Alzheimer's Disease Research Articles

Aerobic exercise regulates gut microbiota profiles and metabolite in the early stage of Alzheimer's disease.

Aerobic exercise (AE) has been shown to offer significant benefits for Alzheimer's disease (AD), potentially influencing the gut microbiota. However, the impact of changes in intestinal flora in early Alzheimer's disease induced by aerobic exercise on metabolic pathways and metabolites is not well understood. In this study, 3-month-old APP/PS1 and C57BL/6 mice were divided into two groups each: a control group (ADC for APP/PS1 and WTC for C57BL/6) and an aerobic exercise group (ADE for APP/PS1 and WTE for C57BL/6). The exercise groups underwent a 20-week aerobic training program on a motorized treadmill before the behavioral test (both the Morris water maze experiment (MWM) and the eight-arm maze test). Fecal samples were collected to analyze gut microbiota profiles via 16S rRNA gene sequencing. At the same time, the metabolic pathway analysis and the detection of metabolites were carried out. At the phylum level, the ADE group exhibited a significant reduced in the relative abundance of Bacteroidetes compared to the ADC group. At the genus level, both Ileibacterium and Faecalibaculum were found to be more abundant in the ADE group than in the ADC group. Additionally, PICRUSt analysis revealed that lipid metabolism and bile acid metabolism pathways were significantly enriched in the cecal microbiota of mice in the ADE group. The metabolites detected further confirmed the changes in the metabolic pathways mentioned above. Aerobic exercise may modify gut microbiota profiles and metabolites in APP/PS1 mice, thereby potentially playing a beneficial role in delaying cognitive impairment associated with early-stage Alzheimer's disease.

Use of biomarkers in the early detection of Alzheimer’s disease

In 1906, Alois Alzheimer described the disease bearing his name, a progressive neurodegenerative pathology with high prevalence. This condition is characterized by progressive cognitive impairment, particularly memory loss, resulting from the degeneration and death of neurons in cortical and subcortical regions. Late diagnosis remains one of the main factors negatively impacting the prognosis of patients with Alzheimer’s disease (AD). Evidence from studies using positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis indicates that neuropathological changes associated with AD begin up to 20 years before the onset of clinical symptoms. This study aims to present the growing role of biomarkers in the early detection of Alzheimer’s disease, emphasizing their importance in identifying early pathological changes before the appearance of clinical symptoms. This review seeks to investigate the use of biomarkers in the early detection of Alzheimer’s disease, focusing on articles from the last five years, both national and international. The methodology will be conducted systematically and structurally. The development of biomarkers for Alzheimer’s disease has advanced considerably, providing essential tools for the prevention, diagnosis, and monitoring of disease progression. Among the most studied biomarkers are Beta-Amyloid and phosphorylated Tau protein, which serve as biological indicators of the underlying pathological processes of the disease. These biomarkers can be measured objectively; however, obtaining this information often requires invasive methods, such as the collection of cerebrospinal fluid (CSF) to quantify protein levels. Phosphorylated Tau protein (p-tau), for instance, has proven particularly useful when combined with other biomarkers, offering a more accurate evaluation of the pathology. The integration of protein, genetic, and lipid biomarkers, together with new measurement platforms, will likely be essential in transforming the clinical approach to AD, providing a more comprehensive understanding of the disease from its early stages to its more advanced phases.

Immune cells: Mediators in the metabolites and Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that predominantly affects elderly individuals across the globe. While genetic, environmental, and lifestyle factors are known to influence the onset of AD, the underlying mechanisms remain unclear. To elucidate the intricate interplay between metabolites and immune cell activation in the ethology of AD, and to determine their collective impact on AD risk. We conducted a comprehensive analysis of genome-wide association studies data to examine the relationships between metabolites, immune cell phenotypes, and the risk of AD. Our study encompassed a comprehensive examination involving 731 distinct immune cell types, 1400 metabolites, and a large cohort comprising10,520 AD cases with 401,661 controls. We employed univariate Mendelian randomization to assess bidirectional relationships between metabolites and AD, metabolites and immune cells, as well as immune cells and AD. Subsequently, multivariate Mendelian randomization was then applied to evaluate the potential mediating role of immune cells on the relationship between metabolites and AD. Specific metabolites, the histidine/pyruvate ratio and homoarginine, were positively associated with the risk of AD, mediated by immune cells. Conversely, 4-hydroxycoumarin and glycolithocholate sulfate showed protective associations against AD. Immune cell markers, CD64 on monocytes and HLA DR on CD14+ CD16- monocytes were linked to higher AD risk, while CD33dim HLA DR+ CD11b- myeloid cells and HLA DR on CD8+ T cells were protective. This study highlights the critical role of immune cells in the pathogenesis of AD, demonstrating how their interaction with specific metabolites influences disease risk.

Sleep spindles and slow oscillations predict cognition and biomarkers of neurodegeneration in mild to moderate Alzheimer's disease.

Changes in sleep physiology can predate cognitive symptoms by decades in persons with Alzheimer's disease (AD), but it remains unclear which sleep characteristics predict cognitive and neurodegenerative changes after AD onset. Using data from a prospective cohort of mild to moderate AD (n=60), we analyzed non-rapid eye movement sleep spindles and slow oscillations (SOs) at baseline and their associations with baseline amyloid beta (Aβ) and tau and with cognition from baseline to 3-year follow-up. Higher spindle and SO activity predicted significant changes in Aβ and tau at baseline, lower Alzheimer's Disease Assessment Scale Cognitive Subscale (better cognitive performance) score, and higher Mini-Mental State Examination score from baseline to 36 months. Spindles and SOs mediated the effect of phosphorylated tau 181 (pTau181)/Aβ42 on cognition, while pTau181/aβ42 moderated the effect of spindles and SOs on cognition. Our findings demonstrate that spindle and SO activity during sleep constitute predictive and non-invasive biomarkers of neurodegeneration and cognition in AD patients. Sleep spindles predict long-term cognitive performance in AD. Sleep spindle and SOs can be predictive, non-invasive biomarkers for AD. Sleep may be one of the most important modifiable risk factors for AD progression. Sleep microarchitecture is a novel therapeutic target for preserving brain heath. Sleep physiology can provide novel therapeutic targets to slow AD progression.

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.

MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention.

Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing methods often encounter several common issues: first, the data representations lack sufficient information; second, the extracted features are not comprehensive; and third, most methods lack interpretability when modeling drug-target binding. To overcome the above-mentioned problems, we propose an interpretable deep learning model called MutualDTA for predicting DTA. MutualDTA leverages the power of pretrained models to obtain accurate representations of drugs and targets. It also employs well-designed modules to extract hidden features from these representations. Furthermore, the interpretability of MutualDTA is realized by the Mutual-Attention module, which (i) establishes relationships between drugs and proteins from the perspective of intermolecular interactions between drug atoms and protein amino acid residues and (ii) allows MutualDTA to capture the binding sites based on attention scores. The test results on two benchmark data sets show that MutualDTA achieves the best performance compared to the 12 state-of-the-art models. Attention visualization experiments show that MutualDTA can capture partial interaction sites, which not only helps drug developers reduce the search space for binding sites, but also demonstrates the interpretability of MutualDTA. Finally, the trained MutualDTA is applied to screen high-affinity drug screens targeting Alzheimer's disease (AD)-related proteins, and the screened drugs are partially present in the anti-AD drug library. These results demonstrate the reliability of MutualDTA in drug development.

2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione protects against MPP+-induced neurotoxicity by ameliorating oxidative stress, apoptosis and autophagy in SH-SY5Y cells.

2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione (DMDD) is a cyclohexanedione compound extracted from the roots of Averrhoa carambola L. Several studies have documented its beneficial effects on diabetes, Alzheimer's disease, and cancer. However, its potential neuroprotective effects on Parkinson's disease (PD) have not yet been explored. The present study aimed to investigate the protective effects and underlying mechanisms of DMDD in a cellular model of PD. In this study, SH-SY5Y cells were incubated with or without DMDD following intoxication with the parkinsonian neurotoxin 1-methyl-4-phenylpyridine (MPP+). Cell viability and apoptosis were evaluated using 3-(4,5-Dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay and Hoechst 33,342 staining, respectively. The mitochondrial membrane potential (Δψm) was assessed through the JC-10 assay. The activities of superoxide dismutase (SOD) and the levels of reactive oxygen species (ROS) were measured using WST-8 and DCFH-DA assays. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore significant biological processes and pathways influenced by DMDD. Molecular docking was employed to predict the domains of potential protein targets interacting with DMDD. Western blotting was subsequently conducted to determine the protein expression levels of TH, Nrf2, Bax, Bcl-2, Caspase-3, Beclin-1, PARP, LC3-II, LC3-I, p-PI3K, PI3K, p-mTOR and mTOR. Our study showed that DMDD treatment significantly increased cell viability and reduced apoptosis in MPP+-treated SH-SY5Y cells. In addition, DMDD treatment reversed the loss of TH expression and Δψm in MPP+-exposed SH-SY5Y cells. Moreover, DMDD treatment reduced MPP+-induced ROS production by promoting SOD activity. Additionally, compared with those in the MPP+ group, the protein expression levels of Beclin-1, Caspase-3, and PARP and the LC3II/I ratio were significantly decreased, whereas the protein expression levels of Nrf2 and the Bcl-2/Bax, p-PI3K/PI3K, and p-mTOR/mTOR ratios were significantly increased in the DMDD-treated group. In conclusion, DMDD protects against MPP+-induced cytotoxicity by mitigating oxidative stress, apoptosis, and autophagy. PI3K/mTOR signaling at least partly mediates the cytoprotective effect of DMDD.

Caregivers' Perspectives on Discussions of Medical Treatment Preferences for People Living with Dementia Are Associated with Their Dementia Health Literacy and the Caregiving Relationship.

People living with dementia experience progressive functional decline and increased dependence on caregivers. This study examined the influence of caregivers' dementia health literacy on perceptions of medical care preferences and advanced care planning (ACP) in people living with dementia. This analysis used data from a cross-sectional survey, "Care Planning for Individuals with Dementia", administered nationwide by Alzheimer's Disease Centers. We conducted binary, ordinal, and multinomial logistic regression. On average, surveyed caregivers (n=431) were 78.3 years, had 16 years of education, and were mainly white (88.5%). Most lived with (76.8%) and were the designated healthcare proxy (95.1%), with high dementia knowledge scores (mean=8.4/10). As caregivers' dementia knowledge scores increased, they were 1.27 times more likely (p=0.02) to endorse comfort care. Caregivers with greater knowledge about severe dementia were less likely to need further treatment preference-related discussions (knowing a lot: OR=0.17, p<0.001; knowing some things: OR=0.37, p=0.006). Caregivers live apart from patients were 2.71 times more likely to know about such discussions (p<0.001). Caregivers of people in earlier stages endorsed greater needs for further conversations with clinicians (no impairment & MCI: OR=7.38, p=0.002; mild impairment: OR=5.32, p=0.005) and their care recipients (no impairment & MCI: OR=5.24, p=0.02). These findings highlight the role of dementia-specific education in ACP discussions among people living with dementia, caregivers, and healthcare clinicians. These findings are important since evidence suggests that ACP may promote quality of life, reduce iatrogenic harm, minimize healthcare overutilization, and alleviate care-related burdens.

Adverse Childhood Experiences and Subjective Cognitive Decline Among Transgender Adults.

Adverse childhood experiences (ACEs) are associated with an increased risk of developing chronic health conditions, including Alzheimer's disease and related dementias (ADRD) and subjective cognitive decline (SCD), self-reported confusion/memory loss, and an early clinical manifestation of ADRD. While ACEs and SCD have both been individually studied in transgender and nonbinary (TGN) adults, no study has examined the relationship between the two among this population. This study sought to establish the prevalence of ACEs and their association with SCD among TGN adults. Cross-sectional, secondary analysis of publicly available data. 2019-2021 Behavioral Risk Factor Surveillance System data, representing 16 US states that assessed ACEs, SCD, and self-reported gender identity were used to determine the association between ACEs and SCD among TGN adults aged 45+ (N = 206). Pearson's chi-squared/Fisher's exact tests assessed the association between ACEs (individual, categorical, sum score) and SCD. Crude and adjusted odds ratios (aORs) along with 95% confidence intervals (CIs) were calculated to investigate the associations between ACEs and SCD. 18% (n = 38) of TGN adults in the sample endorsed SCD, 60% (n = 120) experienced any ACE, 20% (n = 41) 1 ACE, and 18% (n = 37) experienced > 4 ACEs. Nearly 50% experienced childhood abuse (n = 94) or household dysfunction (n = 92). Among those with SCD, 34% (n = 13) reported > 4 ACEs, and 73% (n = 26) reported childhood abuse or household dysfunction (n = 27). Most ACES were associated with and increased the risk of SCD, even after adjusting for BRFSS year, age, race, education, and employment. The odds of SCD increased 40% as the number of ACEs increased (aOR = 1.4, 95% CI: 1.2-1.6, p < 0.0001). The odds of SCD were higher with childhood abuse (aOR = 4.3, 95% CI: 1.88-10.02, p < 0.01) or household dysfunction (aOR = 4.7, 95% CI: 2.00-11.07, p < 0.01). ACEs increase the risk of SCD among TGN adults. Gender-affirming and trauma-informed nursing care are important, and screening and interventions for ACEs and SCD are needed to help reduce the risk of SCD and ADRD. Examining how adverse childhood experiences impact different aspects of health, including brain health, is important to nursing practice as it can provide clinical care strategies and identify interventions to specifically address ways to improve the health and well-being of transgender and nonbinary people.

Tinosinenside A inhibits neuroinflammation and protects HT22 cells by suppressing the TLR4/NF-κB/NLRP3 signaling pathway in BV2 cells.

Microglia-mediated neuroinflammation plays a crucial role in Alzheimer's disease (AD). Tinosinenside A (Tis A) is a novel sesquiterpene glycoside isolated from the dried rattan stem of Tinospora sinensis (Lour.) Merr. Tis A exhibited anti-inflammatory and neuroprotective activities in vitro. However, the mechanism underlying the inhibition of neuroinflammation and protection of nerve cells remains obscure. This study used lipopolysaccharide (LPS)-induced inflammatory response in BV2 cells to simulate a neuroinflammatory model and used Aβ1-42-induced HT22 cells to establish an AD cell model, aiming to investigate the efficacy and mechanism of Tis A through anti-neuroinflammation to protect nerve cells. Tis A had no effect on the proliferation of BV2 and HT22 cells at the tested concentrations. The time- and dose-dependent effects of Tis A on the LPS-induced inflammatory response of BV2 cells demonstrated that the best anti-inflammatory efficacy appeared after 12h of pretreatment. Tis A inhibited the gene levels of TNF-α, IL-6, IL-1β, iNOS, and IL-10 while enhancing the gene levels of IL-4 and TGF-β. Additionally, Tis A reduced the gene expression levels of CD16 and CD32 and increased the CD36 and CD206 gene expression levels. It also downregulated the protein expression of Iba-1 and iNOS while upregulating CD206. Tis A obviously inhibited NLRP3 gene and protein expression in LPS-stimulated BV2 cells. The inhibitory effect of Tis A on NLRP3 was counteracted by the NLRP3 activator nigericin and overexpression plasmid GV358. Tis A inhibits NLRP3 protein expression to reduce the assembly of NLRP3/ASC/Caspase-1 inflammasome, then regulates the TLR4/NF-κB/NLRP3 signaling pathway. It regulates microglia activation and M1/M2 phenotypic polarization, then inhibits the production of inflammatory factors, and reduces the apoptosis rate of HT22 cells under inflammatory conditions, improving the survival rate of nerve cells to protect neurons.

Polygenic burden of short tandem repeat expansions promotes risk for Alzheimer’s disease

Studies of the genetics of Alzheimer’s disease (AD) have largely focused on single nucleotide variants and short insertions/deletions. However, most of the disease heritability has yet to be uncovered, suggesting that there is substantial genetic risk conferred by other forms of genetic variation. There are over one million short tandem repeats (STRs) in the genome, and their link to AD risk has not been assessed. As pathogenic expansions of STR cause over 30 neurologic diseases, it is important to ascertain whether STRs may also be implicated in AD risk. Here, we genotype 312,731 polymorphic STR tracts genome-wide using PCR-free whole genome sequencing data from 2981 individuals (1489 AD case and 1492 control individuals). We implement an approach to identify STR expansions as STRs with tract lengths that are outliers from the population. We then test for differences in aggregate burden of expansions in case versus control individuals. AD patients harbor a 1.19-fold increase of STR expansions compared to healthy elderly controls (p = 8.27×10-3, two-sided Mann-Whitney test). Individuals carrying >30 STR expansions have a 3.69-fold higher odds of having AD and have more severe AD neuropathology. AD STR expansions are highly enriched within active promoters in post-mortem hippocampal brain tissues and particularly within SINE-VNTR-Alu (SVA) retrotransposons. Together, these results demonstrate that expanded STRs within active promoter regions of the genome associate with risk of AD.

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.

Alzheimer’s disease diagnosis by 3D-SEConvNeXt

Alzheimer’s disease (AD) constitutes a fatal neurodegenerative disorder and represents the most prevalent form of dementia among the elderly population. Traditional manual AD classification methods, such as clinical diagnosis, are known to be time-consuming and labor-intensive, with relatively low accuracy. Therefore, our work aims to develop a new deep learning framework to tackle this challenge. Our proposed model integrates ConvNeXt with three-dimensional (3D) convolution and incorporates a 3D Squeeze-and-Excitation (3D-SE) attention mechanism to enhance early classification of AD. The experimental data is sourced from the publicly accessible Alzheimer’s disease Neuroimaging Initiative (ADNI) database, with raw Magnetic Resonance Imaging (MRI) data preprocessed using SPM12 software. Subsequently, the preprocessed data is input into the 3D-SEConvNeXt network to perform four classification tasks: distinguishing between AD and Normal Control (NC), Mild Cognitive Impairment (MCI) and NC, AD and MCI, as well as AD, MCI, and NC. The experimental results indicate that the 3D-SEConvNeXt model consistently outperforms alternative models in terms of accuracy, achieving commendable outcomes in early AD diagnostic tasks.

Highly specific amyloid and tau PET ligands for ATN classification in suspected Alzheimer's disease patients.

This study aims to accurately classify ATN profiles using highly specific amyloid and tau PET ligands and MRI in patients with cognitive impairment and suspected Alzheimer's disease (AD). It also aims to explore the relationship between quantified amyloid and tau deposition and cognitive function. Twenty-seven patients (15 women and 12 men; age range: 64-81years) were included in this study. Amyloid and tau PET scans were performed using 18F-NAV4694 and 18F-MK6240, respectively. For each patient, amyloid and tau PET images were visually assessed and classified as either amyloid-positive or amyloid-negative, and as 18F-MK6240 Braak stage 0 (tau-negative) or Braak stages I-VI (tau-positive). Voxel-based morphometry of three-dimensional T1-weighted MRI was used to evaluate neurodegeneration. Amyloid and tau depositions were quantified using the Centiloid scale and standardized uptake value ratio (SUVR), respectively. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE). Patients were categorized into seven ATN profiles. Six patients (22%) exhibited a normal AD biomarker profile, 15 patients (56%) fell within the Alzheimer's continuum, and 14 patients (52%) were diagnosed with AD. Additionally, six patients (22%) displayed non-AD pathological changes. Positive and negative findings of amyloid and tau PET were concordant in 24 patients (89%). Among the 14 patients diagnosed with AD, the Centiloid scale for amyloid deposition did not show a significant negative correlation with MMSE scores (r = 0.269, p = 0.451). In contrast, the SUVR for tau deposition in the neocortex exhibited a significant negative correlation (r = -0.689, p = 0.014), while tau deposition in the mesial temporal region did not show a significant correlation (r = 0.158, p = 0.763). Highly specific amyloid and tau PET scans, along with MRI, can be utilized to accurately classify ATN profiles in patients with cognitive impairment and suspected AD. The discordance in amyloid and tau PET findings in three patients allowed for a more precise AD diagnosis. Furthermore, tau PET imaging provided insight into the propagation of tau deposition in the neocortex beyond the mesial temporal region, which is associated with cognitive decline.

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.

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.

Extracellular Vesicles: A Promising Therapeutic Approach to Alzheimer's Disease.

Extracellular vesicles (EVs) are nano-sized membranous particles that are secreted by various cell types and play a critical role in intercellular communication. Their unique properties and remarkable ability to deliver bioactive cargo to target cells have made them promising tools in the treatment of various diseases, including Alzheimer's disease (AD). AD is a devastating neurodegenerative disease characterized by progressive cognitive decline and neuropathological hallmarks, such as amyloid-beta plaques and neurofibrillary tangles. Despite extensive research, no disease-modifying therapy for AD is currently available. However, EVs have emerged as a potential therapeutic agent in AD due to their ability to cross the blood-brain barrier, deliver bioactive cargo, and modulate neuroinflammation. This review provides a comprehensive overview of the current knowledge on the role of EVs in AD and discusses their potential as a therapeutic approach. It covers the mechanisms of action, potential therapeutic targets, and challenges and limitations of EV-based therapies for AD.

Di Huang Yi Zhi Fang improves cognitive function in APP/PS1 mice by inducing neuronal mitochondrial autophagy through the PINK1-parkin pathway.

Alzheimer's disease (AD) is an irreversible age-related neurodegenerative condition characterized by the deposition of amyloid-β (Aβ) peptides and neurofibrillary tangles. Di Huang Yi Zhi (DHYZ) formula, a traditional Chinese herbal compound comprising several prescriptions, demonstrates properties that improve cognitive abilities in clinical. Nonetheless, its molecular mechanisms on treating AD through improving neuron cells mitochondria function have not been deeply investigated. This study administered DHYZ to APP/PS1 mice to explore its potential therapeutic mechanisms in AD treatment. APP/PS1 transgenic mice were given DHYZ (L, M, H), donepezil, or distilled water for a consecutive 12-week period. The Morris water maze test was used to assess memory capacity, transmission electron microscopy was used to observe mitochondrial and synaptic structures, immunohistochemistry and western blot detected proteins involved in the mitochondrial autophagy pathway, ELISA measured serum Aβ content, and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling assessed neuronal cell apoptosis. DHYZ demonstrates a notable therapeutic impact on mice with AD, effectively improving cognitive and memory impairments. DHYZ decreases Aβ accumulation in the hippocampus by reducing BACE1 activity and enhancing Aβ clearance through the blood-brain barrier. Additionally, DHYZ significantly suppresses neuronal apoptosis, enhances synaptic structure, and increases synapse numbers, processes strongly linked to the activation of mitochondrial PINK1-Parkin autophagy. DHYZ enhances cognitive function in APP/PS1 mice by stimulating neuronal mitochondrial autophagy through the PINK1-Parkin pathway.

Trafficking of Muscarinic 1 Acetylcholine Receptor Regulated by VPS35 in Alzheimer's Disease.

Muscarinic 1 acetylcholine receptor (M1AChR) is a member of the Gprotein- coupled receptor superfamily, with the dysfunction being linked to the onset of Alzheimer's Disease (AD). Retromer complex with Vacuolar Protein Sorting-35 (VPS35) as the core plays an important role in the transport of biological proteins and has been confirmed to be closely related to the pathogenesis of AD. This study was designed to determine whether VPS35 could affect the trafficking mechanism of M1AChRs. The interaction between VPS35 and M1AChR was studied by co-immunoprecipitation method, and the recycling of M1AChR influence by VPS35 was analyzed using biotinylation technology. It was found that VPS35 affected the localization of M1AChR on the cell membrane by regulating intracellular M1AChR transport, thus controlling the M1AChR-mediated cholinergic signaling pathway. The findings presented here provide a potential pathogenesis and pathway for the treatment of 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.