Role of Body-Fluid Biomarkers in Alzheimer's Disease Diagnosis

Natural flavonoids as potential therapeutics in the management of Alzheimer's disease: a review

Alzheimer's disease (AD) is an age-dependent neurodegenerative disorder which is associated with the accumulation of proteotoxic Aβ peptides, and pathologically characterized by the deposition of Aβ-enriched plaques and neurofibrillary tangles. Given the social and economic burden caused by the rising frequency of AD, there is an urgent need for the development of appropriate therapeutics. Natural compounds are gaining popularity as alternatives to synthetic drugs due to their neuroprotective properties and higher biocompatibility. While natural compound's therapeutic effects for AD have been recently investigated in numerous in vitro and in vivo studies, only few have developed to clinical trials. The present review aims to provide a brief overview of the therapeutic effects, new insights, and upcoming perspectives of the preclinical and clinical trials of flavonoids for the treatment of Alzheimer's disease.

Alzheimer's Disease: Significant Benefit from the Yeast-Based Models

Alzheimer's disease (AD) is an age-related, multifaceted neurological disorder associated with accumulation of aggregated proteins (amyloid Aβ and hyperphosphorylated tau), loss of synapses and neurons, and alterations in microglia. AD was recognized by the World Health Organization as a global public health priority. The pursuit of a better understanding of AD forced researchers to pay attention to well-defined single-celled yeasts. Yeasts, despite obvious limitations in application to neuroscience, show high preservation of basic biological processes with all eukaryotic organisms and offer great advantages over other disease models due to the simplicity, high growth rates on low-cost substrates, relatively simple genetic manipulations, the large knowledge base and data collections, and availability of an unprecedented amount of genomic and proteomic toolboxes and high-throughput screening techniques, inaccessible to higher organisms. Research reviewed above clearly indicates that yeast models, together with other, more simple eukaryotic models including animal models, C. elegans and Drosophila, significantly contributed to understanding Aβ and tau biology. These models allowed high throughput screening of factors and drugs that interfere with Aβ oligomerization, aggregation and toxicity, and tau hyperphosphorylation. In the future, yeast models will remain relevant, with a focus on creating novel high throughput systems to facilitate the identification of the earliest AD biomarkers among different cellular networks in order to achieve the main goal-to develop new promising therapeutic strategies to treat or prevent the disease.

Altered Mitochondrial Morphology and Bioenergetics in a New Yeast Model Expressing Aβ42

Alzheimer's disease (AD) is an incurable, age-related neurological disorder, the most common form of dementia. Considering that AD is a multifactorial complex disease, simplified experimental models are required for its analysis. For this purpose, genetically modified Yarrowia lipolytica yeast strains expressing Aβ42 (the main biomarker of AD), eGFP-Aβ42, Aβ40, and eGFP-Aβ40 were constructed and examined. In contrast to the cells expressing eGFP and eGFP-Aβ40, retaining "normal" mitochondrial reticulum, eGFP-Aβ42 cells possessed a disturbed mitochondrial reticulum with fragmented mitochondria; this was partially restored by preincubation with a mitochondria-targeted antioxidant SkQThy. Aβ42 expression also elevated ROS production and cell death; low concentrations of SkQThy mitigated these effects. Aβ42 expression caused mitochondrial dysfunction as inferred from a loose coupling of respiration and phosphorylation, the decreased level of ATP production, and the enhanced rate of hydrogen peroxide formation. Therefore, we have obtained the same results described for other AD models. Based on an analysis of these and earlier data, we suggest that the mitochondrial fragmentation might be a biomarker of the earliest preclinical stage of AD with an effective therapy based on mitochondria- targeted antioxidants. The simple yeast model constructed can be a useful platform for the rapid screening of such compounds.

Comorbidities Incorporated to Improve Prediction for Prevalent Mild Cognitive Impairment and Alzheimer's Disease in the HABS-HD Study

BACKGROUND

Blood biomarkers have the potential to transform Alzheimer's disease (AD) diagnosis and monitoring, yet their integration with common medical comorbidities remains insufficiently explored.

OBJECTIVE

This study aims to enhance blood biomarkers' sensitivity, specificity, and predictive performance by incorporating comorbidities. We assess this integration's efficacy in diagnostic classification using machine learning, hypothesizing that it can identify a confident set of predictive features.

METHODS

We analyzed data from 1,705 participants in the Health and Aging Brain Study-Health Disparities, including 116 AD patients, 261 with mild cognitive impairment, and 1,328 cognitively normal controls. Blood samples were assayed using electrochemiluminescence and single molecule array technology, alongside comorbidity data gathered through clinical interviews and medical records. We visually explored blood biomarker and comorbidity characteristics, developed a Feature Importance and SVM-based Leave-One-Out Recursive Feature Elimination (FI-SVM-RFE-LOO) method to optimize feature selection, and compared four models: Biomarker Only, Comorbidity Only, Biomarker and Comorbidity, and Feature-Selected Biomarker and Comorbidity.

RESULTS

The combination model incorporating 17 blood biomarkers and 12 comorbidity variables outperformed single-modal models, with NPV12 at 92.78%, AUC at 67.59%, and Sensitivity at 65.70%. Feature selection led to 22 chosen features, resulting in the highest performance, with NPV12 at 93.76%, AUC at 69.22%, and Sensitivity at 70.69%. Additionally, interpretative machine learning highlighted factors contributing to improved prediction performance.

CONCLUSIONS

In conclusion, combining feature-selected biomarkers and comorbidities enhances prediction performance, while feature selection optimizes their integration. These findings hold promise for understanding AD pathophysiology and advancing preventive treatments.

Combination of Serum and Plasma Biomarkers Could Improve Prediction Performance for Alzheimer’s Disease

Alzheimer’s disease (AD) can be predicted either by serum or plasma biomarkers, and a combination may increase predictive power, but due to the high complexity of machine learning, it may also incur overfitting problems. In this paper, we investigated whether combining serum and plasma biomarkers with feature selection could improve prediction performance for AD. 150 D patients and 150 normal controls (NCs) were enrolled for a serum test, and 100 patients and 100 NCs were enrolled for the plasma test. Among these, 79 ADs and 65 NCs had serum and plasma samples in common. A 10 times repeated 5-fold cross-validation model and a feature selection method were used to overcome the overfitting problem when serum and plasma biomarkers were combined. First, we tested to see if simply adding serum and plasma biomarkers improved prediction performance but also caused overfitting. Then we employed a feature selection algorithm we developed to overcome the overfitting problem. Lastly, we tested the prediction performance in a 10 times repeated 5-fold cross validation model for training and testing sets. We found that the combined biomarkers improved AD prediction but also caused overfitting. A further feature selection based on the combination of serum and plasma biomarkers solved the problem and produced an even higher prediction performance than either serum or plasma biomarkers on their own. The combined feature-selected serum–plasma biomarkers may have critical implications for understanding the pathophysiology of AD and for developing preventative treatments.

Effects of Electroacupuncture on the Correlation between Serum and Central Immunity in AD Model Animals

Objective

The goal was to investigate the connection between neuroinflammation in the brain and serum inflammatory markers as Alzheimer's disease progressed. We also sought to determine whether electroacupuncture had an effect on inflammatory markers found in blood and other brain regions.

Methods

As an animal model for AD, we used senescence-accelerated mouse prone 8 (SAMP8) mice. To examine the effects and probable mechanism of electroacupuncture, we used HE staining, immunofluorescence staining, western blotting, and enzyme-linked immunosorbent assay.

Results

Electroacupuncture therapy protected neurons, significantly downregulated the Iba-1 level in the hippocampus (p value was 0.003), frontal lobe cortex (p value was 0.042), and temporal lobe cortex (p value was 0.013) of the AD animal model, all of which had significantly lower levels of IL-6 (p value was 0.001), IL-1β (p value was 0.001), and TNF-α (p value was 0.001) in their serum.

Conclusion

The amounts of IL-6, IL-1β, and TNF-α detected in the serum were strongly linked to the levels discovered in the hippocampus and the frontal lobes of the brain, respectively. A better understanding of the electroacupuncture process as well as the course of Alzheimer's disease and the therapeutic benefits of electroacupuncture may be gained by using biomarkers such as serum inflammatory marker biomarkers.

New RNA-Based Breakthroughs in Alzheimer's Disease Diagnosis and Therapeutics

Dementia is described as the fifth leading cause of death worldwide and Alzheimer’s disease (AD) is recognized as the most common, causing a huge impact on health costs and quality of patients’ lives. The main hallmarks that are commonly associated with the pathologic process are amyloid deposition, pathologic Tau phosphorylation and neurodegeneration. It is still unclear how these events are linked to the disease progression, due to the complex pathologic mechanisms. Nevertheless, several hypotheses have been proposed for a better understanding of AD. The AD diagnosis is performed by using a combination of several tools to detect β-amyloid peptide (Aβ) deposits and modifications in cognitive performance, sometimes being expensive and invasive. In the treatment field, there is still an absence of effective treatments to delay or stop the progression of the disease, with most of the approved drugs used to relieve symptoms, and all of them with significant adverse side effects. Considering all limitations, the need to establish new and more effective diagnostic and therapeutic strategies becomes clear. This review aims not only to describe the disease and its impact but also to collect the currently available diagnostic and therapeutic strategies, highlighting new promising RNA-based strategies for AD.

News about the Role of Fluid and Imaging Biomarkers in Neurodegenerative Diseases

Biomarkers are molecules that are variable in their origin, nature, and mechanism of action; they are of great relevance in biology and also in medicine because of their specific connection with a single or several diseases. Biomarkers are of two types, which in some cases are operative with each other. Fluid biomarkers, started around 2000, are generated in fluid from specific proteins/peptides and miRNAs accumulated within two extracellular fluids, either the central spinal fluid or blood plasma. The switch of these proteins/peptides and miRNAs, from free to segregated within extracellular vesicles, has induced certain advantages including higher levels within fluids and lower operative expenses. Imaging biomarkers, started around 2004, are identified in vivo upon their binding by radiolabeled molecules subsequently revealed in the brain by positron emission tomography and/or other imaging techniques. A positive point for the latter approach is the quantitation of results, but expenses are much higher. At present, both types of biomarker are being extensively employed to study Alzheimer’s and other neurodegenerative diseases, investigated from the presymptomatic to mature stages. In conclusion, biomarkers have revolutionized scientific and medical research and practice. Diagnosis, which is often inadequate when based on medical criteria only, has been recently improved by the multiplicity and specificity of biomarkers. Analogous results have been obtained for prognosis. In contrast, improvement of therapy has been limited or fully absent, especially for Alzheimer’s in which progress has been inadequate. An urgent need at hand is therefore the progress of a new drug trial design together with patient management in clinical practice.

Therapeutic Strategies and Nano-Drug Delivery Applications in Management of Aging Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder in which the death of brain cells causes memory loss and cognitive decline. Existing drugs only suppress symptoms or delay further deterioration but do not address the cause of the disease. In spite of screening numerous drug candidates against various molecular targets of AD, only a few candidates, such as acetylcholinesterase inhibitors, are currently utilized as an effective clinical therapy. Currently, nano-based therapies can make a difference, providing new therapeutic options by helping drugs to cross the blood-brain barrier and enter the brain more effectively. The main aim of this review was to highlight advances in research on the development of nano-based therapeutics for improved treatment of AD.

The Viral Hypothesis in Alzheimer's Disease: Novel Insights and Pathogen-Based Biomarkers

Early diagnosis of Alzheimer’s disease (AD) and the identification of significant risk factors are necessary to better understand disease progression, and to develop intervention-based therapies prior to significant neurodegeneration. There is thus a critical need to establish biomarkers which can predict the risk of developing AD before the onset of cognitive decline. A number of studies have indicated that exposure to various microbial pathogens can accelerate AD pathology. Additionally, several studies have indicated that amyloid-β possess antimicrobial properties and may act in response to infection as a part of the innate immune system. These findings have led some to speculate that certain types of infections may play a significant role in AD pathogenesis. In this review, we will provide an overview of studies which suggest pathogen involvement in AD. Additionally, we will discuss a number of pathogen-associated biomarkers which may be effective in establishing AD risk. Infections that increase the risk of AD represent a modifiable risk factor which can be treated with therapeutic intervention. Pathogen-based biomarkers may thus be a valuable tool for evaluating and decreasing AD risk across the population.