Alzheimer's Disease Pathology Research Articles

Cuproptosis and copper as potential mechanisms and intervention targets in Alzheimer's disease.

Recently study has found a new form of copper-dependent death called cuproptosis, which differs from apoptosis, ferroptosis, and necrosis. The main process of cuproptosis is copper directly combined with lipid-acetylated proteins in the TCA cycle of mitochondrial response, leading to the aggregation of lipid-acetylated proteins and the loss of Fe-S cluster proteins, resulting in mitochondrial dysfunction, and eventually causing cell death. Previous studies demonstrated that an imbalance in copper homeostasis exacerbates the pathological progression of Alzheimer's disease (AD) through the induction of oxidative stress, inflammatory response, and the accumulation of Aβ deposition and tau protein hyperphosphorylation. However, the underlying mechanisms remains to be elucidated. More importantly, research identifies the role of cuproptosis and further elucidates the underlying molecular mechanisms in AD. This review summarized the effects of copper metabolism on AD pathology, the characteristics and mechanism of cuproptosis and we discuss the significance of cuproptosis in the pathogenesis of AD.

Microstructural white matter injury contributes to cognitive decline: Besides amyloid and tau.

Cognitive decline and the progression to Alzheimer's disease (AD) are traditionally associated with amyloid-beta (Aβ) and tau pathologies. This study aims to evaluate the relationships between microstructural white matter injury, cognitive decline and AD core biomarkers. We conducted a longitudinal study of 566 participants using peak width of skeletonized mean diffusivity (PSMD) to quantify microstructural white matter injury. The associations of PSMD with changes in cognitive functions, AD pathologies (Aβ, tau, and neurodegeneration), and volumes of AD-signature regions of interest (ROI) or hippocampus were estimated. The associations between PSMD and the incidences of clinical progression were also tested. Covariates included age, sex, education, apolipoprotein E4 status, smoking, and hypertension. Higher PSMD was associated with greater cognitive decline (β=-0.012, P < 0.001 for Mini-Mental State Examination score; β<0, P < 0.05 for four cognitive domains) and a higher risk of clinical progression from normal cognition to mild cognitive impairment (MCI) or AD (Hazard ratio=2.11 [1.38-3.23], P < 0.001). These associations persisted independently of amyloid status. PSMD did not predict changes in Aβ or tau levels, but predicted changes in volumes of AD-signature ROI (β=-0.003, P < 0.001) or hippocampus (β=-0.002, P = 0.010). Besides, the whole-brain PSMD could predict cognitive decline better than regional PSMDs. PSMD may be a valuable biomarker for predicting cognitive decline and clinical progression to MCI and AD, providing insights besides traditional Aβ and tau pathways. Further research could elucidate its role in clinical assessments and therapeutic strategies.

Lignans from Schisandra chinensis (Turcz.) Baill ameliorates cognitive impairment in Alzheimer's disease and alleviates ferroptosis by activating the Nrf2/FPN1 signaling pathway and regulating iron levels.

Schisandra chinensis (Turcz.) Baill (S. chinensis), first recorded in Shennong's Classic of the Materia Medica, is described as a "top grade medicine". As a traditional Chinese medicine of tonifying the kidneys and the brain, S. chinensis is widely used to treat diseases such as amnesia and dementia. Alzheimer's disease (AD) is a neurodegenerative disease, and ferroptosis is one of the essential causes of AD. Although previous studies have suggested that the lignans of S. chinensis (SCL) have neuroprotective effects, it is unclear whether SCL can alleviate AD pathology by inhibiting ferroptosis. To investigate the effect of SCL on AD caused by ferroptosis and its possible molecular mechanism. This study was based on SAMR1/SAMP8 mouse models along with Erastin-induced HT22cell lines to examine the influence of SCL on ferroptosis in AD. The S. chinensis was extracted via 75% EtOH-H2O and identified by HPLC/UPLC-QTOF-MS. MWM assessed spatial learning, while HE staining, biochemical detection, IHC, and WB analyzed AD pathology and iron metabolism. Mitochondrial changes were evaluated by TEM, and confocal imaging post-SCL treatment analyzed ROS, MMP, and Fe2+ levels in HT22cells. IF determined the expression levels and localization of Nrf2 and FPN1. CETSA was deployed to study the interaction between SCL and Nrf2. Treatment with SCL mitigated cognitive dysfunction and reduced p-Tau as well as neuronal loss in AD model mice. Additionally, the administration of SCL alleviated oxidative stress and maintained relatively intact mitochondrial ridges and membranes, decreased TFR and DMT1 protein expression, and upregulated FTH1. Consistent with the in vivo results, SCL inhibited Erastin-induced ferroptosis in HT22cells. SCL promoted Nrf2 nuclear translocation and upregulated FPN1, SLC7A11, and GPX4 protein expressions while decreasing FACL4. The improvement of ferroptosis by SCL was associated with the regulation of the Nrf2/FPN1 signaling pathway. The novel discoveries of this study suggest that SCL can suppress ferroptosis in the brains of AD model mice and exerts a partial protective effect against Erastin-induced ferroptosis in HT22cells, in which the Nrf2/FPN1 signaling pathway plays a crucial role.

Identifying proteomic prognostic markers for Alzheimer's disease with survival machine learning: The Framingham Heart Study.

Protein abundance levels, sensitive to both physiological changes and external interventions, are useful for assessing the Alzheimer's disease (AD) risk and treatment efficacy. However, identifying proteomic prognostic markers for AD is challenging by their high dimensionality and inherent correlations. Our study analyzed 1128 plasma proteins, measured by the SOMAscan platform, from 858 participants 55 years and older (mean age 63 years, 52.9 % women) of the Framingham Heart Study (FHS) Offspring cohort. We conducted regression analysis and machine learning models, including LASSO-based Cox proportional hazard regression model (LASSO) and generalized boosted regression model (GBM), to identify protein prognostic markers. These markers were used to construct a weighted proteomic composite score, the AD prediction performance of which was assessed using time-dependent area under the curve (AUC). The association between the composite score and memory domain was examined in 339 (of the 858) participants with available memory scores, and in a separate group of 430 participants younger than 55 years (mean age 46, 56.7 % women). Over a mean follow-up of 20 years, 132 (15.4 %) participants developed AD. After adjusting for baseline age, sex, education, and APOE ε4 + status, regression models identified 309 proteins (P ≤ 0.2). After applying machine learning methods, nine of these proteins were selected to develop a composite score. This score improved AD prediction beyond the factors of age, sex, education, and APOE ε4 + status across 15-25 years of follow-up, achieving its peak AUC of 0.84 in the LASSO model at the 22-year follow-up. It also showed a consistent negative association with memory scores in the 339 participants (beta = -0.061, P = 0.046), 430 participants (beta = -0.060, P = 0.018), and the pooled 769 samples (beta = -0.058, P = 0.003). These findings highlight the utility of machine learning method in identifying proteomic markers in improving AD prediction and emphasize the complex pathology of AD. The composite score may aid early AD detection and efficacy monitoring, warranting further validation in diverse populations.

Role of NLRP3 Inflammasome in Chronic Pain and Alzheimer's Disease-A Review.

The coexistence of Alzheimer's disease (AD) and chronic pain (CP) in the elderly population has been extensively documented, and a growing body of evidence supports the potential interconnections between these two conditions. This comprehensive review explores the mechanisms by which CP may contribute to the development and progression of AD, with a particular focus on neuroinflammatory pathways and the role of microglia, as well as the activation of the NLR family pyrin domain containing 3 (NLRP3) inflammasome. The review proposes that prolonged pain processing in critical brain regions can dysregulate the activity of the NLRP3 inflammasome within microglia, leading to the overproduction of pro-inflammatory cytokines and excessive oxidative stress in these regions. This aberrant microglial response also results in localized neuroinflammation in brain areas crucial for cognitive function. Additionally, CP as a persistent physiological and psychological stressor may be associated with hypothalamic-pituitary-adrenal (HPA) axis dysfunction, systemic inflammation, disruption of the blood-brain barrier (BBB), and neuroinflammation. These pathophysiological changes can cause morphological and functional impairments in brain regions responsible for cognition, memory, and neurotransmitter production, potentially contributing to the development and progression of CP-associated AD. Resultant neuroinflammation can further promote amyloid-beta (Aβ) plaque deposition, a hallmark of AD pathology. Potential therapeutic interventions targeting these neuroinflammatory pathways, particularly through the regulation of microglial NLRP3 activation, hold promise for improving outcomes in individuals with comorbid CP and AD. However, further research is required to fully elucidate the complex interplay between these conditions and develop effective treatment strategies.

Elevation of ganglioside degradation pathway drives GM2 and GM3 within amyloid plaques in a transgenic mouse model of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease that accounts for two-thirds of all dementia cases, and age is the strongest risk factor. In addition to the amyloid hypothesis, lipid dysregulation is now recognized as a core component of AD pathology. Gangliosides are a class of membrane lipids of the glycosphingolipid family and are enriched in the central nervous system (CNS). Ganglioside dysregulation has been implicated in various neurodegenerative diseases, including AD, but the spatial distribution of ganglioside dysregulation with respect to amyloid-beta (Aβ) deposition is not well understood. To address this gap, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) was employed to investigate the age-dependent expression profiles of the A-series ganglioside species GD1a, GM1, GM2, and GM3 in the APP/PS1 transgenic mouse model of AD in which age-dependent amyloid-beta (Aβ) plaques develop. This study utilized a dual-resolution approach in combination with whole-brain imaging for comprehensive detection of ganglioside expression across neuroanatomical regions via high-resolution imaging of the cerebral cortex and hippocampus to investigate plaque-associated ganglioside alterations. The results revealed age-dependent changes in the complex gangliosides GM1 and GD1a across white and gray matter regions in both wildtype and APP/PS1 mice. Significantly greater levels of simple gangliosides GM2 and GM3 were observed in the cortex and dentate gyrus of the hippocampus in transgenic mice at 12 and 18m than in age-matched controls. The accumulation of GM3 colocalized with Aβ plaques in aged APP/PS1 mice and correlated with Hexa gene expression, suggesting that ganglioside degradation is a mechanism for the accumulation of GM3. This work is the first to demonstrate that age-related ganglioside dysregulation is spatiotemporally associated with Aβ plaques using sophisticated MSI and reveals novel mechanistic insights into lipid regulation in AD.

Gut microbiota in Alzheimer's disease: Understanding molecular pathways and potential therapeutic perspectives.

Accumulating evidence suggests that gut microbiota (GM) plays a crucial role in Alzheimer's disease (AD) pathogenesis and progression. This narrative review explores the complex interplay between GM, the immune system, and the central nervous system in AD. We discuss mechanisms through which GM dysbiosis can compromise intestinal barrier integrity, enabling pro-inflammatory molecules and metabolites to enter systemic circulation and the brain, potentially contributing to AD hallmarks. Additionally, we examine other pathophysiological mechanisms by which GM may influence AD risk, including the production of short-chain fatty acids, secondary bile acids, and tryptophan metabolites. The role of the vagus nerve in gut-brain communication is also addressed. We highlight potential therapeutic implications of targeting GM in AD, focusing on antibiotics, probiotics, prebiotics, postbiotics, phytochemicals, and fecal microbiota transplantation. While preclinical studies showed promise, clinical evidence remains limited and inconsistent. We critically assess clinical trials, emphasizing challenges in translating GM-based therapies to AD patients. The reviewed evidence underscores the need for further research to elucidate precise molecular mechanisms linking GM to AD and determine whether GM dysbiosis is a contributing factor or consequence of AD pathology. Future studies should focus on large-scale clinical trials to validate GM-based interventions' efficacy and safety in AD.

Clinical decision points for two plasma p-tau217 laboratory developed tests in neuropathology confirmed samples.

We evaluated the diagnostic performance of two commercial plasma p-tau217 immunoassays compared to cerebrospinal fluid (CSF) testing and neuropathology. One hundred and seventy plasma samples from the University of British Columbia Hospital Clinic for Alzheimer's (AD) and Related Disorders were analyzed for p-tau217 using Fujirebio and ALZpath assays. Decision points were determined using CSF testing and autopsy findings as the standard. Fujirebio and ALZpath p-tau217 had similar overall analytical and clinical performance, with distinct decision points for each assay. Based on autopsy findings, both p-tau217 assays identified individuals with AD from other neurodegenerative diseases (ALZpath area under the curve [AUC]=0.94, Fujirebio AUC=0.90). The ALZpath assay detected AD pathology at milder disease stages compared to the Fujirebio assay. Our study reinforces the clinical utility of plasma p-tau217 as an AD biomarker. Differences in test performance and clinical decision points suggest an assay-specific diagnostic approach is required for plasma p-tau217 in clinical practice. Two commercially available p-tau217 immunoassays (ALZpath and Fujirebio) showed equal performance based on CSF testing.ALZpath p-tau217 showed higher performance compared to Fujirebio p-tau217 based on AD diagnosis by neuropathology confirmation.Specific plasma p-tau217 assays may require distinct decision points for AD screening, diagnosis, and disease progression monitoring.

Sex-specific transcriptomic profiling reveals key players in bone loss associated with Alzheimer's disease.

Alzheimer's disease (AD), a progressive neurodegenerative disorder, is frequently associated with musculoskeletal complications, including sarcopenia and osteoporosis, which substantially impair patient quality of life. Despite these clinical observations, the molecular mechanisms linking AD to bone loss remain insufficiently explored. In this study, we examined the femoral bone microarchitecture and transcriptomic profiles of APP/PS1 transgenic mouse models of AD to elucidate the disease's impact on bone pathology and identify potential gene candidates associated with bone deterioration. We performed micro-computed tomography (microCT) and RNA transcriptome analysis on the femoral bone of these mice. We observed a significant reduction in bone microstructure in both male and female APP/PS1 mice compared to their wild-type counterparts. Transcriptomic analysis of femoral bone tissue revealed substantial differential gene expression between AD mice and controls. Specifically, APP/PS1 mice exhibited differential expression in 289 protein-coding genes across both sexes. Notably, in female APP/PS1 mice, 664 genes were differentially expressed, with key genes such as Shh, Efemp1, Arg1, EphA2, Irx1, and PORCN potentially implicated in bone loss. In male APP/PS1 mice, 787 genes were differentially expressed, with Sel1l, Ffar4, Hspa1a, AMH, WFS1, and CLIC1 emerging as notable candidates in the context of bone deterioration. Gene Ontology (GO) enrichment analysis further revealed distinct sex-specific gene pathways between male and female APP/PS1 mice, underscoring the differential molecular underpinnings of bone pathology in AD. This study identifies novel sex-specific genes in the APP/PS1 mouse model and proposes potential therapeutic targets to mitigate bone loss in AD patients.

Research Progress in the Molecular Mechanism of NLRP3 Inflammasome in Alzheimer's Disease and Regulation by Natural Plant Products.

Alzheimer's disease (AD) is a prominent neurodegenerative disorder affecting the central nervous system in the elderly. Current understanding of AD primarily centers on the gradual decline in cognitive and memory functions, believed to be influenced by factors including mitochondrial dysfunction, β-amyloid aggregation, and neuroinflammation. Emerging research indicates that neuroinflammation plays a significant role in the development of AD, with the inflammasome potentially mediating inflammatory responses that contribute to neurodegeneration. Recent studies in AD pathology have identified a novel form of inflammasome referred to as NOD-like receptor pyrin domain-containing 3 (NLRP3) inflammasome. Pathological alterations closely associated with NLRP3 inflammasome activation have been observed in the brain tissues of AD patients, transgenic mice, and in vitro neurocyte models. Numerous studies have demonstrated the potent neuroprotective properties of natural plant products (NPPs) against NLRP3 inflammasome-mediated AD pathology. This review provides a comprehensive examination of the NLRP3 inflammasome, its involvement in AD pathology, and the mechanisms underlying the therapeutic effects of NPP targeting the NLRP3 inflammasome.

Inhibition of amyloid-beta aggregation by phenyl butyric acid analogs and bile acids: a comprehensive in silico study.

Alzheimer's disease (AD) is a degenerative neurological disorder defined by the formation of β-amyloid (Aβ) plaques and neurofibrillary tangles within the brain. Current pharmacological treatments for AD only provide symptomatic relief, and there is a lack of definitive disease-modifying therapies. Chemical chaperones, such as 4-Phenylbutyric acid (4PBA) and Tauroursodeoxycholic acid, have shown neuroprotective effects in animal and cell culture models. However, their therapeutic application is limited due to low bioavailability and poor ability to cross the blood-brain barrier. The study aims to design and identify novel derivatives of 4PBA analogs & bile acids using computational molecular docking, ADME/pharmacokinetic predictions, and molecular dynamic (MD) simulations to develop potential anti-aggregation compounds targeting Aβ, a key player in AD pathology. A comprehensive library of 25,802 derivatives was created using 3PPA, 3MPP, 5PVA, IPA, and bile acid scaffolds, which were examined for their pharmacokinetic characteristics and binding affinities with the Aβ protein. Molecular docking and ADME predictions revealed IPA-1 and DCA-1 as leading candidates due to their robust binding interactions with the Aβ protein, along with minimal toxicity, high solubility, and good absorption profiles. Further, MD analysis over an extended period at 100ns confirmed the better stability of IPA-1 and DCA-1 during interaction with the protein. These findings highlight promising drug candidates, necessitating further validation through cell and animal studies.

Age-related p53 SUMOylation accelerates senescence and tau pathology in Alzheimer's disease.

Aging is a major risk factor for Alzheimer's disease (AD). With the prevalence of AD increased, a mechanistic linkage between aging and the pathogenesis of AD needs to be further addressed. Here, we report that a small ubiquitin-related modifier (SUMO) modification of p53 is implicated in the process which remarkably increased in AD patient's brain. Mechanistically, SUMOylation of p53 at K386 residue causes the dissociation of SET/p53 complex, thus releasing SET into the cytoplasm, SET further interacts with cytoplasmic PP2A and inhibits its activity, resulting in tau hyperphosphorylation in neurons. In addition, SUMOylation of p53 promotes the p53 Ser15 phosphorylation that mediates neuronal senescence. Notably, p53 SUMOylation contributes to synaptic damage and cognitive defects in AD model mice. We also demonstrate that the SUMOylation inhibiter, Ginkgolic acid, recovering several senescent phenotypes drove by p53 SUMOylation in primary neurons. These findings suggest a previously undiscovered etiopathogenic relationship between aging and AD that is linked to p53 SUMOylation and the potential of SUMOylated p53-based therapeutics for neurodegeneration such as Alzheimer's disease.

Association Between Metabolomics Findings and Brain Hypometabolism in Mild Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative condition with rising prevalence due to the aging global population. Existing methods for diagnosing AD are struggling to detect the condition in its earliest and most treatable stages. One early indicator of AD is a substantial decrease in the brain's glucose metabolism. Metabolomics can detect metabolic disturbances in biofluids, which may be advantageous for early detection of some ADrelated changes. The study aims to predict brain hypometabolism in Alzheimer's disease using metabolomics findings and develop a predictive model based on metabolomic data. The data used in this study were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project. We conducted a longitudinal cohort study with three assessment time points to investigate the predictive ability of baseline metabolomic data for modeling longitudinal fluorodeoxyglucose-positron emission tomography (FDG-PET) trajectory changes in AD patients. A total number of 44 participants with AD were included. The cognitive abilities of participants were evaluated using the Alzheimer's Disease Assessment Scale (ADAS) and the Mini-Mental State Examination (MMSE), while the overall severity of dementia was measured by the Clinical Dementia Rating-Sum of Boxes (CDR-SB). We employed the ADNI's FDG MetaROIs (Meta Regions of Interest) dataset to identify AD-associated hypometabolism in the brain. These MetaROIs were selected based on areas frequently mentioned in FDG-PET studies of AD and MCI subjects. Across models, we observed consistent positive relationships between specific cholesterol esters - CE (20:3) (p = 0.005) and CE (18:3) (p = 0.0039) - and FDG-PET metrics, indicating these baseline metabolites may be valuable indicators of future PET score changes. Selected triglycerides like DG-O (16:0-20:4) also showed time-specific positive associations (p = 0.017). This research provides new insights into the disruptions in the metabolic network linked to AD pathology. These findings could pave the way for identifying novel biomarkers and potential treatment targets for AD.

Cognitive variation reflects amyloid, tau, and neurodegenerative biomarkers in Alzheimer's disease.

In Alzheimer's disease (AD), the accumulation of neuropathological markers such as amyloid-β plaques, neurofibrillary tangles, and cortical neurodegeneration occurs over many years before overt manifestation of cognitive impairment. There is thus a need for neuropsychological markers that are indicative of pathological changes in the early stages of the disease. Intra-individual cognitive variability (IICV), defined as the variation of an individual's performance across cognitive domains, is a promising neuropsychological marker measuring heterogeneous changes in cognition that may reflect these early pathological changes. In this study, we comprehensively evaluated the global and regional associations of IICV with positron emission tomography (PET) and magnetic resonance imaging (MRI) measures of AD biomarkers in cognitively normal (CN) and mild cognitive impairment (MCI) participants. We found that higher IICV was robustly associated with increased Aβ, increased tau, decreased brain glucose metabolism, and reduced cortical thickness. Higher IICV was also associated with tau (OR = 2.53, P < .001) and fluorodeoxyglucose (OR = 1.34, P < .001) positivity but not Aβ positivity (OR = 1.15, P = .107). In regional analyses, IICV showed widespread associations with AD biomarkers, with the strongest Aβ and tau effects in the frontal and temporal regions, respectively. The strongest regional cortical thickness effects were found in the entorhinal and parahippocampal cortices. Our findings suggest that IICV may be a useful neuropsychological marker for increased Aβ, and especially increased tau and neurodegeneration that are reflective of emerging AD pathology in individuals without dementia.

Association of Alzheimer’s and Lewy body disease pathology with basal forebrain volume and cognitive impairment

BackgroundDegeneration of the basal forebrain cholinergic system is a hallmark feature shared by Alzheimer’s disease (AD) and Lewy body disease (LBD) whereas hippocampus atrophy is more specifically related to AD. We aimed to investigate the relationship between basal forebrain and hippocampus atrophy, cognitive decline, and neuropathology in a large autopsy sample.MethodsData were obtained from the National Alzheimer’s Coordinating Center (NACC). Basal forebrain and hippocampus volumes were extracted using an established automated MRI volumetry approach. Associations of regional volumes with pathological markers (Braak stage, CERAD score, and McKeith criteria for LB pathology) and cognitive performance were assessed using Bayesian statistical methods.ResultsWe included people with autopsy-confirmed pure AD (N = 248), pure LBD (N = 22), and mixed AD/LBD (N = 185). Posterior basal forebrain atrophy was most severe in mixed AD/LB pathology compared to pure AD (Bayes factor against the null hypothesis BF10 = 16.2) or pure LBD (BF10 = 4.5). In contrast, hippocampal atrophy was primarily associated with AD pathology, independent of LB pathology (pure AD vs. pure LBD: BF10 = 166, pure AD vs. mixed AD/LBD: BF10 = 0.11, pure LBD vs. mixed AD/LBD: BF10 = 350). Cognitive performance was more impaired in AD pathology groups, with Braak stage being the strongest predictor. Hippocampal volume partially mediated this relationship between tau pathology and cognitive impairment, while basal forebrain volume had a limited role in mediating the relationship between pathological burden and cognitive outcomes.ConclusionIn a heterogeneous autopsy sample, AD and LB pathology both contribute to cholinergic basal forebrain degeneration whereas hippocampus atrophy is more specifically related to AD pathology. Cognitive deficits are primarily associated with tau pathology which is partly mediated by hippocampus, but not basal forebrain atrophy.

An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.

Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD. We define a syndrome as a unique biomarker progression pattern and develop a lag measure to cluster pre-dementia individuals, reflecting their pathology's multi-dimensionality. The technique uses the time-ordering of events to group individuals based on their position along the disease process and the relative positions of their markers. An application using Alzheimer's Disease Neuroimaging Initiative (ADNI) data highlights the need for our novel approach to clustering individuals into syndrome groups. Accurately characterizing biomarker curves associated with brain damage requires an initial step that groups individuals on a syndrome basis, accounting for the heterogeneity of underlying pathologies in clinical AD. Developed a novel distance measure and clustering approach for AD biomarker trajectories. Identified distinct subgroups with different biomarker progression patterns in ADNI data. Findings challenge the traditional amyloid cascade hypothesis and suggest AD heterogeneity. Clustering approach accounts for shifts in time and emphasizes progression patterns. Results have implications for AD diagnosis, targeted interventions, and clinical trials.

Nutrition: A non-negligible factor in the pathogenesis and treatment of Alzheimer's disease.

Alzheimer's disease (AD) is a degenerative disease characterized by progressive cognitive dysfunction. The strong link between nutrition and the occurrence and progression of AD pathology has been well documented. Poor nutritional status accelerates AD progress by potentially aggravating amyloid beta (Aβ) and tau deposition, exacerbating oxidative stress response, modulating the microbiota-gut-brain axis, and disrupting blood-brain barrier function. The advanced stage of AD tends to lead to malnutrition due to cognitive impairments, sensory dysfunctions, brain atrophy, and behavioral and psychological symptoms of dementia (BPSD). This, in turn, produces a vicious cycle between malnutrition and AD. This review discusses how nutritional factors and AD deteriorate each other from the early stage of AD to the terminal stages of AD, focusing on the potential of different levels of nutritional factors, ranging from micronutrients to diet patterns. This review provides novel insights into reducing the risk of AD, delaying its progression, and improving prognosis. HIGHLIGHTS: Two-fifths of Alzheimer's disease (AD) cases worldwide have been attributed to potentially modifiable risk factors. Up to ≈26% of community-dwelling patients with AD are malnourished, compared to 7%∼76% of institutionalized patients. Undernutrition effects the onset, progression, and prognosis of AD through multiple mechanisms. Various levels of nutritional supports were confirmed to be protective factors for AD via specific mechanisms.

Network Diffusion-Constrained Variational Generative Models for Investigating the Molecular Dynamics of Brain Connectomes Under Neurodegeneration

Alzheimer’s disease (AD) is a complex and progressive neurodegenerative condition with significant societal impact. Understanding the temporal dynamics of its pathology is essential for advancing therapeutic interventions. Empirical and anatomical evidence indicates that network decoupling occurs as a result of gray matter atrophy. However, the scarcity of longitudinal clinical data presents challenges for computer-based simulations. To address this, a first-principles-based, physics-constrained Bayesian framework is proposed to model time-dependent connectome dynamics during neurodegeneration. This temporal diffusion network framework segments pathological progression into discrete time windows and optimizes connectome distributions for biomarker Bayesian regression, conceptualized as a learning problem. The framework employs a variational autoencoder-like architecture with computational enhancements to stabilize and improve training efficiency. Experimental evaluations demonstrate that the proposed temporal meta-models outperform traditional static diffusion models. The models were evaluated using both synthetic and real-world MRI and PET clinical datasets that measure amyloid beta, tau, and glucose metabolism. The framework successfully distinguishes normative aging from AD pathology. Findings provide novel support for the “decoupling” hypothesis and reveal eigenvalue-based evidence of pathological destabilization in AD. Future optimization of the model, integrated with real-world clinical data, is expected to improve applications in personalized medicine for AD and other neurodegenerative diseases.

Targeting SPI1 to mitigate amyloid-β pathology in Alzheimer's disease.

SPI1, a transcription factor implicated in myeloid cell development, has emerged as a genetic risk factor for Alzheimer's disease (AD). Recent in vivo studies reveal that Spi1 knockdown in mice exacerbates AD pathology by increasing amyloid-β aggregation and gliosis while Spi1 overexpression ameliorates these features. Transcriptomic analyses suggest that Spi1 regulates microglial immune response, complement activation, and phagocytosis. SPI1 regulation of these processes may explain how SPI1 affects AD risk. Further studies, including human validation, are needed to explore the dynamic influence of SPI1 across AD stages, its applicability to clinical settings, and its potential as a therapeutic target.

Unlocking the Therapeutic Potential of Natural Products for Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by memory loss and cognitive decline. With current treatments offering limited effectiveness, researchers are turning to natural products that can target various aspects of AD pathology. Clinically approved natural products, such as galantamine and huperzine A, have shown success in AD treatments. Furthermore, compounds such as epigallocatechin gallate, quercetin, and resveratrol are in clinical trials. This Perspective examines nearly 100 natural compounds with promising neuroprotective effects in preclinical and clinical studies. These compounds exhibit diverse pharmacological actions that help to prevent neurodegeneration while improving cognitive functions. Their unique structures further enhance their biological activities, making them promising candidates for drug discovery. This Perspective stresses the importance of further clinical research to maximize the medical benefits of these compounds and highlights their potential as innovative remedies for AD. Continued exploration of these compounds is crucial to fully leverage their capabilities in combating AD.