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

Wang, Li; Gao, Zheng; Chen, Gang; Geng, Deqin; Gao, Dianshuai

doi:10.3390/brainsci13020200

Cited by 13 publications

(5 citation statements)

References 71 publications

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“…In rats, apigenin demonstrated GABAergic activity that was independent of GABA- benzodiazepine receptors and possibly mediated by the GABA A receptor ( 57 ). Apigenin also decreased levels of Tnf-α, Il-6, and iNos1 while maintaining elevated levels of Bdnf and glial Gdnf mRNA ( 77 , 78 ). Findings involving BDNF are interesting given that this protein was reported to be significantly lower in insomniac patients with short sleep duration ( 79 ).…”

Section: Apigenin and Sleepmentioning

confidence: 94%

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

Kramer,

Johnson

2024

Front. Nutr.

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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.

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Section: Apigenin and Sleepmentioning

confidence: 94%

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

Kramer,

Johnson

2024

Front. Nutr.

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“…Additionally, it was found that GDNF along with adenosine rendered neuroprotection in PD patients with sleep disturbances. Low levels of GDNF were found in PD patients with more serious sleep related disorders . In another study, it was found that microencapsulation of GDNF led to sustained release in circulation for a much longer time.…”

Section: Novel Targets For Improved Pd Therapeuticsmentioning

confidence: 96%

“…Low levels of GDNF were found in PD patients with more serious sleep related disorders. 153 In another study, it was found that microencapsulation of GDNF led to sustained release in circulation for a much longer time. A single intrastriatal administration of microencapsulated GDNF was done in MTPT induced PD in monkeys.…”

Section: Glial Cell-line Derived Neurotrophic Factor (Gdnf)mentioning

confidence: 99%

Uncovering Novel Therapeutic Targets for Parkinson’s Disease

Soni

Delvadia

Joharapurkar

et al. 2023

ACS Chem. Neurosci.

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Parkinson's disease (PD) is the second most prevailing progressive disorder leading to neurodegeneration, typically in people above 65 years of age. Motor clinical manifestations of PD appear in a much later stage and include rigidity, tremors, akinesia, and gait dysfunction. There are also nonmotor symptoms like GI and olfactory dysfunction. However, they cannot be considered for diagnosis of the disease, as they are unspecific. PD pathogenesis is mainly characterized by deposits of inclusion bodies on dopaminergic (DA) neurons in substantia nigra pars compacta region (SNpc) of the brain. The major component of these inclusion bodies, are αsynuclein aggregates. α-Synuclein undergoes misfolding and oligomerization to form aggregates and fibrils. These aggregates gradually propagate PD pathology. Other prominent features of this pathological development include mitochondrial dysfunction, neuroinflammation, oxidative stress, and impaired autophagy. These all contribute to neuronal degeneration. Besides this, there are many underlying factors which influence these processes. These factors comprise molecular proteins and signaling cascades. In this review, we have listed out underexplored molecular targets that may aid in development of neoteric and advanced therapeutics.

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“…Additional motor symptoms often seen in individuals with PD include impaired postural stability and reduced velocity of movement (Alfonsetti et al, 2022). PD is associated with other nonmotor symptoms, including cognitive impairment (dementia), mood disorders (depression), sensory abnormalities (restless legs), sensitivity to temperature changes, and gastrointestinal dysfunctions (Wang et al, 2023). Significant progress has been achieved by researchers in the exploration of therapeutic options for individuals Journal of Disability Research 2024 experiencing both motor and nonmotorized manifestations of PD despite the inherent incurability of this condition.…”

Section: Introductionmentioning

confidence: 99%

Developing System-based Voice Features for Detecting Parkinson’s Disease Using Machine Learning Algorithms

Al-Nefaie,

Aldhyani,

Koundal

2024

Journal of Disability Research

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Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a deficit of dopamine in the brain. This condition has the potential to impact individuals of advanced age. The procedure for diagnosing PD is currently not well established. Diagnostics includes a range of methods, including the identification and evaluation of symptoms, the implementation of clinical trials, and the use of laboratory tests. This research work employs a range of machine learning (ML) algorithms, including k-nearest neighbors (k-NN), support vector machines (SVMs), random forest (RF), logistic regression (LR), and AdaBoost boosting approaches, to predict the occurrence of PD and assist healthcare practitioners in recommending tailored treatment plans. To evaluate the suggested ML methods, it is customary to use a standard dataset consisting of various biological voice measures obtained from individuals afflicted with PD as well as healthy individuals. The experimental results demonstrate that the LR model achieves an accuracy of 86%, the k-NN model achieves an accuracy of 92%, the SVM model achieves an accuracy of 95%, the RF model achieves an accuracy of 95%, and the AdaBoost boosting model achieves an accuracy of 93%. SVM and RF are well acknowledged for their high accuracy in classification tasks. Upon conducting a comparative analysis with other studies, it was shown that the proposed intervention yielded outcomes that were either comparable to or superior to those reported in previous research.

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

Cited by 13 publications

References 71 publications

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

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

Uncovering Novel Therapeutic Targets for Parkinson’s Disease

Developing System-based Voice Features for Detecting Parkinson’s Disease Using Machine Learning Algorithms

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