The role of Ca2+ signaling in Parkinson's disease

Zaichick, Sofia; McGrath, Kaitlyn; Caraveo, Gabriela

doi:10.1242/dmm.028738

Cited by 156 publications

(106 citation statements)

References 320 publications

(321 reference statements)

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“…Calcium ions can trigger AS aggregation in vitro , even at low micromolar concentrations, and thus, it has been proposed that Ca(II) might induce cytoplasmic AS aggregates in cells (Nath et al ; Follett et al ; Rcom‐H’cheo‐Gauthier et al ). Accordingly, the study of AS‐Ca(II) interactions and their role in protein aggregation and Parkinson’s disease became an active area of research in the last years (Rcom‐H’cheo‐Gauthier et al ; Zaichick et al ). Here we summarized the most important recent findings.…”

Section: α‐Synuclein Is a Metal‐binding Proteinmentioning

confidence: 99%

Effects of alpha‐synuclein post‐translational modifications on metal binding

González

Arcos-López

König

et al. 2019

Journal of Neurochemistry

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Parkinson’s disease is the second most common neurodegenerative disorder worldwide. Neurodegeneration in this pathology is characterized by the loss of dopaminergic neurons in the substantia nigra, coupled with cytoplasmic inclusions known as Lewy bodies containing α‐synuclein. The brain is an organ that concentrates metal ions, and there is emerging evidence that a break‐down in metal homeostasis may be a critical factor in a variety of neurodegenerative diseases. α‐synuclein has emerged as an important metal‐binding protein in the brain, whereas these interactions play an important role in its aggregation and might represent a link between protein aggregation, oxidative damage, and neuronal cell loss. Additionally, α‐synuclein undergoes several post‐translational modifications that regulate its structure and physiological function, and may be linked to the aggregation and/or oligomer formation. This review is focused on the interaction of this protein with physiologically relevant metal ions, highlighting the cases where metal‐AS interactions profile as key modulators for its structural, aggregation, and membrane‐binding properties. The impact of α‐synuclein phosphorylation and N‐terminal acetylation in the metal‐binding properties of the protein are also discussed, underscoring a potential interplay between PTMs and metal ion binding in regulating α‐synuclein physiological functions and its role in pathology. This article is part of the Special Issue “Synuclein”.

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Section: α‐Synuclein Is a Metal‐binding Proteinmentioning

confidence: 99%

Effects of alpha‐synuclein post‐translational modifications on metal binding

González

Arcos-López

König

et al. 2019

Journal of Neurochemistry

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“…The top-ranked GO terms are associated with GPCR signaling, calcium homeostasis, and sensory perception 17/30 (Table S6). The calcium ion homeostasis dysregulation is an important pathological feature of PD [2] and is associated with α-syn aggregation and neuronal death [102].…”

Section: Age-dependent Pathway/go Changesmentioning

confidence: 99%

A new synuclein-transgenic mouse model for early Parkinson’s reveals molecular features of preclinical disease

Hendrickx

Garcia

Ashrafi

et al. 2020

Preprint

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Understanding Parkinson's disease (PD) in particular in its earliest phases is important for diagnosis and treatment. However, human brain samples are collected post-mortem, reflecting mainly end stage disease. Because brain samples of mouse models can be collected at any stage of the disease process, they are useful to investigate PD progression. Here, we compare ventral midbrain transcriptomics profiles from α-synuclein transgenic mice with a progressive, early PD-like striatum neurodegeneration across different ages using pathway, gene set and network analysis methods. Our study uncovers statistically significant altered genes across ages and between genotypes with known, suspected or unknown function in PD pathogenesis and key pathways associated with disease progression. Among those are genotype-dependent alterations associated with synaptic plasticity, neurotransmission, as well as mitochondria-related genes and dysregulation of lipid metabolism. Age-dependent changes were among others observed in neuronal and synaptic activity, calcium homeostasis, and membrane receptor signaling pathways, many of which linked to G-protein coupled receptors. Most importantly, most changes occurred before neurodegeneration was detected in this model, which points to a sequence of gene expression events that may be relevant for disease initiation and progression. It is tempting to speculate that molecular changes similar to those changes observed in our model happen in midbrain dopaminergic neurons before they start to degenerate. In other words, we believe we have uncovered molecular changes that accompany the progression from preclinical to early PD. 1/30 models provide a useful means to investigate PD-associated molecular changes, in particular those preceding nigro-striatal degeneration. The elucidation of such early changes can shed light into disease causation and drivers of disease progression, thus in turn pointing to novel targets for intervention as well as biomarkers [16,45].Whole transcriptome analysis enables to compare thousands of genes between two or more groups [9], and provides a valuable method for identifying coordinated changes in gene expression patterns that are not captured by single-gene or protein measurement approaches [59]. Despite of these advantages, only a limited amount of studies have used transcriptomics on α-synuclein-based transgenic mouse models for PD [13, 67, 71-73, 94, 98]. Alpha-synuclein, a pre-synaptic protein believed to be a moderator of the synaptic vesicle cycle, is a major component of Lewy bodies [87]. In addition, mutations or multiplications in its genes leads to familiar forms of PD [26,46]. Transcriptomics studies on α-synuclein-based transgenic mouse models for PD have only looked at differentially expressed genes (DEGs) in relation to pre-defined cellular pathways or gene sets from public annotation databases [13,67,[71][72][73]94]. Most of them used only one [71][72][73] or two age groups [13,67,94,98] of the mouse model for their analyses, and some of them were perform...

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“…It was reported that the expression of CBPs in general is very low in case of SNc neurons (Chung et al, 2005;Greene et al, 2005;Mendez et al, 2005) and reduces even further under PD (Fairless et al, 2019;Hurley et al, 2013;Yamada et al, 1990;Zaichick et al, 2017).…”

Section: Enhancement Of Cbp Expressionmentioning

confidence: 99%

“…In the proposed model, intracellular calcium concentration in the SNc neuron is dependent on calcium-binding proteins, mitochondria (MT) and endoplasmic reticulum (ER) (Zaichick et al, 2017;Zündorf and Reiser, 2011). The intracellular calcium concentration dynamics ([ ]) of the SNc neuron (Muddapu and Chakravarthy, 2020) is given by,…”

Section: Biophysical (Conductance-based) Neuron Model (Snc)mentioning

confidence: 99%

A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson’s Disease

Muddapu

Chakravarthy

2020

Preprint

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Parkinson's disease (PD) is a neurodegenerative disorder caused by loss of dopaminergic neurons in Substantia Nigra pars compacta (SNc). Although the exact cause of the cell death is not clear, the hypothesis that metabolic deficiency is a key facor has been gaining attention in the recent years. In the present study, we investigate this hypothesis using a multi-scale computational model of the subsystem of the basal ganglia comprising Subthalamic Nucleus (STN), Globus Pallidus externa (GPe) and SNc. The model is a multiscale model in that interactions among the three nuclei are simulated using more abstract Izhikevich neuron models, while the molecular pathways involved in cell death of SNc neurons are simulated in terms of detailed chemical kinetics. Simulation results obtained from the proposed model showed that energy deficiencies occurring at cellular and network levels could precipitate the excitotoxic loss of SNc neurons in PD. At the subcellular level, the models show how calcium elevation leads to apoptosis of SNc neurons. The therapeutic effects of several neuroprotective interventions are also simulated in the model. From neuroprotective studies, it was clear that glutamate inhibition and apoptotic signal blocker therapies were able to halt the progression of SNc cell loss when compared to other therapeutic interventions, which only slows down the progression of SNc cell loss. Deficiency Izhikevich (Spiking) Neuronal Model (STN, GPe) The Izhikevich neuronal models are capable of exhibiting biologically realistic firing patterns, at a relatively low computational expense (Izhikevich, 2003). The proposed model of HEM consists of GPe and STN neurons are modeled as Izhikevich spiking neuron model, where the Izhikevich parameters are adopted from the literature (Mandali et al., 2015;Michmizos and Nikita, 2011). Based on the anatomical data of rat basal ganglia, the neuronal population sizes in the model are selected (Arbuthnott and Wickens, 2007;Oorschot, 1996).The external bias current ( ) was adjusted to match the firing rate of nuclei with published data (Tripathy et al., 2015).

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The role of Ca2+ signaling in Parkinson's disease

Cited by 156 publications

References 320 publications

Effects of alpha‐synuclein post‐translational modifications on metal binding

Effects of alpha‐synuclein post‐translational modifications on metal binding

A new synuclein-transgenic mouse model for early Parkinson’s reveals molecular features of preclinical disease

A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson’s Disease

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