Pursuing Multiple Biomarkers for Early Idiopathic Parkinson’s Disease Diagnosis

Gopar-Cuevas, Yareth; Duarte-Jurado, Ana Patricia; Díaz-Pérez, Rosa Nelly; Saucedo‐Cárdenas, Odila; Loera‐Arias, María de Jesús; Montes‐de‐Oca‐Luna, Roberto; Rodríguez-Rocha, Humberto; García-García, Aracely

doi:10.1007/s12035-021-02500-z

Cited by 9 publications

(6 citation statements)

References 175 publications

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“…Currently, researchers are exploring novel biomarkers for diagnosing and predicting PD [43][44][45][46]. Although numerous studies have been conducted, no widely recognized and easy-to-use predictive tool currently exists.…”

Section: Discussionmentioning

confidence: 99%

Applications of Machine Learning to Diagnosis of Parkinson’s Disease

Lai,

Li,

et al. 2023

Brain Sciences

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Background: Accurate diagnosis of Parkinson’s disease (PD) is challenging due to its diverse manifestations. Machine learning (ML) algorithms can improve diagnostic precision, but their generalizability across medical centers in China is underexplored. Objective: To assess the accuracy of an ML algorithm for PD diagnosis, trained and tested on data from different medical centers in China. Methods: A total of 1656 participants were included, with 1028 from Beijing (training set) and 628 from Fuzhou (external validation set). Models were trained using the least absolute shrinkage and selection operator–logistic regression (LASSO-LR), decision tree (DT), random forest (RF), eXtreme gradient boosting (XGboost), support vector machine (SVM), and k-nearest neighbor (KNN) techniques. Hyperparameters were optimized using five-fold cross-validation and grid search techniques. Model performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, accuracy, sensitivity (recall), specificity, precision, and F1 score. Variable importance was assessed for all models. Results: SVM demonstrated the best differentiation between healthy controls (HCs) and PD patients (AUC: 0.928, 95% CI: 0.908–0.947; accuracy: 0.844, 95% CI: 0.814–0.871; sensitivity: 0.826, 95% CI: 0.786–0.866; specificity: 0.861, 95% CI: 0.820–0.898; precision: 0.849, 95% CI: 0.807–0.891; F1 score: 0.837, 95% CI: 0.803–0.868) in the validation set. Constipation, olfactory decline, and daytime somnolence significantly influenced predictability. Conclusion: We identified multiple pivotal variables and SVM as a precise and clinician-friendly ML algorithm for prediction of PD in Chinese patients.

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Section: Discussionmentioning

confidence: 99%

Applications of Machine Learning to Diagnosis of Parkinson’s Disease

Lai,

Li,

et al. 2023

Brain Sciences

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“…Furthermore, metformin attenuates cognitive dysfunction in mice with accelerated age by inhibiting calpain signalling and endoplasmic reticulum stress 57 . Besides, different studies illustrated that metformin can reduce PD neuropathology through activation of AMPK which inhibit oxidative stress, mitochondrial dysfunction and accumulation of α‐Syn 58,59 . Furthermore, metformin attenuates the development of brain insulin resistance a hallmark of PD and other neurodegenerative diseases 60 .…”

Section: Role Of Calpain/cdk5 Inhibitors In Pdmentioning

confidence: 99%

Cyclin‐dependent kinase 5 (CDK5) inhibitors in Parkinson disease

Alrouji,

Al‐kuraishy,

Al‐Gareeb

et al. 2024

J Cellular Molecular Medi

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Cyclin‐dependent kinase 5 (Cdk5) is a protein expressed in postmitotic neurons in the central nervous system (CNS). Cdk5 is activated by p35 and p39 which are neuron regulatory subunits. Cdk5/p35 complex is activated by calpain protease to form Cdk5/p35 which has a neuroprotective effect by regulating the synaptic plasticity and memory functions. However, exaggerated Cdk5 is implicated in different types of neurodegenerative diseases including Parkinson disease (PD). Therefore, modulation of Cdk5 signalling may mitigate PD neuropathology. Therefore, the aim of the present review was to discuss the critical role of Cdk5 in the pathogenesis of PD, and how Cdk5 inhibitors are effectual in the management of PD. In conclusion, overactivated Cdk5 is involved the development of neurodegeneration, and Cdk5/calpain inhibitors such as statins, metformin, fenofibrates and rosiglitazone can attenuate the progression of PD neuropathology.

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“…The onset of cardinal motor PD features corresponds with substantial, up to 80%, loss of dopaminergic neurons (reviewed in [163]). It may be preceded by other, nonspecific symptoms (prodromal phase), such as REM sleep behavior disorder (RBD); hyposmia; depression; and autonomic dysfunction manifested as constipation, urinary urgency, erectile dysfunction, or orthostatic hypotension.…”

Section: Diagnostic Potential Of Clusterin In Pdmentioning

confidence: 99%

“…The CSF is a well-established source of biomarkers for central nervous system diseases, including NDDs, as their concentration in other body fluids is usually extremely low. However, it is only accessible through invasive procedures; therefore, noninvasive or minimally invasive systemic biomarkers are sought after, particularly for screening and disease monitoring purposes [163,165]. Although the nonclinical PD biomarkers of the prodromal phase are needed to allow for developing early disease-modifying therapies [160,164], both CSF and systemic biomarkers for PD have received relatively little attention.…”

Section: Diagnostic Potential Of Clusterin In Pdmentioning

confidence: 99%

“…Although the nonclinical PD biomarkers of the prodromal phase are needed to allow for developing early disease-modifying therapies [160,164], both CSF and systemic biomarkers for PD have received relatively little attention. Moreover, the available studies have produced rather unimpressive and/or inconsistent results [163,166]. They are frequently conducted on small cohorts of living patients and thus without a definite confirmation by a postmortem analysis of both the disease pathology and the absence of other abnormalities, potentially affecting clusterin concentration.…”

Section: Diagnostic Potential Of Clusterin In Pdmentioning

confidence: 99%

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HDL Accessory Proteins in Parkinson’s Disease—Focusing on Clusterin (Apolipoprotein J) in Regard to Its Involvement in Pathology and Diagnostics—A Review

2022

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Parkinson’s disease (PD)—a neurodegenerative disorder (NDD) characterized by progressive destruction of dopaminergic neurons within the substantia nigra of the brain—is associated with the formation of Lewy bodies containing mainly α-synuclein. HDL-related proteins such as paraoxonase 1 and apolipoproteins A1, E, D, and J are implicated in NDDs, including PD. Apolipoprotein J (ApoJ, clusterin) is a ubiquitous, multifunctional protein; besides its engagement in lipid transport, it modulates a variety of other processes such as immune system functionality and cellular death signaling. Furthermore, being an extracellular chaperone, ApoJ interacts with proteins associated with NDD pathogenesis (amyloid β, tau, and α-synuclein), thus modulating their properties. In this review, the association of clusterin with PD is delineated, with respect to its putative involvement in the pathological mechanism and its application in PD prognosis/diagnosis.

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Pursuing Multiple Biomarkers for Early Idiopathic Parkinson’s Disease Diagnosis

Cited by 9 publications

References 175 publications

Applications of Machine Learning to Diagnosis of Parkinson’s Disease

Applications of Machine Learning to Diagnosis of Parkinson’s Disease

Cyclin‐dependent kinase 5 (CDK5) inhibitors in Parkinson disease

HDL Accessory Proteins in Parkinson’s Disease—Focusing on Clusterin (Apolipoprotein J) in Regard to Its Involvement in Pathology and Diagnostics—A Review

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