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NeuroSci
Special Issues
Parkinson's Disease Research: Current Insights and Future Directions
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Parkinson's Disease Research: Current Insights and Future Directions

A special issue of NeuroSci (ISSN 2673-4087).

Deadline for manuscript submissions: 25 June 2025 | Viewed by 2871

Special Issue Editor

Dr. Ikuko Miyazaki

E-Mail Website
Guest Editor
Department of Medical Neurobiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, Okayama 700-8558, Japan
Interests: Parkinson’s Disease; neurological disorders; neuroscience; neurobiology; neuron-glia interaction; neuropharmacology; neurotoxicology

Special Issue Information

Dear Colleagues,

Parkinson’s disease (PD) is a debilitating neurodegenerative disorder with a complex pathophysiology, significantly affecting the motor and non-motor functions of millions globally. Despite extensive research efforts, the precise mechanisms underlying PD remain elusive, and current treatments primarily offer symptomatic relief without addressing disease progression. The need for innovative therapeutic strategies and early diagnostic tools is more pressing than ever.

This Special Issue aims to provide a comprehensive overview of the latest advancements in PD research, emphasizing current insights and exploring future directions for effective diagnosis, treatment, and management. We seek to gather cutting-edge research and expert opinions that can deepen our understanding of PD and pave the way for novel therapeutic approaches.

The main focus of this Special Issue will be the evaluation of molecular pathways as pharmacological targets for treatment strategies that may improve the management of Parkinson’s disease. This Special Issue will provide a platform for all pharmaceutical and translational scientists to research important breakthroughs in drug discovery and new therapeutics in this field.

Potential topics include, but are not limited to, those listed below.

Pathophysiology and Molecular Mechanisms

  • Investigations into the genetic, epigenetic, and biochemical pathways involved in PD.
  • Role of α-synuclein aggregation, mitochondrial dysfunction, neuroinflammation, and oxidative stress.

Biomarkers for Early Detection

  • Identification and validation of biomarkers for early and accurate diagnosis.
  • Neuroimaging techniques, cerebrospinal fluid analysis, and blood-based biomarkers.

Innovative Therapeutic Approaches

  • Advances in pharmacological treatments targeting specific molecular pathways.
  • Non-pharmacological therapies such as deep brain stimulation, gene therapy, and stem cell transplantation.

Neuroprotective Strategies

  • Strategies to slow or halt disease progression.
  • Study of neuroprotective agents, lifestyle interventions (diet, exercise), and their impact on disease course.

Genetics and Personalized Medicine

We are pleased to invite you to contribute original articles, reviews, communications, and other forms of scholarly work. We look forward to your contributions to this Special Issue.

Dr. Ikuko Miyazaki
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. NeuroSci is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Parkinson's disease
  • α-synuclein aggregation
  • mitochondrial dysfunction
  • neuroinflammation
  • oxidative stress
  • neuroimaging

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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12 pages, 837 KiB  
Article
Intensive Speech Therapy for Hypokinetic Dysarthria in Parkinson’s Disease: Targeting the Five Subsystems of Speech Production with Clinical and Instrumental Evaluation
by Annalisa Gison, Marco Ruggiero, Davide Tufarelli, Stefania Proietti, Daniela Moscariello and Marianna Valente
NeuroSci 2025, 6(1), 7; https://doi.org/10.3390/neurosci6010007 - 16 Jan 2025
Viewed by 793
Abstract
Background: Hypokinetic dysarthria is a speech disorder observed in almost 90% of PD patients that can appear at any stage of the disease, usually worsening as the disease progresses. Today, speech therapy intervention in PD is seen as a possible therapeutic option [...] Read more.
Background: Hypokinetic dysarthria is a speech disorder observed in almost 90% of PD patients that can appear at any stage of the disease, usually worsening as the disease progresses. Today, speech therapy intervention in PD is seen as a possible therapeutic option to alleviate and slow down the progression of symptoms. This study aims to investigate the validity of traditional speech therapy in dysarthria with the aim of improving the quality of life of PD patients, by comparing subjective clinical assessment with objective instrumental measures (IOPI and voice analysis). Methods: This is an observational study of 30 patients with hypokinetic dysarthria due to PD. The patients underwent speech therapy treatment with a frequency of three times per week for 12 consecutive weeks. Patients were evaluated at the time of enrollment (T0), at the start of treatment (T1), and at the end of the same (T2). Six months after the end of treatment (T3), a follow-up was performed based on disability and phonatory evaluation. Results: This study showed significant improvements (<0.001) from the start (T1) to the end of treatment (T2), with increases in the Barthel Index score, Robertson Dysarthria Profile, and IOPI measurements for tongue and lip strength, along with enhanced phonometer scores and tongue endurance. Correlations highlighted that tongue endurance decreased with age, CIRS, and MDS-UPDRS, while showing a positive association with MoCA scores. Conclusions: Significant improvements were observed in tongue and lip strength, phonatory duration, intensity, and vocal quality between pre- (T1) and post-treatment (T2). This study underscores the importance of early and continuous speech therapy treatment for comprehensive speech function enhancement. Full article
(This article belongs to the Special Issue Parkinson's Disease Research: Current Insights and Future Directions)
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15 pages, 3061 KiB  
Article
Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning
by Henry Weresh, Kallin Hermann, Ali Al-Salahat, Amna Noor, Taylor Billion, Yu-Ting Chen, Abubakar Tauseef and Ali Bin Abdul Jabbar
NeuroSci 2025, 6(1), 6; https://doi.org/10.3390/neurosci6010006 - 15 Jan 2025
Viewed by 782
Abstract
Background: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis [...] Read more.
Background: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD’s mortality characterizes temporal shifts, examines demographic and regional differences, and provides machine-learning predictions. Methods: PD-related deaths in the United States were gathered from CDC WONDER. Age-adjusted mortality rates (AAMR) were collected, and trends were analyzed based on gender, race, region, age, and place of death. Annual percent change and average annual percent change were calculated using Joinpoint Regression program. Forecasts were obtained using the optimal Autoregressive Integrated Moving Average (ARIMA) model. Results: Overall mortality rate due to Parkinson’s increased from 1999 to 2022. Male gender, White race, Southern region, and older ages were associated with higher mortality compared to other groups. Deaths at home decreased and hospice deaths increased during the study period. Conclusions: This study highlights the increasing rate of PD AAMR and how it may become even more prevalent with time, emphasizing the value of increasing knowledge surrounding the disease and its trends to better prepare health systems and individual families for the burden of PD. Full article
(This article belongs to the Special Issue Parkinson's Disease Research: Current Insights and Future Directions)
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14 pages, 1598 KiB  
Article
Harmonization for Parkinson’s Disease Multi-Dataset T1 MRI Morphometry Classification
by Mohammed Saqib and Silvina G. Horovitz
NeuroSci 2024, 5(4), 600-613; https://doi.org/10.3390/neurosci5040042 - 29 Nov 2024
Viewed by 696
Abstract
Classification of disease and healthy volunteer cohorts provides a useful clinical alternative to traditional group statistics due to individualized, personalized predictions. Classifiers for neurodegenerative disease can be trained on structural MRI morphometry, but require large multi-scanner datasets, introducing confounding batch effects. We test [...] Read more.
Classification of disease and healthy volunteer cohorts provides a useful clinical alternative to traditional group statistics due to individualized, personalized predictions. Classifiers for neurodegenerative disease can be trained on structural MRI morphometry, but require large multi-scanner datasets, introducing confounding batch effects. We test ComBat, a common harmonization model, in an example application to classify subjects with Parkinson’s disease from healthy volunteers and identify common pitfalls, including data leakage. We used a multi-dataset cohort of 372 subjects (216 with Parkinson’s disease, 156 healthy volunteers) from 11 identified scanners. We extracted both FreeSurfer and the determinant of Jacobian morphometry to compare single-scanner and multi-scanner classification pipelines. We confirm the presence of batch effects by running single scanner classifiers which could achieve wildly divergent AUCs on scanner-specific datasets (mean:0.651 ± 0.144). Multi-scanner classifiers that considered neurobiological batch effects between sites could easily achieve a test AUC of 0.902, though pipelines that prevented data leakage could only achieve a test AUC of 0.550. We conclude that batch effects remain a major issue for classification problems, such that even impressive single-scanner classifiers are unlikely to generalize to multiple scanners, and that solving for batch effects in a classifier problem must avoid circularity and reporting overly optimistic results. Full article
(This article belongs to the Special Issue Parkinson's Disease Research: Current Insights and Future Directions)
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