The Latest Articles on Parkinson's Disease

Our staff editors continue to share exciting, interesting, and thought-provoking reading material in the recommended articles series.

This week, we would like to share several latest articles on Parkinson’s disease.

Title: Disease stage-dependent changes in brain levels and neuroprotective effects of neuroactive steroids in Parkinson's disease
Authors: Sabina Luchetti, Philippe Liere, Antoine Pianos, Ronald W.H. Verwer, Arja Sluiter, Inge Huitinga, Michael Schumacher, Dick F. Swaab, Matthew R.J. Mason
Type: Research Article
Abstract:

Neuroactive steroids are known neuroprotective agents and neurotransmitter regulators. We previously found that expression of the enzymes synthesizing 5α-dihydroprogesterone (5α-DHP), allopregnanolone (ALLO), and dehydroepiandrosterone sulfate (DHEAS) were reduced in the substantia nigra (SN) of Parkinson's Disease (PD) brain. Here, concentrations of a comprehensive panel of steroids were measured in human post-mortem brains of PD patients and controls. Gas chromatography-mass spectrometry (GC/MS) was used to measure steroid levels in SN (involved in early symptoms) and prefrontal cortex (PFC) (involved later in the disease) of five control (CTR) and nine PD donors, divided into two groups: PD4 (PD-Braak stages 1–4) and PD6 (PD-Braak stages 5–6).

In SN, ALLO was increased in PD4 compared to CTR and 5α-DHP and ALLO levels were diminished in PD6 compared to PD4. The ALLO metabolite 3α5α20α-hexahydroprogesterone (3α5α20α-HHP) was higher in PD4 compared to CTR. In PFC, 3α5α20α-HHP was higher in PD4 compared to both CTR and PD6.

The effects of 5α-DHP, ALLO and DHEAS were tested on human post-mortem brain slices of patients and controls in culture. RNA expression of genes involved in neuroprotection, neuroinflammation and neurotransmission was analysed after 5 days of incubation with each steroid. In PD6 slices, both 5α-DHP and ALLO induced an increase of the glutamate reuptake effector GLAST1, while 5α-DHP also increased gene expression of the neuroprotective TGFB. In CTR slices, ALLO caused reduced expression of IGF1 and GLS, while DHEAS reduced the expression of p75 and the anti-apoptotic molecule APAF1.

Together these data suggest that a potentially protective upregulation of ALLO occurs at early stages of PD, followed by a downregulation of progesterone metabolites at later stages that may exacerbate the pathological changes, especially in SN. Neuroprotective effects of neurosteroids are thus dependent on the neuropathological stage of the disease.

Title: 25-year trends in first-time hospitalizations for Parkinson's disease and subsequent mortality: A Danish nationwide cohort study
Authors: M. Osler, G.T. Okholm, T.S.H. Jørgensen, M.P. Rozing
Type: Research Article
Abstract:

Background
In most countries, incidence and mortality for Parkinson's disease (PD) have not been monitored by surveillance registries, although it could demonstrate the need for primary and tertiary prevention.

Objective
To examine 25-year trends in first-time hospitalizations for PD in Denmark and subsequent short and long-term mortality.

Methods
In a nationwide population-based cohort we identified all 34,947 individuals with a first-time hospitalization for PD from 1995 through 2019. We calculated standardized incidence rates of PD and 1-year and 5-year mortality by sex. Mortality rates were compared with a reference cohort randomly selected from the background population matched on sex, age, and index date.

Results
The annual standardized incidence rate of PD was relatively stable during the study period in both men and women. The incidence of PD was higher in men than in women and with the highest incidence in those aged 70–79 years. One and 5-year mortality risk after first-time hospitalization for PD was similar for men and women, and decreased by around 30% and 20%, respectively, between 1995 and 2019. The matched reference cohort had a similar decline in mortality over time.

Conclusion
The rate of first-time hospitalization for PD was relatively stable between 1995 and 2019, whereas subsequent short and long-term mortality declined during the period as in the reference cohort.

Title: Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review
Authors: Luis Sigcha, Luigi Borzì, Federica Amato, Irene Rechichi, Carlos Ramos-Romero, Andrés Cárdenas, Luis Gascó, Gabriella Olmo
Type: Review
Abstract:
Parkinson’s disease (PD) is a neurodegenerative disorder that produces both motor and non-motor complications, degrading the quality of life of PD patients. Over the past two decades, the use of wearable devices in combination with machine learning algorithms has provided promising methods for more objective and continuous monitoring of PD. Recent advances in artificial intelligence have provided new methods and algorithms for data analysis, such as deep learning (DL). The aim of this article is to provide a comprehensive review of current applications where DL algorithms are employed for the assessment of motor and non-motor manifestations (NMM) using data collected via wearable sensors. This paper provides the reader with a summary of the current applications of DL and wearable devices for the diagnosis, prognosis, and monitoring of PD, in the hope of improving the adoption, applicability, and impact of both technologies as support tools. Following PRISMA (Systematic Reviews and Meta-Analyses) guidelines, sixty-nine studies were selected and analyzed. For each study, information on sample size, sensor configuration, DL approaches, validation methods and results according to the specific symptom under study were extracted and summarized. Furthermore, quality assessment was conducted according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) method. The majority of studies (74%) were published within the last three years, demonstrating the increasing focus on wearable technology and DL approaches for PD assessment. However, most papers focused on monitoring (59%) and computer-assisted diagnosis (37%), while few papers attempted to predict treatment response. Motor symptoms (86%) were treated much more frequently than NMM (14%). Inertial sensors were the most commonly used technology, followed by force sensors and microphones. Finally, convolutional neural networks (52%) were preferred to other DL approaches, while extracted features (38%) and raw data (37%) were similarly used as input for DL models. The results of this review highlight several challenges related to the use of wearable technology and DL methods in the assessment of PD, despite the advantages this technology could bring in the development and implementation of automated systems for PD assessment.
Access this article: https://doi.org/10.1016/j.eswa.2023.120541

Title: Directed connectivity in Parkinson's disease patients during over-ground and treadmill walking
Authors: Miguel Fernandez-del-Olmo, Jose Andrés Sánchez-Molina, Sabela Novo-Ponte, Noa Fogelson
Type: Research Article
Abstract:
Treadmill walking is considered a useful therapeutic tool for improving gait in Parkinson's disease (PD) patients. The study investigated the role of top-down, frontal-parietal versus bottom-up parietal-frontal networks, during over-ground and treadmill walking in PD and control subjects, using functional connectivity. To this end, EEG was recorded simultaneously, during a ten-minute period of continuous walking either over-ground or on a treadmill, in thirteen PD patients and thirteen age-matched controls. We evaluated EEG directed connectivity, using phase transfer entropy in three frequency bands: theta, alpha and beta. PD patients showed increased top-down connectivity during over-ground compared with treadmill walking, in the beta frequency range. Control subjects showed no significant differences in connectivity between the two walking conditions. Our results suggest that in PD patients, OG walking was associated with increased allocation of attentional resources, compared with that on the TL. These functional connectivity modulations may shed further light on the mechanisms underlying treadmill versus overground walking in PD.
Access this article: https://doi.org/10.1016/j.exger.2023.112220

Title: Antiparkinsonian effects of polyphenols: A narrative review with a focus on the modulation of the gut-brain axis
Authors: Wei Zhang, Xiaoyu Dong, Rui Huang
Type: Review
Abstract:
Polyphenols, which are naturally occurring bioactive compounds in fruits and vegetables, are emerging as potential therapeutics for neurological disorders such as Parkinson’s disease (PD). Polyphenols have diverse biological activities, such as anti-oxidative, anti-inflammatory, anti-apoptotic, and α-synuclein aggregation inhibitory effects, which could ameliorate PD pathogenesis. Studies have shown that polyphenols are capable of regulating the gut microbiota (GM) and its metabolites; in turn, polyphenols are extensively metabolized by the GM, resulting in the generation of bioactive secondary metabolites. These metabolites may regulate various physiological processes, including inflammatory responses, energy metabolism, intercellular communication, and host immunity. With increasing recognition of the importance of the microbiota-gut-brain axis (MGBA) in PD etiology, polyphenols have attracted growing attention as MGBA regulators. In order to address the potential therapeutic role of polyphenolic compounds in PD, we focused on MGBA.
Access this article: https://doi.org/10.1016/j.phrs.2023.106787