Low Levels of Adenosine and GDNF Are Potential Risk Factors for Parkinson's Disease with Sleep Disorders

Cerebrospinal fluid mesencephalic astrocyte-derived neurotrophic factor: A moderating effect on sleep time and cognitive function

BACKGROUND

Sleeping late has been associated with cognitive impairment, and insufficient sleep can affect the secretion of feeding-related cytokines. Feeding-related cytokines may contribute to cognitive deficits resulting from delayed bedtime. Glial cell line-derived neurotrophic factor (GDNF) and mesencephalic astrocyte-derived neurotrophic factor (MANF), which are feeding-related neurotrophic factors, have been associated with improved cognitive function and neuroprotective abilities. Enhanced expression of GDNF and MANF is linked to increased energy expenditure and hyperphagia, respectively.

AIMS

This study aimed to investigate the association between cerebrospinal fluid (CSF) GDNF, MANF, cognition, and sleep time and to explore the moderating effects of GDNF and MANF on cognitive impairment in individuals who sleep late.

METHOD

This cross-sectional study included participants (mean age 31.76 ± 10.22 years) who were categorized as ≤23 o'clock sleepers (n = 66) and >23 o'clock sleepers (n = 125) based on sleep time. Cognition was assessed using Montreal Cognitive Assessment (MoCA), and GDNF and MANF levels in CSF were measured.

RESULTS

MANF may play a moderating role in the relationship between sleep time and cognition (R2 = 0.06, β = 0.59, p = 0.031). Age showed a negative correlation with MoCA scores (R2 = 0.08, β = -0.18), while education exhibited a positive correlation (β = 0.17, both p < 0.05). Only ≤23 o'clock sleepers exhibited a negative correlation between MANF levels and BMI (r = -0.35, p = 0.005).

CONCLUSIONS

This study provides hitherto undocumented evidence of the potential protective effect of CSF MANF on cognitive impairment of late sleepers, which suggests that maintaining a regular sleep schedule may contribute to cognition and overall health, with MANF playing a role in this process.

Apigenin: a natural molecule at the intersection of sleep and aging

NAD+, a pivotal coenzyme central to metabolism, exhibits a characteristic decline with age. In mice, NAD+ levels can be elevated via treatment with apigenin, a natural flavonoid that inhibits the NAD+-consuming glycoprotein CD38. In animal models, apigenin positively impacts both sleep and longevity. For example, apigenin improves learning and memory in older mice, reduces tumor proliferation in a mouse xenograft model of triple-negative breast cancer, and induces sedative effects in mice and rats. Moreover, apigenin elongates survival in fly models of neurodegenerative disease and apigenin glycosides increase lifespan in worms. Apigenin's therapeutic potential is underscored by human clinical studies using chamomile extract, which contains apigenin as an active ingredient. Collectively, chamomile extract has been reported to alleviate anxiety, improve mood, and relieve pain. Furthermore, dietary apigenin intake positively correlates with sleep quality in a large cohort of adults. Apigenin's electron-rich flavonoid structure gives it strong bonding capacity to diverse molecular structures across receptors and enzymes. The effects of apigenin extend beyond CD38 inhibition, encompassing agonistic and antagonistic modulation of various targets, including GABA and inflammatory pathways. Cumulatively, a large body of evidence positions apigenin as a unique molecule capable of influencing both aging and sleep. Further studies are warranted to better understand apigenin's nuanced mechanisms and clinical potential.

The significance of glial cell line-derived neurotrophic factor analysis in Progressive Supranuclear Palsy

Progressive Supranuclear Palsy (PSP) is an atypical parkinsonism. Major subtypes of the disease: PSP-Richardson's Syndrome (PSP-RS) and PSP Parkinsonism Predominant (PSP-P) vary in clinical features, the pathomechanism remains unexplored. The aim of this work is to analyze the relevance of glial cell line-derived neurotrophic factor (GDNF) evaluation in the serum and cerebrospinal fluid (CSF) in PSP subtypes and to verify its significance as a possible factor in the in vivo examination. Authors assessed the concentration of GDNF in the serum and CSF of 12 patients with PSP-RS, 12 with PSP-P and 12 controls. Additionally authors evaluated patients using Unified Parkinson's Disease Rating Scale-III part (UPDRS-III), Frontal Assessment Battery (FAB) and Magnetic Resonance Imaging (MRI). The evaluation revealed significantly increased concentrations of GDNF in the CSF among PSP-RS patients and substantially increased concentrations of GDNF in the serum in PSP-P. Though the GDNF concentrations differentiated PSP subtypes, no correlations between with clinical factors were observed however certain correlations with atrophic changes in MRI were detected. GDNF is a factor which may impact the pathogenesis of PSP. Possible implementation of GDNF as a therapeutic factor could be a perspective in the search for therapy in this currently incurable disease.

To re-examine the intersection of microglial activation and neuroinflammation in neurodegenerative diseases from the perspective of pyroptosis

Neurodegenerative diseases (NDs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and motor neuron disease, are diseases characterized by neuronal damage and dysfunction. NDs are considered to be a multifactorial disease with diverse etiologies (immune, inflammatory, aging, genetic, etc.) and complex pathophysiological processes. Previous studies have found that neuroinflammation and typical microglial activation are important mechanisms of NDs, leading to neurological dysfunction and disease progression. Pyroptosis is a new mode involved in this process. As a form of programmed cell death, pyroptosis is characterized by the expansion of cells until the cell membrane bursts, resulting in the release of cell contents that activates a strong inflammatory response that promotes NDs by accelerating neuronal dysfunction and abnormal microglial activation. In this case, abnormally activated microglia release various pro-inflammatory factors, leading to the occurrence of neuroinflammation and exacerbating both microglial and neuronal pyroptosis, thus forming a vicious cycle. The recognition of the association between pyroptosis and microglia activation, as well as neuroinflammation, is of significant importance in understanding the pathogenesis of NDs and providing new targets and strategies for their prevention and treatment.

Automatic and Early Detection of Parkinson's Disease by Analyzing Acoustic Signals Using Classification Algorithms Based on Recursive Feature Elimination Method

Parkinson's disease (PD) is a neurodegenerative condition generated by the dysfunction of brain cells and their 60-80% inability to produce dopamine, an organic chemical responsible for controlling a person's movement. This condition causes PD symptoms to appear. Diagnosis involves many physical and psychological tests and specialist examinations of the patient's nervous system, which causes several issues. The methodology method of early diagnosis of PD is based on analysing voice disorders. This method extracts a set of features from a recording of the person's voice. Then machine-learning (ML) methods are used to analyse and diagnose the recorded voice to distinguish Parkinson's cases from healthy ones. This paper proposes novel techniques to optimize the techniques for early diagnosis of PD by evaluating selected features and hyperparameter tuning of ML algorithms for diagnosing PD based on voice disorders. The dataset was balanced by the synthetic minority oversampling technique (SMOTE) and features were arranged according to their contribution to the target characteristic by the recursive feature elimination (RFE) algorithm. We applied two algorithms, t-distributed stochastic neighbour embedding (t-SNE) and principal component analysis (PCA), to reduce the dimensions of the dataset. Both t-SNE and PCA finally fed the resulting features into the classifiers support-vector machine (SVM), K-nearest neighbours (KNN), decision tree (DT), random forest (RF), and multilayer perception (MLP). Experimental results proved that the proposed techniques were superior to existing studies in which RF with the t-SNE algorithm yielded an accuracy of 97%, precision of 96.50%, recall of 94%, and F1-score of 95%. In addition, MLP with the PCA algorithm yielded an accuracy of 98%, precision of 97.66%, recall of 96%, and F1-score of 96.66%.

Orexin pathway in Parkinson's disease: a review

Parkinson's disease (PD) is a progressive neurodegenerative disease (NDD) caused by dopaminergic neuron degeneration in the substantia nigra (SN). Orexin is a neuropeptide that plays a role in the pathogenesis of PD. Orexin has neuroprotective properties in dopaminergic neurons. In PD neuropathology, there is also degeneration of orexinergic neurons in the hypothalamus, in addition to dopaminergic neurons. However, the loss of orexinergic neurons in PD began after the degeneration of dopaminergic neurons. Reduced activity of orexinergic neurons has been linked to developing and progressing motor and non-motor symptoms in PD. In addition, the dysregulation of the orexin pathway is linked to the development of sleep disorders. The hypothalamic orexin pathway regulates various aspects of PD neuropathology at the cellular, subcellular, and molecular levels. Finally, non-motor symptoms, particularly insomnia and disturbed sleep, promote neuroinflammation and the accumulation of neurotoxic proteins as a result of defects in autophagy, endoplasmic reticulum (ER) stress, and the glymphatic system. As a result, this review aimed to highlight the potential role of orexin in PD neuropathology.