scholarly journals Patterns of Expression of Purinergic Receptor P2RY12, a Putative Marker for Non-Activated Microglia, in Aged and Alzheimer’s Disease Brains

2020 ◽  
Vol 21 (2) ◽  
pp. 678 ◽  
Author(s):  
Douglas G. Walker ◽  
Tiffany M. Tang ◽  
Anarmaa Mendsaikhan ◽  
Ikuo Tooyama ◽  
Geidy E. Serrano ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Purinergic Receptor ◽  
Pathological Process ◽  
Middle Temporal Gyrus ◽  
Reactive Microglia ◽  
Activated Microglia ◽  
Hla Dr ◽  
Microglial Phenotype ◽  
Putative Marker

Neuroinflammation is considered a key pathological process in neurodegenerative diseases of aging, including Alzheimer’s disease (AD). Many studies have defined phenotypes of reactive microglia, the brain-resident macrophages, with different antigenic markers to identify those potentially causing inflammatory damage. We took an alternative approach with the goal of characterizing the distribution of purinergic receptor P2RY12-positive microglia, a marker previously defined as identifying homeostatic or non-activated microglia. We examined the expression of P2RY12 by dual-color light and fluorescence immunohistochemistry using sections of middle temporal gyrus from AD, high plaque and low plaque non-demented cases in relation to amyloid beta (Aβ) plaques and phosphorylated tau, markers of pathology, and HLA-DR, IBA-1, CD68, and progranulin, microglial phenotype markers. In low plaque cases, P2RY12-positive microglia mostly had non-activated morphologies, while the morphologies of P2RY12-positive microglia in AD brains were highly variable, suggesting its expression could encompass a wider range of phenotypes than originally hypothesized. P2RY12 expression by microglia differed depending on the types of plaques or tangles they were associated with. Areas of inflammation characterized by lack of P2RY12-positive microglia around mature plaques could be observed, but many diffuse plaques showed colocalization with P2RY12-positive microglia. Based on these results, P2RY12 expression by microglia should not be considered solely a marker of resting microglia as P2RY12 immunoreactivity was identifying microglia positive for CD68, progranulin and to a limited extent HLA-DR, markers of activation.

Occurrence of HLA-DR Reactive Microglia in Alzheimer's Disease

1988 ◽  
Vol 540 (1 Advances in N) ◽  
pp. 319-323 ◽  
Author(s):  
P. L. McGEER ◽  
S. ITAGAKI ◽  
H. TAGO ◽  
E. G. McGEER
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Reactive Microglia ◽  
Hla Dr

Reactive microglia are positive for HLA-DR in the substantia nigra of Parkinson's and Alzheimer's disease brains

Neurology ◽  
1988 ◽  
Vol 38 (8) ◽  
pp. 1285-1285 ◽  
Author(s):  
P. L. McGeer ◽  
S. Itagaki ◽  
B. E. Boyes ◽  
E. G. McGeer
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Substantia Nigra ◽  
Reactive Microglia ◽  
Hla Dr

Consideration of a Pharmacological Combinatorial Approach to Inhibit Chronic Inflammation in Alzheimer’s Disease

2019 ◽  
Vol 16 (11) ◽  
pp. 1007-1017 ◽  
Author(s):  
James G. McLarnon
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Chronic Inflammation ◽  
Preventive Strategy ◽  
Subsequent Work ◽  
Activated Microglia ◽  
Starting Point ◽  
Anti Inflammatory ◽  
Cocktail Approach

A combinatorial cocktail approach is suggested as a rationale intervention to attenuate chronic inflammation and confer neuroprotection in Alzheimer’s disease (AD). The requirement for an assemblage of pharmacological compounds follows from the host of pro-inflammatory pathways and mechanisms present in activated microglia in the disease process. This article suggests a starting point using four compounds which present some differential in anti-inflammatory targets and actions but a commonality in showing a finite permeability through Blood-brain Barrier (BBB). A basis for firstchoice compounds demonstrated neuroprotection in animal models (thalidomide and minocycline), clinical trial data showing some slowing in the progression of pathology in AD brain (ibuprofen) and indirect evidence for putative efficacy in blocking oxidative damage and chemotactic response mediated by activated microglia (dapsone). It is emphasized that a number of candidate compounds, other than ones suggested here, could be considered as components of the cocktail approach and would be expected to be examined in subsequent work. In this case, systematic testing in AD animal models is required to rigorously examine the efficacy of first-choice compounds and replace ones showing weaker effects. This protocol represents a practical approach to optimize the reduction of microglial-mediated chronic inflammation in AD pathology. Subsequent work would incorporate the anti-inflammatory cocktail delivery as an adjunctive treatment with ones independent of inflammation as an overall preventive strategy to slow the progression of AD.

scholarly journals Neuroinflammation characterizes the earliest changes in Alzheimer’s disease pathology and associated subjective cognitive impairment in adult hydrocephalus biopsies

2020 ◽  
Author(s):  
Wenrui Huang ◽  
Anne Marie Bartosch ◽  
Harrison Xiao ◽  
Xena Flowers ◽  
Sandra Leskinen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Status ◽  
Subjective Cognitive Decline ◽  
Cognitive Symptoms ◽  
Microglial Phenotype ◽  
Neuronal Genes ◽  
Early Alzheimer’S Disease ◽  
Disease Associated Genes ◽  
Microglial Response

AbstractIn an effort to better characterize the transcriptomic changes that accompany early Alzheimer’s disease (AD) pathology in living patients and correlate with contemporaneous cognitive data, we performed RNA-seq on 106 cortical biopsies that were taken during shunt placement for adult onset hydrocephalus with varying degrees of comorbid AD pathology. A restricted set of genes correlate with AD pathology in these biopsies, and co-expression network analysis demonstrates an evolution from microglial homeostasis to a disease-associated microglial phenotype in conjunction with increasing AD pathologic burden, along with a subset of additional astrocytic and neuronal genes that accompany these changes. Further analysis demonstrates that these correlations are driven by patients that report mild cognitive symptoms, despite similar levels of β-amyloid and tau pathology in comparison to patients who report no cognitive symptoms. Interestingly, downregulation of homeostatic genes and upregulation of disease-associated genes also correlate with microglial plaque invasion and an activated microglial morphology, and this change is not sensitive to cognitive status, suggesting that an initial microglial response to AD pathology is eventually maladaptive. Taken together, these findings highlight a restricted set of microglial and non-microglial genes and suggest that early AD pathology is largely characterized by a loss of homeostatic genes and an activated microglial phenotype that continues to evolve in conjunction with accumulating AD pathology in the setting of subjective cognitive decline.

scholarly journals A Machine Learning Approach to Unmask Novel Gene Signatures and Prediction of Alzheimer’s Disease Within Different Brain Regions

2021 ◽  
Author(s):  
Abhibhav Sharma ◽  
Pinki Dey
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Non Coding Rna ◽  
Machine Learning Approach ◽  
Microarray Datasets ◽  
Rna Genes

AbstractAlzheimer’s disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unrevealed the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.

scholarly journals APP Regulates Microglial Phenotype in a Mouse Model of Alzheimer's Disease

2016 ◽  
Vol 36 (32) ◽  
pp. 8471-8486 ◽  
Author(s):  
G. D. Manocha ◽  
A. M. Floden ◽  
K. Rausch ◽  
J. A. Kulas ◽  
B. A. McGregor ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mouse Model ◽  
Model Of Alzheimer’S Disease ◽  
Microglial Phenotype

The complexity of Alzheimer's disease: an evolving puzzle

2021 ◽  
Author(s):  
Sandro Sorbi ◽  
Camilla Ferrari
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
New Technologies ◽  
Clinical Symptoms ◽  
Real Life ◽  
Pathological Process ◽  
Point Of View ◽  
Biological Entity ◽  
History Of ◽  
Static View

The history of Alzheimer's disease (AD) started in 1907, but we needed to wait until the end of the century to identify the component of pathological hallmarks, genetic subtypes and to formulate the first pathogenic hypothesis. Thanks to biomarkers and new technologies, the concept of AD then rapidly changed from a static view of an amnestic dementia of the presenium to a biological entity that could be clinically manifested as normal cognition or dementia of different types. What is clearly emerging from studies is that AD is heterogeneous in each aspect, such as amyloid composition, tau distribution, relation between amyloid and tau, clinical symptoms, genetic background, and thus it is probably impossible to explain AD with a single pathological process. The scientific approach to AD suffers from chronological mismatches between clinical, pathological and technological data, causing difficulty in conceiving diagnostic gold standards and in creating models for drug discovery and screening. A recent mathematical computer-based approach offers the opportunity to study AD in real life and to provide a new point of view and the final missing pieces of the AD puzzle.

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