Faculty Opinions recommendation of Investigation of the human brain metabolome to identify potential markers for early diagnosis and therapeutic targets of Alzheimer's disease.

2013 ◽  
Author(s):  
Laetitia Davidovic
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Human Brain ◽  
Therapeutic Targets

Investigation of the Human Brain Metabolome to Identify Potential Markers for Early Diagnosis and Therapeutic Targets of Alzheimer’s Disease

2013 ◽  
Vol 85 (3) ◽  
pp. 1803-1811 ◽  
Author(s):  
Stewart F. Graham ◽  
Olivier P. Chevallier ◽  
Dominic Roberts ◽  
Christian Hölscher ◽  
Christopher T. Elliott ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Human Brain ◽  
Therapeutic Targets

A Transfer Learning Approach for Early Diagnosis of Alzheimer’s Disease on MRI Images

Neuroscience ◽  
2021 ◽  
Author(s):  
Atif Mehmood ◽  
Shuyuan yang ◽  
Zhixi feng ◽  
Min wang ◽  
AL Smadi Ahmad ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Transfer Learning ◽  
Learning Approach

Phenylalanine Metabolism is Dysregulated in Human Hippocampus with Alzheimer’s Disease Related Pathological Changes

2021 ◽  
pp. 1-14
Author(s):  
Pan Liu ◽  
Qian Yang ◽  
Ning Yu ◽  
Yan Cao ◽  
Xue Wang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Human Brain ◽  
Pathological Examination ◽  
Pathological Changes ◽  
Targeted Metabolomics ◽  
Phenylpyruvic Acid ◽  
Postmortem Human Brain ◽  
Metabolic Dysregulation ◽  
Phenylalanine Metabolism

Background: Alzheimer’s disease (AD) is one of the most challenging diseases causing an increasing burden worldwide. Although the neuropathologic diagnosis of AD has been established for many years, the metabolic changes in neuropathologic diagnosed AD samples have not been fully investigated. Objective: To elucidate the potential metabolism dysregulation in the postmortem human brain samples assessed by AD related pathological examination. Methods: We performed untargeted and targeted metabolomics in 44 postmortem human brain tissues. The metabolic differences in the hippocampus between AD group and control (NC) group were compared. Results: The results show that a pervasive metabolic dysregulation including phenylalanine metabolism, valine, leucine, and isoleucine biosynthesis, biotin metabolism, and purine metabolism are associated with AD pathology. Targeted metabolomics reveal that phenylalanine, phenylpyruvic acid, and N-acetyl-L-phenylalanine are upregulated in AD samples. In addition, the enzyme IL-4I1 catalyzing transformation from phenylalanine to phenylpyruvic acid is also upregulated in AD samples. Conclusion: There is a pervasive metabolic dysregulation in hippocampus with AD-related pathological changes. Our study suggests that the dysregulation of phenylalanine metabolism in hippocampus may be an important pathogenesis for AD pathology formation.

scholarly journals The Role of Salivary Biomarkers in the Early Diagnosis of Alzheimer’s Disease and Parkinson’s Disease

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 371
Author(s):  
Patrycja Pawlik ◽  
Katarzyna Błochowiak
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Neurodegenerative Diseases ◽  
Diagnostic Tool ◽  
Clinical Symptoms ◽  
Early Screening ◽  
Salivary Biomarkers

Many neurodegenerative diseases present with progressive neuronal degeneration, which can lead to cognitive and motor impairment. Early screening and diagnosis of neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) are necessary to begin treatment before the onset of clinical symptoms and slow down the progression of the disease. Biomarkers have shown great potential as a diagnostic tool in the early diagnosis of many diseases, including AD and PD. However, screening for these biomarkers usually includes invasive, complex and expensive methods such as cerebrospinal fluid (CSF) sampling through a lumbar puncture. Researchers are continuously seeking to find a simpler and more reliable diagnostic tool that would be less invasive than CSF sampling. Saliva has been studied as a potential biological fluid that could be used in the diagnosis and early screening of neurodegenerative diseases. This review aims to provide an insight into the current literature concerning salivary biomarkers used in the diagnosis of AD and PD. The most commonly studied salivary biomarkers in AD are β-amyloid1-42/1-40 and TAU protein, as well as α-synuclein and protein deglycase (DJ-1) in PD. Studies continue to be conducted on this subject and researchers are attempting to find correlations between specific biomarkers and early clinical symptoms, which could be key in creating new treatments for patients before the onset of symptoms.

scholarly journals Artificial intelligence-based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shingo Tsuji ◽  
Takeshi Hase ◽  
Ayako Yachie-Kinoshita ◽  
Taiko Nishino ◽  
Samik Ghosh ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Drug Target ◽  
Target Genes ◽  
Drug Repositioning ◽  
Therapeutic Targets ◽  
Machine Learning Techniques ◽  
Computational Framework ◽  
Novel Therapeutic

Abstract Background Identifying novel therapeutic targets is crucial for the successful development of drugs. However, the cost to experimentally identify therapeutic targets is huge and only approximately 400 genes are targets for FDA-approved drugs. As a result, it is inevitable to develop powerful computational tools that can identify potential novel therapeutic targets. Fortunately, the human protein-protein interaction network (PIN) could be a useful resource to achieve this objective. Methods In this study, we developed a deep learning-based computational framework that extracts low-dimensional representations of high-dimensional PIN data. Our computational framework uses latent features and state-of-the-art machine learning techniques to infer potential drug target genes. Results We applied our computational framework to prioritize novel putative target genes for Alzheimer’s disease and successfully identified key genes that may serve as novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we could infer repositionable candidate-compounds for the disease (e.g., tamoxifen, bosutinib, and dasatinib). Conclusions Our deep learning-based computational framework could be a powerful tool to efficiently prioritize new therapeutic targets and enhance the drug repositioning strategy.

Genetic evidence for microglia-associated pathways as therapeutic targets for Alzheimer's disease

2016 ◽  
Vol 39 ◽  
pp. S6
Author(s):  
Claudio Villegas-Llerena ◽  
Mar Matarin ◽  
John Hardy ◽  
Jennifer Pocock
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Therapeutic Targets ◽  
Genetic Evidence
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