Novel biomarkers in Alzheimer's disease using high resolution proteomics and metabolomics: miRNAS, proteins and metabolites

Regulatory roles of microRNAs in modulating mitochondrial dynamics, amyloid beta fibrillation, microglial activation, and cholinergic signaling: Implications for alzheimer's disease pathogenesis

Alzheimer's Disease (AD) remains a formidable challenge due to its complex pathology, notably involving mitochondrial dysfunction and dysregulated microRNA (miRNA) signaling. This study delves into the underexplored realm of miRNAs' impact on mitochondrial dynamics and their interplay with amyloid-beta (Aβ) aggregation and tau pathology in AD. Addressing identified gaps, our research utilizes advanced molecular techniques and AD models, alongside patient miRNA profiles, to uncover miRNAs pivotal in mitochondrial regulation. We illuminate novel miRNAs influencing mitochondrial dynamics, Aβ, and tau, offering insights into their mechanistic roles in AD progression. Our findings not only enhance understanding of AD's molecular underpinnings but also spotlight miRNAs as promising therapeutic targets. By elucidating miRNAs' roles in mitochondrial dysfunction and their interactions with hallmark AD pathologies, our work proposes innovative strategies for AD therapy, aiming to mitigate disease progression through targeted miRNA modulation. This contribution marks a significant step toward novel AD treatments, emphasizing the potential of miRNAs in addressing this complex disease.

A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis

Alzheimer's disease (AD) is a complex form of dementia and due to its high phenotypic variability, its diagnosis and monitoring can be quite challenging. Biomarkers play a crucial role in AD diagnosis and monitoring, but interpreting these biomarkers can be problematic due to their spatial and temporal heterogeneity. Therefore, researchers are increasingly turning to imaging-based biomarkers that employ data-driven computational approaches to examine the heterogeneity of AD. In this comprehensive review article, we aim to provide health professionals with a comprehensive view of past applications of data-driven computational approaches in studying AD heterogeneity and planning future research directions. We first define and offer basic insights into different categories of heterogeneity analysis, including spatial heterogeneity, temporal heterogeneity, and spatial-temporal heterogeneity. Then, we scrutinize 22 articles relating to spatial heterogeneity, 14 articles relating to temporal heterogeneity, and five articles relating to spatial-temporal heterogeneity, highlighting the strengths and limitations of these strategies. Furthermore, we discuss the importance of understanding spatial heterogeneity in AD subtypes and their clinical manifestations, biomarkers for abnormal orderings and AD stages, the recent advancements in spatial-temporal heterogeneity analysis for AD, and the emerging role of omics data integration in advancing personalized diagnosis and treatment for AD patients. By emphasizing the significance of understanding AD heterogeneity, we hope to stimulate further research in this field to facilitate the development of personalized interventions for AD patients.

Understanding the multifaceted role of miRNAs in Alzheimer's disease pathology

Small non-coding RNAs (miRNAs) regulate gene expression by binding to mRNA and mediating its degradation or inhibiting translation. Since miRNAs can regulate the expression of several genes, they have multiple roles to play in biological processes and human diseases. The majority of miRNAs are known to be expressed in the brain and are involved in synaptic functions, thus marking their presence and role in major neurodegenerative disorders, including Alzheimer's disease (AD). In AD, amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs) are known to be the major hallmarks. The clearance of Aβ and tau is known to be associated with miRNA dysregulation. In addition, the β-site APP cleaving enzyme (BACE 1), which cleaves APP to form Aβ, is also found to be regulated by miRNAs, thus directly affecting Aβ accumulation. Growing evidences suggest that neuroinflammation can be an initial event in AD pathology, and miRNAs have been linked with the regulation of neuroinflammation. Inflammatory disorders have also been associated with AD pathology, and exosomes associated with miRNAs are known to regulate brain inflammation, suggesting for the role of systemic miRNAs in AD pathology. Several miRNAs have been related in AD, years before the clinical symptoms appear, most of which are associated with regulating the cell cycle, immune system, stress responses, cellular senescence, nerve growth factor (NGF) signaling, and synaptic regulation. Phytochemicals, especially polyphenols, alter the expression of various miRNAs by binding to miRNAs or binding to the transcriptional activators of miRNAs, thus control/alter various metabolic pathways. Awing to the sundry biological processes being regulated by miRNAs in the brain and regulation of expression of miRNAs via phytochemicals, miRNAs and the regulatory bioactive phytochemicals can serve as therapeutic agents in the treatment and management of AD.

Development of circulating microRNA-based biomarkers for medical decision-making: a friendly reminder of what should NOT be done

Circulating cell-free microRNAs (miRNAs) represent a major reservoir for biomarker discovery. Unfortunately, their implementation in clinical practice is limited due to a profound lack of reproducibility. The great technical variability linked to major pre-analytical and analytical caveats makes the interpretation of circulating cell-free miRNA data challenging and leads to inconsistent findings. Additional efforts directed to standardization are fundamental. Several well-established protocols are currently used by independent groups worldwide. Nonetheless, there are some specific aspects in specimen collection and processing, sample handling, miRNA quantification, and data analysis that should be considered to ensure reproducibility of results. Here, we have addressed this challenge using an alternative approach. We have highlighted and discussed common pitfalls that negatively impact the robustness of circulating miRNA quantification and their application for clinical decision-making. Furthermore, we provide a checklist usable by investigators to facilitate and ensure the control of the whole miRNA quantification and analytical process. We expect that these recommendations improve the reproducibility of findings, and ultimately, facilitate the incorporation of circulating miRNA profiles into clinical practice as the next generation of disease biomarkers.

Gender differences contribute to variability of serum lipid biomarkers for Alzheimer's disease

Background: Alzheimer's disease (AD) cannot currently be diagnosed by a blood test. One reason may be gender differences. Another may be the statistical methods used. The authors evaluate these possibilities. Objective: The authors applied serum lipidomics to find AD biomarkers in men and women. They hypothesized that AD biomarkers would differ between genders and that machine-learning algorithms would improve diagnostic performance. Methods: Serum lipids were analyzed by mass spectrometry for a training set of AD cases and controls and in a blinded test set. Statistical analyses considered gender differences. Results: Lipids best classifying AD subjects differed significantly between men and women. Robust statistical algorithms did not improve diagnostic performance. Conclusion: Poor performance of AD biomarkers appears to be due primarily to inherent variability in AD patients.

Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis

INTRODUCTION

Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD.

AREAS COVERED

This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments.

EXPERT OPINION

It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.

Epigenetic modifications in spinal ligament aging

Spinal stenosis is a common degenerative spine disorder in the aged population and the spinal ligament aging is a main contributor to this chronic disease. However, the underlying mechanisms of spinal ligament aging remain unclear. Epigenetics is the study of heritable and reversible changes in the function of a gene or genome that occur without any alteration in the primary DNA sequence. Epigenetic alterations have been demonstrated to play crucial roles in age-related diseases and conditions, and they are recently studied as biomarkers and therapeutic targets in the field of cancer research. The main epigenetic modifications, including DNA methylation alteration, histone modifications as well as dysregulated noncoding RNA modulation, have all been implicated in spinal ligament aging diseases. DNA methylation modulates the expression of critical genes including WNT5A, GDNF, ACSM5, miR-497 and miR-195 during spinal ligament degeneration. Histone modifications widely affect gene expression and obvious histone modification abnormalities have been found in spinal ligament aging. MicroRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) exert crucial regulating effects on spinal ligament aging conditions via targeting various osteogenic or fibrogenic differentiation related genes. To our knowledge, there is no systematic review yet to summarize the involvement of epigenetic mechanisms of spinal ligament aging in degenerative spinal diseases. In this study, we systematically discussed the different epigenetic modifications and their potential functions in spinal ligament aging process.

Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches

BACKGROUND

Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds.

AIM OF REVIEW

The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.