The probabilistic model of Alzheimer disease: the amyloid hypothesis revised

Sleep disturbance in clinical and preclinical scrapie-infected sheep measured by polysomnography

Neurodegenerative diseases are characterised by neuronal loss and abnormal deposition of pathological proteins in the nervous system. Among the most common neurodegenerative diseases are Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease and transmissible spongiform encephalopathies (TSEs). Sleep and circadian rhythm disturbances are one of the most common symptoms in patients with neurodegenerative diseases. Currently, one of the main objectives in the study of TSEs is to try to establish an early diagnosis, as clinical signs do not appear until the damage to the central nervous system is very advanced, which prevents any therapeutic approach. In this paper, we provide the first description of sleep disturbance caused by classical scrapie in clinical and preclinical sheep using polysomnography compared to healthy controls. Fifteen sheep classified into three groups, clinical, preclinical and negative control, were analysed. The results show a decrease in total sleep time as the disease progresses, with significant changes between control, clinical and pre-clinical animals. The results also show an increase in sleep fragmentation in clinical animals compared to preclinical and control animals. In addition, sheep with clinical scrapie show a total loss of Rapid Eye Movement sleep (REM) and alterations in Non Rapid Eyes Movement sleep (NREM) compared to control sheep, demonstrating more shallow sleep. Although further research is needed, these results suggest that prion diseases also produce sleep disturbances in animals and that polysomnography could be a diagnostic tool of interest in clinical and preclinical cases of prion diseases.

Integrative Single-Plaque Analysis Reveals Signature Aβ and Lipid Profiles in the Alzheimer's Brain

Cerebral accumulation of amyloid-β (Aβ) initiates molecular and cellular cascades that lead to Alzheimer's disease (AD). However, amyloid deposition does not invariably lead to dementia. Amyloid-positive but cognitively unaffected (AP-CU) individuals present widespread amyloid pathology, suggesting that molecular signatures more complex than the total amyloid burden are required to better differentiate AD from AP-CU cases. Motivated by the essential role of Aβ and the key lipid involvement in AD pathogenesis, we applied multimodal mass spectrometry imaging (MSI) and machine learning (ML) to investigate amyloid plaque heterogeneity, regarding Aβ and lipid composition, in AP-CU versus AD brain samples at the single-plaque level. Instead of focusing on a population mean, our analytical approach allowed the investigation of large populations of plaques at the single-plaque level. We found that different (sub)populations of amyloid plaques, differing in Aβ and lipid composition, coexist in the brain samples studied. The integration of MSI data with ML-based feature extraction further revealed that plaque-associated gangliosides GM2 and GM1, as well as Aβ1-38, but not Aβ1-42, are relevant differentiators between the investigated pathologies. The pinpointed differences may guide further fundamental research investigating the role of amyloid plaque heterogeneity in AD pathogenesis/progression and may provide molecular clues for further development of emerging immunotherapies to effectively target toxic amyloid assemblies in AD therapy. Our study exemplifies how an integrative analytical strategy facilitates the unraveling of complex biochemical phenomena, advancing our understanding of AD from an analytical perspective and offering potential avenues for the refinement of diagnostic tools.

Complex relationships of socioeconomic status with vascular and Alzheimer's pathways on cognition

INTRODUCTION

AD and CVD, which frequently co-occur, are leading causes of age-related cognitive decline. We assessed how demographic factors, socioeconomic status (SES) as indicated by education and occupation, vascular risk factors, and a range of biomarkers associated with both CVD (including white matter hyperintensities [WMH], diffusion MRI abnormalities, infarctions, and microbleeds) and AD (comprising amyloid-PET and tau-PET) collectively influence cognitive function.

METHODS

In this cross-sectional population study, structural equation models were utilized to understand these associations in 449 participants (mean age (SD) = 74.5 (8.4) years; 56% male; 7.5% cognitively impaired).

RESULTS

(1) Higher SES had a protective effect on cognition with mediation through the vascular pathway. (2) The effect of amyloid directly on cognition and through tau was 11-fold larger than the indirect effect of amyloid on cognition through WMH. (3) There is a significant effect of vascular risk on tau deposition.

DISCUSSION

The utilized biomarkers captured the impact of CVD and AD on cognition. The overall effect of vascular risk and SES on these biomarkers are complex and need further investigation.

The potential of five c-miRNAs as serum biomarkers for Late-Onset Alzheimer's disease diagnosis: miR-10a-5p, miR-29b-2-5p, miR-125a-5p, miR-342-3p, and miR-708-5p

The nervous system is rich in miRNAs, indicating an important role of these molecules in regulating processes associated with cognition, memory, and others. Therefore, qualitative and quantitative imbalances involving such miRNAs may be involved in dementia contexts, including Late-Onset Alzheimer's Disease (LOAD). To test the viability of circulating miRNAs (c-miRNAs) as biomarkers for LOAD, we proceed accordingly to the following reasoning. The first stage was to discover and identify profile of c-miRNAs by RNA sequencing (RNA-Seq). For this purpose, blood serum samples were used from LOAD patients (n = 5) and cognitively healthy elderly control group (CTRL_CH) (n = 5), all over 70 years old. We identified seven c-miRNAs differentially expressed (p ≤ 0.05) in the serum of LOAD patients compared to CTRL_CH (miR-10a-5p; miR-29b-2-5p; miR-125a-5p; miR-342-3p, miR-708-5p, miR-380-5p and miR-340-3p). Of these, five (p ≤ 0.01) were selected for in silico analysis (miR-10a-5p; miR-29b-2-5p; miR-125a-5p; miR-342-3p, miR-708-5p), for which 44 relevant target genes were found regulated by these c-miRNAs and related to LOAD. Through the analysis of these target genes in databases, it was possible to observe that they have functions related to the development and progress of LOAD, directly or indirectly connecting the different Alzheimer's pathways. Thus, this work found five promising serum c-miRNAs as options for biomarkers contributing to LOAD diagnosis. Our study shows the complex network between these molecules and LOAD, supporting the relevance of studies using c-miRNAs in dementia contexts.

Neuroinflammation in Alzheimer's disease: insights from peripheral immune cells

Alzheimer's disease (AD) is a serious brain disorder characterized by the presence of beta-amyloid plaques, tau pathology, inflammation, neurodegeneration, and cerebrovascular dysfunction. The presence of chronic neuroinflammation, breaches in the blood-brain barrier (BBB), and increased levels of inflammatory mediators are central to the pathogenesis of AD. These factors promote the penetration of immune cells into the brain, potentially exacerbating clinical symptoms and neuronal death in AD patients. While microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in AD, recent evidence suggests the infiltration of cerebral vessels and parenchyma by peripheral immune cells, including neutrophils, T lymphocytes, B lymphocytes, NK cells, and monocytes in AD. These cells participate in the regulation of immunity and inflammation, which is expected to play a huge role in future immunotherapy. Given the crucial role of peripheral immune cells in AD, this article seeks to offer a comprehensive overview of their contributions to neuroinflammation in the disease. Understanding the role of these cells in the neuroinflammatory response is vital for developing new diagnostic markers and therapeutic targets to enhance the diagnosis and treatment of AD patients.

Potential therapeutic natural compounds for the treatment of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a complicated neurodegenerative disease with cognitive impairment occurring in the older people, in which extracellular accumulation of β-amyloid and intracellular aggregation of hyperphosphorylated tau are regarded as the prevailing theories. However, the exact AD mechanism has not been determined. Moreover, there is no effective treatment available in phase III trials to eradicate AD, which is imperative to explore novel treatments.

PURPOSE

A number of up-to-date pre-clinical studies on cognitive impairment is beneficial to clarify the pathology of AD. This review recapitulates several advances in AD pathobiology and discusses the neuroprotective effects of natural compounds, such as phenolic compounds, natural polysaccharides and oligosaccharides, peptide, and lipids, underscoring the therapeutic potential for AD.

METHODS

Electronic databases involving PubMed, Web of Science, and Google Scholar were searched up to October 2023. Articles were conducted using the keywords like Alzheimer's disease, pathogenic mechanisms, natural compounds, and neuroprotection.

RESULT

This review summarized several AD pathologies and the neuroprotective effects of natural compounds such as natural polysaccharides and oligosaccharides, peptide, and lipids.

CONCLUSION

We have discussed the pathogenic mechanisms of AD and the effect natural products on neurodegenerative diseases particularly in treating AD. Specifically, we investigated the molecular pathways and links between natural compounds and Alzheimer's disease such as through NF-κB, Nrf2, and mTOR pathway. Further investigation is necessary in exploring the bioactivity and effectiveness of natural compounds in clinical trials, which may provide a promising treatment for AD patients.

Multicolor, Cell-Impermeable, and High Affinity BACE1 Inhibitor Probes Enable Superior Endogenous Staining and Imaging of Single Molecules

The prevailing but not undisputed amyloid cascade hypothesis places the β-site of APP cleaving enzyme 1 (BACE1) center stage in Alzheimer's Disease pathogenesis. Here, we investigated functional properties of BACE1 with novel tag- and antibody-free labeling tools, which are conjugates of the BACE1-inhibitor IV (also referred to as C3) linked to different impermeable Alexa Fluor dyes. We show that these fluorescent small molecules bind specifically to BACE1, with a 1:1 labeling stoichiometry at their orthosteric site. This is a crucial property especially for single-molecule and super-resolution microscopy approaches, allowing characterization of the dyes' labeling capabilities in overexpressing cell systems and in native neuronal tissue. With multiple colors at hand, we evaluated BACE1-multimerization by Förster resonance energy transfer (FRET) acceptor-photobleaching and single-particle imaging of native BACE1. In summary, our novel fluorescent inhibitors, termed Alexa-C3, offer unprecedented insights into protein-protein interactions and diffusion behavior of BACE1 down to the single molecule level.

p75 neurotrophin receptor modulation in mild to moderate Alzheimer disease: a randomized, placebo-controlled phase 2a trial

p75 neurotrophin receptor (p75NTR) signaling pathways substantially overlap with degenerative networks active in Alzheimer disease (AD). Modulation of p75NTR with the first-in-class small molecule LM11A-31 mitigates amyloid-induced and pathological tau-induced synaptic loss in preclinical models. Here we conducted a 26-week randomized, placebo-controlled, double-blinded phase 2a safety and exploratory endpoint trial of LM11A-31 in 242 participants with mild to moderate AD with three arms: placebo, 200 mg LM11A-31 and 400 mg LM11A-31, administered twice daily by oral capsules. This trial met its primary endpoint of safety and tolerability. Within the prespecified secondary and exploratory outcome domains (structural magnetic resonance imaging, fluorodeoxyglucose positron-emission tomography and cerebrospinal fluid biomarkers), significant drug-placebo differences were found, consistent with the hypothesis that LM11A-31 slows progression of pathophysiological features of AD; no significant effect of active treatment was observed on cognitive tests. Together, these results suggest that targeting p75NTR with LM11A-31 warrants further investigation in larger-scale clinical trials of longer duration. EU Clinical Trials registration: 2015-005263-16 ; ClinicalTrials.gov registration: NCT03069014 .

Matrix Remodeling Enzymes as Potential Fluid Biomarkers of Neurodegeneration in Alzheimer's Disease

This study investigated the diagnostic accuracy of plasma biomarkers-specifically, matrix metalloproteinase (MMP-9), tissue inhibitor of metalloproteinase (TIMP-1), CD147, and the MMP-/TIMP-1 ratio in patients with Alzheimer's disease (AD) dementia. The research cohort comprised patients diagnosed with probable AD dementia and a control group of cognitively unimpaired (CU) individuals. Neuroradiological assessments included brain magnetic resonance imaging (MRI) following dementia protocols, with subsequent volumetric analysis. Additionally, cerebrospinal fluid (CSF) AD biomarkers were classified using the A/T/N system, and apolipoprotein E (APOE) ε4 carrier status was determined. Findings revealed elevated plasma levels of MMP-9 and TIMP-1 in AD dementia patients compared to CU individuals. Receiver operating characteristic (ROC) curve analysis demonstrated significant differences in the areas under the curve (AUC) for MMP-9 (p < 0.001) and TIMP-1 (p < 0.001). Notably, plasma TIMP-1 levels were significantly lower in APOE ε4+ patients than in APOE ε4- patients (p = 0.041). Furthermore, APOE ε4+ patients exhibited reduced hippocampal volume, particularly in total, right, and left hippocampal measurements. TIMP-1 levels exhibited a positive correlation, while the MMP-9/TIMP-1 ratio showed a negative correlation with hippocampal volume parameters. This study sheds light on the potential use of TIMP-1 as a diagnostic marker and its association with hippocampal changes in AD.

Bio-Nano Toolbox for Precision Alzheimer's Disease Gene Therapy

Alzheimer's disease (AD) is the most burdensome aging-associated neurodegenerative disorder, and its treatment encounters numerous failures during drug development. Although there are newly approved in-market β-amyloid targeting antibody solutions, pathological heterogeneity among patient populations still challenges the treatment outcome. Emerging advances in gene therapies offer opportunities for more precise personalized medicine; while, major obstacles including the pathological heterogeneity among patient populations, the puzzled mechanism for druggable target development, and the precision delivery of functional therapeutic elements across the blood-brain barrier remain and limit the use of gene therapy for central neuronal diseases. Aiming for "precision delivery" challenges, nanomedicine provides versatile platforms that may overcome the targeted delivery challenges for AD gene therapy. In this perspective, to picture a toolbox for AD gene therapy strategy development, the most recent advances from benchtop to clinics are highlighted, possibly available gene therapy targets, tools, and delivery platforms are outlined, their challenges as well as rational design elements are addressed, and perspectives in this promising research field are discussed.

Angiotensin Converting Enzyme (ACE) expression in microglia reduces amyloid β deposition and neurodegeneration by increasing SYK signaling and endolysosomal trafficking

Genome-wide association studies (GWAS) have identified many gene polymorphisms associated with an increased risk of developing Late Onset Alzheimer's Disease (LOAD). Many of these LOAD risk-associated alleles alter disease pathogenesis by influencing microglia innate immune responses and lipid metabolism. Angiotensin Converting Enzyme (ACE), a GWAS LOAD risk-associated gene best known for its role in regulating systemic blood pressure, also enhances innate immunity and lipid processing in peripheral myeloid cells, but a role for ACE in modulating the function of myeloid-derived microglia remains unexplored. Using novel mice engineered to express ACE in microglia and CNS associated macrophages (CAMs), we find that ACE expression in microglia reduces Aβ plaque load, preserves vulnerable neurons and excitatory synapses, and greatly reduces learning and memory abnormalities in the 5xFAD amyloid mouse model of Alzheimer's Disease (AD). ACE-expressing microglia show enhanced Aβ phagocytosis and endolysosomal trafficking, increased clustering around amyloid plaques, and increased SYK tyrosine kinase activation downstream of the major Aβ receptors, TREM2 and CLEC7A. Single microglia sequencing and digital spatial profiling identifies downstream SYK signaling modules that are expressed by ACE expression in microglia that mediate endolysosomal biogenesis and trafficking, mTOR and PI3K/AKT signaling, and increased oxidative phosphorylation, while gene silencing or pharmacologic inhibition of SYK activity in ACE-expressing microglia abrogates the potentiated Aβ engulfment and endolysosomal trafficking. These findings establish a role for ACE in enhancing microglial immune function and they identify a potential use for ACE-expressing microglia as a cell-based therapy to augment endogenous microglial responses to Aβ in AD.

Towards Early Diagnosis and Screening of Alzheimer's Disease Using Frequency Locked Whispering Gallery Mode Microtoroid Biosensors

Alzheimer's disease (AD) is a progressive form of dementia affecting almost 55 million people worldwide. It is characterized by the abnormal deposition of amyloid plaques and neurofibrillary tangles within the brain, leading to a pathological cascade of neuron degeneration and death as well as memory loss and cognitive decline. Amyloid beta (Aβ) is an AD biomarker present in cerebrospinal fluid and blood serum and correlates with the presence of amyloid plaques and tau tangles in the brain. Measuring the levels of Aβ can help with early diagnosis of AD, which is key for studying novel AD drugs and delaying the symptoms of dementia. However, this goal is difficult to achieve due to the low levels of AD biomarkers in biofluids. Here we demonstrate for the first time the use of FLOWER (frequency locked optical whispering evanescent resonator) for quantifying the levels of post-mortem cerebrospinal fluid (CSF) Aβ42 in clinicopathologically classified control, mild cognitive impairment (MCI), and AD participants. FLOWER is capable of measuring CSF Aβ42 (area under curve, AUC = 0.92) with higher diagnostic performance than standard ELISA (AUC = 0.82) and was also able to distinguish between control and MCI samples. Our results demonstrate the capability of FLOWER for screening CSF samples for early diagnosis of Alzheimer's pathology.

The Intersection of cerebral cholesterol metabolism and Alzheimer's disease: Mechanisms and therapeutic prospects

Alzheimer's disease (AD) is a common neurodegenerative disease in the elderly, the exact pathogenesis of which remains incompletely understood, and effective preventive and therapeutic drugs are currently lacking. Cholesterol plays a vital role in cell membrane formation and neurotransmitter synthesis, and its abnormal metabolism is associated with the onset of AD. With the continuous advancement of imaging techniques and molecular biology methods, researchers can more accurately explore the relationship between cholesterol metabolism and AD. Elevated cholesterol levels may lead to vascular dysfunction, thereby affecting neuronal function. Additionally, abnormal cholesterol metabolism may affect the metabolism of β-amyloid protein, thereby promoting the onset of AD. Brain cholesterol levels are regulated by multiple factors. This review aims to deepen the understanding of the subtle relationship between cholesterol homeostasis and AD, and to introduce the latest advances in cholesterol-regulating AD treatment strategies, thereby inspiring readers to contemplate deeply on this complex relationship. Although there are still many unresolved important issues regarding the risk of brain cholesterol and AD, and some studies may have opposite conclusions, further research is needed to enrich our understanding. However, these findings are expected to deepen our understanding of the pathogenesis of AD and provide important insights for the future development of AD treatment strategies targeting brain cholesterol homeostasis.

Plasma biomarkers increase diagnostic confidence in patients with Alzheimer's disease or frontotemporal lobar degeneration

BACKGROUND

The recent development of techniques to assess plasma biomarkers has changed the way the research community envisions the future of diagnosis and management of Alzheimer's disease (AD) and other neurodegenerative disorders. This work aims to provide real world evidence on the clinical impact of plasma biomarkers in an academic tertiary care center.

METHODS

Anonymized clinical reports of patients diagnosed with AD or Frontotemporal Lobar Degeneration with available plasma biomarkers (Aβ42, Aβ42/Aβ40, p-tau181, p-tau231, NfL, GFAP) were independently assessed by two neurologists who expressed diagnosis and diagnostic confidence three times: (T0) at baseline based on the information collected during the first visit, (T1) after plasma biomarkers, and (T2) after traditional biomarkers (when available). Finally, we assessed whether clinicians' interpretation of plasma biomarkers and the consequent clinical impact are consistent with the final diagnosis, determined after the conclusion of the diagnostic clinical and instrumental work-up by the actual managing physicians who had complete access to all available information.

RESULTS

Clinicians assessed 122 reports, and their concordance ranged from 81 to 91% at the three time points. At T1, the presentation of plasma biomarkers resulted in a change of diagnosis in 2% (2/122, p = 1.00) of cases, and in increased diagnostic confidence in 76% (91/120, p < 0.001) of cases with confirmed diagnosis. The change in diagnosis and the increase in diagnostic confidence after plasma biomarkers were consistent with the final diagnosis in 100% (2/2) and 81% (74/91) of cases, respectively. At T2, the presentation of traditional biomarkers resulted in a further change of diagnosis in 13% (12/94, p = 0.149) of cases, and in increased diagnostic confidence in 88% (72/82, p < 0.001) of cases with confirmed diagnosis.

CONCLUSIONS

In an academic tertiary care center, plasma biomarkers supported clinicians by increasing their diagnostic confidence in most cases, despite a negligible impact on diagnosis. Future prospective studies are needed to assess the full potential of plasma biomarkers on clinical grounds.

A nonlinear meccano for Alzheimer's emergence by amyloid β-mediated glutamatergic hyperactivity

The pathophysiological process of Alzheimer's disease (AD) is believed to begin many years before the formal diagnosis of AD dementia. This protracted preclinical phase offers a crucial window for potential therapeutic interventions, yet its comprehensive characterization remains elusive. Accumulating evidence suggests that amyloid-β (Aβ) may mediate neuronal hyperactivity in circuit dysfunction in the early stages of AD. At the same time, neural activity can also facilitate Aβ accumulation through intricate feed-forward interactions, complicating elucidating the conditions governing Aβ-dependent hyperactivity and its diagnostic utility. In this study, we use biophysical modeling to shed light on such conditions. Our analysis reveals that the inherently nonlinear nature of the underlying molecular interactions can give rise to the emergence of various modes of hyperactivity. This diversity in the mechanisms of hyperactivity may ultimately account for a spectrum of AD manifestations.

Tracking mitochondrial Cu(I) fluctuations through a ratiometric fluorescent probe in AD model cells: Towards understanding how AβOs induce mitochondrial Cu(I) dyshomeostasis

Mitochondrial copper signaling pathway plays a role in Alzheimer's disease (AD), especially in relevant Amyloid-β oligomers (AβOs) neurotoxicity and mitochondrial dysfunction. Clarifying the relationship between mitochondrial copper homeostasis and both of mitochondrial dysfunction and AβOs neurotoxicity is important for understanding AD pathogenesis. Herein, we designed and synthesized a ratiometric fluorescent probe CHC-NS4 for Cu(I). CHC-NS4 possesses excellent ratiometric response, high selectivity to Cu(I) and specific ability to target mitochondria. Under mitochondrial dysfunction induced by oligomycin, mitochondrial Cu(I) levels gradually increased, which may be related to inhibition of ATP7A-mediated Cu(I) exportation and/or high expression of COX. On this basis, CHC-NS4 was further utilized to visualize the fluctuations of mitochondrial Cu(I) levels during progression of AD model cells induced by AβOs. It was found that mitochondrial Cu(I) levels were gradually elevated during the AD progression, which depended on not only AβOs concentration but also incubation time. Moreover, endocytosis maybe served as a prime pathway mode for mitochondrial Cu(I) dyshomeostasis induced by AβOs during AD progression. These results have provided a novel inspiration into mitochondrial copper biology in AD pathogenesis.

APOE4 homozygozity represents a distinct genetic form of Alzheimer's disease

This study aimed to evaluate the impact of APOE4 homozygosity on Alzheimer's disease (AD) by examining its clinical, pathological and biomarker changes to see whether APOE4 homozygotes constitute a distinct, genetically determined form of AD. Data from the National Alzheimer's Coordinating Center and five large cohorts with AD biomarkers were analyzed. The analysis included 3,297 individuals for the pathological study and 10,039 for the clinical study. Findings revealed that almost all APOE4 homozygotes exhibited AD pathology and had significantly higher levels of AD biomarkers from age 55 compared to APOE3 homozygotes. By age 65, nearly all had abnormal amyloid levels in cerebrospinal fluid, and 75% had positive amyloid scans, with the prevalence of these markers increasing with age, indicating near-full penetrance of AD biology in APOE4 homozygotes. The age of symptom onset was earlier in APOE4 homozygotes at 65.1, with a narrower 95% prediction interval than APOE3 homozygotes. The predictability of symptom onset and the sequence of biomarker changes in APOE4 homozygotes mirrored those in autosomal dominant AD and Down syndrome. However, in the dementia stage, there were no differences in amyloid or tau positron emission tomography across haplotypes, despite earlier clinical and biomarker changes. The study concludes that APOE4 homozygotes represent a genetic form of AD, suggesting the need for individualized prevention strategies, clinical trials and treatments.

Role of autophagy-related genes in liver cancer prognosis

Autophagy, a highly conserved process of protein and organelle degradation, has emerged as a critical regulator in various diseases, including cancer progression. In the context of liver cancer, the predictive value of autophagy-related genes remains ambiguous. Leveraging chip datasets from the TCGA and GTEx databases, we identified 23 differentially expressed autophagy-related genes in liver cancer. Notably, five key autophagy genes, PRKAA2, BIRC5, MAPT, IGF1, and SPNS1, were highlighted as potential prognostic markers, with MAPT showing significant overexpression in clinical samples. In vitro cellular assays further demonstrated that MAPT promotes liver cancer cell proliferation, migration, and invasion by inhibiting autophagy and suppressing apoptosis. Subsequent in vivo studies further corroborated the pro-tumorigenic role of MAPT by suppressing autophagy. Collectively, our model based on the five key genes provides a promising tool for predicting liver cancer prognosis, with MAPT emerging as a pivotal factor in tumor progression through autophagy modulation.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

INTRODUCTION

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

METHODS

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

RESULTS

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

DISCUSSION

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

HIGHLIGHTS

A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

What is Alzheimer's disease? An analysis of nosological perspectives from the 20th and 21st centuries

BACKGROUND

Recent US proposals suggest defining Alzheimer's disease (AD) based on β-amyloidosis alone. This sparked debates that echoed historical ones about the significance of brain lesions and clinical phenotype.

METHODS

This review covers debates on AD nosology through three key periods: AD's discovery in German-speaking countries in the early 20th century, its redefinition in Anglo-Saxon countries in the 1960s-1980s, and current debates on the biological or clinicobiological definitions of AD. Key players' opinions are focused on.

RESULTS

At the beginning of the 20th century, AD was defined as a clinicopathological entity. Debates arose around the pathological anchor, which included extended neurofibrillary tangles versus neuritic plaques (Alzheimer vs. Fischer) and its association with senile dementia (Kraepelin). In the 1960s-1980s, the debate shifted towards whether AD could be diagnosed using qualitative or quantitative neuropathological features and whether it was a unique process (Terry and Katzman) or had subtypes (Roth). The current definition proposed by the US Alzheimer's Association is based purely on biological β-amyloid abnormalities and represents a double break: from the historical clinicopathological definition of AD and from the historical emphasis on tau or combined tau and β-amyloid high levels of pathology. Conversely, the clinicobiological proposal of the International Working Group remains aligned with historical concepts of AD.

CONCLUSIONS

This historical perspective illustrates the unresolved questions surrounding AD pathogenesis, role of lesions, and the clinical phenotype, especially for sporadic cases. The intense nosological debates throughout the history of AD also illustrate the diversity of theoretical frameworks for defining disease in medicine.

Pesticides impacts on human health and the environment with their mechanisms of action and possible countermeasures

Pesticides are chemical constituents used to prevent or control pests, including insects, rodents, fungi, weeds, and other unwanted organisms. Despite their advantages in crop production and disease management, the use of pesticides poses significant hazards to the environment and public health. Pesticide elements have now perpetually entered our atmosphere and subsequently contaminated water, food, and soil, leading to health threats ranging from acute to chronic toxicities. Pesticides can cause acute toxicity if a high dose is inhaled, ingested, or comes into contact with the skin or eyes, while prolonged or recurrent exposure to pesticides leads to chronic toxicity. Pesticides produce different types of toxicity, for instance, neurotoxicity, mutagenicity, carcinogenicity, teratogenicity, and endocrine disruption. The toxicity of a pesticide formulation may depend on the specific active ingredient and the presence of synergistic or inert compounds that can enhance or modify its toxicity. Safety concerns are the need of the hour to control contemporary pesticide-induced health hazards. The effectiveness and implementation of the current legislature in providing ample protection for human health and the environment are key concerns. This review explored a comprehensive summary of pesticides regarding their updated impacts on human health and advanced safety concerns with legislation. Implementing regulations, proper training, and education can help mitigate the negative impacts of pesticide use and promote safer and more sustainable agricultural practices.

A synergetic turn in cognitive neuroscience of brain diseases

Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.

Efficacy and safety of repetitive Transcranial Magnetic Stimulation and transcranial Direct Current Stimulation in memory deficits in patients with Alzheimer's disease: Meta-analysis and systematic review

Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are two of the most used non-pharmacological interventions for Alzheimer's Disease (AD). However, most of the clinical trials have focused on evaluating the effects on global cognition and not on specific cognitive functions. Therefore, considering that memory loss is one of the hallmark symptoms of AD, we aim to assess the efficacy and safety of tDCS and rTMS in memory deficits. For that, multilevel random effect models were performed considering the standardized mean difference (SMD) between active and sham stimulation. A total of 19 studies with 411 participants demonstrated positive effects in memory after tDCS (SMD=0.20, p = 0.04) and rTMS (SMD=0.44, p = 0.001). Subgroup analysis revealed that tDCS had greater efficacy when administered in temporal regions (SMD=0.32, p = 0.04), whereas rTMS was superior when applied in frontal regions (SMD=0.61, p < 0.001). Therefore, depending on the brain region of stimulation, both interventions produced a positive effect on memory symptoms in AD patients. Finally, the safety of both techniques was observed in the AD population after the reporting of almost no serious events.

Ultrasensitive and Multiple Biomarker Discrimination for Alzheimer's Disease via Plasmonic & Microfluidic Sensing Technologies

As the population ages, the worldwide prevalence of Alzheimer's disease (AD) as the most common dementia in the elderly is increasing dramatically. However, a long-term challenge is to achieve rapid and accurate early diagnosis of AD by detecting hallmarks such as amyloid beta (Aβ42). Here, a multi-channel microfluidic-based plasmonic fiber-optic biosensing platform is established for simultaneous detection and differentiation of multiple AD biomarkers. The platform is based on a gold-coated, highly-tilted fiber Bragg grating (TFBG) and a custom-developed microfluidics. TFBG excites a high-density, narrow-cladding-mode spectral comb that overlaps with the broad absorption of surface plasmons for high-precision interrogation, enabling ultrasensitive monitoring of analytes. In situ detection and in-parallel discrimination of different forms of Aβ42 in cerebrospinal fluid (CSF) are successfully demonstrated with a detection of limit in the range of ≈30-170 pg mL-1, which is one order of magnitude below the clinical cut-off level in AD onset, providing high detection sensitivity for early diagnosis of AD. The integration of the TFBG sensor with multi-channel microfluidics enables simultaneous detection of multiple biomarkers using sub-µL sample volumes, as well as combining initial binding rate and real-time response time to differentiate between multiple biomarkers in terms of binding kinetics. With the advantages of multi-parameter, low consumption, and highly sensitive detection, the sensor represents an urgently needed potentials for large-scale diagnosis of diseases at early stage.

Association of APOE gene with longitudinal changes of CSF amyloid beta and tau levels in Alzheimer's disease: racial differences

BACKGROUND

The Apolipoprotein E (APOE) ε4 allele is a risk factor for late-onset Alzheimer's disease (AD). However, no investigation has focused on racial differences in the longitudinal effect of APOE genotypes on CSF amyloid beta (Aβ42) and tau levels in AD.

METHODS

This study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 222 participants with AD, 264 with cognitive normal (CN), and 692 with mild cognitive impairment (MCI) at baseline and two years follow-up. We used a linear mixed model to investigate the effect of APOE-ε4-genotypes on longitudinal changes in the amyloid beta and tau levels.

RESULTS

Individuals with 1 or 2 APOE ε4 alleles revealed significantly higher t-Tau and p-Tau, but lower amyloid beta Aβ42 compared with individuals without APOE ε4 alleles. Significantly higher levels of log-t-Tau, log-p-Tau, and low levels of log-Aβ42 were observed in the subjects with older age, being female, and the two diagnostic groups (AD and MCI). The higher p-Tau and Aβ42 values are associated with poor Mini-Mental State Examination (MMSE) performance. Non-Hispanic Africa American (AA) and Hispanic participants were associated with decreased log-t-Tau levels (β =  - 0.154, p = 0.0112; β =  - 0.207, and p = 0.0016, respectively) as compared to those observed in Whites. Furthermore, Hispanic participants were associated with a decreased log-p-Tau level (β =  - 0.224, p = 0.0023) compared to those observed in Whites. There were no differences in Aβ42 level for non-Hispanic AA and Hispanic participants compared with White participants.

CONCLUSION

Our study, for the first time, showed that the APOE ε4 allele was associated with these biomarkers, however with differing degrees among racial groups.

Epilepsy and epileptiform activity in late-onset Alzheimer disease: clinical and pathophysiological advances, gaps and conundrums

A growing body of evidence has demonstrated a link between Alzheimer disease (AD) and epilepsy. Late-onset epilepsy and epileptiform activity can precede cognitive deterioration in AD by years, and its presence has been shown to predict a faster disease course. In animal models of AD, amyloid and tau pathology are linked to cortical network hyperexcitability that precedes the first signs of memory decline. Thus, detection of epileptiform activity in AD has substantial clinical importance as a potential novel modifiable risk factor for dementia. In this Review, we summarize the epidemiological evidence for the complex bidirectional relationship between AD and epilepsy, examine the effect of epileptiform activity and seizures on cognition in people with AD, and discuss the precision medicine treatment strategies based on the latest research in human and animal models. Finally, we outline some of the unresolved questions of the field that should be addressed by rigorous research, including whether particular clinicopathological subtypes of AD have a stronger association with epilepsy, and the sequence of events between epileptiform activity and amyloid and tau pathology.

Impact of APOE on amyloid and tau accumulation in argyrophilic grain disease and Alzheimer's disease

Alzheimer's disease (AD), characterized by the deposition of amyloid-β (Aβ) in senile plaques and neurofibrillary tangles of phosphorylated tau (pTau), is increasingly recognized as a complex disease with multiple pathologies. AD sometimes pathologically overlaps with age-related tauopathies such as four repeat (4R)-tau predominant argyrophilic grain disease (AGD). While AGD is often detected with AD pathology, the contribution of APOE4 to AGD risk is not clear despite its robust effects on AD pathogenesis. Specifically, how APOE genotype influences Aβ and tau pathology in co-occurring AGD and AD has not been fully understood. Using postmortem brain samples (N = 353) from a neuropathologically defined cohort comprising of cases with AD and/or AGD pathology built to best represent different APOE genotypes, we measured the amounts of major AD-related molecules, including Aβ40, Aβ42, apolipoprotein E (apoE), total tau (tTau), and pTau181, in the temporal cortex. The presence of tau lesions characteristic of AD (AD-tau) was correlated with cognitive decline based on Mini-Mental State Examination (MMSE) scores, while the presence of AGD tau lesions (AGD-tau) was not. Interestingly, while APOE4 increased the risk of AD-tau pathology, it did not increase the risk of AGD-tau pathology. Although APOE4 was significantly associated with higher levels of insoluble Aβ40, Aβ42, apoE, and pTau181, the APOE4 effect was no longer detected in the presence of AGD-tau. We also found that co-occurrence of AGD with AD was associated with lower insoluble Aβ42 and pTau181 levels. Overall, our findings suggest that different patterns of Aβ, tau, and apoE accumulation mediate the development of AD-tau and AGD-tau pathology, which is affected by APOE genotype.

Polypathologic Associations with Gray Matter Atrophy in Neurodegenerative Disease

Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer's pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid-[Formula: see text], tau, TDP-43, and [Formula: see text]-synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient's primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and [Formula: see text]-synuclein burden were inversely associated with regional volumes, but amyloid-[Formula: see text] was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and [Formula: see text]-synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology.

Extra-Virgin Olive Oil in Alzheimer's Disease: A Comprehensive Review of Cellular, Animal, and Clinical Studies

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is characterized by several pathological hallmarks, including the deposition of amyloid-β (Aβ) plaques, neurofibrillary tangles, blood-brain barrier (BBB) dysfunction, increased oxidative stress, and neuroinflammation. Current treatment options include monoclonal antibody drugs, acetylcholinesterase, and n-methyl-d-aspartate (NMDA) antagonists. Although those treatments provide some improvements in patients' quality of life, they fail to prevent or cure AD. Current research aims to identify novel targets and tools for AD prevention and modification. In this context, several studies showed the beneficial effect of the Mediterranean diet in the prevention and treatment of AD. One integral component of the Mediterranean diet is olive oil and extra-virgin olive oil (EVOO), which is high in phenolic compounds. EVOO and other olive-related phenolic compounds have been shown to reduce the risk of developing mild cognitive impairment (MCI) and AD. In this review, we discuss the mechanisms by which EVOO and phenolic compounds exert neuroprotective effects, including modulation of AD pathologies and promotion of cognitive health. Findings indicate that EVOO and its phenolic constituents influence key pathological processes of AD, such as Aβ aggregation, tau phosphorylation, and neuroinflammation, while also enhancing BBB integrity and reducing oxidative stress. The human studies cited reveal a consistent trend where the consumption of olive oil is associated with cognitive benefits and a decreased risk of AD and related dementias. In conclusion, EVOO and its phenolic compounds hold promising potential for the prevention and treatment of AD, representing a significant shift towards more effective strategies against this complex neurodegenerative disorder.

Advances in targeted tracking and detection of soluble amyloid-β aggregates as a biomarker of Alzheimer's disease

Misfolding and aggregation of amyloid-β (Aβ) peptides are key hallmarks of Alzheimer's disease (AD). With accumulating evidence suggesting that different Aβ species have varied neurotoxicity and implications in AD development, the discovery of affinity ligands and analytical approaches to selective distinguish, detect, and monitor Aβ becomes an active research area. Remarkable advances have been achieved, which not only promote our understanding of the biophysical chemistry of the protein aggregation during neurodegeneration, but also provide promising tools for early detection of the disease. In view of this, we summarize the recent progress in selective and sensitive approaches for tracking and detection of Aβ species. Specific attentions are given to soluble Aβ oligomers, due to their crucial roles in AD development and occurrence at early stages. The design principle, performance of targeting units, and their cooperative effects with signal reporters for Aβ analysis are discussed. The applications of the novel targeting probes and sensing systems for dynamic monitoring oligomerization, measuring Aβ in biosamples and in vivo imaging in brain are summarized. Finally, the perspective and challenges are discussed regarding the future development of Aβ-targeting analytical tools to explore the unknown field to contribute to the early diagnosis and treatment of AD.

Data-driven modelling of neurodegenerative disease progression: thinking outside the black box

Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.

Controversial Past, Splendid Present, Unpredictable Future: A Brief Review of Alzheimer Disease History

Background: The concept of Alzheimer disease (AD)-since its histological discovery by Alzheimer to the present day-has undergone substantial modifications. Methods: We conducted a classical narrative review of this field with a bibliography selection (giving preference to Medline best match). Results: The following subjects are reviewed and discussed: Alzheimer's discovery, Kraepelin's creation of a new disease that was a rare condition until the 1970's, the growing interest and investment in AD as a major killer in a society with a large elderly population in the second half of the 20th century, the consolidation of the AD clinicopathological model, and the modern AD nosology based on the dominant amyloid hypothesis among many others. In the 21st century, the development of AD biomarkers has supported a novel biological definition of AD, although the proposed therapies have failed to cure this disease. The incidence of dementia/AD has shown a decrease in affluent countries (possibly due to control of risk factors), and mixed dementia has been established as the most frequent etiology in the oldest old. Conclusions: The current concept of AD lacks unanimity. Many hypotheses attempt to explain its complex physiopathology entwined with aging, and the dominant amyloid cascade has yielded poor therapeutic results. The reduction in the incidence of dementia/AD appears promising but it should be confirmed in the future. A reevaluation of the AD concept is also necessary.

Neuroprotective effects and possible mechanisms of berberine in animal models of Alzheimer's disease: a systematic review and meta-analysis

Background: Recently, multiple preclinical studies have reported the beneficial effect of berberine in the treatment of Alzheimer's disease (AD). Nevertheless, the neuroprotective effects and possible mechanisms of berberine against AD are not universally recognized. This study aimed to conduct a systematic review and meta-analysis by integrating relevant animal studies to assess the neuroprotective effects and potential mechanisms of berberine on AD. Methods: We systematically searched PubMed, Embase, Scopus and Web of Science databases that reported the effects of berberine on AD models up to 1 February 2023. The escape latency, times of crossing platform, time spent in the target quadrant and pro-oligomerized amyloid beta 42 (Aβ1-42) were included as primary outcomes. The secondary outcomes were the Tau-ps 204, Tau-ps 404, β-site of APP cleaving enzyme (BACE1), amyloid precursor protein (APP), acetylcholine esterase (AChE), tumor necrosis factor ⍺ (TNF-α), interleukin 1β (IL-1β), IL-6, nitric oxide (NO), glial fibrillary acidic protein (GFAP), malonaldehyde (MDA), glutathione S-transferase (GST), glutathione (GSH), glutathione peroxidase (GPx), Beclin-1 and neuronal apoptosis cells. This meta-analysis was conducted using RevMan 5.4 and STATA 15.1. The SYRCLE's risk of bias tool was used to assess the methodological quality. Results: Twenty-two studies and 453 animals were included in the analysis. The overall results showed that berberine significantly shortened the escape latency (p < 0.00001), increased times of crossing platform (p < 0.00001) and time spent in the target quadrant (p < 0.00001), decreased Aβ1-42 deposition (p < 0.00001), Tau-ps 202 (p < 0.00001) and Tau-ps 404 (p = 0.002), and improved BACE1, APP, AChE, Beclin-1, neuronal apoptosis cells, oxidative stress and inflammation levels. Conclusion: Berberine may be a promising drug for the treatment of AD based on preclinical evidence (especially when the dose was 5-260 mg/kg). The potential mechanisms for these protective effects may be closely related to anti-neuroinflammation, anti-oxidative stress, modulation of autophagy, inhibition of neuronal apoptosis and protection of cholinergic system. However, these results may be limited by the quality of existing research. Larger and methodologically more rigorous preclinical research are needed to provide more convincing evidence.

Neutrophil extracellular traps in central nervous system (CNS) diseases

Excessive induction of inflammatory and immune responses is widely considered as one of vital factors contributing to the pathogenesis and progression of central nervous system (CNS) diseases. Neutrophils are well-studied members of inflammatory and immune cell family, contributing to the innate and adaptive immunity. Neutrophil-released neutrophil extracellular traps (NETs) play an important role in the regulation of various kinds of diseases, including CNS diseases. In this review, current knowledge on the biological features of NETs will be introduced. In addition, the role of NETs in several popular and well-studied CNS diseases including cerebral stroke, Alzheimer's disease, multiple sclerosis, amyotrophic lateral sclerosis (ALS), and neurological cancers will be described and discussed through the reviewing of previous related studies.

Silver nanoparticle-based SERS sensors for sensitive detection of amyloid-β aggregates in biological fluids

One of the hallmarks of Alzheimer's disease (AD) pathogenesis is the production, aggregation, and deposition of amyloid-β (Aβ) peptide. Surface-enhanced Raman spectroscopy (SERS) is a promising analytical technique capable of providing valuable information on chemical composition and molecule conformations in biological samples. However, one of the main challenges for introducing the SERS technique into the practice is preparation of scalable and at the same time stable nanostructured sensors with uniform spatial distribution of nanoparticles. Herein, we propose SERS platforms for reproducible, sensitive, label-free quantification of amyloid-β aggregates for short-wavelength - 532 and 633 nm - lasers. A SERS sensor - based on silver nanoparticles immobilized into a chitosan film (AgNP/CS) - provided a uniform distribution of AgNPs from a colloidal suspension across the SERS sensor, resulting in nanomolar limits of detection (LODs) for Aβ42 aggregates with a portable 532 nm laser. The laser-induced deposition was used to obtain denser periodic plasmonic sensors (AgNP/LID) with a uniform nanoparticle distribution. The AgNP/LID SERS sensor allowed for 15 pM LOD for Aβ42 aggregates with 633 nm laser. Notably, both nanostructured substrates allowed to distinguish amyloid aggregates from monomers. Therefore, our approach demonstrated applicability of SERS for detection of macromolecular volumetric objects as amyloid-β aggregates for fundamental biological studies as well as for "point-of-care" diagnostics and screening for early stages of neurodegenerative diseases.

Review of electrospun microtube array membrane (MTAM)-a novel new class of hollow fiber for encapsulated cell therapy (ECT) in clinical applications

Encapsulated cell therapy (ECT) shows significant potential for treating neurodegenerative disorders including Alzheimer's and Parkinson's, which currently lack curative medicines and must be managed symptomatically. This novel technique encapsulates functional cells with a semi-permeable membrane, providing protection while enabling critical nutrients and therapeutic substances to pass through. Traditional ECT procedures, on the other hand, pose difficulties in terms of cell survival and retrieval. We introduce the Microtube Array Membrane (MTAM), a revolutionary technology that solves these constraints, in this comprehensive overview. Microtube Array Membrane has distinct microstructures that improve encapsulated cells' long-term viability by combining the advantages of macro and micron scales. Importantly, the MTAM platform improves biosafety by allowing the entire encapsulated unit to be retrieved in the event of an adverse reaction. Our findings show that MTAM-based ECT has a great potential in a variety of illness situations. For cancer treatment, hybridoma cells secreting anti-CEACAM 6 antibodies inhibit triple-negative breast cancer cell lines for an extended period of time. In animal brain models of Alzheimer's disease, hybridoma cells secreting anti-pTau antibodies successfully reduce pTau buildup, accompanied by improvements in memory performance. In mouse models, MTAM-encapsulated primary cardiac mesenchymal stem cells dramatically improve overall survival and heart function. These findings illustrate the efficacy and adaptability of MTAM-based ECT in addressing major issues such as immunological isolation, cell viability, and patient safety. We provide new possibilities for the treatment of neurodegenerative illnesses and other conditions by combining the potential of ECT with MTAM. Continued research and development in this subject has a lot of promise for developing cell therapy and giving hope to people suffering from chronic diseases.

Once upon a time, the Amyloid Cascade Hypothesis

Recent trials with monoclonal antibodies targeting amyloid-β (Aβ) in Alzheimer's disease (AD) have sparked a renewed interest in disease-modifying therapies. Despite their promise, these trials leave the issue open and posit some doubts about the validity of the Amyloid Cascade Hypothesis (ACH). While some scores of neurocognitive tests improved upon treatment, real-world clinical benefits were minimal. This Viewpoint discusses additional, often overlooked findings from these trials. We also emphasize the multifactorial nature of AD and the need for a broader research perspective beyond the simplistic disease model provided by the ACH.

Identifying the joint signature of brain atrophy and gene variant scores in Alzheimer's Disease

The joint modeling of genetic data and brain imaging information allows for determining the pathophysiological pathways of neurodegenerative diseases such as Alzheimer's disease (AD). This task has typically been approached using mass-univariate methods that rely on a complete set of Single Nucleotide Polymorphisms (SNPs) to assess their association with selected image-derived phenotypes (IDPs). However, such methods are prone to multiple comparisons bias and, most importantly, fail to account for potential cross-feature interactions, resulting in insufficient detection of significant associations. Ways to overcome these limitations while reducing the number of traits aim at conveying genetic information at the gene level and capturing the integrated genetic effects of a set of genetic variants, rather than looking at each SNP individually. Their associations with brain IDPs are still largely unexplored in the current literature, though they can uncover new potential genetic determinants for brain modulations in the AD continuum. In this work, we explored an explainable multivariate model to analyze the genetic basis of the grey matter modulations, relying on the AD Neuroimaging Initiative (ADNI) phase 3 dataset. Cortical thicknesses and subcortical volumes derived from T1-weighted Magnetic Resonance were considered to describe the imaging phenotypes. At the same time the genetic counterpart was represented by gene variant scores extracted by the Sequence Kernel Association Test (SKAT) filtering model. Moreover, transcriptomic analysis was carried on to assess the expression of the resulting genes in the main brain structures as a form of validation. Results highlighted meaningful genotype-phenotype interactionsas defined by three latent components showing a significant difference in the projection scores between patients and controls. Among the significant associations, the model highlighted EPHX1 and BCAS1 gene variant scores involved in neurodegenerative and myelination processes, hence relevant for AD. In particular, the first was associated with decreased subcortical volumes and the second with decreasedtemporal lobe thickness. Noteworthy, BCAS1 is particularly expressed in the dentate gyrus. Overall, the proposed approach allowed capturing genotype-phenotype interactions in a restricted study cohort that was confirmed by transcriptomic analysis, offering insights into the underlying mechanisms of neurodegeneration in AD in line with previous findings and suggesting new potential disease biomarkers.

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links

In recent years, deep learning approaches have gained significant attention in predicting brain disorders using neuroimaging data. However, conventional methods often rely on single-modality data and supervised models, which provide only a limited perspective of the intricacies of the highly complex brain. Moreover, the scarcity of accurate diagnostic labels in clinical settings hinders the applicability of the supervised models. To address these limitations, we propose a novel self-supervised framework for extracting multiple representations from multimodal neuroimaging data to enhance group inferences and enable analysis without resorting to labeled data during pre-training. Our approach leverages Deep InfoMax (DIM), a self-supervised methodology renowned for its efficacy in learning representations by estimating mutual information without the need for explicit labels. While DIM has shown promise in predicting brain disorders from single-modality MRI data, its potential for multimodal data remains untapped. This work extends DIM to multimodal neuroimaging data, allowing us to identify disorder-relevant brain regions and explore multimodal links. We present compelling evidence of the efficacy of our multimodal DIM analysis in uncovering disorder-relevant brain regions, including the hippocampus, caudate, insula, - and multimodal links with the thalamus, precuneus, and subthalamus hypothalamus. Our self-supervised representations demonstrate promising capabilities in predicting the presence of brain disorders across a spectrum of Alzheimer's phenotypes. Comparative evaluations against state-of-the-art unsupervised methods based on autoencoders, canonical correlation analysis, and supervised models highlight the superiority of our proposed method in achieving improved classification performance, capturing joint information, and interpretability capabilities. The computational efficiency of the decoder-free strategy enhances its practical utility, as it saves compute resources without compromising performance. This work offers a significant step forward in addressing the challenge of understanding multimodal links in complex brain disorders, with potential applications in neuroimaging research and clinical diagnosis.

APOE-ε4 Alleles Modify the Decline of MMSE Scores Associated With Time-Dependent PM2.5 Exposure: Findings From a Community-Based Longitudinal Cohort Study

OBJECTIVE

Limited research has explored the long-term effect of reduced PM2.5 exposure on cognitive function. This study aimed to investigate the effects of time-dependent PM2.5 exposure and the interactions of PM2.5 and aging on declines in Mini-Mental State Examination (MMSE) scores, in carriers and non-carriers of the APOE-ε4 allele.

METHODS

Participants aged over 60 were recruited for this cohort study, undergoing MMSE tests twice from the Taiwan Biobank Program from 2008 to 2020. Participants with dementia or baseline MMSE scores <24 were excluded. Annual PM2.5 levels were estimated using a hybrid kriging/land use regression model with extreme gradient boosting, treated as a time-dependent variable. Generalized estimating equations were used to assess the impacts of repeated PM2.5 on MMSE decline, further stratified by the presence of APOE-ε4 alleles.

RESULTS

After follow-up, 290 participants out of the overall 7,000 community residents in the Biobank dataset demonstrated incidences of MMSE declines (<24), with an average MMSE score decline of 1.11 per year. Participants with ε4/ε4 alleles in the APOE gene had significantly 3.68-fold risks of MMSE decline. High levels of PM2.5 across all visits were significantly associated with worsening of scores on the overall MMSE. As annual levels of PM2.5 decreased over time, the impact of PM2.5 on MMSE decline also slowly diminished.

CONCLUSION

Long-term PM2.5 exposure may be associated with increased risk of MMSE decline, despite improvements in ambient PM2.5 levels over time. Validation of these results necessitates a large-scale prospective cohort study with more concise cognitive screening tools.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

Introduction

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

Methods

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

Results

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

Discussion

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

The Impact of Apolipoprotein E (APOE) Epigenetics on Aging and Sporadic Alzheimer's Disease

Sporadic Alzheimer's disease (AD) derives from an interplay among environmental factors and genetic variants, while epigenetic modifications have been expected to affect the onset and progression of its complex etiopathology. Carriers of one copy of the apolipoprotein E gene (APOE) ε4 allele have a 4-fold increased AD risk, while APOE ε4/ε4-carriers have a 12-fold increased risk of developing AD in comparison with the APOE ε3-carriers. The main longevity factor is the homozygous APOE ε3/ε3 genotype. In the present narrative review article, we summarized and described the role of APOE epigenetics in aging and AD pathophysiology. It is not fully understood how APOE variants may increase or decrease AD risk, but this gene may affect tau- and amyloid-mediated neurodegeneration directly or indirectly, also by affecting lipid metabolism and inflammation. For sporadic AD, epigenetic regulatory mechanisms may control and influence APOE expression in response to external insults. Diet, a major environmental factor, has been significantly associated with physical exercise, cognitive function, and the methylation level of several cytosine-phosphate-guanine (CpG) dinucleotide sites of APOE.

Catechol-Amyloid Interactions

This review introduces multifaceted mutual interactions between molecules containing a catechol moiety and aggregation-prone proteins. The complex relationships between these two molecular species have previously been elucidated primarily in a unidirectional manner, as demonstrated in cases involving the development of catechol-based inhibitors for amyloid aggregation and the elucidation of the role of functional amyloid fibers in melanin biosynthesis. This review aims to consolidate scattered clues pertaining to catechol-based amyloid inhibitors, functional amyloid scaffold of melanin biosynthesis, and chemically designed peptide fibers for providing chemical insights into the role of the local three-dimensional orientation of functional groups in manifesting such interactions. These orientations may play crucial, yet undiscovered, roles in various supramolecular structures.

Prediction of misfolded proteins spreading in Alzheimer's disease using machine learning and spreading models

The pervasive impact of Alzheimer's disease on aging society represents one of the main challenges at this time. Current investigations highlight 2 specific misfolded proteins in its development: Amyloid-$\beta$ and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on 2 machine learning approaches which we compare with known simulation models. The first approach applies an autoregressive model constrained by structural connectivity, while the second is based on graph convolutional networks. The aim is to predict concentrations of Amyloid-$\beta$ 2 yr after a provided baseline. We also evaluate its real-world effectiveness and suitability by providing a web service for physicians and researchers. In experiments, the autoregressive model generally outperformed state-of-the-art models resulting in lower prediction errors. While it is important to note that a comprehensive prognostic plan cannot solely rely on amyloid beta concentrations, their prediction, achieved by the discussed approaches, can be valuable for planning therapies and other cures, especially when dealing with asymptomatic patients for whom novel therapies could prove effective.

Small Molecules N-Phenylbenzofuran-2-carboxamide and N-Phenylbenzo[b]thiophene-2-carboxamide Promote Beta-Amyloid (Aβ42) Aggregation and Mitigate Neurotoxicity

This study reports the unusual ability of small molecules N-phenylbenzofuran-2-carboxamide (7a) and N-phenylbenzo[b]thiophene-2-carboxamide (7b) to promote and accelerate Aβ42 aggregation. In the in vitro aggregation kinetic assays, 7a was able to demonstrate rapid increases in Aβ42 fibrillogenesis ranging from 1.5- to 4.7-fold when tested at 1, 5, 10, and 25 μM compared to Aβ42-alone control. Similarly, compound 7b also exhibited 2.9- to 4.3-fold increases in Aβ42 fibrillogenesis at the concentration range tested. Electron microscopy studies at 1, 5, 10, and 25 μM also demonstrate the ability of compounds 7a and 7b to promote and accelerate Aβ42 aggregation with the formation of long, elongated fibril structures. Both 7a and 7b were not toxic to HT22 hippocampal neuronal cells and strikingly were able to prevent Aβ42-induced cytotoxicity in HT22 hippocampal neuronal cells (cell viability ∼74%) compared to the Aβ42-treated group (cell viability ∼20%). Fluorescence imaging studies using BioTracker 490 green, Hoeschst 33342, and the amyloid binding dye ProteoStat further demonstrate the ability of 7a and 7b to promote Aβ42 fibrillogenesis and prevent Aβ42-induced cytotoxicity to HT22 hippocampal neuronal cells. Computational modeling studies suggest that both 7a and 7b can interact with the Aβ42 oligomer and pentamers and have the potential to modulate the self-assembly pathways. The 8-anilino-1-naphthalenesulfonic acid (ANS) dye binding assay also demonstrates the ability of 7a and 7b to expose the hydrophobic surface of Aβ42 to the solvent surface that promotes self-assembly and rapid fibrillogenesis. These studies demonstrate the unique ability of small molecules 7a and 7b to alter the self-assembly and misfolding pathways of Aβ42 by promoting the formation of nontoxic aggregates. These findings have direct implications in the discovery and development of novel small-molecule-based chemical and pharmacological tools to study the Aβ42 aggregation mechanisms, and in the design of novel antiamyloid therapies to treat Alzheimer's disease.

Pathways linking microbiota-gut-brain axis with neuroinflammatory mechanisms in Alzheimer's pathophysiology

Disturbances in the local and peripheral immune systems are closely linked to a wide range of diseases. In the context of neurodegenerative disorders such as Alzheimer's disease (AD), inflammation plays a crucial role, often appearing as a common manifestation despite the variability in the occurrence of other pathophysiological hallmarks. Thus, combating neuroinflammation holds promise in treating complex pathophysiological diseases like AD. Growing evidence suggests the gut microbiome's crucial role in shaping the pathogenesis of AD by influencing inflammatory mediators. Gut dysbiosis can potentially activate neuroinflammatory pathways through bidirectional signaling of the gut-brain axis; however, the precise mechanisms of this complex interweaved network remain largely unclear. In these milieus, this review attempts to summarize the contributing role of gut microbiome-mediated neuroinflammatory signals in AD pathophysiology, while also pondering potential mechanisms through which commensal and pathogenic gut microbes affect neuroinflammation. While certain taxa such as Roseburia and Escherichia have been strongly correlated with AD, other clades such as Bacteroides and Faecalibacterium exhibit variations at the species and strain levels. In order to disentangle the inflammatory aspects of neurodegeneration attributed to the gut microbiome, it is imperative that future mechanistic studies investigate the species/strain-level dependency of commensals, opportunistic, and pathogenic gut microbes that consistently show correlations with AD patients across multiple associative studies.

Aging gene signature of memory CD8+ T cells is associated with neurocognitive functioning in Alzheimer's disease

BACKGROUND

Memory CD8+ T cells expand with age. We previously demonstrated an age-associated expansion of effector memory (EM) CD8+ T cells expressing low levels of IL-7 receptor alpha (IL-7Rαlow) and the presence of its gene signature (i.e., IL-7Rαlow aging genes) in peripheral blood of older adults without Alzheimer's disease (AD). Considering age as the strongest risk factor for AD and the recent finding of EM CD8+ T cell expansion, mostly IL-7Rαlow cells, in AD, we investigated whether subjects with AD have alterations in IL-7Rαlow aging gene signature, especially in relation to genes possibly associated with AD and disease severity.

RESULTS

We identified a set of 29 candidate genes (i.e., putative AD genes) which could be differentially expressed in peripheral blood of patients with AD through the systematic search of publicly available datasets. Of the 29 putative AD genes, 9 genes (31%) were IL-7Rαlow aging genes (P < 0.001), suggesting the possible implication of IL-7Rαlow aging genes in AD. These findings were validated by RT-qPCR analysis of 40 genes, including 29 putative AD genes, additional 9 top IL-7R⍺low aging but not the putative AD genes, and 2 inflammatory control genes in peripheral blood of cognitively normal persons (CN, 38 subjects) and patients with AD (40 mild cognitive impairment and 43 dementia subjects). The RT-qPCR results showed 8 differentially expressed genes between AD and CN groups; five (62.5%) of which were top IL-7Rαlow aging genes (FGFBP2, GZMH, NUAK1, PRSS23, TGFBR3) not previously reported to be altered in AD. Unbiased clustering analysis revealed 3 clusters of dementia patients with distinct expression levels of the 40 analyzed genes, including IL-7Rαlow aging genes, which were associated with neurocognitive function as determined by MoCA, CDRsob and neuropsychological testing.

CONCLUSIONS

We report differential expression of "normal" aging genes associated with IL-7Rαlow EM CD8+ T cells in peripheral blood of patients with AD, and the significance of such gene expression in clustering subjects with dementia due to AD into groups with different levels of cognitive functioning. These results provide a platform for studies investigating the possible implications of age-related immune changes, including those associated with CD8+ T cells, in AD.