoms (after 4 years). We also considered a group of PD patients without axial symptoms for at least 4 years after surgery. Results: At baseline, early-axial PD patients (n = 28) had a higher on-state Unified Parkinson’s Disease Rating Scale III (15.0 ± 5.6 to 11.6 ± 6.2, p = 0.020), higher axial score (2.4 ± 1.8 to 0.7 ± 1.0, p < 0.001) and worse dopaminergic response (0.62 ± 0.12 to 0.70 ± 0.11, p = 0.005), than non-axial PD patients (n = 51). Early-axial PD patients had short-term recall impairment, not seen in non-axial PD (36.3 ± 7.6 to 40.3 ± 9.3, p = 0.041). These variables were similar between late-axial PD (n = 18) and non-axial PD, but late-axial PD showed worse frontal dysfunction. Conclusions: PD patients with early axial symptoms after DBS may have a significantly worse presurgical motor phenotype, poorer dopaminergic response and memory impairment. This may correspond to a more severe form of PD.

Paeoniflorin ameliorates cognitive impairment in Parkinson's disease via JNK/p53 signaling

Paeoniflorin (PF) has numerous benefits, including anti-inflammatory and anti-apoptosis effects. However, it is not clear if it has neuroprotective effects against cognitive impairment (CI) in Parkinson's disease (PD). Through network pharmacology, we identified probable targets as well as signal pathways through which PF might affect CI in PD. Then, we experimentally validated our findings. The core genes of the protein-protein interactions (PPI) network include MAPK8 (JNK), TP53, CASP3 (caspase-3), postsynaptic density protein-95 (PSD-95) and synaptophysin (SYN). Pathway enrichment analysis revealed that genes involved in apoptosis and mitogen-activated protein kinase (MAPK) signaling were significantly enriched. Because JNK is a key mediator of p53-induced apoptosis, we wondered if JNK/p53 pathway influences the effects of PF against apoptosis in mouse model of PD. Molecular docking analysis showed that PF had good affinity for JNK/p53. The results of the experiments indicated that PF ameliorated behavioral impairments and upregulated the expression of the dopamine (DA) neurons, suppressed cell apoptosis in substantia nigra pars compacta (SNpc) of PD. Additionally, PF improved 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced neuronal injury by inhibiting apoptosis in hippocampal neurons of the CA1 and CA3, and upregulating PSD-95 as well as SYN protein levels. Similar protective effects were observed upon JNK/p53 pathway inhibition using SP600125. Overall, PF improved CI in PD by inhibiting JNK/p53 pathway.

Gait‐Related Metabolic Covariance Networks at Rest in Parkinson's Disease

Background

Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted.

Objective

The aim of this study was to identify neural networks of discrete gait impairments in PD.

Methods

Fifty‐five participants with early‐stage PD and 20 age‐matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [¹⁸F]‐2‐fluoro‐2‐deoxyglucose‐positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD.

Results

In PD, we identified two metabolic gait‐related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity.

Conclusions

We have identified two novel gait‐related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Update on CSF Biomarkers in Parkinson's Disease

Progress in developing disease-modifying therapies in Parkinson’s disease (PD) can only be achieved through reliable objective markers that help to identify subjects at risk. This includes an early and accurate diagnosis as well as continuous monitoring of disease progression and therapy response. Although PD diagnosis still relies mainly on clinical features, encouragingly, advances in biomarker discovery have been made. The cerebrospinal fluid (CSF) is a biofluid of particular interest to study biomarkers since it is closest to the brain structures and therefore could serve as an ideal source to reflect ongoing pathologic processes. According to the key pathophysiological mechanisms, the CSF status of α-synuclein species, markers of amyloid and tau pathology, neurofilament light chain, lysosomal enzymes and markers of neuroinflammation provide promising preliminary results as candidate biomarkers. Untargeted approaches in the field of metabolomics provide insights into novel and interconnected biological pathways. Markers based on genetic forms of PD can contribute to identifying subgroups suitable for gene-targeted treatment strategies that might also be transferable to sporadic PD. Further validation analyses in large PD cohort studies will identify the CSF biomarker or biomarker combinations with the best value for clinical and research purposes.

Noninvasive vagus nerve stimulation in Parkinson's disease: current status and future prospects

INTRODUCTION

Parkinson's disease (PD) is a common progressive neurodegenerative disorder with multifactorial etiology. While dopaminergic medication is the standard therapy in PD, it provides limited symptomatic treatment and non-pharmacological interventions are currently being trialed.

AREAS COVERED

Recent pathophysiological theories of Parkinson's suggest that aggregated α-synuclein form in the gut and spread to nuclei in the brainstem via autonomic connections. In this paper, we review the novel hypothesis that noninvasive vagus nerve stimulation (nVNS), targeting efferent and afferent vagal projections, is a promising therapeutic tool to improve gait and cognitive control and ameliorate non-motor symptoms in people with Parkinson's. We conducted an unstructured search of the literature for any studies employing nVNS in PD as well as for studies examining the efficacy of nVNS on improving cognitive function and where nVNS has been applied to co-occurring conditions in PD.

EXPERT OPINION

Evidence of nVNS as a novel therapeutic to improve gait in PD is preliminary, but early signs indicate the possibility that nVNS may be useful to target dopa-resistant gait characteristics in early PD. The evidence for nVNS as a therapeutic tool is, however, limited and further studies are needed in both brain health and disease.

Association of sleep disturbance and freezing of gait in Parkinson disease: prevention/delay implications

STUDY OBJECTIVES

Freezing of gait (FOG) severely impairs life quality of Parkinson disease (PD) patients. The relationship between sleep disturbance and FOG in PD remains unclear, so in this study, we aimed to investigate that relationship.

METHODS

First, we assessed clinical characteristics of freezers and nonfreezers among PD patients. Next, we assessed clinical characteristics of PD patients with different PDSS1 scores (score on first item of Parkinson's Disease Sleep Scale). Finally, we prospectively followed a cohort of nonfreezers from a baseline clinical visit and to a maximum of 18 months and performed a Cox regression analysis to further investigate the relationship between PDSS1 score and FOG in PD.

RESULTS

A total of 163 participants with PD were included in the baseline analysis. The freezers had significantly worse sleep compared with the nonfreezers. The proportion of freezers in the patients with low PDSS1 score (PDSS1 < 6) was significantly higher than that in the patients with high PDSS1 score (PDSS1 ≥ 6). A total of 52 nonfreezers were prospectively followed. During a maximum 18-month follow-up, FOG incidence (73%) in the PDSS1 < 6 group was significantly higher than that (24%) in the PDSS1 ≥ 6 group (P = .008). Low PDSS1 score (hazard ratio = 4.23, 95% CI 1.64-10.92, P = .003) and high levodopa equivalent daily dose (hazard ratio = 4.18, 95% CI 1.62-10.75, P = .003) were significantly associated with an increased hazard of FOG.

CONCLUSIONS

Our study indicated that low PDSS1 score may be a risk indicator for the development of FOG and provided important insights into potential targets for the prevention/delay of FOG in PD.

Emerging targets for the diagnosis of Parkinson's disease: examination of systemic biomarkers

Parkinson's disease (PD) is a highly prevalent and irreversible neurodegenerative disorder that is typically diagnosed in an advanced stage. Currently, there are no approved biomarkers that reliably identify PD patients before they have undergone extensive neuronal damage, eliminating the opportunity for future disease-modifying therapies to intervene in disease progression. This unmet need for diagnostic and therapeutic biomarkers has fueled PD research for decades, but these efforts have not yet yielded actionable results. Recently, studies exploring mechanisms underlying PD progression have offered insights into multisystemic contributions to pathology, challenging the classic perspective of PD as a disease isolated to the brain. This shift in understanding has opened the door to potential new biomarkers from multiple sites in the body. This review focuses on emerging candidates for PD biomarkers in the context of current diagnostic approaches and multiple organ systems that contribute to disease.

White matter hyperintensities mediate the impact of amyloid ß on future freezing of gait in Parkinson's disease

BACKGROUND

Freezing of gait (FOG) is a common symptom in Parkinson's Disease (PD) patients. Previous studies have reported relationships between FOG, substantia nigra (SN) degeneration, dopamine transporter (DAT) concentration, as well as amyloid β deposition. However, there is a paucity of research on the concurrent impact of white matter damage.

OBJECTIVES

To assess the inter-relationships between these different co-morbidities, their impact on future FOG and whether they act independently of each other.

METHODS

We used baseline MRI and longitudinal gait data from 423 de novo PD patients from the Parkinson's Progression Markers Initiative (PPMI). We used deformation based morphometry (DBM) from T1-weighted MRI to measure SN atrophy, and segmentation of white matter hyperintensities (WMH) as a measure of WM pathological load. Putamen and caudate DAT levels from SPECT as well as cerebrospinal fluid (CSF) amyloid β were obtained directly from the PPMI. Following correlation analyses, we investigated whether WMH burden mediates the impact of amyloid β on future FOG.

RESULTS

SN DBM, WMH load, putamen and caudate DAT activity and CSF amyloid β levels were significantly different between PD patients with and without future FOG (p < 0.008). Mediation analysis demonstrated an effect of CSF amyloid β levels on future FOG via WMH load, independent of SN atrophy and striatal DAT activity levels.

CONCLUSIONS

Amyloid β might impact future FOG in PD patients through an increase in WMH burden, in a pathway independent of Lewy body pathology.

Cholinergic Basal Forebrain Volumes Predict Gait Decline in Parkinson's Disease

BACKGROUND

Gait disturbance is an early, disabling feature of Parkinson's disease (PD) that is typically refractory to dopaminergic medication. The cortical cholinergic system, originating in the nucleus basalis of Meynert of the basal forebrain, has been implicated. However, it is not known if degeneration in this region relates to a worsening of disease-specific gait impairment.

OBJECTIVE

To evaluate associations between sub-regional cholinergic basal forebrain volumes and longitudinal progression of gait impairment in PD.

METHODS

99 PD participants and 47 control participants completed gait assessments via an instrumented walkway during 2 minutes of continuous walking, at baseline and for up to 3 years, from which 16 spatiotemporal characteristics were derived. Sub-regional cholinergic basal forebrain volumes were measured at baseline via MRI and a regional map derived from post-mortem histology. Univariate analyses evaluated cross-sectional associations between sub-regional volumes and gait. Linear mixed-effects models assessed whether volumes predicted longitudinal gait changes.

RESULTS

There were no cross-sectional, age-independent relationships between sub-regional volumes and gait. However, nucleus basalis of Meynert volumes predicted longitudinal gait changes unique to PD. Specifically, smaller nucleus basalis of Meynert volume predicted increasing step time variability (P = 0.019) and shortening swing time (P = 0.015); smaller posterior nucleus portions predicted shortening step length (P = 0.007) and increasing step time variability (P = 0.041).

CONCLUSIONS

This is the first study to demonstrate that degeneration of the cortical cholinergic system predicts longitudinal progression of gait impairments in PD. Measures of this degeneration may therefore provide a novel biomarker for identifying future mobility loss and falls. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Current Perspectives on the Assessment and Management of Gait Disorders in Parkinson's Disease

Gait dysfunction is a key defining feature of Parkinson's disease (PD), and is associated with symptoms of freezing and an increased risk of falls. In this narrative review, we cover the putative mechanisms of gait dysfunction in PD, the assessment of gait abnormalities, and the management of symptoms caused by the inherent difficulty in walking. Our understanding of the causes of gait problems in PD has progressed in recent times, moving from neurocognitive theory to correlates of affected neuronal pathways. In particular, this can be shown to correspond with abnormalities in responses to dual-task paradigms and dysfunction in cholinergic signaling. Great progress has been made in the sophistication and precision of gait assessment; however, it has firmly remained in the research domain. There is significant momentum behind wearable technologies that can be used by patients in their own environment, acting as digital biomarkers that can not only reflect progression but also independently discriminate PD from non-PD individuals. The treatment of gait dysfunction has historically relied on physical therapies and training combined with a view to mitigating the impact of such consequences as falls. Pharmacological therapies that are the mainstay of treatment in PD have tended to address symptoms like bradykinesia; however, optimization of dopaminergic therapies likely has a positive effect on quality of gait. Other targets have been assessed with the goal of improving gait, of which medications that improve cholinergic signaling appear most promising. Neuromodulation techniques are increasingly used in the form of deep-brain stimulation; however, standard targets, such as the globus pallidus interna, have a modest effect on gait. Considerable benefit has been seen through targeting the pedunculopontine nucleus, and a dual-target approach may be warranted. Stimulation of the spinal cord and brain through direct or magnetic approaches has been assessed, but requires further evidence.

Gait Progression Over 6 Years in Parkinson's Disease: Effects of Age, Medication, and Pathology

Background: Gait disturbance is an early, cardinal feature of Parkinson's disease (PD) associated with falls and reduced physical activity. Progression of gait impairment in Parkinson's disease is not well characterized and a better understanding is imperative to mitigate impairment. Subtle gait impairments progress in early disease despite optimal dopaminergic medication. Evaluating gait disturbances over longer periods, accounting for typical aging and dopaminergic medication changes, will enable a better understanding of gait changes and inform targeted therapies for early disease. This study aimed to describe gait progression over the first 6 years of PD by delineating changes associated with aging, medication, and pathology. Methods: One-hundred and nine newly diagnosed PD participants and 130 controls completed at least two gait assessments. Gait was assessed at 18-month intervals for up to 6 years using an instrumented walkway to measure sixteen spatiotemporal gait characteristics. Linear mixed-effects models assessed progression. Results: Ten gait characteristics significantly progressed in PD, with changes in four of these characteristics attributable to disease progression. Age-related changes also contributed to gait progression; changes in another two characteristics reflected both aging and disease progression. Gait impairment progressed irrespective of dopaminergic medication change for all characteristics except step width variability. Conclusions: Discrete gait impairments continue to progress in PD over 6 years, reflecting a combination of, and potential interaction between, disease-specific progression and age-related change. Gait changes were mostly unrelated to dopaminergic medication adjustments, highlighting limitations of current dopaminergic therapy and the need to improve interventions targeting gait decline.

Unraveling Pathophysiological Mechanisms of Parkinson's Disease: Contribution of CSF Biomarkers

Diagnosis of Parkinson's disease (PD) relies on clinical history and physical examination, but misdiagnosis is common in early stages. Identification of biomarkers for PD may allow for early and more precise diagnosis and provide information about prognosis. Developments in analytical chemistry allow for the detection of a large number of molecules in cerebrospinal fluid (CSF), which are known to be associated with the pathogenesis of PD. Given the pathophysiology of PD, CSF α-synuclein species have the strongest rationale for use, also providing encouraging preliminary results in terms of early diagnosis. In the field of classical Alzheimer's disease (AD) biomarkers, low CSF Aβ₄₂ levels have shown a robust prognostic value in terms of development of cognitive impairment. Other CSF biomarkers including lysosomal enzymes, neurofilament light chain, markers of neuroinflammation and oxidative stress, although promising, have not proved to be reliable for diagnostic and prognostic purposes yet. Overall, the implementation of CSF biomarkers may give a substantial contribution to the optimal use of disease-modifying drugs.

Gait variability is linked to the atrophy of the Nucleus Basalis of Meynert and is resistant to STN DBS in Parkinson's disease

Parkinson’s disease (PD) is a systemic brain disorder where the cortical cholinergic network begins to degenerate early in the disease process. Readily accessible, quantitative, and specific behavioral markers of the cortical cholinergic network are lacking. Although degeneration of the dopaminergic network may be responsible for deficits in cardinal motor signs, the control of gait is a complex process and control of higher-order aspects of gait, such as gait variability, may be influenced by cognitive processes attributed to cholinergic networks. We investigated whether swing time variability, a metric of gait variability that is independent from gait speed, was a quantitative behavioral marker of cortical cholinergic network integrity in PD.

Twenty-two individuals with PD and subthalamic nucleus (STN) deep brain stimulation (PD-DBS cohort) and twenty-nine age-matched controls performed a validated stepping-in-place (SIP) task to assess swing time variability off all therapy. The PD-DBS cohort underwent structural MRI scans to measure gray matter volume of the Nucleus Basalis of Meynert (NBM), the key node in the cortical cholinergic network. In order to determine the role of the dopaminergic system on swing time variability, it was measured ON and OFF STN DBS in the PD-DBS cohort, and on and off dopaminergic medication in a second PD cohort of thirty-two individuals (PD-med). A subset of eleven individuals in the PD-DBS cohort completed the SIP task again off all therapy after three years of continuous DBS to assess progression of gait impairment.

Swing time variability was significantly greater (i.e., worse) in PD compared to controls and greater swing time variability was related to greater atrophy of the NBM, as was gait speed. STN DBS significantly improved cardinal motor signs and gait speed but did not improve swing time variability, which was replicated in the second cohort using dopaminergic medication. Swing time variability continued to worsen in PD, off therapy, after three years of continuous STN DBS, and NBM atrophy showed a trend for predicting the degree of increase. In contrast, cardinal motor signs did not progress. These results demonstrate that swing time variability is a reliable marker of cortical cholinergic health, and support a framework in which higher-order aspects of gait control in PD are reliant on the cortical cholinergic system, in contrast to other motor aspects of PD that rely on the dopaminergic network.

Differential protein expression in diverse brain areas of Parkinson's and Alzheimer's disease patients

Many hypotheses have been postulated to define the etiology of sporadic Parkinson's and Alzheimer's disorders (PD and AD) but there is no consensus on what causes these devastating age-related diseases. Braak staging of both pathologies helped researchers to better understand the progression and to identify their prodromal and symptomatic phases. Indeed, it is well accepted that Lewy body pathology and neurofibrillary tangles appearance correlates with disease progression and severity of symptoms in PD and AD, respectively. Additionally, several studies in PD and AD models try to disclose which cellular mechanisms are defaulted and trigger the neurodegenerative process that culminates with neuronal death causing PD and AD classical symptomatology. Herein, we determined expression levels of proteins involved in microtubule assembly, autophagic-lysosomal pathway and unfolded protein response in the cortex, hippocampus and SNpc of PD and AD patients, vascular dementia patients and aged-match controls. The differential expression allowed us to determine which pathways are determinant to synaptic dysfunction and to establish a time line for disease progression. Our results allow us to challenge the hypothesis that both PD and AD pathologies are caused by α-synuclein or Aβ pathology propagation throughout the brain in a prion-like manner.

The path to biomarker-based diagnostic criteria for the spectrum of neurodegenerative diseases

Introduction: The postmortem examination still represents the reference standard for detecting the pathological nature of chronic neurodegenerative diseases (NDD). This approach displays intrinsic conceptual limitations since NDD represent a dynamic spectrum of partially overlapping phenotypes, shared pathomechanistic alterations that often give rise to mixed pathologies.Areas covered: We scrutinized the international clinical diagnostic criteria of NDD and the literature to provide a roadmap toward a biomarker-based classification of the NDD spectrum. A few pathophysiological biomarkers have been established for NDD. These are time-consuming, invasive, and not suitable for preclinical detection. Candidate screening biomarkers are gaining momentum. Blood neurofilament light-chain represents a robust first-line tool to detect neurodegeneration tout court and serum progranulin helps detect genetic frontotemporal dementia. Ultrasensitive assays and retinal scans may identify Aβ pathology early, in blood and the eye, respectively. Ultrasound also represents a minimally invasive option to investigate the substantia nigra. Protein misfolding amplification assays may accurately detect α-synuclein in biofluids.Expert opinion: Data-driven strategies using quantitative rather than categorical variables may be more reliable for quantification of contributions from pathophysiological mechanisms and their spatial-temporal evolution. A systems biology approach is suitable to untangle the dynamics triggering loss of proteostasis, driving neurodegeneration and clinical evolution.

Goalkeeper Game: A New Assessment Tool for Prediction of Gait Performance Under Complex Condition in People With Parkinson's Disease

Background: People with Parkinson's disease (PD) display poorer gait performance when walking under complex conditions than under simple conditions. Screening tests that evaluate gait performance changes under complex walking conditions may be valuable tools for early intervention, especially if allowing for massive data collection. Objectives: To investigate the use of the Goalkeeper Game (GG) to predict impairment in gait performance under complex conditions in people with Parkinson's disease (PPD) and compare its predictive power with the one of the Montreal Cognitive Assessment (MoCA) test. Methods: 74 PPD (HY stages: 23 in stage 1; 31 in stage 2; 20 in stage 3), without dementia (MoCA cut-off 21), tested in ON period with dopaminergic medication were submitted to single individual cognitive/motor evaluation sessions. MoCA and GG were used to assess cognition, and the dynamic gait index (DGI) test was used to assess gait performance under complex condition. GG test resulted in 9 measures extracted via a statistical model. The predictive power of the GG measures and the MoCA score with respect to gait performance, as assessed by DGI, were compared. Results: The predictive models based on GG obtained a better score of prediction (65%) then MoCA (56%) for DGI scores (at a 50% specificity). Conclusion: GG is a novel tool for noninvasive screening that showed a superior predictive power in assessing gait performance under complex condition in people with PD than the well-established MoCa test.

Parkinsonian gait in aging: A feature of Alzheimer's pathology?

INTRODUCTION

Central neurological gait abnormalities (CNGA; i.e. frontal or parkinsonian) are frequently associated with neurodegenerative conditions in older adults, but their pathophysiological substrates remain poorly described. This cross-sectional study aims to assess the association between cerebrospinal fluid (CSF) Alzheimer's biomarkers and CNGA.

METHODS

CSF biomarkers (phosphor-tau, total tau and Aβ1-42) were measured in 52 patients with CNGA (77.33 ± 6.09 years; 28.8% female). Gait phenotypes were evaluated by two diagnosis-blinded assessors and classified as frontal gait, parkinsonian gait or other gait abnormalities.

RESULTS

Parkinsonian gait was significantly associated with a decreased CSF Aβ42 even after adjusting on age, gender, comorbidities and white matter changes (β: -0.32; 95% CI: [-340.6; -22.9]; p value: 0.026). Phosphor-tau and total tau were not associated with any other CNGA (i.e. frontal gait and other gait abnormalities).

DISCUSSION

Parkinsonian gait represents a gait phenotype of Alzheimer's pathology in patients with CNGA.

Differential Gait Decline in Parkinson's Disease Enhances Discrimination of Gait Freezers from Non-Freezers

BACKGROUND

Freezing of gait (FOG) is a debilitating feature of Parkinson's disease (PD) for which treatments are limited. To develop neuroprotective strategies, determining whether disease progression is different in phenotypic variants of PD is essential.

OBJECTIVE

To determine if freezers have a faster decline in spatiotemporal gait parameters.

METHODS

Subjects were enrolled in a longitudinal study and assessed every 3- 6 months. Continuous gait in the levodopa ON-state was collected using a gait mat (Protokinetics). The slope of change/year in spatiotemporal gait parameters was calculated.

RESULTS

26 freezers, 31 non-freezers, and 25 controls completed an average of 6 visits over 28 months. Freezers had a faster decline in mean stride-length, stride-velocity, swing-%, single-support-%, and variability in single-support-% compared to non-freezers (p < 0.05). Gait decline was not correlated with initial levodopa dose, duration of levodopa therapy, change in levodopa dose or change in Montreal Cognitive Assessment scores (p > 0.25). Gait progression parameters were required to obtain 95% accuracy in categorizing freezers and non-freezers groups in a forward step-wise binary regression model. Change in mean stride-length, mean stride-width, and swing-% variability along with initial foot-length variability, mean swing-% and apathy scores were significant variables in the model.

CONCLUSION

Freezers had a faster temporal decline in objectively quantified gait, and inclusion of longitudinal gait changes in a binary regression model greatly increased categorization accuracy. Levodopa dosing, cognitive decline and disease severity were not significant in our model. Early detection of this differential decline may help define freezing prone groups for testing putative treatments.

Immunotherapy Targeting Neurodegenerative Proteinopathies: α-Synucleinopathies and Tauopathies

α-Synuclein and tau deposition in the central nervous system is responsible for various parkinsonian syndromes, including Parkinson’s disease, multiple system atrophy, dementia with Lewy bodies, progressive supranuclear palsy and corticobasal degeneration. Emerging evidence has suggested that pathologic α-synuclein and tau are transmitted from cell to cell and further accelerate the aggregation of pathologic proteins in neighboring cells. Furthermore, extracellular pathologic proteins have also been reported to provoke inflammatory responses that lead to neurodegeneration. Therefore, immunotherapies targeting extracellular α-synuclein and tau have been proposed as potential disease-modifying strategies. In this review, we summarize completed phase I trials and ongoing phase II trials of immunotherapies against α-synuclein and tau and further discuss concerns and hurdles to overcome in the future.

Using gait analysis' parameters to classify Parkinsonism: A data mining approach

INTRODUCTION

Parkinson's disease (PD) is the second most common neurodegenerative disorder in the world, while Progressive Supranuclear Palsy (PSP) is an atypical Parkinsonism resembling PD, especially in early stage. Assumed that gait dysfunctions represent a major motor symptom for both pathologies, gait analysis can provide clinicians with subclinical information reflecting subtle differences between these diseases. In this scenario, data mining can be exploited in order to differentiate PD patients at different stages of the disease course and PSP using all the variables acquired through gait analysis.

METHODS

A cohort of 46 subjects (divided into three groups) affected by PD patients at different stages and PSP patients was acquired through gait analysis and spatial and temporal parameters were analysed. Synthetic Minority Over-sampling Technique was used to balance our imbalanced dataset and cross-validation was applied to provide different training and testing sets. Then, Random Forests and Gradient Boosted Trees were implemented.

RESULTS

Accuracy, error, precision, recall, specificity and sensitivity were computed for each group and for both algorithms, including 16 features. Random Forests obtained the highest accuracy (86.4%) but also specificity and sensitivity were particularly high, overcoming the 90% for PSP group.

CONCLUSION

The novelty of the study is the use of a data mining approach on the spatial and temporal parameters of gait analysis in order to classify patients affected by typical (PD) and atypical Parkinsonism (PSP) based on gait patterns. This application would be helpful for clinicians to distinguish PSP from PD at early stage, when the differential diagnosis is particularly challenging.

Aβ42/Aβ40 and Aβ42/Aβ38 Ratios Are Associated with Measures of Gait Variability and Activities of Daily Living in Mild Alzheimer's Disease: A Pilot Study

Gait disturbances are some of the earliest changes in dementia and their monitoring presents an opportunity for early diagnosis. The exact relationship between gait and well-established biomarkers of Alzheimer’s disease (AD) remains to be clarified. In this study we compared gait-related measures with cerebrospinal fluid (CSF) markers of AD pathology. We recruited seventeen participants with mild AD in a multi-site study and performed gait assessment as well as lumbar punctures to obtain CSF. CSF Aβ₄₂/Aβ₄₀ and Aβ₄₂/Aβ₃₈ correlated positively with measures of variability (step time and step length) in the clinic-based assessments. This was driven by a negative relationship between gait variability and Aβ₄₀ and Aβ₃₈ but not Aβ₄₂.The amyloid ratios and gait variability measures were also associated with more severe functional impairment. We interpret these data as an indication that increasing amyloid production (i.e., increasing Aβ₄₀ and Aβ₃₈) is associated with diminishing cognitive-motor control of gait. These preliminary results suggest that the two amyloid ratios may be a marker of the earliest disturbances in the interplay between cognitive and motor control which characterize dementia.

Translational Informatics for Parkinson's Disease: from Big Biomedical Data to Small Actionable Alterations

Parkinson's disease (PD) is a common neurological disease in elderly people, and its morbidity and mortality are increasing with the advent of global ageing. The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations. To highlight the use of big data for precision PD medicine, we review PD big data and informatics for the translation of basic PD research to clinical applications. We emphasize some key findings in clinically actionable changes, such as susceptibility genetic variations for PD risk population screening, biomarkers for the diagnosis and stratification of PD patients, risk factors for PD, and lifestyles for the prevention of PD. The challenges associated with the collection, storage, and modelling of diverse big data for PD precision medicine and healthcare are also summarized. Future perspectives on systems modelling and intelligent medicine for PD monitoring, diagnosis, treatment, and healthcare are discussed in the end.

Gait analysis with wearables predicts conversion to parkinson disease

Objective

Quantification of gait with wearable technology is promising; recent cross‐sectional studies showed that gait characteristics are potential prodromal markers for Parkinson disease (PD). The aim of this longitudinal prospective observational study was to establish gait impairments and trajectories in the prodromal phase of PD, identifying which gait characteristics are potentially early diagnostic markers of PD.

Methods

The 696 healthy controls (mean age = 63 ± 7 years) recruited in the Tubingen Evaluation of Risk Factors for Early Detection of Neurodegeneration study were included. Assessments were performed longitudinally 4 times at 2‐year intervals, and people who converted to PD were identified. Participants were asked to walk at different speeds under single and dual tasking, with a wearable device placed on the lower back; 14 validated clinically relevant gait characteristics were quantified. Cox regression was used to examine whether gait at first visit could predict time to PD conversion after controlling for age and sex. Random effects linear mixed models (RELMs) were used to establish longitudinal trajectories of gait and model the latency between impaired gait and PD diagnosis.

Results

Sixteen participants were diagnosed with PD on average 4.5 years after first visit (converters; PDC). Higher step time variability and asymmetry of all gait characteristics were associated with a shorter time to PD diagnosis. RELMs indicated that gait (lower pace) deviates from that of non‐PDC approximately 4 years prior to diagnosis.

Interpretation

Together with other prodromal markers, quantitative gait characteristics can play an important role in identifying prodromal PD and progression within this phase. ANN NEUROL 2019;86:357–367

The neural correlates of discrete gait characteristics in ageing: A structured review

Gait is complex, described by diverse characteristics underpinned by widespread central nervous system networks including motor and cognitive functions. Despite this, neural substrates of discrete gait characteristics are poorly understood, limiting understanding of gait impairment in ageing and disease. This structured review aims to map gait characteristics, defined from a pre-specified model reflecting independent gait domains, to brain imaging parameters in older adults. Fifty-two studies of 38,029 yielded were reviewed. Studies showed inconsistent approaches when mapping gait assessment to neural substrates, limiting conclusions. Gait impairments typically associated with brain deterioration, specifically grey matter atrophy and white matter integrity loss. Gait velocity, a global measure of gait control, was most frequently associated with these imaging markers within frontal and basal ganglia regions, and its decline predicted from white matter volume and integrity measurements. Fewer studies assessed additional gait measures or functional imaging parameters. Future studies mapping regional neuroanatomical and functional correlates of gait are needed, including those which take a multi-process network perspective to better understand mobility in health and disease.

Parkinson's and Lewy body dementia CSF biomarkers

The clinical diagnosis of Parkinson's disease (PD) and Dementia with Lewy bodies (DLB) is challenging due to highly variable clinical presentation and clinical and pathological overlap with other neurodegenerative diseases. Since cerebrospinal fluid (CSF) mirrors the pathological changes taking place in the brain, it represents a promising source of biomarkers. With respect to classical AD biomarkers, low CSF Aβ₄₂ levels have shown a robust prognostic value in terms of development of cognitive impairment in PD and DLB. In the differential diagnosis between AD and DLB, a potential role of t-tau, p-tau and Aβ₄₂/Aβ₃₈ ratio has been demonstrated. Regarding CSF α-synuclein (α-syn) species, lower levels of total α-synuclein (t-α-syn) and higher concentration of oligomeric-α-synuclein (o-α-syn) and phosphorylated α-synuclein (p-α-syn) have been observed in PD. Furthermore, the detection of "pro-aggregating" α-synuclein has enabled the discrimination of patients affected by synucleinopathies with high sensitivity and specificity. New promising biomarkers are emerging: GCase activity (reduced in PD and DLB patients vs. controls), CSF/serum albumin ratio (increased in PD and DLB), fatty-acid-binding protein (increased in AD and DLB vs. PD), visinin-like protein-1 (increased in AD vs. DLB) and monoamines (useful in differential diagnosis among PD and DLB). These encouraging results need to be confirmed by future studies.

Potential Utility of 123I-MIBG Scintigraphy as a Predictor of Falls in Parkinson's Disease

Background: Falls are associated with poor prognosis in patients with Parkinson's disease (PD). Although several factors related to falls were reported in patients with PD, objective predictors of falls are not identified. We aimed to determine whether ¹²³I-meta-iodobenzylguanidine (MIBG) cardiac scintigraphy could be a useful biomarker to predict falls. Methods: Forty-five patients with PD were enrolled in this study. These subjects were followed up more than 5 years after MIBG scintigraphy and were divided into two groups: one with decreased uptake of MIBG and the other without decreased uptake of MIBG. The cut-off value for the delayed heart-to-mediastinum ratio was 1.8. Kaplan-Meier analysis and a log-rank test were performed to test the predictive power of MIBG cardiac scintigraphy for falls. Univariate analysis was selected because we did not have appropriate data for adjustment, such as motor and cognitive assessment. Results: The group with decreased uptake of MIBG had a significantly higher incidence of falls than that without decreased uptake of MIBG (P = 0.022, log-rank test). Conclusions: Although the limitations of this study were lack of several key factors including motor and cognitive assessment, MIBG cardiac scintigraphy may be used to predict falls in patients with PD.

Progressive Gait Deficits in Parkinson's Disease: A Wearable-Based Biannual 5-Year Prospective Study

Background: Gait changes occur during all Parkinson’s disease (PD) stages and wearable sensor-derived gait parameters may quantify PD progression. However, key aspects that may qualify quantitative gait parameters as progression markers in PD remain elusive.

Objectives: Longitudinal changes in gait parameters from a lower-back sensor under convenient and challenging walking conditions in early- and mid-stage PD patients (E-PD, M-PD) compared to controls were investigated.

Methods: Normal- and fast-pace parameters (step: number, time, velocity, variability) were assessed every 6 months for up to 5 years in 22 E-PD (<4 years baseline disease duration), 18 M-PD (>5 years) and 24 controls. Parameter trajectories and associations with MDS-UPDRS-III were tested using generalized estimating equations.

Results: Normal-pace step number (annual change in E-PD: 2.1%, Time^∗Group: p = 0.001) and step time variability (8.5%, p < 0.05) longitudinally increased in E-PD compared to controls (0.7%, -12%). For fast pace, no significant progression differences between groups were observed. Longitudinal changes in M-PD did not differ significantly from controls. MDS-UPDRS-III was largely associated with normal-pace parameters in M-PD.

Conclusion: Wearables can quantify progressive gait deficits indicated by increasing step number and step time variability in E-PD. In M-PD, and for fast-pace, gait parameters possess limited potential as PD progression markers.

Technological advances and changing indications for lumbar puncture in neurological disorders

Technological advances have changed the indications for and the way in which lumbar puncture is done. Suspected CNS infection remains the most common indication for lumbar puncture, but new molecular techniques have broadened CSF analysis indications, such as the determination of neuronal autoantibodies in autoimmune encephalitis. New screening techniques have increased sensitvity for pathogen detection and can be used to identify pathogens that were previously unknown to cause CNS infections. Evidence suggests that potential treatments for neurodegenerative diseases, such as Alzheimer's disease, will rely on early detection of the disease with the use of CSF biomarkers. In addition to being used as a diagnostic tool, lumbar puncture can also be used to administer intrathecal treatments as shown by studies of antisense oligonucleotides in patients with spinal muscular atrophy. Lumbar puncture is generally a safe procedure but complications can occur, ranging from minor (eg, back pain) to potentially devastating (eg, cerebral herniation). Evidence that an atraumatic needle tip design reduces complications of lumbar puncture is compelling, and reinforces the need to change clinical practice.

The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control

Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions-including Parkinson's disease, ataxia, and dementia-we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel 'big data' approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction.

Cerebrospinal fluid biomarker for Parkinson's disease: An overview

In Parkinson's disease (PD), there is a wide field of recent and ongoing search for useful biomarkers for early and differential diagnosis, disease monitoring or subtype characterization. Up to now, no biofluid biomarker has entered the daily clinical routine. Cerebrospinal fluid (CSF) is often used as a source for biomarker development in different neurological disorders because it reflects changes in central-nervous system homeostasis. This review article gives an overview about different biomarker approaches in PD, mainly focusing on CSF analyses. Current state and future perspectives regarding classical protein markers like alpha‑synuclein, but also different "omics" techniques are described. In conclusion, technical advancements in the field already yielded promising results, but further multicenter trials with well-defined cohorts, standardized protocols and integrated data analysis of different modalities are needed before successful translation into routine clinical application.