<scp>R</scp>eduction of <scp>GAPDH</scp> in lenses of <scp>P</scp>arkinson's disease patients: <scp>A</scp> possible new biomarker

Klettner, Alexa; Tholey, Andreas; Wiegandt, Alena; Richert, Elisabeth; Nölle, Bernhard; Deuschl, Günther; Roider, Johann; Schneider, Susanne A.

doi:10.1002/mds.26863

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…For this study, results issued by the Welch's U -Test are consistent with the current state-of-the-art as reflected in Gallegos et al ( 2015 ), Klettner et al ( 2016 ), Xu et al ( 2017 ), Hu et al ( 2017 ), Vanle et al ( 2017 ), and Abbasi et al ( 2018 ), particulary for CSF and RNA tests ( CSF Alpha-synuclein , p- τ 181P , Total- τ, and GAPDH ). We confirm this hypothesis as we obtain better ensemble classification results when those biomarkers are included in our multimodal experiments.…”

Section: Discussionsupporting

confidence: 91%

Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease

Castillo-Barnes

Ramı́rez

Segovia

et al. 2018

Front. Neuroinform.

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In last years, several approaches to develop an effective Computer-Aided-Diagnosis (CAD) system for Parkinson's Disease (PD) have been proposed. Most of these methods have focused almost exclusively on brain images through the use of Machine-Learning algorithms suitable to characterize structural or functional patterns. Those patterns provide enough information about the status and/or the progression at intermediate and advanced stages of Parkinson's Disease. Nevertheless this information could be insufficient at early stages of the pathology. The Parkinson's Progression Markers Initiative (PPMI) database includes neurological images along with multiple biomedical tests. This information opens up the possibility of comparing different biomarker classification results. As data come from heterogeneous sources, it is expected that we could include some of these biomarkers in order to obtain new information about the pathology. Based on that idea, this work presents an Ensemble Classification model with Performance Weighting. This proposal has been tested comparing Healthy Control subjects (HC) vs. patients with PD (considering both PD and SWEDD labeled subjects as the same class). This model combines several Support-Vector-Machine (SVM) with linear kernel classifiers for different biomedical group of tests—including CerebroSpinal Fluid (CSF), RNA, and Serum tests—and pre-processed neuroimages features (Voxels-As-Features and a list of defined Morphological Features) from PPMI database subjects. The proposed methodology makes use of all data sources and selects the most discriminant features (mainly from neuroimages). Using this performance-weighted ensemble classification model, classification results up to 96% were obtained.

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Section: Discussionsupporting

confidence: 91%

Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease

Castillo-Barnes

Ramı́rez

Segovia

et al. 2018

Front. Neuroinform.

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“…Despite these differences between studies, further investigations of the eye in PD are desirable, given that it is known that ocular structures are involved in the pathology of several neurodegenerative diseases . For example, tears, lens, cornea, and retina have already been investigated and proposed as sources for possible PD biomarkers.…”

Section: Discussionmentioning

confidence: 99%

Phosphorylated α‐synuclein in the retina is a biomarker of Parkinson's disease pathology severity

et al. 2018

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These data suggest that phosphorylated α-synuclein accumulates in the retina in parallel with that in the brain, including in early stages preceding development of clinical signs of parkinsonism or dementia. Therefore, the retina may provide an in vivo indicator of brain pathology severity, and its detection could help in the diagnosis and monitoring of disease progression. © 2018 International Parkinson and Movement Disorder Society.

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“…Moreover, Inter-alpha trypsin inhibitor, heavy chain 2 (ITIH2) has also been identi ed during in ammation 68 , and may contribute to the cascade of events leading to neuronal degeneration 69 . However, the changes of GAPDH in PD patients are controversial in some literature, with some studies nding that overexpression of GAPDH was found in a mouse model of rotenone-induced PD, it can promotes neuron apoptosis in neurodegenerative disorders 70,71 , while some reporting the decrease of GAPDH expression in PD patients could impede the elimination of damaged mitochondria via mitophagy thus increasing cellular cytotoxicity 72 . Currently, the pathogenesis of PD is recognized as the aggregation of α-synuclein, and evidence is mounting that a relationship between proteasome system dysfunction and the pathogenesis of PD.…”

Section: Discussionmentioning

confidence: 99%

Integrated proteomics analysis in cerebrospinal fluid and saliva reveals the changes of endopeptidase activity in Parkinson`s disease

Yin

Liu

et al. 2023

Preprint

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Background The prodromal phase of Parkinson's disease can reach 10–20 years, and clinically meaningful biomarkers associated with Parkinson's disease (PD) have not been developed based on biofluid samples. Here, we aimed to identify novel biofulid candidate biomarkers by integrating CSF and saliva proteomes in PD. Methods We used a high-throughput tandem mass spectrometry to analyze 120 CSF samples and 203 saliva samples. Weighted gene co-expression network analysis (WGCNA) were performed to determine the protein features that are significantly correlated with the clinical parameters. Additionally, We used machine learning techniques to identify candidate biomarkers for PD diagnose. Results In total, we identified 2,585 and 4,301 proteins in CSF and saliva, respectively. Among these proteins, 10 differentially expressed proteins (DEPs) were in common between CSF and saliva proteome, mainly involved in the negative regulation of endopeptidase activity as well as hyaluronan metabolic. Interestingly, persistent activation of the negative regulation of endopeptidase activity during the progression of PD. WGCNA analysis revealed a significant negative correlation between AGT protein and UPDRS score in both CSF and saliva. In addition, machine learning identified a combination of 5 protein (GAPDH, GNS, ITIH2, CTSL, and GPX3) as biomarkers for PD, with an area-under-the-curve (AUC) of 0.877–0.958. Conclusion In summary, we integrated and analyzed the proteomes of CSF and saliva proteomes, confirming that CSF and saliva proteome could both reflect the occurrence and development of PD. Furthermore, we found that endopeptidase activity might be a potential pathogenesis of PD, especially during the progression of disease. In addition, we also discovered valuable candidate biomarkers for PD diagnosis.

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Reduction of GAPDH in lenses of Parkinson's disease patients: A possible new biomarker

Cited by 9 publications

References 23 publications

Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease

Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease

Phosphorylated α‐synuclein in the retina is a biomarker of Parkinson's disease pathology severity

Integrated proteomics analysis in cerebrospinal fluid and saliva reveals the changes of endopeptidase activity in Parkinson`s disease

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