scholarly journals Review of prodromal symptoms in Parkinson's Disease detected by MRI, EEG And microbiome

2019 ◽  
Author(s):  
Isabel Cristina Echeverri ◽  
Maria de la Iglesia Vayá ◽  
Jose Molina Mateo ◽  
Francia Restrepo de Mejia ◽  
Belarmino Segura Giraldo
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Substantia Nigra ◽  
Evidence Synthesis ◽  
Magnetic Resonance Images ◽  
Event Related Potential ◽  
Motor Symptoms ◽  
The Brain ◽  
Early Parkinson’S Disease

Context: Parkinson’s disease (PD) is catalogued as a disorder that causes motor symptoms; the evidence of literature shows the PD starts with non-motor signs, which can be detected in prodromal phases. These previous phases can be analyzed and studied through magnetic resonance images (MRI), electroencephalography (EEG) and microbiome.Objective: To systematically review the areas of the brain and brain-gut axis which affect in early Parkinson’s disease that can possibly be visualized and analyzed by MRI, EEG and the microbiome.Evidence acquisition: Pubmed and Embase databases were used until July 30, 2018 as to search for early Parkinson’s disease at its earliest non-motor symptoms stage by using MRI, EEG, and microbiome. The search was performed according to the requirements of a systematic review. In order to identify reports, we evaluated them following the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria. Evidence synthesis: MRI and EEG have provided the advances to find features for PD over the last decade. Those techniques identify motor symptoms on substantia nigra where the patient shows a dopamine deficiency. However, over recent years, researchers have found that PD has prodromal phases, that is, PD is not simply a neurodegenerative disorder characterized by the dysfunction of dopaminergic. Thus, high field MRI, event-related potential (ERP) and microbiota data shows a significant change on the brain cortex, white and grey matter, the extrapyramidal system, brain signals and the gut.Conclusion: The structural MRI is a useful technique in detecting the stages of motor symptoms on the substantia nigra in patients with PD. The use of magnetic resonance as an early detector requires a high magnetic field, as to identify the areas which diagnose that the patient could be in the premotor stages. On the other hand, EEG performed well in detecting PD features. Furthermore, microbiome sequencing might include the classification of bacterial families that could help to detect PD in its prodromal phase. Thus, the combination of all these techniques can support the possibility of diagnosing PD in its very early stages.

scholarly journals Neuroinflammation and protein pathology in Parkinson’s disease dementia

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Antonina Kouli ◽  
Marta Camacho ◽  
Kieren Allinson ◽  
Caroline H. Williams-Gray
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
T Lymphocytes ◽  
Substantia Nigra ◽  
Amyloid Β ◽  
Brain Regions ◽  
Parkinson’S Disease Dementia ◽  
Activated Microglia ◽  
Cell Counts ◽  
The Brain

AbstractParkinson’s disease dementia is neuropathologically characterized by aggregates of α-synuclein (Lewy bodies) in limbic and neocortical areas of the brain with additional involvement of Alzheimer’s disease-type pathology. Whilst immune activation is well-described in Parkinson’s disease (PD), how it links to protein aggregation and its role in PD dementia has not been explored. We hypothesized that neuroinflammatory processes are a critical contributor to the pathology of PDD. To address this hypothesis, we examined 7 brain regions at postmortem from 17 PD patients with no dementia (PDND), 11 patients with PD dementia (PDD), and 14 age and sex-matched neurologically healthy controls. Digital quantification after immunohistochemical staining showed a significant increase in the severity of α-synuclein pathology in the hippocampus, entorhinal and occipitotemporal cortex of PDD compared to PDND cases. In contrast, there was no difference in either tau or amyloid-β pathology between the groups in any of the examined regions. Importantly, we found an increase in activated microglia in the amygdala of demented PD brains compared to controls which correlated significantly with the extent of α-synuclein pathology in this region. Significant infiltration of CD4+ T lymphocytes into the brain parenchyma was commonly observed in PDND and PDD cases compared to controls, in both the substantia nigra and the amygdala. Amongst PDND/PDD cases, CD4+ T cell counts in the amygdala correlated with activated microglia, α-synuclein and tau pathology. Upregulation of the pro-inflammatory cytokine interleukin 1β was also evident in the substantia nigra as well as the frontal cortex in PDND/PDD versus controls with a concomitant upregulation in Toll-like receptor 4 (TLR4) in these regions, as well as the amygdala. The evidence presented in this study show an increased immune response in limbic and cortical brain regions, including increased microglial activation, infiltration of T lymphocytes, upregulation of pro-inflammatory cytokines and TLR gene expression, which has not been previously reported in the postmortem PDD brain.

scholarly journals Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Neurological Disorders ◽  
Magnetic Resonance Images ◽  
Future Research ◽  
Comparative Performance

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.

Parkinson's Disease

2019 ◽  
pp. 252-273 ◽  
Author(s):  
Vaibhav Walia ◽  
Ashish Gakkhar ◽  
Munish Garg
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Dopaminergic Neurons ◽  
Older Patients ◽  
Neurodegenerative Disorder ◽  
Progressive Loss ◽  
The Brain

Parkinson's disease (PD) is a neurodegenerative disorder in which a progressive loss of the dopaminergic neurons occurs. The loss of the neurons is most prominent in the substantia nigra region of the brain. The prevalence of PD is much greater among the older patients suggesting the risk of PD increases with the increase of age. The exact cause of the neurodegeneration in PD is not known. In this chapter, the authors introduce PD, demonstrate its history, pathogenesis, neurobiology, sign and symptoms, diagnosis, and pharmacotherapy.

Magnetic resonance imaging of the substantia nigra in Parkinson's disease

2012 ◽  
Vol 27 (7) ◽  
pp. 822-830 ◽  
Author(s):  
Stéphane Lehéricy ◽  
Michael A. Sharman ◽  
Clarisse Longo Dos Santos ◽  
Raphaël Paquin ◽  
Cecile Gallea
Keyword(s):  
Magnetic Resonance Imaging ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Substantia Nigra ◽  
Resonance Imaging

scholarly journals Dynamic changes in the CD163+ and CCR2+ peripheral monocytes during Parkinson’s disease

2021 ◽  
Author(s):  
Sara Konstantin Nissen ◽  
Kristine Farmen ◽  
Mikkel Carstensen ◽  
Claudia Schulte ◽  
David Goldeck ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dendritic Cells ◽  
Alpha Synuclein ◽  
Mononuclear Phagocytes ◽  
Motor Symptoms ◽  
Hla Dr ◽  
Non Motor Symptoms ◽  
The Brain ◽  
Classical Monocytes

AbstractBackgroundAlpha-synuclein aggregates and accumulation are associated with immune activation and neurodegeneration in Parkinson’s disease. The immune activation is not only dependent on the brain-resident microglial cells but also involves peripheral immune cells, such as mononuclear phagocytes including monocytes and dendritic cells, found in the blood as well as infiltrated into the brain. Understanding the involvement of the peripheral immune component in Parkinson’s disease is essential for the development of immunomodulatory treatment, which might modify disease progression. We aimed to study the profile of circulating mononuclear phagocytes in early- and late-stage Parkinson’s disease by analyzing surface-expressed molecules related to phagocytosis, alpha-synuclein sensing, and tissue-migration.MethodsMulti-color flow cytometry on peripheral mononuclear cells from cross-sectional samples of 80 gender-balance individuals with early- and late-stage sporadic Parkinson’s disease, and 29 controls, as well as longitudinal samples from seven patients and one control. Cells were delineated into natural killer cells, monocyte subtypes, and dendritic cells with cell frequencies and surface marker expressions compared between patients and controls, and correlated with standardized clinical motor and non-motor scores.ResultsOverall, we found elevated frequencies and surface levels of markers related to migration (CCR2, CD11b) and phagocytosis (CD163) particularly on the elevated classical and intermediate monocytes in patients with Parkinson’s disease for less than five years. This corresponded to a decrease of non-classical monocytes and dendritic cells. We observed an increased HLA-DR expression late in disease and sexual-dimorphism with TLR-4 expression decreased in women with PD but not in males. The disease-associated immune changes on TLR4, CCR2, and CD11b were correlated with non-motor symptoms such as olfaction or cognition. While many alterations were normalized at late disease stage, other changes remained, such as the increased HLA-DR and CD163 expressions.ConclusionsOur data highlight a role for peripheral CD163+ and migration-competent classical monocytes in Parkinson’s disease. The study further suggests that the peripheral immune system is dynamically altered in Parkinson’s disease stages and directly related to both non-motor symptoms and the sex-bias of the disease.

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