Diagnostic Model of Alzheimer’s Disease in the Elderly Based on Protein and Metabolic Biomarkers

Background: With the accelerating aging process, the number of participants with Alzheimer’s disease (AD) is rising sharply, causing a huge economic burden. Objective: This study aimed to identify blood protein and metabolic biomarkers and explore the diagnostic model for AD among elderly in southeast China. Methods: We established a cohort among population with high risk AD in Zhejiang Province in 2018. Case and control groups each consisting of 45 subjects, matched for gender and age, were randomly selected from the cohort. Based on bioinformatics research, PRM/MRM technology was used to detect candidate biomarkers. Ensemble-based feature selection and machine learning methods was used to screen important variables as risk indicators for AD. Based on the risk biomarkers, the risk diagnostic model of AD in the elderly was constructed and evaluated. Results: Cystine and CPB2 were evaluated as biomarkers. The diagnostic model is constructed using logistic regression algorithm with the best cutoff value, sensitivity, specificity, and accuracy of 0.554, 0.895, 0.976, and 0.938, respectively, which determined by Youden’s index. The results showed that the model with protein and metabolite had a high efficiency. Conclusion: It showed that the diagnostic model constructed by Cystine and CPB2 had a good performance on sample classification. This study was of great significance for the early screening and diagnosis of AD, timely intervention, control and delay the development of dementia in southeast China.

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Development of Random Forest Algorithm Based Prediction Model of Alzheimer’s Disease Using Neurodegeneration Pattern

Psychiatry Investigation ◽

10.30773/pi.2020.0304 ◽

2021 ◽

Vol 18 (1) ◽

pp. 69-79

Author(s):

JeeYoung Kim ◽

Minho Lee ◽

Min Kyoung Lee ◽

Sheng-Min Wang ◽

Nak-Young Kim ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Random Forest ◽

Diagnostic Accuracy ◽

Prediction Model ◽

Clinical Symptoms ◽

The Elderly ◽

Structural Mri ◽

Brain Segmentation ◽

Model Of Alzheimer’S Disease

Objective Alzheimer’s disease (AD) is the most common type of dementia and the prevalence rapidly increased as the elderly population increased worldwide. In the contemporary model of AD, it is regarded as a disease continuum involving preclinical stage to severe dementia. For accurate diagnosis and disease monitoring, objective index reflecting structural change of brain is needed to correctly assess a patient’s severity of neurodegeneration independent from the patient’s clinical symptoms. The main aim of this paper is to develop a random forest (RF) algorithm-based prediction model of AD using structural magnetic resonance imaging (MRI).Methods We evaluated diagnostic accuracy and performance of our RF based prediction model using newly developed brain segmentation method compared with the Freesurfer’s which is a commonly used segmentation software.Results Our RF model showed high diagnostic accuracy for differentiating healthy controls from AD and mild cognitive impairment (MCI) using structural MRI, patient characteristics, and cognitive function (HC vs. AD 93.5%, AUC 0.99; HC vs. MCI 80.8%, AUC 0.88). Moreover, segmentation processing time of our algorithm (<5 minutes) was much shorter than of Freesurfer’s (6–8 hours).Conclusion Our RF model might be an effective automatic brain segmentation tool which can be easily applied in real clinical practice.

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The Dynamics of β-Amyloid Proteoforms Accumulation in the Brain of a 5xFAD Mouse Model of Alzheimer’s Disease

International Journal of Molecular Sciences ◽

10.3390/ijms23010027 ◽

2021 ◽

Vol 23 (1) ◽

pp. 27

Author(s):

Anna E. Bugrova ◽

Polina A. Strelnikova ◽

Maria I. Indeykina ◽

Alexey S. Kononikhin ◽

Natalia V. Zakharova ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Mouse Model ◽

Senile Plaques ◽

The Elderly ◽

Mobility Separation ◽

Model Of Alzheimer’S Disease ◽

Β Amyloid ◽

Ion Mobility Separation ◽

The Brain

Alzheimer’s disease (AD) is the leading cause of dementia among the elderly. Neuropathologically, AD is characterized by the deposition of a 39- to 42-amino acid long β-amyloid (Aβ) peptide in the form of senile plaques. Several post-translational modifications (PTMs) in the N-terminal domain have been shown to increase the aggregation and cytotoxicity of Aβ, and specific Aβ proteoforms (e.g., Aβ with isomerized D7 (isoD7-Aβ)) are abundant in the senile plaques of AD patients. Animal models are indispensable tools for the study of disease pathogenesis, as well as preclinical testing. In the presented work, the accumulation dynamics of Aβ proteoforms in the brain of one of the most widely used amyloid-based mouse models (the 5xFAD line) was monitored. Mass spectrometry (MS) approaches, based on ion mobility separation and the characteristic fragment ion formation, were applied. The results indicated a gradual increase in the Aβ fraction of isoD7-Aβ, starting from approximately 8% at 7 months to approximately 30% by 23 months of age. Other specific PTMs, in particular, pyroglutamylation, deamidation, and oxidation, as well as phosphorylation, were also monitored. The results for mice of different ages demonstrated that the accumulation of Aβ proteoforms correlate with the formation of Aβ deposits. Although the mouse model cannot be a complete analogue of the processes occurring in the human brain in AD, and several of the observed parameters differ significantly from human values supposedly due to the limited lifespan of the model animals, this dynamic study provides evidence on at least one of the possible mechanisms that can trigger amyloidosis in AD, i.e., the hypothesis on the relationship between the accumulation of isoD7-Aβ and the progression of AD-like pathology.

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Progress in Target Drug Molecules for Alzheimer's Disease

Current Topics in Medicinal Chemistry ◽

10.2174/1568026619666191203113745 ◽

2020 ◽

Vol 20 (1) ◽

pp. 4-36 ◽

Cited By ~ 4

Author(s):

Jiayang Xie ◽

Ruirui Liang ◽

Yajiang Wang ◽

Junyi Huang ◽

Xin Cao ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Side Effects ◽

Research And Development ◽

Neurodegenerative Disease ◽

High Efficiency ◽

The Elderly ◽

Drug Molecules ◽

Target Drug

Alzheimer's disease (AD) is a chronic neurodegenerative disease that 4 widespread in the elderly. The etiology of AD is complicated, and its pathogenesis is still unclear. Although there are many researches on anti-AD drugs, they are limited to reverse relief symptoms and cannot treat diseases. Therefore, the development of high-efficiency anti-AD drugs with no side effects has become an urgent need. Based on the published literature, this paper summarizes the main targets of AD and their drugs, and focuses on the research and development progress of these drugs in recent years.

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Effect Of Nhexane Extract Of Caryota No Seed On Markers Of Neurodegeneration And Fecundity In Drosophila Melanogaster

Gerontology & Geriatric Medicine ◽

10.24966/ggm-8662/100073 ◽

2020 ◽

Vol 6 (5) ◽

pp. 1-7

Author(s):

Chinonye A Maduagwuna ◽

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Drosophila Melanogaster ◽

Neurodegenerative Diseases ◽

Cognitive Functions ◽

The Elderly ◽

Common Cause ◽

Chronic Neuroinflammation

Study background: Chronic neuroinflammation is a common emerging hallmark of several neurodegenerative diseases. Alzheimer’s Disease (AD) is the most common cause of dementia among the elderly and is characterized by loss of memory and other cognitive functions.

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