Parkinson's Disease Field Research Articles

Chapter 6 - Clinical/surgical considerations

While there are a diverse number of indications for the potential use of cell and gene therapies in people, many of the medical conditions being treated need to consider some general clinical and surgical issues, not only in designing clinical trials, but also in the eventual application of the therapy if shown to be successful. Such issues include the precision of the diagnosis and stage of disease, the presence of significant comorbidity, as well as the challenges that may be encountered in trial designs involving the neurosurgical delivery of these advanced interventions. This chapter discusses details of these issues that have arisen particularly in the field of Parkinson disease and other forms of neurodegeneration, although the general principles and considerations discussed may be equally relevant to other neurologic and nonneurologic conditions.

Identification of genetic risk loci and causal insights associated with Parkinson's disease in African and African admixed populations: a genome-wide association study

An understanding of the genetic mechanisms underlying diseases in ancestrally diverse populations is an important step towards development of targeted treatments. Research in African and African admixed populations can enable mapping of complex traits, because of their genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns. We aimed to do a comprehensive genome-wide assessment in African and African admixed individuals to better understand the genetic architecture of Parkinson's disease in these underserved populations. We performed a genome-wide association study (GWAS) in people of African and African admixed ancestry with and without Parkinson's disease. Individuals were included from several cohorts that were available as a part of the Global Parkinson's Genetics Program, the International Parkinson's Disease Genomics Consortium Africa, and 23andMe. A diagnosis of Parkinson's disease was confirmed clinically by a movement disorder specialist for every individual in each cohort, except for 23andMe, in which it was self-reported based on clinical diagnosis. We characterised ancestry-specific risk, differential haplotype structure and admixture, coding and structural genetic variation, and enzymatic activity. We included 197 918 individuals (1488 cases and 196 430 controls) in our genome-wide analysis. We identified a novel common risk factor for Parkinson's disease (overall meta-analysis odds ratio for risk of Parkinson's disease 1·58 [95% CI 1·37-1·80], p=2·397 × 10-14) and age at onset at the GBA1 locus, rs3115534-G (age at onset β=-2·00 [SE=0·57], p=0·0005, for African ancestry; and β=-4·15 [0·58], p=0·015, for African admixed ancestry), which was rare in non-African or non-African admixed populations. Downstream short-read and long-read whole-genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. The identified signal seems to be associated with decreased glucocerebrosidase activity. Our study identified a novel genetic risk factor in GBA1 in people of African ancestry, which has not been seen in European populations, and it could be a major mechanistic basis of Parkinson's disease in African populations. This population-specific variant exerts substantial risk on Parkinson's disease as compared with common variation identified through GWAS and it was found to be present in 39% of the cases assessed in this study. This finding highlights the importance of understanding ancestry-specific genetic risk in complex diseases, a particularly crucial point as the Parkinson's disease field moves towards targeted treatments in clinical trials. The distinctive genetics of African populations highlights the need for equitable inclusion of ancestrally diverse groups in future trials, which will be a valuable step towards gaining insights into novel genetic determinants underlying the causes of Parkinson's disease. This finding opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk of Parkinson's disease. The Global Parkinson's Genetics Program, which is funded by the Aligning Science Across Parkinson's initiative, and The Michael J Fox Foundation for Parkinson's Research.

Racial and Ethnic Disparities in Parkinson Disease: A Call to Action.

Health disparities are pervasive in the United States. In the field of Parkinson disease (PD), profound racial and ethnic disparities exist in diagnosis, treatment, and research participation, leading to differential health outcomes and lack of generalizable research data. Racial and ethnic disparities not only limit our understanding of this complex heterogeneous disorder but also hamper our ability to provide new evidence-based care for America's most vulnerable populations. In this report, we summarize findings from our comprehensive white paper for the Michael J. Fox Foundation that reviews the current state of knowledge on racial and ethnic disparities in PD care in the following areas: epidemiology, etiology, phenotype and diagnosis, treatment, and research. We also identify knowledge gaps and necessary policy changes to ensure equitable, high-value care for all persons with PD. These strategies are designed to help identify and reduce health disparities among persons with PD and may serve as a model for other neurologic diseases.

Parkinson’s Disease Detection using Machine Learning Algorithms

Abstract: The main goal of the study is to inspect the performance of the different Supervised Algorithms for the improving the Parkinson Disease diagnosis by detection. We have used Five machine learning techniques for the detection of Parkinson Disease datasets. KNN,LR,DT,NB and XGBoost were used for the prediction of Parkinson Disease. The Performance of the classifiers is evaluated via, precission, Accuracy, F1-Score, Recall and Support. Where after computing with different classifier we got result as KNN shows the accuracy level 96% for Parkinson Disease. XGBoost achieved the second highest classification accuracy of 91%. Moreover, in the terms of accuracy for analyzing the Parkinson Disease dataset ,NB achieved the lowest accuracy of 76%. In our study has emphasized the current Parkinson Disease research trends and scope in relational to clinical research fields by machine learning technique .That will be effective impact in field of Parkinson Disease.

A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM.

In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As this often leads to inaccurate evaluations, a more objective system for symptom monitoring in a patient's daily life is claimed. In this regard, the use of wearable medical devices is crucial. This study aims at presenting a review on STAT-ONTM, a wearable medical device Class IIa, which provides objective information on the distribution and severity of PD motor symptoms in home environments. The sensor analyzes inertial signals, with a set of validated machine learning algorithms running in real time. The device was developed for 12 years, and this review aims at gathering all the results achieved within this time frame. First, a compendium of the complete journey of STAT-ONTM since 2009 is presented, encompassing different studies and developments in funded European and Spanish national projects. Subsequently, the methodology of database construction and machine learning algorithms design and development is described. Finally, clinical validation and external studies of STAT-ONTM are presented.

Drug repurposing strategies of relevance for Parkinson's disease.

Parkinson's disease is a highly disabling, progressive neurodegenerative disease that manifests as a mix of motor and non‐motor signs. Although we are equipped with some symptomatic treatments, especially for the motor signs of the disease, there are still no established disease‐modifying drugs so the disease progresses unchecked. Standard drug discovery programs for disease‐modifying therapies have provided key insights into the pathogenesis of Parkinson's disease but, of the many positive candidates identified in pre‐clinical studies, none has yet translated into a successful clinically efficacious drug. Given the huge cost of drug discovery programs, it is not surprising that much attention has turned toward repurposing strategies. The trialing of an established therapeutic has the advantage of bypassing the need for preclinical safety testing and formulation optimization, thereby cutting both time and costs involved in getting a treatment to the clinic. Additional reduced failure rates for repurposed drugs are also a potential bonus. Many different strategies for drug repurposing are open to researchers in the Parkinson's disease field. Some of these have already proven effective in identifying suitable drugs for clinical trials, lending support to such approaches. In this review, we present a summary of the different strategies for drug repurposing, from large‐scale epidemiological correlation analysis through to single‐gene transcriptional approaches. We provide examples of past or ongoing studies adopting each strategy, where these exist. For strategies that have yet to be applied to Parkinson's disease, their utility is illustrated using examples taken from other disorders.

Menagerie: A text-mining tool to support animal-human translation in neurodegeneration research.

Discovery studies in animals constitute a cornerstone of biomedical research, but suffer from lack of generalizability to human populations. We propose that large-scale interrogation of these data could reveal patterns of animal use that could narrow the translational divide. We describe a text-mining approach that extracts translationally useful data from PubMed abstracts. These comprise six modules: species, model, genes, interventions/disease modifiers, overall outcome and functional outcome measures. Existing National Library of Medicine natural language processing tools (SemRep, GNormPlus and the Chemical annotator) underpin the program and are further augmented by various rules, term lists, and machine learning models. Evaluation of the program using a 98-abstract test set achieved F1 scores ranging from 0.75-0.95 across all modules, and exceeded F1 scores obtained from comparable baseline programs. Next, the program was applied to a larger 14,481 abstract data set (2008-2017). Expected and previously identified patterns of species and model use for the field were obtained. As previously noted, the majority of studies reported promising outcomes. Longitudinal patterns of intervention type or gene mentions were demonstrated, and patterns of animal model use characteristic of the Parkinson's disease field were confirmed. The primary function of the program is to overcome low external validity of animal model systems by aggregating evidence across a diversity of models that capture different aspects of a multifaceted cellular process. Some aspects of the tool are generalizable, whereas others are field-specific. In the initial version presented here, we demonstrate proof of concept within a single disease area, Parkinson's disease. However, the program can be expanded in modular fashion to support a wider range of neurodegenerative diseases.

Dispositional optimism, depression, disability and quality of life in Parkinson's disease.

Very little research on dispositional optimism (DO) has been carried out in the field of Parkinson's disease (PD). The present cross-sectional study, focusing on this personality trait, was performed with two main aims: i) to compare DO between patients with PD and a control group (CG); ii) to perform, in the PD group, a regression analysis including health-related variables, such as depression, anxiety, quality of life (QoL) and activities of daily living. Seventy PD participants and 70 healthy volunteers were enrolled in the study. The Mann-Whitney test was used to compare life orientation between the PD and CG groups. In the PD group, Pearson's correlation analysis was used to investigate the relationship between the measures of DO and the other variables. Means of log-linear regression were also used. Mean ratios adjusted for sex, age, education, and severity of disease were estimated, with relative 95% confidence intervals and p-values. The main results were as follows: i) no significant difference in DO was found between the PD participants and the CG; ii) DO was positively associated with QoL and emotional distress and inversely correlated with the Unified Parkinson's Disease Rating Scale; iii) DO was not correlated with disability. In conclusion, high DO predicts a satisfactory quality of life, low emotional distress and reduced disease severity in PD.

Twenty Sixth Annual Symposium on Etiology, Pathogenesis, and Treatment of Parkinson Disease and Other Movement Disorders

AbstractTo be held on Friday, 11 May 2012, in the Four Seasons Ballroom at the Four Seasons, Irving, Texas, 8:00 a.m. to 1:00 p.m.The symposium will consist of current issues in Parkinson disease and other movement disorders. There will be peer‐reviewed platform and poster presentations designed to communicate recent research advances, including new pharmacological and non‐pharmacological treatment options in the field of Parkinson disease, Huntington disease, ataxia, dystonia, myoclonus, Tourette's syndrome, tremor and other movement disorders. © .

Premotor Parkinson disease

In February 2008, supported by an unrestricted educational grant from Lundbeck and Teva, a group of clinical researchers and scientists in the field of Parkinson disease (PD) scheduled a 1-day meeting to discuss current issues around two important research areas in PD: the early stages of PD, and new prospects for neuroprotective therapies. During the past 20 years, we have witnessed fundamental changes in our understanding of PD, but these two areas of intense research have dramatically expanded our knowledge of when and where in the nervous system PD starts, and have also contributed to the development of appropriate drug trials on disease modification. We now …