Challenges of modifying disease progression in prediagnostic Parkinson's disease

Artificial intelligence in Parkinson's disease: Early detection and diagnostic advancements

Parkinson's disease (PD) is the second most common neurodegenerative disorder, globally affecting men and women at an exponentially growing rate, with currently no cure. Disease progression starts when dopaminergic neurons begin to die. In PD, the loss of neurotransmitter, dopamine is responsible for the overall communication of neural cells throughout the body. Clinical symptoms of PD are slowness of movement, involuntary muscular contractions, speech & writing changes, lessened automatic movement, and chronic tremors in the body. PD occurs in both familial and sporadic forms and modifiable and non-modifiable risk factors and socioeconomic conditions cause PD. Early detectable diagnostics and treatments have been developed in the last several decades. However, we still do not have precise early detectable biomarkers and therapeutic agents/drugs that prevent and/or delay the disease process. Recently, artificial intelligence (AI) science and machine learning tools have been promising in identifying early detectable markers with a greater rate of accuracy compared to past forms of treatment and diagnostic processes. Artificial intelligence refers to the intelligence exhibited by machines or software, distinct from the intelligence observed in humans that is based on neural networks in a form and can be used to diagnose the longevity and disease severity of disease. The term Machine Learning or Neural Networks is a blanket term used to identify an emerging technology that is created to work in the way of a "human brain" using many intertwined neurons to achieve the same level of raw intelligence as that of a brain. These processes have been used for neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease, to assess the severity of the patient's condition. In the current article, we discuss the prevalence and incidence of PD, and currently available diagnostic biomarkers and therapeutic strategies. We also highlighted currently available artificial intelligence science and machine learning tools and their applications to detect disease and develop therapeutic interventions.

Identification of Prodromal Parkinson Disease: We May Be Able to But Should We?

Parkinson disease (PD) remains a progressive and incurable disease. Research over the past decade provides strong evidence of a detectible phase before the clinical diagnosis, known as the prodromal phase of PD (pPD). In this article, we review the debate about disclosure of risk of progression to PD and related disorders to individuals through the perspectives of the pillars of medical ethics: beneficence, nonmaleficence, autonomy, and justice. There is evidence that lifestyle modification may have positive effects on onset and progression of PD, providing justification of potential benefit. From a societal perspective, a diagnosis of pPD could allow targeted recruitment to disease-modifying trials. Regarding nonmaleficence, direct evidence that catastrophic reactions are scarce is largely derived from studies of monogenic conditions, which may not be generalizable. Diagnosis of PD can be traumatic, and appropriate communication and evaluation of circumstances to weigh up disclosure is crucial. Future research should therefore examine the potential harms of early and of false-positive diagnoses and specifically examine these matters in diverse populations. Autonomy balances the right to know and the right not to know, so an individualized patient-centered approach and shared decision-making is essential, acknowledging that knowledge of being in the prodromal phase could prolong autonomy in the longer term. Distributive justice brings focus toward health care and related planning at the individual and societal level and affects the search for disease modification in PD. We must acknowledge that waiting for established disease states is likely to be too little, too late and results in failures of expensive trials and wasted participant and researcher effort. Ultimately, clinicians must arrive at a decision with the patient that solicits and integrates patients' goals, taking into account their individual life circumstances, perspectives, and philosophies, recognizing that one size cannot fit all.

Longitudinal study investigating the influence of COMT gene polymorphism on cortical thickness changes in Parkinson's disease over four years

Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting over 3% of those over 65. It's caused by reduced dopaminergic neurons and Lewy bodies, leading to motor and non-motor symptoms. The relationship between COMT gene polymorphisms and PD is complex and not fully elucidated. Some studies have reported associations between certain COMT gene variants and PD risk, while others have not found significant associations. This study investigates how COMT gene variations impact cortical thickness changes in PD patients over time, aiming to link genetic factors, especially COMT gene variations, with PD progression. This study analyzed data from 44 PD patients with complete 4-year imaging follow-up from the Parkinson Progression Marker Initiative (PPMI) database. Magnetic resonance imaging (MRI) scans were acquired using consistent methods across 9 different MRI scanners. COMT single-nucleotide polymorphisms (SNPs) were assessed based on whole genome sequencing data. Longitudinal image analysis was conducted using FreeSurfer's processing pipeline. Linear mixed-effect models were employed to examine the interaction effect of genetic variations and time on cortical thickness, while controlling for covariates and subject-specific variations. The rs165599 SNP stands out as a potential contributor to alterations in cortical thickness, showing a significant reduction in overall mean cortical thickness in both hemispheres in homozygotes (Left: P = 0.023, Right: P = 0.028). The supramarginal, precentral, and superior frontal regions demonstrated significant bilateral alterations linked to rs165599. Our findings suggest that the rs165599 variant leads to earlier manifestation of cortical thinning during the course of the disease. However, it does not result in more severe cortical thinning outcomes over time. There is a need for larger cohorts and control groups to validate these findings and consider genetic variant interactions and clinical features to elucidate the specific mechanisms underlying COMT-related neurodegenerative processes in PD.

Pharmacotherapy for Disease Modification in Early Parkinson's Disease: How Early Should We Be?

Slowing or halting progression continues to be a major unmet medical need in Parkinson's disease (PD). Numerous trials over the past decades have tested a broad range of interventions without ultimate success. There are many potential reasons for this failure and much debate has focused on the need to test 'disease-modifying' candidate drugs in the earliest stages of disease. While generally accepted as a rational approach, it is also associated with significant challenges around the selection of trial populations as well as trial outcomes and durations. From a health care perspective, intervening even earlier and before at-risk subjects have gone on to develop overt clinical disease is at the heart of preventive medicine. Recent attempts to develop a framework for a biological definition of PD are aiming to enable 'preclinical' and subtype-specific diagnostic approaches. The present review addresses past efforts towards disease-modification, including drug targets and reasons for failure, as well as novel targets that are currently being explored in disease-modification trials in early established PD. The new biological definitions of PD may offer new opportunities to intervene even earlier. We critically discuss the potential and challenges around planning 'disease-prevention' trials in subjects with biologically defined 'preclinical' or prodromal PD.

Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis

Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest: area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI: 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI: 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI: 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI: 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI: 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.

Epworth sleepiness scale is associated with increased striatal dopamine uptake in Parkinson's disease: a cross-sectional study

PURPOSE

A cross-sectional study was designed to investigate the possible association between Epworth sleepiness scale (ESS) scores and striatal dopamine uptake in the early stages of Parkinson's disease (PD).

METHODS

Two groups of PD patients (n = 464) and healthy controls (HC) (n = 162) were enrolled in the current study from the Parkinson's progression markers initiative cohort ( https://www.ppmi-info.org ). All the subjects were evaluated for excessive daytime sleepiness (EDS) using the ESS. They also completed specific measures to be assessed for motor and non-motor symptoms, including cognitive, gait, autonomic, and olfactory dysfunction. Dopamine transporter (DaT) scans were used to identify dopamine transporter impairments. Spatial normalization for DaTscan imaging of participants was performed to reach consistent orientation.

RESULTS

A significant correlation was found between ESS score and right putamen (P < 0.001; correlation coefficient = 0.186) and left putamen (P = 0.003; correlation coefficient = 0.139) dopamine uptake in PD patients. The same results were revealed after adjusted Pearson's correlation for the effects of handedness, age, gender, and education. No significant correlation was found between the ESS score and the amount of caudate nucleus dopamine uptake in PD patients. Moreover, there was a significant association between caudate nucleus dopamine uptake and ESS score in neither PD patients nor HCs.

CONCLUSIONS

The results of our study suggest that increased dopaminergic function of putamen nuclei may be associated with ESS scores in the early stages of PD. Further studies are needed at different PD stages and evaluate PD progression as a possible confounder.

Monitoring Substantia Nigra Degeneration Using Free Water Imaging across Prodromal and Clinical Parkinson's Disease

BACKGROUND

Substantia nigra (SN) free water has been suggested as a good surrogate marker in Parkinson's disease (PD). However, its usefulness for diagnosing prodromal PD (pPD) and monitoring disease progression warrants further validation.

OBJECTIVE

The aim was to investigate SN free water values across prodromal and clinical stages of PD.

METHODS

Four groups were enrolled in this study: 48 healthy controls (HC), 43 pPD patients, 50 de novo PD (dnPD) patients, and 49 medicated PD (mPD) patients. Based on diffusion tensor images, free water maps were calculated, and SN free water values were extracted from the anterior SN (ASN) and posterior SN (PSN). The SN free water values were compared among the four groups, and associations between free water and clinical symptoms were explored. The distinguishing power of PSN free water was evaluated using the receiver operating characteristic curve analysis. Follow-up was performed for 14 pPD patients.

RESULTS

PSN free water in the pPD group was significantly higher than that in the HC group and significantly lower than that in the dnPD group. Surprisingly, the mPD group showed decreased PSN free water compared to the dnPD group. There was a positive correlation between motor symptoms and PSN free water in the pPD and dnPD groups. Longitudinal analysis showed a significant increase in PSN free water in pPD patients over time.

CONCLUSIONS

The PSN free water increased from prodromal to early clinical stages, but the trend might be reversed in late disease stages. This biphasic trend should be considered when applying this marker in future studies. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Development of Small Molecules Targeting α-Synuclein Aggregation: A Promising Strategy to Treat Parkinson’s Disease

Parkinson’s disease, the second most common neurodegenerative disorder worldwide, is characterized by the accumulation of protein deposits in the dopaminergic neurons. These deposits are primarily composed of aggregated forms of α-Synuclein (α-Syn). Despite the extensive research on this disease, only symptomatic treatments are currently available. However, in recent years, several compounds, mainly of an aromatic character, targeting α-Syn self-assembly and amyloid formation have been identified. These compounds, discovered by different approaches, are chemically diverse and exhibit a plethora of mechanisms of action. This work aims to provide a historical overview of the physiopathology and molecular aspects associated with Parkinson’s disease and the current trends in small compound development to target α-Syn aggregation. Although these molecules are still under development, they constitute an important step toward discovering effective anti-aggregational therapies for Parkinson’s disease.

Plasma extracellular vesicle tau, β-amyloid, and α-synuclein and the progression of Parkinson's disease: a follow-up study

Background

Plasma extracellular vesicle (EV) contents are promising biomarkers of Parkinson's disease (PD). The pathognomonic proteins of PD, including α-synuclein, tau, and β-amyloid, are altered in people with PD (PwP) and are associated with clinical presentation in previous cross-sectional studies. However, the dynamic changes in these plasma EV proteins in PwP and their correlation with clinical progression remain unclear.

Objective

We investigated the dynamic changes in plasma EV α-synuclein, tau, and β-amyloid and their correlation with/prediction of clinical progression in PwP.

Design

A cohort study.

Methods

In total, 103 PwP and 37 healthy controls (HCs) completed baseline assessment and 1-year follow-up. Clinical assessments included Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III, Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). Plasma EVs were isolated, and immunomagnetic reduction-based immunoassay was used to assess α-synuclein, tau, and β-amyloid 1-42 (Aβ1-42) levels within the EVs.

Results

Compared with HCs, significant differences were noted in the annual changes in all three EV pathognomonic proteins in PwP. Although the absolute changes in plasma EV pathognomonic proteins did not significantly correlate with clinical changes, PwP with elevated baseline plasma EV tau (upper-half) levels demonstrated significantly greater decline in motor and cognition, and increased plasma EV α-synuclein levels were associated with postural instability and the gait disturbance motor subtype. For PwP with elevated levels of all three biomarkers, clinical deterioration was significant, as indicated by UPDRS-II scores, postural instability and gait disturbance subscores of UPDRS-III, and MMSE score.

Conclusion

The combination of plasma EV α-synuclein, tau, and Aβ1-42 may identify PwP with a high risk of deterioration. Our findings can elucidate the interaction between these pathognomonic proteins, and they may serve as treatment response markers and can be applied in treatment approaches for disease modification.

The Role of Cannabinoid Type 2 Receptors in Parkinson's Disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disease and currently represents a clear unmet medical need. Therefore, novel preventive and therapeutic strategies are needed. Cannabinoid type 2 (CB2) receptors, one of the components of the endocannabinoid system, can regulate neuroinflammation in PD. Here, we review the current preclinical and clinical studies investigating the CB2 receptors in PD with the aim to clarify if these receptors could have a role in PD. Preclinical data show that CB2 receptors could have a neuroprotective action in PD and that the therapeutic targeting of CB2 receptors could be promising. Indeed, it has been shown that different CB2 receptor-selective agonists exert protective effects in different PD models. Moreover, the alterations in the expression of CB2 receptors observed in brain tissues from PD animal models and PD patients suggest the potential value of CB2 receptors as possible novel biomarkers for PD. However, to date, there is no direct evidence of the role of CB2 receptors in PD. Further studies are strongly needed in order to fully clarify the role of CB2 receptors in PD and thus pave the way to novel possible diagnostic and therapeutic opportunities for PD.

Research progress on neuromolecular imaging of REM sleep behavior disorder

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is an important non-motor complication of Parkinson's disease. At the same time, iRBD is considered to be the prodromal stage of α-synucleinopathy. This high risk of conversion suggests that iRBD becomes a nerve It is a window for early research on degenerative diseases and is the best candidate for neuroprotection trials. A wide range of neuroimaging techniques has improved our understanding of iRBD as a prodromal stage of the disease. In addition, neuroimaging of abnormal iRBD is expected to be a potential biomarker for predicting clinical phenotypic transformation. This article reviews the research progress of neuromolecular imaging in patients with iRBD from the perspective of iRBD transforming synucleinopathies.

Deep Clinical Phenotyping of Parkinson's Disease: Towards a New Era of Research and Clinical Care

Despite recent advances in technology, clinical phenotyping of Parkinson's disease (PD) has remained relatively limited as current assessments are mainly based on empirical observation and subjective categorical judgment at the clinic. A lack of comprehensive, objective, and quantifiable clinical phenotyping data has hindered our capacity to diagnose, assess patients' conditions, discover pathogenesis, identify preclinical stages and clinical subtypes, and evaluate new therapies. Therefore, deep clinical phenotyping of PD patients is a necessary step towards understanding PD pathology and improving clinical care. In this review, we present a growing community consensus and perspective on how to clinically phenotype this disease, that is, to phenotype the entire course of disease progression by integrating capacity, performance, and perception approaches with state-of-the-art technology. We also explore the most studied aspects of PD deep clinical phenotypes, namely, bradykinesia, tremor, dyskinesia and motor fluctuation, gait impairment, speech impairment, and non-motor phenotypes.

Postoperative Complication Rates After One-Level Cervical Spine Surgery in Patients with Parkinson Disease: A Database Study

OBJECTIVE

Parkinson disease (PD) is a risk factor for worse surgical outcomes. The degree to which PD affects outcomes in cervical spine surgery is not well understood. Therefore, we characterize rates of postoperative complications among patients with PD who undergo cervical spine surgery.

METHODS

Using the PearlDiver database, we identified patients who underwent 1-level anterior cervical discectomy and fusion (ACDF), posterior cervical fusion (PCF), or discectomy/decompression with concomitant PD between 2011 and 2019. Patients with PD who underwent surgery and had 1 year follow-up were included. Complications 30, 60, and 90 days after surgery were identified and aggregated into body systems (e.g., respiratory and gastrointestinal). Comparison controls without concomitant PD who received cervical spine (C-spine) surgery were matched for age, sex, and comorbidities.

RESULTS

A total of 259,443 ACDFs, 30,929 PCFs, and 29,563 decompressions were identified. Of these procedures, 1117 were performed on patients with PD (0.35%). The highest 90-day complications rates in patients with PD were pulmonary and gastrointestinal related (6.05%) in those who received ACDF, neuro related (8.51%) in those who received PCF, and genitourinary related (8.76%) in those who received a decompression. Compared with patients without PD, postoperative complications rates were similar and not significantly different.

CONCLUSIONS

Patients with PD who receive ACDF have higher rates of pulmonary (6.05%), neurologic (5.24%), and psychiatric (3.23%) complications at 90 days. The differences did not reach statistical significance. This finding suggests that patients with PD do not experience higher rates of acute postoperative complications when undergoing 1-level cervical spine surgery.

Acupuncture for Parkinson's disease: From theory to practice

Advances in molecular biology and biochemistry have improved the treatment of Parkinson's disease (PD). There has been extensive evidence on the benefit of standard treatment (e.g., deep brain stimulation, levodopa, and dopamine agonists) and acupuncture for PD. This article aims to distill the similarities and differences in the treatment concepts between Chinese and Western medicine from the perspective of reinforcing the deficiency and purging the excess, summarize the latest evidence on the benefits of acupuncture for PD from theory to practice, and propose prospective treatment options for PD.

Efficacy of Acupuncture for Parkinson's Disease Anxiety: Two-Stage Protocol for a Randomized Controlled Clinical Trial

Parkinson's disease anxiety (PDA) is a nonmotor symptom of Parkinson's disease (PD) that is often neglected. PDA poses a far-reaching challenge to the treatment of PD. Acupuncture could be successful in the treatment of PDA. However, the evidence for this is still limited. We propose a two-stage clinical trial. In stage 1, a total of 70 volunteers with PDA will be randomly assigned to either acupuncture (manual acupuncture) or control group (sham acupuncture) in a 1 : 1 ratio. Treatments will be performed for four weeks. The change in the Hamilton Rating Scale for Anxiety (HAMA) score from baseline to week 4 and week 12 will be the primary outcome. The levels of adrenocorticotropic hormone (ACTH), cortisol (CORT), serotonin (5-HT), and corticotropin-releasing factor (CRH) in the patients' serum and the scores on the Hoehn–Yahr Rating Scale and the Unified Parkinson's Disease Rating Scale (UPDRS) will all be considered among the secondary outcomes. Participants will be followed up until week 12. In stage 2, a total of 82 volunteers with PDA will be randomly assigned to either an acupuncture (manual acupuncture) or a control group (anti-Parkinson drugs only) in a 1 : 1 ratio. HAMA score will be the primary outcome. Universality, feasibility and cost effectiveness, Hoehn–Yahr Rating Scale, UPDRS, and serological indicators will be secondary outcomes. Participants will be followed up until week 4. The statistical analysis will include all the allocated individuals. The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine's Research Ethical Committee authorized this procedure, and the trial is registered with ChiCTR2100047253.

White Matter Microstructural Alterations in Newly Diagnosed Parkinson’s Disease: A Whole-Brain Analysis Using dMRI

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD’s pathophysiology.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

Characterizing mild cognitive impairment in prodromal Parkinson's disease: A community-based study in China

Objective

The International Parkinson and Movement Disorder Society (MDS) has published research criteria for prodromal Parkinson's disease (pPD), which includes cognitive impairment as a prodromal marker. However, the clinical features of mild cognitive impairment (MCI) in pPD remain unknown. Our study aimed to evaluate the frequency and clinical features of mild cognitive impairment of pPD in the elderly in China.

Methods

The cross‐sectional community‐based study recruited 2688 participants aged ≥50 years. Subjects were diagnosed with pPD according to the MDS criteria. Overall, 39 pPD and 22 healthy controls underwent comprehensive clinical and neuropsychological assessment. MCI was also diagnosed by the MDS criteria. Next, we investigated the relationship between clinical factors and cognition.

Results

Among the 2,663 dementia‐free and Parkinson disease (PD)‐free participants, 55 met the criteria for pPD (2.1%) and 23 pPD met the criteria for MCI. Memory, attention/working memory, and executive function were the most frequent impaired domains, and amnestic MCI multidomain phenotype was the most frequent MCI subtype (69.57%) in pPD. Additionally, correlation analysis revealed that the global cognitive performance was negatively related to UPDRS‐III score (r = −0.456, p = 0.004).

Conclusion

MCI, specifically impairment in memory, attention/working memory, and executive domain, is present at the prodromal stage of PD. In addition, cognitive performance is correlated with motor symptoms in pPD. Our results reflect that cognitive profile, combined with motor symptoms, can help clinicians to identify individuals with pPD early, as those would be the optimal candidates for neuroprotective therapy.

The Genetics of Parkinson's Disease and Implications for Clinical Practice

The genetic landscape of Parkinson’s disease (PD) is characterised by rare high penetrance pathogenic variants causing familial disease, genetic risk factor variants driving PD risk in a significant minority in PD cases and high frequency, low penetrance variants, which contribute a small increase of the risk of developing sporadic PD. This knowledge has the potential to have a major impact in the clinical care of people with PD. We summarise these genetic influences and discuss the implications for therapeutics and clinical trial design.

Associations between lifestyle and amyotrophic lateral sclerosis stratified by C9orf72 genotype: a longitudinal, population-based, case-control study

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is considered to be caused by both genetic and environmental factors. The causal cascade is, however, not known. We aimed to assess lifestyle during the presymptomatic phase of ALS, stratified by C9orf72 mutation, and examine evidence supporting causality of lifestyle factors.

METHODS

This study was a longitudinal, population-based, case-control study that used data from the Prospective ALS study the Netherlands. We included patients with a C9orf72 mutation (C9+ group), patients without a C9orf72 mutation (C9- group), and controls. Patients fulfilled the revised El Escorial criteria and were recruited through neurologists and rehabilitation physicians in the Netherlands as well as the Dutch Neuromuscular Patient Association and ALS Centrum website. 1322 population-based controls, matched for age and sex, were enrolled via the patients' general practitioners. Blood relatives or spouses of patients were not eligible as controls. We studied the relationship between ALS risk and smoking, alcohol, physical activity, body-mass index (BMI), and energy intake by the use of structured questionnaires. Smoking, physical activity, and BMI were longitudinally assessed up to 50 years before onset (defined as the period before onset of muscle weakness or bulbar symptoms for cases, or age at completing the questionnaire for controls). We calculated posterior probabilities (P(θ|x)) for causal effects of smoking, alcohol, and BMI, using Bayesian instrumental variable analyses.

FINDINGS

Between Jan 1, 2006 and Jan 27, 2016, we included 143 patients in the C9+ group, 1322 patients in the C9- group, and 1322 controls. Compared with controls, cigarette pack-years (C9+ group mean difference from control 3·15, 95% CI 0·36 to 5·93, p=0·027; C9- group 3·20, 2·02 to 4·39, p<0·0001) and daily energy intake at symptom onset (C9+ group 712 kJ, 95% CI 212 to 1213, p=0·0053; C9- group 497, 295 to 700, p<0·0001) were higher in the C9+ and C9- groups, whereas current BMI (C9+ group -2·01 kg/m², 95% CI -2·73 to -1·29, p<0·0001; C9- group -1·35, -1·64 to -1·06, p<0·0001) and lifetime alcohol consumption (C9+ group -5388 units, 95% CI -9113 to -1663, p=0·0046; C9- group -2185, -3748 to -622, p=0·0062) were lower in the C9+ and C9- groups. Median BMI during the presymptomatic phase for the C9+ group was lower (-0·69 kg/m², 95% CI -1·24 to -0·13, p=0·015) and physical activity was similar (-348 metabolic equivalent of task [MET], 95% CI -966 to 270, p=0·27) to controls, whereas both the median BMI during the presymptomatic phase (0·27 kg/m², 95% CI 0·04 to 0·50, p=0·022) and physical activity (585 MET, 291 to 878, p=0·0001) were higher in the C9- group than controls. Longitudinal analyses showed more cigarette pack-years in the C9- (starting 47 years pre-onset) and C9+ (starting 24 years pre-onset) groups, and higher physical activity over time in the C9- group (starting >30 years pre-onset). BMI of the C9+ group increased more slowly and was significantly lower (starting at 36 years pre-onset) than in controls, whereas the BMI of the C9- group was higher than controls (23-49 years pre-onset, becoming lower 10 years pre-onset). Instrumental variable analyses supported causal effects of alcohol consumption (P(θ|x)=0·9347) and smoking (P(θ|x)=0·9859) on ALS in the C9- group. We found evidence supporting a causal effect of increased BMI at younger age (mean 33·8 years, SD 11·7) in the C9- group (P[θ|x]=0·9272), but not at older ages.

INTERPRETATION

Lifestyle during the presymptomatic phase differs between patients with ALS and controls decades before onset, depends on C9- status, and is probably part of the presymptomatic causal cascade. Identification of modifiable disease-causing lifestyle factors offers opportunities to lower risk of developing neurodegenerative disease.

FUNDING

Netherlands ALS Foundation.

Challenges in the diagnosis of Parkinson's disease

Parkinson's disease is the second most common neurodegenerative disease and its prevalence has been projected to double over the next 30 years. An accurate diagnosis of Parkinson's disease remains challenging and the characterisation of the earliest stages of the disease is ongoing. Recent developments over the past 5 years include the validation of clinical diagnostic criteria, the introduction and testing of research criteria for prodromal Parkinson's disease, and the identification of genetic subtypes and a growing number of genetic variants associated with risk of Parkinson's disease. Substantial progress has been made in the development of diagnostic biomarkers, and genetic and imaging tests are already part of routine protocols in clinical practice, while novel tissue and fluid markers are under investigation. Parkinson's disease is evolving from a clinical to a biomarker-supported diagnostic entity, for which earlier identification is possible, different subtypes with diverse prognosis are recognised, and novel disease-modifying treatments are in development.

Increased free water in the substantia nigra in idiopathic REM sleep behaviour disorder

Imaging markers sensitive to neurodegeneration in the substantia nigra are critically needed for future disease-modifying trials. Previous studies have demonstrated the utility of posterior substantia nigra free water as a marker of progression in Parkinson's disease. In this study, we tested the hypothesis that free water is elevated in the posterior substantia nigra of idiopathic REM sleep behaviour disorder, which is considered a prodromal stage of synucleinopathy. We applied free-water imaging to 32 healthy control subjects, 34 patients with idiopathic REM sleep behaviour disorder and 38 patients with Parkinson's disease. Eighteen healthy control subjects and 22 patients with idiopathic REM sleep behaviour disorder were followed up and completed longitudinal free-water imaging. Free-water values in the substantia nigra were calculated for each individual and compared among groups. We tested the associations between posterior substantia nigra free water and uptake of striatal dopamine transporter in idiopathic REM sleep behaviour disorder. Free-water values in the posterior substantia nigra were significantly higher in the patients with idiopathic REM sleep behaviour disorder patients than in the healthy control subjects, but were significantly lower in patients with idiopathic REM sleep behaviour disorder than in patients with Parkinson's disease. In addition, we observed significantly negative associations between posterior substantia nigra free-water values and dopamine transporter striatal binding ratios in the idiopathic REM sleep behaviour disorder patients. Longitudinal free-water imaging analyses were conducted with a linear mixed-effects model, and showed a significant Group × Time interaction in posterior substantia nigra, identifying increased mean free-water values in posterior substantia nigra of idiopathic REM sleep behaviour disorder over time. These results demonstrate that free water in the posterior substantia nigra is a valid imaging marker of neurodegeneration in idiopathic REM sleep behaviour disorder, which has the potential to be used as an indicator in disease-modifying trials.

Comprehensive serum metabolic and proteomic characterization on cognitive dysfunction in Parkinson's disease

Background

Given the increased incidence of Parkinson's disease (PD) and the lack of accurate early diagnosis of PD with cognitive impairment (PD-CI), we compared the serum metabolomes and proteomes of 26 patients with PD without cognitive impairment (PD-N) and 31 patients with PD-CI by combining grade-dependent proteomics and metabolomics analyses.

Methods

Logistic and linear regression analyses were performed for differential metabolic indicators, cognition, and clinical diagnosis. Ingenuity pathway analysis (IPA) was used to identify metabolites linked to different pathways. Bioinformatics revealed 16 differentially expressed proteins and 32 metabolites.

Results

The positive metabolic indicators related to the differential proteins were one sphingolipid, five phosphatidylcholines, and five long-chain fatty acids. The obtained metabolic and proteomics IPA network highlighted the central term of this network was inflammation and abnormal lipid metabolism which are prominent in PD-CI. There was a strong negative correlation between the Mini-Mental State Examination (MMSE)score and LPC (18:1). The receiver operating characteristic (ROC) of LPC (18:1) for PD-N and PD-CI showed that the area under the curve (AUC) value was 0.660 (P=0.039).

Conclusions

In conclusion, serum LPC (18:1) is inversely linked to cognition in PD and presented its potential clinical value in distinguishing the presence or absence of cognitive impairment in PD. The deeper implication of our discovery indicates abnormal lipid metabolism is associated with changes of cognitive status and suggests the potential for possibility of immune system- inflammatory involvement.

Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations

Idiopathic Parkinson's Disease (iPD) is a common motor neurodegenerative disorder. It affects more frequently the elderly population, causing a significant emotional burden both for the patient and caregivers, due to the disease-related onset of motor and cognitive disabilities. iPD's clinical hallmark is the onset of cardinal motor symptoms such as bradykinesia, rest tremor, rigidity, and postural instability. However, these symptoms appear when the neurodegenerative process is already in an advanced stage. Furthermore, the greatest challenge is to distinguish iPD from other similar neurodegenerative disorders, "atypical parkinsonisms", such as Multisystem Atrophy, Progressive Supranuclear Palsy and Cortical Basal Degeneration, since they share many phenotypic manifestations, especially in the early stages. The diagnosis of these neurodegenerative motor disorders is essentially clinical. Consequently, the diagnostic accuracy mainly depends on the professional knowledge and experience of the physician. Recent advances in artificial intelligence have made it possible to analyze the large amount of clinical and instrumental information in the medical field. The application machine learning algorithms to the analysis of neuroimaging data appear to be a promising tool for identifying microstructural alterations related to the pathological process in order to explain the onset of symptoms and the spread of the neurodegenerative process. In this context, the search for quantitative biomarkers capable of identifying parkinsonian patients in the prodromal phases of the disease, of correctly distinguishing them from atypical parkinsonisms and of predicting clinical evolution and response to therapy represent the main goal of most current clinical research studies. Our aim was to review the recent literature and describe the current knowledge about the contribution given by machine learning applications to research and clinical management of parkinsonian syndromes.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Therapy of Parkinson's Disease Subtypes

Early descriptions of subtypes of Parkinson's disease (PD) are dominated by the approach of predetermined groups. Experts defined, from clinical observation, groups based on clinical or demographic features that appeared to divide PD into clinically distinct subsets. Common bases on which to define subtypes have been motor phenotype (tremor dominant vs akinetic-rigid or postural instability gait disorder types), age, nonmotor dominant symptoms, and genetic forms. Recently, data-driven approaches have been used to define PD subtypes, taking an unbiased statistical approach to the identification of PD subgroups. The vast majority of data-driven subtyping has been done based on clinical features. Biomarker-based subtyping is an emerging but still quite undeveloped field. Not all of the subtyping methods have established therapeutic implications. This may not be surprising given that they were born largely from clinical observations of phenotype and not in observations regarding treatment response or biological hypotheses. The next frontier for subtypes research as it applies to personalized medicine in PD is the development of genotype-specific therapies. Therapies for GBA-PD and LRRK2-PD are already under development. This review discusses each of the major subtyping systems/methods in terms of its applicability to therapy in PD, and the opportunities and challenges designing clinical trials to develop the evidence base for personalized medicine based on subtypes.

Long noncoding RNA NEAT1 knockdown inhibits MPP+-induced apoptosis, inflammation and cytotoxicity in SK-N-SH cells by regulating miR-212-5p/RAB3IP axis

BACKGROUND

Some long non-coding RNAs (lncRNAs) have been suggested to play critical roles in Parkinson's disease (PD) pathogenesis, including nuclear enriched abundant transcript 1 (NEAT1). The purpose of this study was to further elucidate the molecular mechanism of NEAT1 in PD.

METHODS

The expression levels of NEAT1, miR-212-5p and RAB3A-interacting protein (RAB3IP) were determined by quantitative real-time polymerase chain reaction (qRT-PCR). Cell viability and apoptosis were evaluated by Cell Counting Kit-8 (CCK-8) assay and flow cytometry analysis, respectively. Western blot analysis was applied to detect the protein expression of IL-1β, TNF-α and RAB3IP. The LDH activity, ROS generation and SOD activity were measured by Lactate LDH activity assay kit, ROS assay kit, and SOD activity assay kit, respectively. Dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were performed to verify the relationship between miR-212-5p and NEAT1 or mRNA of RAB3IP. 1-methyl-4-phenylpyridinium ion (MPP⁺)-treated SK-N-SH cells were used as an in vitro model of PD.

RESULTS

NEAT1 and RAB3IP were upregulated while miR-212-5p was downregulated in SK-N-SH cells treated with MPP⁺. NEAT1 knockdown or miR-212-5p overexpression inhibited MPP⁺-induced apoptosis, inflammation and cytotoxicity in SK-N-SH cells. Moreover, miR-212-5p was a direct target of NEAT1 and its downregulation reversed the eff ;ects caused by NEAT1 knockdown in MPP⁺-induced SK-N-SH cells. Furthermore, RAB3IP was a downstream target of miR-212-5p and its overexpression attenuated the effects of miR-212-5p restoration in MPP⁺-induced SK-N-SH cells. Besides, NEAT1 acted as a molecular sponge of miR-212-5p to regulate RAB3IP expression.

CONCLUSION

NEAT1 knockdown suppressed MPP⁺-induced apoptosis, inflammation and cytotoxicity in SK-N-SH cells through regulating miR-212-5p and RAB3IP expression, providing a possible therapeutic strategy for PD patients.

Intracellular delivery of Parkin rescues neurons from accumulation of damaged mitochondria and pathological α-synuclein

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by mitochondrial dysfunction, Lewy body formation, and loss of dopaminergic neurons. Parkin, an E3 ubiquitin ligase, is thought to inhibit PD progression by removing damaged mitochondria and suppressing the accumulation of α-synuclein and other protein aggregates. The present study describes a protein-based therapy for PD enabled by the development of a cell-permeable Parkin protein (iCP-Parkin) with enhanced solubility and optimized intracellular delivery. iCP-Parkin recovered damaged mitochondria by promoting mitophagy and mitochondrial biogenesis and suppressed toxic accumulations of α-synuclein in cells and animals. Last, iCP-Parkin prevented and reversed declines in tyrosine hydroxylase and dopamine expression concomitant with improved motor function induced by mitochondrial poisons or enforced α-synuclein expression. These results point to common, therapeutically tractable features in PD pathophysiology, and suggest that motor deficits in PD may be reversed, thus providing opportunities for therapeutic intervention after the onset of motor symptoms.

Imaging dopamine function and microglia in asymptomatic LRRK2 mutation carriers

Neuroinflammation (microglial activation) and subclinical nigrostriatal dysfunction have been reported in subjects at risk of Parkinsonism. Eight non-manifesting carriers (NMCs) of LRRK2 G2019S mutation had ¹¹C-PK11195 and ¹⁸F-DOPA PET to assess microglial activation and striatal dopamine system integrity, respectively. Comparisons were made with healthy controls. Five LRRK2-NMCs had subclinical reductions of putaminal ¹⁸F-DOPA uptake. Three of them had significantly raised nigral ¹¹C-PK11195 binding bilaterally. These findings indicate that nigrostriatal dysfunction and neuroinflammation occur in LRRK2-NMCs. Studies in larger cohorts with appropriate follow-up are needed to elucidate the significance of neuroinflammation in the premotor phase of LRRK2-PD.

Neuropsychiatric aspects of Parkinson disease psychopharmacology: Insights from circuit dynamics

Parkinson disease (PD) is a neurodegenerative disorder with a complex pathophysiology characterized by the progressive loss of dopaminergic neurons within the substantia nigra. Persons with PD experience several motoric and neuropsychiatric symptoms. Neuropsychiatric features of PD include depression, anxiety, psychosis, impulse control disorders, and apathy. In this chapter, we will utilize the National Institutes of Mental Health Research Domain Criteria (RDoC) to frame and integrate observations from two prevailing disease constructions: neurotransmitter anomalies and circuit physiology. When there is available evidence, we posit how unified translational observations may have clinical relevance and postulate importance outside of PD. Finally, we review the limited evidence available for pharmacologic management of these symptoms.

Patients' views on the ethical challenges of early Parkinson disease detection

Objective

To evaluate the point of view of patients with Parkinson disease (PD) on early detection and risk disclosure in the prodromal phase of PD and to derive recommendations for an ethical framework for the recruitment of prodromal PD cohorts.

Methods

A standardized questionnaire to evaluate the patients' perception on early diagnosis in PD was designed by an interdisciplinary study group. After testing in a preliminary feasibility study (n = 20), the survey was performed retrospectively with patients from our clinic.

Results

A total of 101 patients with PD answered the questions. The majority of patients reported that time from onset of motor symptoms to diagnosis was burdensome, including false diagnoses and many consultations of various medical specialists. However, most of the patients evaluated early risk disclosure with skepticism. Freedom of choice and the potential of changes in lifestyle were rated as important.

Conclusion

Although patients with PD reported the time to diagnosis retrospectively as burdensome, the majority was skeptical regarding early disclosure of risk, especially with regard to the lack of pharmacologic options. Circumstances under which early detection and disclosure would have been approved by the majority of patients were (1) advice on lifestyle changes (exercise, nutrition) as potentially disease course–modifying therapy; (2) the establishment of an early diagnosis “culture,” including early clarification of the patients' wish to know; and (3) regular support and follow-up of individuals after risk disclosure.

Leptin mediates protection of hydrogen sulfide against 6-hydroxydopamine-induced Parkinson's disease: Involving enhancement in Warburg effect

BACKGROUND

Hydrogen sulfide (H₂S) has therapeutic effects on Parkinson's disease (PD). Warburg effect, namely aerobic glycolysis, is benefit to PD. Leptin, a hormone secreted in adipose, plays an important role in the treatment of PD.

OBJECTIVE

To determine whether the mechanism underlying protection of H₂S against PD is involved in promoting Warburg effect via upregulation of leptin.

METHODS

We set a PD model via unilateral intrastriatal injection of 6-hydroxydopamine (6-OHDA) in Sprague Dawley rat. PD-like behavior was analyzed by apomorphine-induced rotations, open field activity test, stepping test and cylinder test. Dopaminergic neurons were detected by immunohistochemistry. The expressions of Hexokinase-2, pyruvate kinase M-2, lactate dehydrogenase, pyruvate dehydrogenase kinase, pyruvate dehydrogenase, and leptin were measured by Western blot. Lactate dehydrogenase (LDHA) activity was monitored by ELISA. The lactate content was measured by lactate assay kit.

RESULTS

We showed that NaHS (a donor of H₂S) prevented 6-OHDA-induced PD-like behaviors as well as the loss of dopaminergic neurons. We also found that NaHS enhanced the Warburg effect and upregulated leptin expression in the substantia nigra of 6-OHDA-exposed rats. While, inhibited leptin signaling by OBR13-A reversed the protections of H₂S against 6-OHDA-exerted PD-like behaviors and the loss of dopaminergic neurons in the substantia nigra, and abolished H₂S-enhanced in the Warburg effect in the substantia nigra.

CONCLUSION

These data indicated that leptin mediates the protection of H₂S against PD, which involves enhancing the Warburg effect of the substantia nigra.

LRRK2 in Parkinson disease: challenges of clinical trials

One of the most common monogenic forms of Parkinson disease (PD) is caused by mutations in the LRRK2 gene that encodes leucine-rich repeat kinase 2 (LRRK2). LRRK2 mutations, and particularly the most common mutation Gly2019Ser, are observed in patients with autosomal dominant PD and in those with apparent sporadic PD, who are clinically indistinguishable from those with idiopathic PD. The discoveries that pathogenic mutations in the LRRK2 gene increase LRRK2 kinase activity and that small-molecule LRRK2 kinase inhibitors can be neuroprotective in preclinical models of PD have placed LRRK2 at the centre of disease modification efforts in PD. Recent investigations also suggest that LRRK2 has a role in the pathogenesis of idiopathic PD and that LRRK2 therapies might, therefore, be beneficial in this common subtype of PD. In this Review, we describe the characteristics of LRRK2-associated PD that are most relevant to the development of LRRK2-targeted therapies and the design and implementation of clinical trials. We highlight strategies for correcting the effects of mutations in the LRRK2 gene, focusing on how to identify which patients are the optimal candidates and how to decide on the timing of such trials. In addition, we discuss challenges in implementing trials of disease-modifying treatment in people who carry LRRK2 mutations.

Best Practices for Generating and Using Alpha-Synuclein Pre-Formed Fibrils to Model Parkinson's Disease in Rodents

Parkinson’s disease (PD) is the second most common neurodegenerative disease, affecting approximately one-percent of the population over the age of sixty. Although many animal models have been developed to study this disease, each model presents its own advantages and caveats. A unique model has arisen to study the role of alpha-synuclein (aSyn) in the pathogenesis of PD. This model involves the conversion of recombinant monomeric aSyn protein to a fibrillar form—the aSyn pre-formed fibril (aSyn PFF)—which is then injected into the brain or introduced to the media in culture. Although many groups have successfully adopted and replicated the aSyn PFF model, issues with generating consistent pathology have been reported by investigators. To improve the replicability of this model and diminish these issues, The Michael J. Fox Foundation for Parkinson’s Research (MJFF) has enlisted the help of field leaders who performed key experiments to establish the aSyn PFF model to provide the research community with guidelines and practical tips for improving the robustness and success of this model. Specifically, we identify key pitfalls and suggestions for avoiding these mistakes as they relate to generating the aSyn PFFs from monomeric protein, validating the formation of pathogenic aSyn PFFs, and using the aSyn PFFs in vivo or in vitro to model PD. With this additional information, adoption and use of the aSyn PFF model should present fewer challenges, resulting in a robust and widely available model of PD.

AAV-Mediated Expression of Dominant-Negative ULK1 Increases Neuronal Survival and Enhances Motor Performance in the MPTP Mouse Model of Parkinson's Disease

Loss of nigrostriatal projections by axonal degeneration is a key early event in Parkinson's disease (PD) pathophysiology, being accountable for the lack of dopamine in the nigrostriatal system and resulting in motor symptoms such as bradykinesia, rigidity, and tremor. Since autophagy is an important mechanism contributing to axonal degeneration, we aimed to evaluate the effects of competitive autophagy inhibition in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of PD in vivo. Adeno-associated viral vector (AAV)-mediated overexpression of a dominant-negative form of the unc-51 like autophagy-initiating kinase (ULK1.DN) in the substantia nigra was induced 3 weeks before MPTP treatment. Analysis of motor behavior demonstrated a significant improvement of ULK1.DN expressing mice after MPTP treatment. Immunohistochemical analyses of dopaminergic nigral neurons and nigrostriatal projections revealed a significant protection from MPTP-induced neurotoxicity after ULK1.DN expression. Western blot analysis linked these findings to an activation of mTOR signaling. Taken together, our results indicate that expression of ULK1.DN can attenuate MPTP-induced axonal neurodegeneration, suggesting that ULK1 could be a promising novel target in the treatment of PD.

Neurorehabilitation Improves the Motor Features in Prodromal SCA2: A Randomized, Controlled Trial

BACKGROUND

The search for early interventions is a novel approach in spinocerebellar ataxias, but there are few studies supporting this notion. This article aimed to assess the efficacy of neurorehabilitation treatment in prodromal spinocerebellar ataxia type 2.

METHODS

Thirty spinocerebellar ataxia type 2 preclinical carriers were enrolled in a randomized, controlled trial using neurorehabilitation. The intervention in the treated group was 4 hours per day, 5 days per week for 12 weeks, emphasizing static balance, gait, and limb coordination. The control group did not receive rehabilitation. The primary outcome measure was the time for 5-m tandem gait over the floor. Secondary outcomes included other timed tests with increased motor complexity, as well as the scores of the SARA and the Inventory of Non-ataxia Symptoms.

RESULTS

The times for 5-m tandem gait over the floor and the mattress were significantly reduced only in the rehabilitated group. Moreover, the times upholding the tandem stance over a mattress and the seesaw were notably increased only in this group. Likewise, the finger-nose and the heel-shin tests were improved in the rehabilitated group alone. The SARA score and the count of nonataxia symptoms were unchanged.

CONCLUSIONS

This rehabilitation program improves the subtle gait, postural and coordinative deficits in prodromal spinocerebellar ataxia type 2, which provided novel hints about the preservation of motor learning and neural plasticity mechanisms in early disease stages, leading chances for other interventional approaches in this and other spinocerebellar ataxias. © 2019 International Parkinson and Movement Disorder Society.

Predicting diagnosis of Parkinson's disease: A risk algorithm based on primary care presentations

BACKGROUND

Diagnosis of Parkinson's disease (PD) is typically preceded by nonspecific presentations in primary care.

OBJECTIVES

The objective of this study was to develop and validate a prediction model for diagnosis of PD based on presentations in primary care.

SETTING

The settings were general practices providing data for The Health Improvement Network UK primary care database.

METHODS

Data from 8,166 patients aged older than age 50 years with incident diagnosis of PD and 46,755 controls were analyzed. Likelihood ratios, sensitivity, specificity, and positive and negative predictive values for individual symptoms and combinations of presentations were calculated. An algorithm for risk of diagnosis of PD within 5 years was calculated using multivariate logistic regression analysis. Split sample analysis was used for model validation with a 70% development sample and a 30% validation sample.

RESULTS

Presentations independently and significantly associated with later diagnosis of PD in multivariate analysis were tremor, constipation, depression or anxiety, fatigue, dizziness, urinary dysfunction, balance problems, memory problems and cognitive decline, hypotension, rigidity, and hypersalivation. The discrimination and calibration of the risk algorithm were good with an area under the curve of 0.80 (95% confidence interval 0.78-0.81). At a threshold of 5%, 37% of those classified as high risk would be diagnosed with PD within 5 years and 99% of those who were not classified as high risk would not be diagnosed with PD.

CONCLUSION

This risk algorithm applied to routine primary care presentations can identify individuals at increased risk of diagnosis of PD within 5 years to allow for monitoring and earlier diagnosis of PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Parkinson's disease: Diagnosis and appreciation of comorbidities

Parkinson's disease (PD) is a complex neuropsychiatric disorder that manifests with a variety of motor and nonmotor symptoms. Its incidence increases with age. It is important for clinicians to be able to distinguish symptoms of aging and other comorbidities from those of PD. The diagnosis of PD has traditionally been rendered using strict criteria that mainly rely on the cardinal motor symptoms of rest tremor, rigidity, and bradykinesia. However, newer diagnostic criteria proposed by the Movement Disorders Society for diagnosis of PD collectively reflect a greater appreciation for the nonmotor symptoms. The treatment of PD remains symptomatic and the most noticeable improvements have been documented in the motor symptoms. Levodopa remains the gold standard for therapy, however there are now many other potential medical and surgical treatment strategies. Nonmotor symptoms have been shown to affect quality of life more than the motor symptoms. There is ongoing research into symptomatic and disease modifying treatments. Given the multisystem involvement in PD, an interdisciplinary patient-centered approach is recommended by most experts. This chapter addresses first the diagnostic approach and the many geriatric considerations. This is followed by a review of the nonmotor symptoms. Finally, a summary of current treatment strategies in PD is presented along with potential treatment complications.

PPAR-γ agonist pioglitazone reduces microglial proliferation and NF-κB activation in the substantia nigra in the 6-hydroxydopamine model of Parkinson's disease

BACKGROUND

Peroxisome proliferator-activated receptor γ (PPAR-γ) agonists have received much attention in research because of their neuroprotective and anti-inflammatory effects that reduce cell death and halt the progression of neurodegeneration. Thus, this study observed the pioglitazone effects on the main inflammatory markers after 6-hydroxydopamine (6-OHDA) lesion.

METHODS

The effects of a 5-day administration of the PPAR-γ agonist pioglitazone (30 mg/kg) in male Wistar rats that received bilateral intranigral infusions of 6-OHDA. After surgery, the rats were evaluated in the open-field test on days 1,7,14, and 21. Immediately after the behavioral tests on day 21, the rats were euthanized, and the substantia nigra was removed to analyze the expression of nuclear factor κB (NF-κB) and IκB by western blot. To immunohistochemical, animals were intracardially perfused, with brain removal that was frozen and sectioned, being selected slices of the SNc region to detect tyrosine hydroxylase (TH) immunoreactivity, microglia activation (Iba-1) and NF-κB translocation in the nucleus.

RESULTS

Pioglitazone protected rats against hypolocomotion and 6-OHDA-induced dopaminergic neurodegeneration on day 7. Decreases in the microglial activation and the NF-κB expression were observed, and the p65 activation was inhibited.

CONCLUSIONS

These results suggest that pioglitazone may be a potential adjuvant for the treatment of Parkinson`s disease because of its effects on pathological markers of the progression of neurodegeneration.

Mitochondrial dysfunction and increased glycolysis in prodromal and early Parkinson's blood cells

Background: Although primarily a neurodegenerative process, there is increasing awareness of peripheral disease mechanisms in Parkinson's disease. To investigate disease processes in accessible patient cells, we studied peripheral blood mononuclear cells in recently diagnosed PD patients and rapid eye movement‐sleep behavior disorder patients who have a greatly increased risk of developing PD. We hypothesized that peripheral blood mononuclear cells may recapitulate cellular pathology found in the PD brain and investigated these cells for mitochondrial dysfunction and oxidative stress.

Methods: Peripheral blood mononuclear cells were isolated and studied from PD patients, rapid eye movement‐sleep behavior disorder patients and age‐ and sex‐matched control individuals from the well‐characterized Oxford Discovery cohort. All participants underwent thorough clinical assessment.

Results: Initial characterization showed that PD patients had elevated levels of CD14 + monocytes and monocytes expressing C‐C motif chemokine receptor 2. Mitochondrial dysfunction and oxidative stress were increased in PD patient peripheral blood mononuclear cells, with elevated levels of mitochondrial reactive oxygen species specifically in patient monocytes. This was combined with reduced levels of the antioxidant superoxide dismutase in blood cells from PD patients and, importantly, also in rapid eye movement‐sleep behavior disorder patients. This mitochondrial dysfunction was associated with a concomitant increase in glycolysis in both PD and rapid eye movement‐sleep behavior disorder patient blood cells independent of glucose uptake or monocyte activation.

Conclusions: This work demonstrates functional bioenergetic deficits in PD and rapid eye movement‐sleep behavior disorder patient blood cells during the early stages of human disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

The Effectiveness of Reality Orientation Therapy in the Treatment of Parkinson Disease Dementia

Patients with Parkinson disease dementia (PDD) have deficits resulting mainly from frontostriatal dysfunction. The aim of this study was to assess the effectiveness of reality orientation therapy (ROT) combined with drug therapy (acetylcholinesterase inhibitors) in PDD treatment and compare it with that of drug therapy alone. Patients (n = 12) with a diagnosis of PDD were divided into 2 groups: group A-drug therapy and ROT; group B-drug therapy alone. Reality orientation therapy was applied weekly for 6 months, and patients were assessed during the same period. Significant improvements in frontostriatal deficits were observed in the group that received the combined therapy, as shown mainly by the scores in verbal fluency in the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery ( P = .02) and in attention in Scales for outcomes of Parkinson's Disease-Cognition ( P = .021) and Clock Drawing Test ( P = .037). Patients who received only medication had worse results in constructional praxis recall in the CERAD battery ( P = .037). Our results indicate that ROT may help in the treatment of frontostriatal cognitive deficits and can potentially be used to complement drug therapy.

An early diagnosis is not the same as a timely diagnosis of Parkinson's disease

Parkinson’s disease is a common neurodegenerative condition that has significant costs to the individual patient and to society. The pathology starts up to a decade before symptoms are severe enough to allow a diagnosis using current criteria. Although the search for disease-modifying treatment continues, it is vital to understand what the right time is for diagnosis. Diagnosis of Parkinson’s disease is based on the classic clinical criteria, but the presence of other clinical features and disease biomarkers may allow earlier diagnosis, at least in a research setting. In this review, we identify the benefits of an early diagnosis, including before the classic clinical features occur. However, picking the right point for a “timely” diagnosis will vary depending on the preferences of the individual patient, efficacy (or existence) of disease-modifying treatment, and the ability for health systems to provide support and management for individuals at every stage of the disease. Good evidence for the quality-of-life benefits of existing symptomatic treatment supports the argument for earlier diagnosis at a time when symptoms are already present. This argument would be significantly bolstered by the development of disease-modifying treatments. Benefits of early diagnosis and treatment would affect not only the individual (and their families) but also the wider society and the research community. Ultimately, however, shared decision-making and the principles of autonomy, beneficence, and non-maleficence will need to be applied on an individual basis when considering a “timely” diagnosis.

Performance of the Movement Disorders Society criteria for prodromal Parkinson's disease: A population-based 10-year study

OBJECTIVE

We aimed to identify prodromal Parkinson's disease (PD) and its predictive accuracy for incident PD in an unselected elderly population and to estimate the relevance of this approach for future neuroprotection trials.

METHODS

We applied the recently published Movement Disorders Society (MDS) research criteria for prodromal PD to participants of the prospective population-based Bruneck Study of the 2005 assessment (n = 574, ages 55-94 years). Cases of incident PD were identified at 3-year, 5-year, and 10-year follow-up visits. We calculated predictive accuracies of baseline prodromal PD status for incident cases, and, based on them, estimated sample sizes for neuroprotection trials with conversion to PD as the primary outcome.

RESULTS

Baseline status of probable prodromal PD (n = 12) had a specificity in predicting incident PD of 98.8% (95% confidence interval, 97.3%-99.5%), a sensitivity of 66.7% (29.6%-90.8%), and a positive predictive value of 40.0% (16.7%-68.8%) over 3 years. Specificity remained stable with increasing follow-up time, sensitivity decreased to 54.6% (28.0%-78.8%) over 5 years and to 35.0% (18.0%-56.8%) over 10 years, whereas positive predictive value rose to 60.0% (31.2%-83.3%) and 77.8% (44.3%-94.7%), respectively. Sample size estimates at 80% power in an intention-to-treat approach ranged from 108 to 540 patients with probable prodromal PD depending on trial duration (3-5 years) and effect size of the agent (30%-50%).

CONCLUSIONS

Our findings show that the MDS criteria for prodromal PD yield moderate to high predictive power for incident PD in a community-based setting and may thus be helpful to define target populations of future neuroprotection trials. © 2018 International Parkinson and Movement Disorder Society.

Lack of pathogenic potential of peripheral α-synuclein aggregates from Parkinson's disease patients

In Parkinson's disease (PD) there is widespread accumulation in the brain of abnormal α-synuclein aggregates forming intraneuronal Lewy bodies (LB). It is now well established that LB-type α-synuclein aggregates also occur in the peripheral autonomic nervous system in PD, from where it has been speculated they may progressively spread to the central nervous system through synaptically-connected brain networks and reach the substantia nigra to trigger herein dopaminergic dysfunction/degeneration and subsequent parkinsonism. Supporting a pathogenic role for α-synuclein aggregates we have previously shown that LB purified from postmortem PD brains promote α-synuclein pathology and dopaminergic neurodegeneration when intracerebrally inoculated into wild-type mice. However, the pathogenic capacity of PD-derived peripheral α-synuclein aggregates remains unknown. Here we addressed this question using purified LB-type α-synuclein aggregates from postmortem PD stellate ganglia (SG), a paravertebral sympathetic ganglion that exhibits consistent and conspicuous Lewy pathology in all PD patients. In contrast to our previous findings using nigral LB extracts, intracerebral inoculation of SG-derived LB into mice did not trigger long-term nigrostriatal neurodegeneration nor α-synuclein pathology. The differential pathogenic capacities of central- and peripheral-derived α-synuclein aggregates appear independent of the absolute amount and basic biochemical properties of α-synuclein within these aggregates and may rely instead on differences in α-synuclein conformation and/or yet unrecognized brain region-specific intrinsic factors. Our results argue against a putative pathogenic capacity of peripheral α-synuclein aggregates to promote α-synuclein pathology in the brain, propagate between neuronal networks or induce neurodegeneration.

A Perspective on Wearable Sensor Measurements and Data Science for Parkinson's Disease

Miniaturized and wearable sensor-based measurements enable the assessment of Parkinson's disease (PD) motor-related features like never before and hold great promise as non-invasive biomarkers for early and accurate diagnosis, and monitoring the progression of PD. High-fidelity human movement reconstruction and simulation can already be conducted in a clinical setting with increasingly precise and affordable motion technology enabling access to high-quality labeled data on patients' subcomponents of movement (kinematics and kinetics). At the same time, body-worn sensors now allow us to extend some quantitative movement-related measurements to patients' daily living activities. This era of patient movement "cognification" is bringing us previously inaccessible variables that encode patients' movement, and that, together with measures from clinical examinations, poses new challenges in data analysis. We present herein examples of the application of an unsupervised methodology to classify movement behavior in healthy individuals and patients with PD where no specific knowledge on the type of behaviors recorded is needed. We are most certainly leaving the early stage of the exponential curve that describes the current technological evolution and soon will be entering its steep ascent. But there is already a benefit to be derived from current motion technology and sophisticated data science methods to objectively measure parkinsonian impairments.