Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer’s Disease

Restoring the epigenome in Alzheimer's disease: advancing HDAC inhibitors as therapeutic agents

Current treatment options for Alzheimer's disease (AD) focus on symptom relief rather than halting disease progression. In this context, targeting histone deacetylation emerges as a promising therapeutic alternative. Dysregulation of histone deacetylase (HDAC) activity is present in AD, contributing to cognitive decline. Pharmacological HDAC inhibition has shown benefits in preclinical models, namely reduced amyloid beta plaque formation, lower phosphorylation and aggregation of tau protein, greater microtubule stability, less neuroinflammation, and improved metabolic homeostasis and cell survival. Nonetheless, clinical trials evidenced limitations such as insufficient selectivity or blood-brain barrier penetration. Hence, future innovative strategies are required to enhance their efficacy/safety.

Epigenetics in Alzheimer's Disease: A Critical Overview

Epigenetic modifications have been implicated in a number of complex diseases as well as being a hallmark of organismal aging. Several reports have indicated an involvement of these changes in Alzheimer's disease (AD) risk and progression, most likely contributing to the dysregulation of AD-related gene expression measured by DNA methylation studies. Given that DNA methylation is tissue-specific and that AD is a brain disorder, the limitation of these studies is the ability to identify clinically useful biomarkers in a proxy tissue, reflective of the tissue of interest, that would be less invasive, more cost-effective, and easily obtainable. The age-related DNA methylation changes have also been used to develop different generations of epigenetic clocks devoted to measuring the aging in different tissues that sometimes suggests an age acceleration in AD patients. This review critically discusses epigenetic changes and aging measures as potential biomarkers for AD detection, prognosis, and progression. Given that epigenetic alterations are chemically reversible, treatments aiming at reversing these modifications will be also discussed as promising therapeutic strategies for AD.

An Overview of the Epigenetic Modifications in the Brain under Normal and Pathological Conditions

Epigenetic changes are changes in gene expression that do not involve alterations to the DNA sequence. These changes lead to establishing a so-called epigenetic code that dictates which and when genes are activated, thus orchestrating gene regulation and playing a central role in development, health, and disease. The brain, being mostly formed by cells that do not undergo a renewal process throughout life, is highly prone to the risk of alterations leading to neuronal death and neurodegenerative disorders, mainly at a late age. Here, we review the main epigenetic modifications that have been described in the brain, with particular attention on those related to the onset of developmental anomalies or neurodegenerative conditions and/or occurring in old age. DNA methylation and several types of histone modifications (acetylation, methylation, phosphorylation, ubiquitination, sumoylation, lactylation, and crotonylation) are major players in these processes. They are directly or indirectly involved in the onset of neurodegeneration in Alzheimer's or Parkinson's disease. Therefore, this review briefly describes the roles of these epigenetic changes in the mechanisms of brain development, maturation, and aging and some of the most important factors dynamically regulating or contributing to these changes, such as oxidative stress, inflammation, and mitochondrial dysfunction.

A hybrid multimodal machine learning model for Detecting Alzheimer's disease

Alzheimer's disease (AD) diagnosis utilizing single modality neuroimaging data has limitations. Multimodal fusion of complementary biomarkers may improve diagnostic performance. This study proposes a multimodal machine learning framework integrating magnetic resonance imaging (MRI), positron emission tomography (PET) and cerebrospinal fluid (CSF) assays for enhanced AD characterization. The model incorporates a hybrid algorithm combining enhanced Harris Hawks Optimization (HHO) algorithm referred to as ILHHO, with Kernel Extreme Learning Machine (KELM) classifier for simultaneous feature selection and classification. ILHHO enhances HHO's search efficiency by integrating iterative mapping (IM) to improve population diversity and local escaping operator (LEO) to balance exploration-exploitation. Comparative analysis with other improved HHO algorithms, classic meta-heuristic algorithms (MHAs), and state-of-the-art MHAs on IEEE CEC2014 benchmark functions indicates that ILHHO achieves superior optimization performance compared to other comparative algorithms. The synergistic ILHHO-KELM model is evaluated on 202 AD Neuroimaging Initiative (ADNI) subjects. Results demonstrate superior multimodal classification accuracy over single modalities, validating the importance of fusing heterogeneous biomarkers. MRI + PET + CSF achieves 99.2 % accuracy for AD vs. normal control (NC), outperforming conventional and proposed methods. Discriminative feature analysis provides further insights into differential AD-related neurodegeneration patterns detected by MRI and PET. The differential PET and MRI features demonstrate how the two modalities provide complementary biomarkers. The neuroanatomical relevance of selected features supports ILHHO-KELM's potential for extracting sensitive AD imaging signatures. Overall, the study showcases the advantages of capitalizing on complementary multimodal data through advanced feature learning techniques for improving AD diagnosis.

Alzheimer's Disease-Related Epigenetic Changes: Novel Therapeutic Targets

Aging is a significant risk factor for Alzheimer's disease (AD), although the precise mechanism and molecular basis of AD are not yet fully understood. Epigenetic mechanisms, such as DNA methylation and hydroxymethylation, mitochondrial DNA methylation, histone modifications, and non-coding RNAs (ncRNAs), play a role in regulating gene expression related to neuron plasticity and integrity, which are closely associated with learning and memory development. This review describes the impact of dynamic and reversible epigenetic modifications and factors on memory and plasticity throughout life, emphasizing their potential as target for therapeutic intervention in AD. Additionally, we present insight from postmortem and animal studies on abnormal epigenetics regulation in AD, as well as current strategies aiming at targeting these factors in the context of AD therapy.

LncRNA THRIL Functions as a Marker for Carotid Artery Stenosis and Affects the Biological Function of Human Aortic Endothelial Cell

Purpose

Carotid artery restenosis (CAS) is a leading contributor to cerebrovascular diseases and one of the leading causes of death in the world. The purpose of this study was to assess the predictive efficiency of long non-coding RNA (lncRNA) TNFalpha-and hnRNP L-related immunoregulatory lncRNA (THRIL) and its association with the pathogenesis of CAS.

Patients and Methods

The expression of THRIL was determined in patients with asymptomatic CAS and human aortic endothelial cell (HAEC) models induced by oxidized low-density lipoprotein (ox-LDL). The receiver operating characteristic (ROC) curve and Kaplan-Meier (K-M) drawings were constructed to predict the risk of poor prognosis in patients with CAS. The cell proliferation, death rate, and inflammation were detected by 3-(4,5-dimethyl-2-thiazyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT), flow cytometry, and enzyme-linked immunosorbent assay (ELISA) assays.

Results

The relative expression of THRIL was elevated in patients with asymptomatic CAS. The findings of ROC curve indicated that THRIL had a predictive possibility on CAS. K-M finding and Cox regression analysis showed that the expression of THRIL and the degree of CAS were independent risk factors for poor prognosis in patients with CAS. THRIL was up-expressed in HAECs induced by ox-LDL. Down-regulation of THRIL could promote the proliferation of HAECs, inhibit cell apoptosis, and restrict cell inflammation.

Conclusion

THRIL was a diagnostic and prognostic biomarker in CAS and played an important role in regulating the proliferation, apoptosis, and inflammation of HAECs induced by ox-LDL.

Gene Expression Profiling as a Novel Diagnostic Tool for Neurodegenerative Disorders

There is a lack of effective diagnostic biomarkers for neurodegenerative disorders (NDDs). Here, we established gene expression profiles for diagnosing Alzheimer’s disease (AD), Parkinson’s disease (PD), and vascular (VaD)/mixed dementia. Patients with AD had decreased APOE, PSEN1, and ABCA7 mRNA expression. Subjects with VaD/mixed dementia had 98% higher PICALM mRNA levels, but 75% lower ABCA7 mRNA expression than healthy individuals. Patients with PD and PD-related disorders showed increased SNCA mRNA levels. There were no differences in mRNA expression for OPRK1, NTRK2, and LRRK2 between healthy subjects and NDD patients. APOE mRNA expression had high diagnostic accuracy for AD, and moderate accuracy for PD and VaD/mixed dementia. PSEN1 mRNA expression showed promising accuracy for AD. PICALM mRNA expression was less accurate as a biomarker for AD. ABCA7 and SNCA mRNA expression showed high-to-excellent diagnostic accuracy for AD and PD, and moderate-to-high accuracy for VaD/mixed dementia. The APOE E4 allele reduced APOE expression in patients with different APOE genotypes. There was no association between PSEN1, PICALM, ABCA7, and SNCA gene polymorphisms and expression. Our study suggests that gene expression analysis has diagnostic value for NDDs and provides a liquid biopsy alternative to current diagnostic methods.

Natural Bioactive Products as Epigenetic Modulators for Treating Neurodegenerative Disorders

Neurodegenerative disorders (NDDs) are major health issues in Western countries. Despite significant efforts, no effective therapeutics for NDDs exist. Several drugs that target epigenetic mechanisms (epidrugs) have been recently developed for the treatment of NDDs, and several of these are currently being tested in clinical trials. Furthermore, various bioproducts have shown important biological effects for the potential prevention and treatment of these disorders. Here, we review the use of natural products as epidrugs to treat NDDs in order to explore the epigenetic effects and benefits of functional foods and natural bioproducts on neurodegeneration.

Linking the Amyloid, Tau, and Mitochondrial Hypotheses of Alzheimer's Disease and Identifying Promising Drug Targets

Damage or loss of brain cells and impaired neurochemistry, neurogenesis, and synaptic and nonsynaptic plasticity of the brain lead to dementia in neurodegenerative diseases, such as Alzheimer's disease (AD). Injury to synapses and neurons and accumulation of extracellular amyloid plaques and intracellular neurofibrillary tangles are considered the main morphological and neuropathological features of AD. Age, genetic and epigenetic factors, environmental stressors, and lifestyle contribute to the risk of AD onset and progression. These risk factors are associated with structural and functional changes in the brain, leading to cognitive decline. Biomarkers of AD reflect or cause specific changes in brain function, especially changes in pathways associated with neurotransmission, neuroinflammation, bioenergetics, apoptosis, and oxidative and nitrosative stress. Even in the initial stages, AD is associated with Aβ neurotoxicity, mitochondrial dysfunction, and tau neurotoxicity. The integrative amyloid-tau-mitochondrial hypothesis assumes that the primary cause of AD is the neurotoxicity of Aβ oligomers and tau oligomers, mitochondrial dysfunction, and their mutual synergy. For the development of new efficient AD drugs, targeting the elimination of neurotoxicity, mutual potentiation of effects, and unwanted protein interactions of risk factors and biomarkers (mainly Aβ oligomers, tau oligomers, and mitochondrial dysfunction) in the early stage of the disease seems promising.

Circulating Non-Coding RNAs as Potential Diagnostic Biomarkers in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is currently the second leading cause of cancer-related deaths worldwide, with high morbidity and mortality. The clinical diagnosis of HCC mainly depends on imaging technology, such as ultrasound and computed tomography, and serum biomarkers, such as alpha-fetoprotein (AFP). However, HCC is still hard to diagnose at an early stage due to the low sensitivity of the above mentioned traditional methods. Typically, HCC is diagnosed at an advanced stage when limited treatment options are available. It is urgent to identify effective biomarkers for the early diagnosis of HCC. Increasing evidence uncovered ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), could be used in HCC diagnosis. The aim of this review is to summarize our understanding of circulating miRNAs, lncRNAs and circRNAs as fluid-based non-invasive biomarkers, and aiming at providing new insights into the diagnosis of HCC.