Inactivation of glyceraldehyde-3-phosphate dehydrogenase by the dopamine metabolite, 3,4-dihydroxyphenylacetaldehyde

Vanle, Brigitte; Florang, Virginia R.; Murry, Daryl J.; Aguirre, Arturo L.; Doorn, Jonathan A.

doi:10.1016/j.bbrc.2017.08.067

Cited by 26 publications

(21 citation statements)

References 34 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: 90%

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: 90%

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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“…Since TH activity is a rate-limiting step in DA synthesis from tyrosine, DOPAL-dependent TH inhibition would indirectly exacerbate the depletion of DA release in nigrostriatal circuits and parkinsonian syndrome. More recently, DOPAL appeared to cause inhibition of GAPDH activity [47]. Also, in this paradigm, both the catechol oxidation and the aldehyde moiety were required for cysteines and lysines modification.…”

Section: 4-dihydroxyphenylacetaldehyde: a Relevant Player In Dopamimentioning

confidence: 99%

Impaired dopamine metabolism in Parkinson’s disease pathogenesis

Masato

Plotegher

Boassa

et al. 2019

Mol Neurodegeneration

235

144

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A full understanding of Parkinson’s Disease etiopathogenesis and of the causes of the preferential vulnerability of nigrostriatal dopaminergic neurons is still an unsolved puzzle. A multiple-hit hypothesis has been proposed, which may explain the convergence of familial, environmental and idiopathic forms of the disease. Among the various determinants of the degeneration of the neurons in Substantia Nigra pars compacta , in this review we will focus on the endotoxicity associated to dopamine dyshomeostasis. In particular, we will discuss the relevance of the reactive dopamine metabolite 3,4-dihydroxyphenylacetaldehyde (DOPAL) in the catechol-induced neurotoxicity. Indeed, the synergy between the catechol and the aldehyde moieties of DOPAL exacerbates its reactivity, resulting in modification of functional protein residues, protein aggregation, oxidative stress and cell death. Interestingly, αSynuclein, whose altered proteostasis is a recurrent element in Parkinson’s Disease pathology, is considered a preferential target of DOPAL modification. DOPAL triggers αSynuclein oligomerization leading to synapse physiology impairment. Several factors can be responsible for DOPAL accumulation at the pre-synaptic terminals, i.e. dopamine leakage from synaptic vesicles, increased rate of dopamine conversion to DOPAL by upregulated monoamine oxidase and decreased DOPAL degradation by aldehyde dehydrogenases. Various studies report the decreased expression and activity of aldehyde dehydrogenases in parkinsonian brains, as well as genetic variants associated to increased risk in developing the pathology. Thus, we discuss how the deregulation of these enzymes might be considered a contributing element in the pathogenesis of Parkinson’s Disease or a down-stream effect. Finally, we propose that a better understanding of the impaired dopamine metabolism in Parkinson’s Disease would allow a more refined patients stratification and the design of more targeted and successful therapeutic strategies.

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“…Dopamine not only spontaneously oxidize to form melanin and neuromelanin, but also is catalyzed to the immediate products being hydrogen peroxide and aldehydes by monoamine oxidase ( Goldstein et al, 2014 ). Monoamine oxidase in the outer membrane of mitochondria catalyzes conversion of cytosolic dopamine to 3,4-dihydroxyphenylacetaldehyde, which is an endogenous neurotoxin implicated in PD ( Panneton et al, 2010 ), cause extensive aggregation of glyceraldehyde-3-phosphate dehydrogenase and irreversibly inhibit the enzyme activity, resulting in the production of reactive oxygen species to damage neurons ( Vanle et al, 2017 ). Dopamine also induces the production of soluble A53T α-synuclein oligomers and promotes the degeneration of neurons in SNc ( Mor et al, 2017 ).…”

Section: Mechanisms Of Neuronal Cell Death In Pdmentioning

confidence: 99%

Cellular and Molecular Basis of Neurodegeneration in Parkinson Disease

Zeng

Geng

Jia

et al. 2018

Front. Aging Neurosci.

168

114

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It has been 200 years since Parkinson disease (PD) was described by Dr. Parkinson in 1817. The disease is the second most common neurodegenerative disease characterized by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Although the pathogenesis of PD is still unknown, the research findings from scientists are conducive to understand the pathological mechanisms. It is well accepted that both genetic and environmental factors contribute to the onset of PD. In this review, we summarize the mutations of main seven genes (α-synuclein, LRRK2, PINK1, Parkin, DJ-1, VPS35 and GBA1) linked to PD, discuss the potential mechanisms for the loss of dopaminergic neurons (dopamine metabolism, mitochondrial dysfunction, endoplasmic reticulum stress, impaired autophagy, and deregulation of immunity) in PD, and expect the development direction for treatment of PD.

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Inactivation of glyceraldehyde-3-phosphate dehydrogenase by the dopamine metabolite, 3,4-dihydroxyphenylacetaldehyde

Cited by 26 publications

References 34 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

Impaired dopamine metabolism in Parkinson’s disease pathogenesis

Cellular and Molecular Basis of Neurodegeneration in Parkinson Disease

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