scholarly journals Mitochondria-mitochondria interaction networks show altered topological patterns in Parkinson’s disease

2020 ◽  
Author(s):  
Massimiliano Zanin ◽  
Bruno F. R. Santos ◽  
Paul M.A. Antony ◽  
Clara Berenguer-Escuder ◽  
Simone B. Larsen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopaminergic Neurons ◽  
Point Mutations ◽  
Alpha Synuclein ◽  
Interaction Networks ◽  
Scale Free ◽  
Midbrain Dopaminergic Neurons ◽  
Machine Learning Approach

SUMMARYMitochondrial dysfunction is linked to pathogenesis of Parkinson’s disease (PD). However, individual-mitochondria-based analyses do not show a uniform feature in PD patients. Since mitochondria interact with each other, we hypothesize that PD-related features might exist in topological patterns of mitochondria-mitochondria interaction networks (MINs). Here we showed that MINs form non-classical scale-free supernetworks in colonic ganglia both from healthy controls and PD patients, however, altered topological patterns are observed in PD patients. These patterns highly correlate with PD clinical scores and a machine-learning approach based on the MIN features accurately distinguish between patients and controls with an area-under-curve value of 0.989. The MINs of midbrain dopaminergic neurons (mDANs) derived from several genetic PD patients also display specific changes. CRISPR/CAS9-based genome correction of alpha-synuclein point mutations reverses the changes in MINs of mDANs. Our MIN network analysis opens a new dimension for a deeper characterization of various complex diseases with mitochondrial dysregulation.

scholarly journals Mitochondria interaction networks show altered topological patterns in Parkinson’s disease

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Massimiliano Zanin ◽  
Bruno F. R. Santos ◽  
Paul M. A. Antony ◽  
Clara Berenguer-Escuder ◽  
Simone B. Larsen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Point Mutations ◽  
Interaction Network ◽  
Critical Dimension ◽  
Alpha Synuclein ◽  
Interaction Networks ◽  
Scale Free ◽  
Midbrain Dopaminergic Neurons ◽  
Highly Correlated

Abstract Mitochondrial dysfunction is linked to pathogenesis of Parkinson’s disease (PD). However, individual mitochondria-based analyses do not show a uniform feature in PD patients. Since mitochondria interact with each other, we hypothesize that PD-related features might exist in topological patterns of mitochondria interaction networks (MINs). Here we show that MINs formed nonclassical scale-free supernetworks in colonic ganglia both from healthy controls and PD patients; however, altered network topological patterns were observed in PD patients. These patterns were highly correlated with PD clinical scores and a machine-learning approach based on the MIN features alone accurately distinguished between patients and controls with an area-under-curve value of 0.989. The MINs of midbrain dopaminergic neurons (mDANs) derived from several genetic PD patients also displayed specific changes. CRISPR/CAS9-based genome correction of alpha-synuclein point mutations reversed the changes in MINs of mDANs. Our organelle-interaction network analysis opens another critical dimension for a deeper characterization of various complex diseases with mitochondrial dysregulation.

scholarly journals Novel Immunotherapeutic Approaches to Target Alpha-Synuclein and Related Neuroinflammation in Parkinson’s Disease

Cells ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 105 ◽  
Author(s):  
Maria Zella ◽  
Judith Metzdorf ◽  
Friederike Ostendorf ◽  
Fabian Maass ◽  
Siegfried Muhlack ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Glial Cell ◽  
Dopaminergic Neurons ◽  
Basic Research ◽  
Alpha Synuclein ◽  
Models Of Disease ◽  
Novel Therapeutic Strategies ◽  
Lymphocyte Populations

The etiology of Parkinson’s disease (PD) is significantly influenced by disease-causing changes in the protein alpha-Synuclein (aSyn). It can trigger and promote intracellular stress and thereby impair the function of dopaminergic neurons. However, these damage mechanisms do not only extend to neuronal cells, but also affect most glial cell populations, such as astroglia and microglia, but also T lymphocytes, which can no longer maintain the homeostatic CNS milieu because they produce neuroinflammatory responses to aSyn pathology. Through precise neuropathological examination, molecular characterization of biomaterials, and the use of PET technology, it has been clearly demonstrated that neuroinflammation is involved in human PD. In this review, we provide an in-depth overview of the pathomechanisms that aSyn elicits in models of disease and focus on the affected glial cell and lymphocyte populations and their interaction with pathogenic aSyn species. The interplay between aSyn and glial cells is analyzed both in the basic research setting and in the context of human neuropathology. Ultimately, a strong rationale builds up to therapeutically reduce the burden of pathological aSyn in the CNS. The current antibody-based approaches to lower the amount of aSyn and thereby alleviate neuroinflammatory responses is finally discussed as novel therapeutic strategies for PD.

scholarly journals Accelerating diagnosis of Parkinson’s disease through risk prediction

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
William Yuan ◽  
Brett Beaulieu-Jones ◽  
Richard Krolewski ◽  
Nathan Palmer ◽  
Christine Veyrat-Follet ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Subsequent Development ◽  
Time Compression ◽  
Disease Modifying Therapies ◽  
Machine Learning Approach ◽  
Diagnostic Window

Abstract Background Characterization of prediagnostic Parkinson’s Disease (PD) and early prediction of subsequent development are critical for preventive interventions, risk stratification and understanding of disease pathology. This study aims to characterize the role of the prediagnostic period in PD and, using selected features from this period as novel interception points, construct a prediction model to accelerate the diagnosis in a real-world setting. Methods We constructed two sets of machine learning models: a retrospective approach highlighting exposures up to 5 years prior to PD diagnosis, and an alternative model that prospectively predicted future PD diagnosis from all individuals at their first diagnosis of a gait or tremor disorder, these being features that appeared to represent the initiation of a differential diagnostic window. Results We found many novel features captured by the retrospective models; however, the high accuracy was primarily driven from surrogate diagnoses for PD, such as gait and tremor disorders, suggesting the presence of a distinctive differential diagnostic period when the clinician already suspected PD. The model utilizing a gait/tremor diagnosis as the interception point, achieved a validation AUC of 0.874 with potential time compression to a future PD diagnosis of more than 300 days. Comparisons of predictive diagnoses between the prospective and prediagnostic cohorts suggest the presence of distinctive trajectories of PD progression based on comorbidity profiles. Conclusions Overall, our machine learning approach allows for both guiding clinical decisions such as the initiation of neuroprotective interventions and importantly, the possibility of earlier diagnosis for clinical trials for disease modifying therapies.

scholarly journals Single Molecule FRET Characterization of Oligomers from Alpha-Synuclein Early Onset Parkinson's Disease Mutants

2014 ◽  
Vol 106 (2) ◽  
pp. 269a ◽  
Author(s):  
Laura Tosatto ◽  
Mathew H. Horrocks ◽  
Cremades Nunilo ◽  
Tim Guilliams ◽  
Mauro Dalla Serra ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Single Molecule ◽  
Early Onset ◽  
Alpha Synuclein ◽  
Single Molecule Fret ◽  
Early Onset Parkinson’S Disease

scholarly journals Editorial for the Special Issue “Animal Models of Parkinson’s Disease and Related Disorders”

2020 ◽  
Vol 21 (12) ◽  
pp. 4250
Author(s):  
Yuzuru Imai
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Animal Models ◽  
Dopaminergic Neurons ◽  
Neurodegenerative Disorder ◽  
Motor Dysfunction ◽  
Special Issue ◽  
Midbrain Dopaminergic Neurons ◽  
Age Dependent ◽  
Common Neurodegenerative Disorder

Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by age-dependent motor dysfunction and degeneration of the midbrain dopaminergic neurons [...]

scholarly journals Alpha-synuclein stepwise aggregation reveals features of an early onset mutation in Parkinson’s disease

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Guilherme A. P. de Oliveira ◽  
Jerson L. Silva
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Onset ◽  
Point Mutations ◽  
Alpha Synuclein ◽  
Amyloid Formation ◽  
Wild Type ◽  
Cryo Electron Microscopy ◽  
Familial Parkinson’S Disease ◽  
Direct Detector

Abstract Amyloid formation is a process involving interconverting protein species and results in toxic oligomers and fibrils. Aggregated alpha-synuclein (αS) participates in neurodegenerative maladies, but a closer understanding of the early αS polymerization stages and polymorphism of heritable αS variants is sparse still. Here, we distinguished αS oligomer and protofibril interconversions in Thioflavin T polymerization reactions. The results support a hypothesis reconciling the nucleation-polymerization and nucleation-conversion-polymerization models to explain the dissimilar behaviors of wild-type and the A53T mutant. Cryo-electron microscopy with a direct detector shows the polymorphic nature of αS fibrils formed by heritable A30P, E46K, and A53T point mutations. By showing that A53T rapidly nucleates competent species, continuously elongates fibrils in the presence of increasing amounts of seeds, and overcomes wild-type surface requirements for growth, our findings place A53T with features that may explain the early onset of familial Parkinson’s disease cases bearing this mutation.

scholarly journals Association Between Decreased Srpk3 Expression And An Increase In Substantia Nigra Alpha-Synuclein Levels In An MPTP-Induced Parkinson’s Disease Mouse Model

2022 ◽  
Author(s):  
Min Hyung Seo ◽  
Sujung Yeo
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Dopaminergic Neurons ◽  
Cell Loss ◽  
Alpha Synuclein ◽  
Mice Model ◽  
Dopaminergic Cell ◽  
The Brain

Abstract Parkinson’s disease (PD) is known as the second most common neurodegenerative disease, which is caused by destruction of dopaminergic neurons in the substantia nigra (SN) of the brain; however, the reason for the death of dopaminergic neurons remains unclear. An increase in α-synuclein (α-syn) is considered an important factor in the pathogenesis of PD. In the current study, we investigated the association between PD and serine/arginine-rich protein specific kinase 3 (Srpk3) in MPTP-induced parkinsonism mice model and in SH-SY5Y cells treated with MPP+. Srpk3 expression was significantly downregulated, while tyrosine hydroxylase (TH) decreased and α-synuclein (α-syn) increased after 4 weeks of MPTP intoxication treatment. Dopaminergic cell reduction and α-syn increase were demonstrated by inhibiting Srpk3 expression by siRNA in SH-SY5Y cells. Moreover, a decrease in Srpk3 expression upon siRNA treatment promoted dopaminergic cell reduction and α-syn increase in SH-SY5Y cells treated with MPP+. These results suggest that the decrease in Srpk3 expression due to Srpk3 siRNA caused both a decrease in TH and an increase in α-syn. This raises new possibilities for studying how Srpk3 controls dopaminergic cells and α-syn expression, which may be related to the pathogenesis of PD. Our results provide an avenue for understanding the role of Srpk3 during dopaminergic cell loss and α-syn increase in the SN. Furthermore, this study could support a therapeutic possibility for PD in that the maintenance of Srpk3 expression inhibited dopaminergic cell reduction.

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