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Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer's Disease.

ABSTRACT: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and represents the leading cause of cognitive impairment and dementia in older individuals throughout the world. The main hallmarks of AD include brain atrophy, extracellular deposition of insoluble amyloid-β (Aβ) plaques, and the intracellular aggregation of protein tau in neurofibrillary tangles. These pathological modifications start many years prior to clinical manifestations of disease and the spectrum of AD progresses along a continuum from preclinical to clinical phases. Therefore, identifying specific biomarkers for detecting AD at early stages greatly improves clinical management. However, stable and non-invasive biomarkers are not currently available for the early detection of the disease. In the search for more reliable biomarkers, epigenetic mechanisms, able to mediate the interaction between the genome and the environment, are emerging as important players in AD pathogenesis. Herein, we discuss altered epigenetic signatures in blood as potential peripheral biomarkers for the early detection of AD in order to help diagnosis and improve therapy.

SUBMITTER: Villa C

PROVIDER: S-EPMC9332601 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer's Disease.

Villa Chiara C Stoccoro Andrea A

Genes 20220722 8

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and represents the leading cause of cognitive impairment and dementia in older individuals throughout the world. The main hallmarks of AD include brain atrophy, extracellular deposition of insoluble amyloid-β (Aβ) plaques, and the intracellular aggregation of protein tau in neurofibrillary tangles. These pathological modifications start many years prior to clinical manifestations of disease and the <i>spectrum</i> of AD progres ...[more]

PMID: 35893045

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Project description:Many factors are involved in Alzheimer's disease (AD) pathology including tau phosphorylation, amyloid β protein (Aβ) accumulation, lipid dysregulation, oxidative stress, and inflammation. The markers of these pathological processes in cerebral spinal fluid are used currently for AD diagnosis. However, peripheral biomarkers are the need of the hour for large population screening for AD. The main objective of the present study is to evaluate the peripheral levels of redox markers, lipid peroxidation (LPO) indicators, and pathological markers in AD patients. Blood was collected from AD patients (n = 45), controls (n = 45), and analyzed for pathological markers of AD including Aβ42 and tau, LPO, and redox indicators. Plasma Aβ42 was significantly (P < 0.001) elevated while total tau was decreased in AD compared to controls. Hydroxynonenal (HNE) and malondialdehyde (MDA) were higher (P < 0.001) in AD patients pointing the enhanced LPO in AD pathology. Receiver operating characteristic curve (ROC) analysis indicated that HNE is a better indicator of LPO compared to MDA. Plasma glutathione (GSH) level was significantly (P < 0.001) low while oxidized glutathione (GSSG) level was higher (P < 0.001) in AD patients with corresponding decrease in GSH/GSSG ratio (P < 0.001). ROC analysis indicated that GSH/GSSG ratio can be used as reliable indicator for redox imbalance in AD with a cutoff value of <8.73 (sensitivity 91.1%, specificity 97.8%). Correlation analysis revealed a positive correlation for both HNE and MDA with Aβ42 and a negative correlation with total tau. Negative correlation was observed between GSH/GSSG ratio and LPO markers. While oxidative stress has been implicated in pathology of various neurodegenerative disorders, the present study pinpoints the direct link between LPO and Aβ production in plasma of AD patients. Normally, at low amyloid concentration in body fluids, this peptide shown to function as a strong metal chelating antioxidant. However, when the Aβ production enhanced as in AD, through gain of functional transformation, Aβ evolves into prooxidant, thereby enhancing oxidative stress and LPO. Altered redox status with enhanced LPO observed in AD blood could contribute to the oxidation and S-glutathionylation proteins, which has to be addressed in future studies.

Project description:BackgroundWith demographic shifts toward older populations, the number of people with dementia is steadily increasing. Alzheimer's disease (AD) is the most common cause of dementia, and no curative treatment is available. The current best strategy is to delay disease progression and to practice early intervention to reduce the number of patients that ultimately develop AD. Therefore, promising novel biomarkers for early diagnosis are urgently required.MethodsTo identify blood-based biomarkers for early diagnosis of AD, we performed RNA sequencing (RNA-seq) analysis of 610 blood samples, representing 271 patients with AD, 91 cognitively normal (CN) adults, and 248 subjects with mild cognitive impairment (MCI). We first estimated cell-type proportions among AD, MCI, and CN samples from the bulk RNA-seq data using CIBERSORT and then examined the differentially expressed genes (DEGs) between AD and CN samples. To gain further insight into the biological functions of the DEGs, we performed gene set enrichment analysis (GSEA) and network-based meta-analysis.ResultsIn the cell-type distribution analysis, we found a significant association between the proportion of neutrophils and AD prognosis at a false discovery rate (FDR) < 0.05. Furthermore, a similar trend emerged in the results of routine blood tests from a large number of samples (n = 3,099: AD, 1,605; MCI, 994; CN, 500). In addition, GSEA and network-based meta-analysis based on DEGs between AD and CN samples revealed functional modules and important hub genes associated with the pathogenesis of AD. The risk prediction model constructed by using the proportion of neutrophils and the most important hub genes (EEF2 and RPL7) achieved a high AUC of 0.878 in a validation cohort; when further applied to a prospective cohort, the model achieved a high accuracy of 0.727.ConclusionsOur model was demonstrated to be effective in prospective AD risk prediction. These findings indicate the discovery of potential biomarkers for early diagnosis of AD, and their further improvement may lead to future practical clinical use.

Dataset Information

Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer's Disease.

Publications

Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer's Disease.

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