scholarly journals Impaired Mitochondrial and Glycolytic Functions in Peripheral Blood Leukocytes of Alzheimer’s Disease

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 120-120
Author(s):  
Ravindra Bharadwaj ◽  
Hayley Gibler ◽  
Sanjay Srivastava ◽  
Hena Tewari
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Normal Subjects ◽  
Blood Leukocytes ◽  
Blood Samples ◽  
Dementia Patients ◽  
Cellular Bioenergetics ◽  
Systemic Nature ◽  
Systemic Defect

Abstract Recent failures of the trials targeting amyloid to treat Alzheimer’s disease (AD) are prompting scientists to explore other pathological pathways. Brains of AD patients have been noted to have impaired mitochondrial function. It has not yet been determined if AD is caused by a systemic defect in cellular bioenergetics. To determine the cellular bioenergetics, we compared the Oxygen Consumption Rate (OCR – indicating oxygen dependent respiration) and Extra Cellular Acidification Rate (ECAR – indicating glycolytic function) in leukocytes of collected blood samples of Alzheimer’s and non-dementia patients. Methods: After IRB approval and consents, blood samples from each clinically diagnosed Alzheimer’s and age matched normal subjects were collected. Immediately after collection the blood samples were analyzed using Agilent Seahorse XFe/XF Analyzer as per protocol by manufacturer. Results: Impaired mitochondrial and glycolytic functions were noted in Alzheimer’s patients as compared to normal subjects. OCR was significantly lower in Alzheimer’s patients. A lower rate of respiration was noted both at basal as well as maximal respiration. Reduced spare respiration capacity was also noted in response to the stressors. Similarly reduced ECAR and reduced glycolytic reserve was also noted in Alzheimer’s patients, indicating impaired oxygen independent mitochondrial respiration. Discussion: This pilot study demonstrates that there is an impaired mitochondrial and glycolytic function in the peripheral blood cells. This indicates towards a systemic nature of the disease and a potential future bio-marker. Further studies should be planned in this direction.

P1-345: BDNF mRNA levels are decreased in peripheral blood samples from subjects with Alzheimer's disease

2008 ◽  
Vol 4 ◽  
pp. T320-T320 ◽  
Author(s):  
Margaret Fahnestock ◽  
Shiyong Peng ◽  
Monica Marchese ◽  
Elaine R. Delvaux ◽  
Paul D. Coleman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Mrna Levels ◽  
Bdnf Mrna ◽  
Blood Samples

scholarly journals Early detection of Alzheimer's disease using the Cambridge Cognitive Examination (CAMCOG)

2000 ◽  
Vol 30 (3) ◽  
pp. 619-627 ◽  
Author(s):  
B. SCHMAND ◽  
G. WALSTRA ◽  
J. LINDEBOOM ◽  
S. TEUNISSE ◽  
C. JONKER
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Normal Subjects ◽  
The Elderly ◽  
Population Based ◽  
Dementia Screening ◽  
Dementia Patients ◽  
Cognitively Intact ◽  
Better Than

Background. Dementia screening instruments, such as the Cambridge Cognitive Examination (CAMCOG), measure a variety of cognitive functions. However, memory impairment generally is the first sign of Alzheimer's disease (AD). It seems logical, therefore, to use only memory-related items for the early detection of AD. We divided the CAMCOG into a memory section and a non-memory section, and tested the hypothesis that the memory section predicts AD better than the non-memory section. We also provide normative data for both sections.Methods. Normal subjects (N = 169) and patients with incident AD (i.e. satisfying AD criteria between 1 and 3 years from baseline; N = 25) were participants in the Amsterdam Study of the Elderly (AMSTEL), a population-based longitudinal study on cognitive decline and dementia. Patients with prevalent AD (i.e. satisfying AD criteria at baseline; N = 155) were either recruited in a memory clinic or came from AMSTEL. Normal subjects were cognitively intact at baseline and remained so for at least 3 years. The CAMCOG was administered to all subjects. AD was diagnosed by DSM-III-R criteria.Results. Logistic regression analysis showed that the memory section was related to prevalent AD, whereas in multivariate analysis the non-memory section was not (after correction for the memory score and demographic characteristics). A similar analysis showed that the memory section predicted incident AD, as did a higher score on the non-memory section. The MMSE did not predict incident AD better than age alone.Conclusion. For the early detection of AD it is best to use the memory and non-memory sections separately instead of the total CAMCOG score.

scholarly journals Association between methylation of BIN1 promoter in peripheral blood and preclinical Alzheimer’s disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hao Hu ◽  
Lan Tan ◽  
Yan-Lin Bi ◽  
Wei Xu ◽  
Lin Tan ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Late Onset ◽  
Early Stage ◽  
Susceptibility Gene ◽  
Subjective Cognitive Decline ◽  
Preclinical Ad ◽  
T Tau ◽  
New Evidence

AbstractThe bridging integrator 1 (BIN1) gene is the second most important susceptibility gene for late-onset Alzheimer’s disease (LOAD) after apolipoprotein E (APOE) gene. To explore whether the BIN1 methylation in peripheral blood changed in the early stage of LOAD, we included 814 participants (484 cognitively normal participants [CN] and 330 participants with subjective cognitive decline [SCD]) from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) database. Then we tested associations of methylation of BIN1 promoter in peripheral blood with the susceptibility for preclinical AD or early changes of cerebrospinal fluid (CSF) AD-related biomarkers. Results showed that SCD participants with significant AD biological characteristics had lower methylation levels of BIN1 promoter, even after correcting for covariates. Hypomethylation of BIN1 promoter were associated with decreased CSF Aβ42 (p = 0.0008), as well as increased p-tau/Aβ42 (p = 0.0001) and t-tau/Aβ42 (p < 0.0001) in total participants. Subgroup analysis showed that the above associations only remained in the SCD subgroup. In addition, hypomethylation of BIN1 promoter was also accompanied by increased CSF p-tau (p = 0.0028) and t-tau (p = 0.0130) in the SCD subgroup, which was independent of CSF Aβ42. Finally, above associations were still significant after correcting single nucleotide polymorphic sites (SNPs) and interaction of APOE ɛ4 status. Our study is the first to find a robust association between hypomethylation of BIN1 promoter in peripheral blood and preclinical AD. This provides new evidence for the involvement of BIN1 in AD, and may contribute to the discovery of new therapeutic targets for AD.

scholarly journals Classifying Non-Dementia and Alzheimer’s Disease/Vascular Dementia Patients Using Kinematic, Time-Based, and Visuospatial Parameters: The Digital Clock Drawing Test

2021 ◽  
Vol 82 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Anis Davoudi ◽  
Catherine Dion ◽  
Shawna Amini ◽  
Patrick J. Tighe ◽  
Catherine C. Price ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Area Under The Curve ◽  
Clock Drawing Test ◽  
Digital Clock ◽  
Clock Drawing ◽  
Drawing Test ◽  
Dementia Patients ◽  
Optimal Area

Background: Advantages of digital clock drawing metrics for dementia subtype classification needs examination. Objective: To assess how well kinematic, time-based, and visuospatial features extracted from the digital Clock Drawing Test (dCDT) can classify a combined group of Alzheimer’s disease/Vascular Dementia patients versus healthy controls (HC), and classify dementia patients with Alzheimer’s disease (AD) versus vascular dementia (VaD). Methods: Healthy, community-dwelling control participants (n = 175), patients diagnosed clinically with Alzheimer’s disease (n = 29), and vascular dementia (n = 27) completed the dCDT to command and copy clock drawing conditions. Thirty-seven dCDT command and 37 copy dCDT features were extracted and used with Random Forest classification models. Results: When HC participants were compared to participants with dementia, optimal area under the curve was achieved using models that combined both command and copy dCDT features (AUC = 91.52%). Similarly, when AD versus VaD participants were compared, optimal area under the curve was, achieved with models that combined both command and copy features (AUC = 76.94%). Subsequent follow-up analyses of a corpus of 10 variables of interest determined using a Gini Index found that groups could be dissociated based on kinematic, time-based, and visuospatial features. Conclusion: The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. These data suggest that kinematic, time-based, and visuospatial behavior obtained using the dCDT may provide additional neurocognitive biomarkers that may be able to identify and tract dementia syndromes.

scholarly journals Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Weishuang Xue ◽  
Jinwei Li ◽  
Kailei Fu ◽  
Weiyu Teng
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Bioinformatics Analysis ◽  
Gene Expression Omnibus ◽  
Venn Diagram ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

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