Serum Levels of Clusterin, PKR, and RAGE Correlate with Amyloid Burden in Alzheimer’s Disease

2021 ◽  
Vol 80 (3) ◽  
pp. 1067-1077
Author(s):  
Paloma Monllor ◽  
Esther Giraldo ◽  
Mari-Carmen Badia ◽  
Jose Garcia de la Asuncion ◽  
Maria-Dolores Alonso ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Serum Proteins ◽  
High Sensitivity ◽  
Serum Levels ◽  
Medical Community ◽  
Csf Biomarkers ◽  
Detection Model ◽  
N Classification ◽  
And Control

Background: Alzheimer’s disease (AD) is the most common form of dementia and biomarkers are essential to help in the diagnosis of this disease. Image techniques and cerebrospinal fluid (CSF) biomarkers are limited in their use because they are expensive or invasive. Thus, the search for blood-borne biomarkers is becoming central to the medical community. Objective: The main objective of this study is the evaluation of three serum proteins as potential biomarkers in AD patients. Methods: We recruited 27 healthy controls, 19 mild cognitive impairment patients, and 17 AD patients. Using the recent A/T/N classification we split our population into two groups (AD and control). We used ELISA kits to determine Aβ42, tau, and p-tau in CSF and clusterin, PKR, and RAGE in serum. Results: The levels of serum clusterin, PKR, and RAGE were statistically different in the AD group compared to controls. These proteins showed a statistically significant correlation with CSF Aβ42. So, they were selected to generate an AD detection model showing an AUC-ROC of 0.971 (CI 95%, 0.931–0.998). Conclusion: The developed model based on serum biomarkers and other co-variates could reflect the AD core pathology. So far, not one single blood-biomarker has been described, with effectiveness offering high sensitivity and specificity. We propose that the complexity of AD pathology could be reflected in a set of biomarkers also including clinical features of the patients.

Decreased α-Synuclein Serum Levels in Patients with Lewy Body Dementia Compared to Alzheimer’s Disease Patients and Control Subjects

2011 ◽  
Vol 31 (6) ◽  
pp. 413-416 ◽  
Author(s):  
Christoph Laske ◽  
Andreas J. Fallgatter ◽  
Elke Stransky ◽  
Katja Hagen ◽  
Daniela Berg ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Lewy Body ◽  
Lewy Body Dementia ◽  
Serum Levels ◽  
Control Subjects ◽  
And Control

scholarly journals Quantitative Measurement of Cerebrospinal Fluid Amyloid-β Species by Mass Spectrometry

2020 ◽  
pp. 1-12
Author(s):  
Yusuke Seino ◽  
Takumi Nakamura ◽  
Tomoo Harada ◽  
Naoko Nakahata ◽  
Takeshi Kawarabayashi ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Quantitative Measurement ◽  
Amyloid Β ◽  
High Sensitivity ◽  
Csf Biomarkers ◽  
Strongly Correlated ◽  
Csf Levels

Background: High sensitivity liquid chromatography mass spectrometry (LC-MS/MS) was recently introduced to measure amyloid-β (Aβ) species, allowing for a simultaneous assay that is superior to ELISA, which requires more assay steps with multiple antibodies. Objective: We validated the Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-43 assay by LC-MS/MS and compared it with ELISA using cerebrospinal fluid (CSF) samples to investigate its feasibility for clinical application. Methods: CSF samples from 120 subjects [8 Alzheimer’s disease (AD) with dementia (ADD), 2 mild cognitive dementia due to Alzheimer’s disease (ADMCI), 14 cognitively unimpaired (CU), and 96 neurological disease subjects] were analyzed. Aβ species were separated using the Shimadzu Nexera X2 system and quantitated using a Qtrap 5500 LC-MS/MS system. Aβ1-40 and Aβ1-42 levels were validated using ELISA. Results: CSF levels in CU were 666±249 pmol/L in Aβ1-38, 2199±725 pmol/L in Aβ1-40, 153.7±79.7 pmol/L in Aβ1-42, and 9.78±4.58 pmol/L in Aβ1-43. The ratio of the amounts of Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-43 was approximately 68:225:16:1. Linear regression analyses showed correlations among the respective Aβ species. Both Aβ1-40 and Aβ1-42 values were strongly correlated with ELISA measurements. No significant differences were observed in Aβ1-38 or Aβ1-40 levels between AD and CU. Aβ1-42 and Aβ1-43 levels were significantly lower, whereas the Aβ1-38/1-42, Aβ1-38/1-43, and Aβ1-40/Aβ1-43 ratios were significantly higher in AD than in CU. The basic assay profiles of the respective Aβ species were adequate for clinical usage. Conclusion: A quantitative LC-MS/MS assay of CSF Aβ species is as reliable as specific ELISA for clinical evaluation of CSF biomarkers for AD.

scholarly journals Blood Circulatory Level of Seven Sirtuins in Alzheimer’s Disease: Potent Biomarker Based on Translational Research

2021 ◽  
Author(s):  
Rashmita Pradhan ◽  
Abhinay Kumar Singh ◽  
Pramod Kumar ◽  
Swati Bajpai ◽  
Mona Pathak ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Roc Analysis ◽  
Serum Proteins ◽  
Neurodegenerative Disorder ◽  
High Sensitivity ◽  
Study Groups ◽  
Protein Markers ◽  
Potential Marker

Abstract Alzheimer's disease (AD) is an accelerating neurodegenerative disorder. Dysfunction of mitochondria and oxidative stress contributes to the pathogenesis of AD. Sirtuins play a role in this pathway and can be a potential marker to study neurodegenerative changes. This study evaluated serum levels of all seven sirtuins (SIRT1 – SIRT7) proteins in three study groups: AD, Mild Cognitive Impairment (MCI), and Geriatric Control (GC) by Surface Plasmon Resonance (SPR) technique. Further, it was validated by the Western blot experiment. ROC analysis was performed to differentiate the study group based on the concentration of serum SIRT proteins. Out of seven sirtuins, serum SIRT1, SIRT3, and SIRT6 levels (mean+SD) were significantly decreased in AD (1.65±0.56, 3.15±0.28, 3.36±0.32ng/µl); compare to MCI (2.17±0.39, 3.60±0.51, 3.73±0.48ng/µl) and GC (2.84±0.47, 4.55±0.48, 4.65±0.55ng/µl). ROC analysis showed the cut-off value with high sensitivity and specificity for cognitive impairment (AD and MCI). The concentration declined significantly with the disease progression. No specific difference was observed in case of other SIRTS between the study groups. This study reveals an inverse relation of serum SIRT1, SIRT3, and SIRT6 concentration with AD. ROC analysis showed that these serum proteins have greater accuracy in diagnosing of AD. This is the first report of estimation of all seven serum sirtuins and the clinical relevance of SIRT3 and SIRT6 as serum protein markers for AD.

scholarly journals Blood circulatory level of seven sirtuins in Alzheimer’s disease: Potent biomarker based on translational research

2021 ◽  
Author(s):  
Rashmita Pradhan ◽  
Abhinay Kumar Singh ◽  
Pramod Kumar ◽  
Swati Bajpai ◽  
Mona Pathak ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Roc Analysis ◽  
Serum Proteins ◽  
Neurodegenerative Disorder ◽  
High Sensitivity ◽  
Study Groups ◽  
Protein Markers ◽  
Potential Marker

Abstract Alzheimer's disease (AD) is an accelerating neurodegenerative disorder. Dysfunction of mitochondria and oxidative stress contributes to the pathogenesis of AD. Sirtuins play a role in this pathway and can be a potential marker to study neurodegenerative changes. This study evaluated serum levels of all seven sirtuins (SIRT1 – SIRT7) proteins in three study groups: AD, Mild Cognitive Impairment (MCI), and Geriatric Control (GC) by Surface Plasmon Resonance (SPR) technique. Further, it was validated by the Western blot experiment. ROC analysis was performed to differentiate the study group based on the concentration of serum SIRT proteins. Out of seven sirtuins, serum SIRT1, SIRT3, and SIRT6 levels (mean ± SD) were significantly decreased in AD (1.65 ± 0.56, 3.15 ± 0.28, 3.36 ± 0.32ng/µl); compare to MCI (2.17 ± 0.39, 3.60 ± 0.51, 3.73 ± 0.48ng/µl) and GC (2.84 ± 0.47, 4.55 ± 0.48, 4.65 ± 0.55ng/µl). ROC analysis showed the cut-off value with high sensitivity and specificity for cognitive impairment (AD and MCI). The concentration declined significantly with the disease progression. No specific difference was observed in case of other SIRTS between the study groups. This study reveals an inverse relation of serum SIRT1, SIRT3, and SIRT6 concentration with AD. ROC analysis showed that these serum proteins have greater accuracy in diagnosing of AD. This is the first report of estimation of all seven serum sirtuins and the clinical relevance of SIRT3 and SIRT6 as serum protein markers for AD.

scholarly journals Altered Bile Acid Profile in Mild Cognitive Impairment and Alzheimer’s Disease: Relationship to Neuroimaging and CSF Biomarkers

2018 ◽  
Author(s):  
Kwangsik Nho ◽  
Alexandra Kueider-Paisley ◽  
Siamak MahmoudianDehkordi ◽  
Matthias Arnold ◽  
Shannon L. Risacher ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Glucose Metabolism ◽  
Cholesterol Metabolism ◽  
Amyloid Β ◽  
Serum Levels ◽  
Model Systems ◽  
Csf Biomarkers ◽  
Clinical Observations ◽  
T Tau

AbstractIntroductionBile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer’s disease (AD) including neuroinflammation and amyloid-β deposition.MethodSerum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n=1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the “A/T/N” (Amyloid, Tau and Neurodegeneration) biomarkers for AD: CSF biomarkers, atrophy (MRI), and brain glucose metabolism ([18F]FDG-PET).ResultsOf 23 BA and relevant calculated ratios, three BA signatures were associated with CSF Aβ1-42 (“A”) and three with CSF p-tau181 (“T”) (corrected p<0.05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy (“N”), respectively (corrected p<0.05).ConclusionThis is the first study to show serum-based BA metabolites are associated with “A/T/N” AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.

SPECIFIC PROPERTIES OF TUBULIN IN THE PREFRONTAL CORTEX IN CONTROL, SCHIZOPHRENIA AND VASCULAR DEMENTIA

2020 ◽  
pp. 65-71
Author(s):  
Burbaeva G.Sh. ◽  
Androsova L.V. ◽  
Vorobyeva E.A. ◽  
Savushkina O.K.
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prefrontal Cortex ◽  
Vascular Dementia ◽  
Binding Activity ◽  
Nephelometric Method ◽  
Rate Of Polymerization ◽  
Mental Diseases ◽  
And Control ◽  
The Brain

The aim of the study was to evaluate the rate of polymerization of tubulin into microtubules and determine the level of colchicine binding (colchicine-binding activity of tubulin) in the prefrontal cortex in schizophrenia, vascular dementia (VD) and control. Colchicine-binding activity of tubulin was determined by Sherlinе in tubulin-enriched extracts of proteins from the samples. Measurement of light scattering during the polymerization of the tubulin was carried out using the nephelometric method at a wavelength of 450-550 nm. There was a significant decrease in colchicine-binding activity and the rate of tubulin polymerization in the prefrontal cortex in both diseases, and in VD to a greater extent than in schizophrenia. The obtained results suggest that not only in Alzheimer's disease, but also in other mental diseases such as schizophrenia and VD, there is a decrease in the level of tubulin in the prefrontal cortex of the brain, although to a lesser extent than in Alzheimer's disease, and consequently the amount of microtubules.

scholarly journals A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaker El-Sappagh ◽  
Jose M. Alonso ◽  
S. M. Riazul Islam ◽  
Ahmad M. Sultan ◽  
Kyung Sup Kwak
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cross Validation ◽  
Disease Risk ◽  
Binary Classification ◽  
Fuzzy Rule ◽  
Large Set ◽  
Detection Model ◽  
Multi Class Classification ◽  
Clinical Measures

AbstractAlzheimer’s disease (AD) is the most common type of dementia. Its diagnosis and progression detection have been intensively studied. Nevertheless, research studies often have little effect on clinical practice mainly due to the following reasons: (1) Most studies depend mainly on a single modality, especially neuroimaging; (2) diagnosis and progression detection are usually studied separately as two independent problems; and (3) current studies concentrate mainly on optimizing the performance of complex machine learning models, while disregarding their explainability. As a result, physicians struggle to interpret these models, and feel it is hard to trust them. In this paper, we carefully develop an accurate and interpretable AD diagnosis and progression detection model. This model provides physicians with accurate decisions along with a set of explanations for every decision. Specifically, the model integrates 11 modalities of 1048 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) real-world dataset: 294 cognitively normal, 254 stable mild cognitive impairment (MCI), 232 progressive MCI, and 268 AD. It is actually a two-layer model with random forest (RF) as classifier algorithm. In the first layer, the model carries out a multi-class classification for the early diagnosis of AD patients. In the second layer, the model applies binary classification to detect possible MCI-to-AD progression within three years from a baseline diagnosis. The performance of the model is optimized with key markers selected from a large set of biological and clinical measures. Regarding explainability, we provide, for each layer, global and instance-based explanations of the RF classifier by using the SHapley Additive exPlanations (SHAP) feature attribution framework. In addition, we implement 22 explainers based on decision trees and fuzzy rule-based systems to provide complementary justifications for every RF decision in each layer. Furthermore, these explanations are represented in natural language form to help physicians understand the predictions. The designed model achieves a cross-validation accuracy of 93.95% and an F1-score of 93.94% in the first layer, while it achieves a cross-validation accuracy of 87.08% and an F1-Score of 87.09% in the second layer. The resulting system is not only accurate, but also trustworthy, accountable, and medically applicable, thanks to the provided explanations which are broadly consistent with each other and with the AD medical literature. The proposed system can help to enhance the clinical understanding of AD diagnosis and progression processes by providing detailed insights into the effect of different modalities on the disease risk.

scholarly journals Commonalities between Copper Neurotoxicity and Alzheimer’s Disease

Toxics ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 4
Author(s):  
Roshni Patel ◽  
Michael Aschner
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Structural Changes ◽  
Copper Ion ◽  
Plaque Formation ◽  
Ion Concentration ◽  
Medical Community ◽  
Disease Etiology ◽  
Parent Protein ◽  
Lead Zinc

Alzheimer’s disease, a highly prevalent form of dementia, targets neuron function beginning from the hippocampal region and expanding outwards. Alzheimer’s disease is caused by elevated levels of heavy metals, such as lead, zinc, and copper. Copper is found in many areas of daily life, raising a concern as to how this metal and Alzheimer’s disease are related. Previous studies have not identified the common pathways between excess copper and Alzheimer’s disease etiology. Our review corroborates that both copper and Alzheimer’s disease target the hippocampus, cerebral cortex, cerebellum, and brainstem, affecting motor skills and critical thinking. Additionally, Aβ plaque formation was analyzed beginning from synthesis at the APP parent protein site until Aβ plaque formation was completed. Structural changes were also noted. Further analysis revealed a relationship between amyloid-beta plaques and copper ion concentration. As copper ion levels increased, it bound to the Aβ monomer, expediting the plaque formation process, and furthering neurodegeneration. These conclusions can be utilized in the medical community to further research on the etiology of Alzheimer’s disease and its relationships to copper and other metal-induced neurotoxicity.

scholarly journals Optical Imaging of Beta-Amyloid Plaques in Alzheimer’s Disease

Biosensors ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 255
Author(s):  
Ziyi Luo ◽  
Hao Xu ◽  
Liwei Liu ◽  
Tymish Y. Ohulchanskyy ◽  
Junle Qu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Optical Imaging ◽  
Imaging Techniques ◽  
High Sensitivity ◽  
Pathological Feature ◽  
Promising Tool ◽  
Abnormal Accumulation ◽  
Accumulation Mechanism ◽  
The Brain

Alzheimer’s disease (AD) is a multifactorial, irreversible, and incurable neurodegenerative disease. The main pathological feature of AD is the deposition of misfolded β-amyloid protein (Aβ) plaques in the brain. The abnormal accumulation of Aβ plaques leads to the loss of some neuron functions, further causing the neuron entanglement and the corresponding functional damage, which has a great impact on memory and cognitive functions. Hence, studying the accumulation mechanism of Aβ in the brain and its effect on other tissues is of great significance for the early diagnosis of AD. The current clinical studies of Aβ accumulation mainly rely on medical imaging techniques, which have some deficiencies in sensitivity and specificity. Optical imaging has recently become a research hotspot in the medical field and clinical applications, manifesting noninvasiveness, high sensitivity, absence of ionizing radiation, high contrast, and spatial resolution. Moreover, it is now emerging as a promising tool for the diagnosis and study of Aβ buildup. This review focuses on the application of the optical imaging technique for the determination of Aβ plaques in AD research. In addition, recent advances and key operational applications are discussed.

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