Search Results (6,627)

Predicting progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) requires models that represent both regional brain abnormalities and their evolution across repeated examinations. We developed a longitudinal graph neural network that integrates structural magnetic resonance imaging, FDG-PET, regional imaging biomarkers, and clinical covariates across irregular follow-up visits. The study included 614 participants with baseline MCI from the Alzheimer’s Disease Neuroimaging Initiative: 218 converters to AD within five years and 396 non-converters, with 2438 eligible longitudinal visits. Each visit was represented as an 82-node brain graph based on the Desikan–Killiany atlas. Node features combined a 128-dimensional multimodal convolutional embedding with four regional biomarkers. Graph-attention layers modelled spatial dependencies, a node-wise gated recurrent unit modelled longitudinal dependencies, and masked temporal self-attention aggregated variable-length visit sequences. Participants were divided at the subject level into development and held-out test sets, and hyperparameters were selected by five-fold cross-validation within the development set. On the held-out test set of 123 participants, the model reached an area under the receiver operating characteristic curve of 0.859 (95% CI 0.795–0.915), balanced accuracy of 0.805 (95% CI 0.736–0.862), sensitivity of 0.781, and specificity of 0.832. The AUC was numerically higher than that of the strongest baseline, a CNN–GRU sequence model, which reached 0.832 (95% CI 0.758–0.894); the paired AUC difference was 0.027 (95% CI 0.009–0.098), the unadjusted DeLong p-value was 0.026, and the Holm-adjusted p-value was 0.052, which was not significant at the conventional 0.05 threshold after correction for multiple comparisons. In ablation experiments, removing temporal modelling reduced the AUC to 0.818, and removing the spatial graph structure reduced it to 0.808, the two largest reductions observed. Integrated-gradient analysis placed the highest importance on hippocampal and entorhinal regions. Combining graph-based spatial modelling with recurrent longitudinal reasoning was associated with higher discrimination than sequence modelling alone, though this difference was not statistically significant after correction for multiple comparisons. Validation was restricted to a single research cohort (ADNI), and no independent external dataset was used; prospective external validation on an independent cohort is required before the model can be considered for clinical use Because FDG-PET was unavailable for 19.3% of visits, we report the headline result separately from a sensitivity analysis restricted to participants with complete FDG-PET at every visit (development set cross-validated AUC 0.891 vs. 0.874 for the full cohort with masked missing FDG-PET); multimodal performance should be read as cohort-dependent rather than as a single unconditional figure. Full article

Introduction: Alzheimer’s disease dementia (AD dementia) is a progressive neurodegenerative disorder associated with cognitive decline. Oxidative stress and inflammation may contribute to its pathophysiology, with clusterin (CLU) and sestrin-2 (SESN2) emerging as potential biomarkers. This study evaluated oxidative stress markers, inflammatory indices, and serum CLU and SESN2 levels in patients with AD dementia. Methods: A total of 48 patients with AD dementia and 39 healthy controls in a broadly comparable age range were enrolled from a neurology outpatient clinic. AD dementia was diagnosed according to internationally accepted clinical criteria. Cognitive function was assessed using Mini-Mental State Examination (MMSE) scores obtained at diagnosis. Serum malondialdehyde (MDA), glutathione (GSH), CLU, and SESN2 were measured, with MDA and GSH analyzed spectrophotometrically and CLU and SESN2 concentrations determined using the enzyme-linked immunosorbent assay (ELISA). Inflammatory indices were calculated from routine hematological and biochemical parameters. Results: A multivariable logistic regression model including age, MDA, and GSH showed excellent discriminatory performance for distinguishing patients with AD dementia from healthy controls. Patients with AD dementia had significantly lower SESN2 levels (p < 0.001) and higher CLU levels (p < 0.001) than controls. No significant associations were observed between inflammatory indices and the investigated clinical or biochemical variables in the AD dementia group (p > 0.05). Conclusions: Oxidative stress and altered SESN2 and CLU levels may be associated with AD dementia, whereas the inflammatory indices showed limited utility. Larger prospective studies are needed to validate these findings and clarify their clinical significance. Full article

Background: Forty-hertz sensory stimulation has emerged as a potential approach for modulating neural activity relevant to Alzheimer’s disease. However, electrophysiological changes following non-flickering 40 Hz light stimulation in older adults remain unclear. This study investigated whether a single-session intervention of non-flickering 40 Hz light stimulation would be associated with increased resting-state 40 Hz oscillations in cognitively normal older adults. Methods: In this uncontrolled single-arm pilot study, 16 cognitively normal older adults underwent a 60 min session of non-flickering 40 Hz light stimulation. Resting-state EEG was recorded immediately before and after stimulation. Relative power within 38–42 Hz was analyzed across six predefined scalp regions and the whole-brain measure using one-tailed Wilcoxon signed-rank tests with Benjamini–Hochberg false discovery rate (FDR) correction. Exploratory real-time EEG recordings during stimulation were available in 10 participants. Results: After FDR correction, resting-state 38–42 Hz relative power was higher post-stimulation in the central (FDR = 0.045, effect size = 0.555) and right temporal (FDR = 0.014, effect size = 0.724) regions. In the absolute-power sensitivity analysis, only the right temporal increase remained significant after FDR correction (FDR = 0.042). Exploratory during-stimulation analysis showed a nominally increased 38–42 Hz signal-to-noise ratio in the right temporal region (p = 0.026). One participant reported very mild fatigue; no other adverse responses were reported. Conclusions: This pilot study suggests regional increases in resting-state 38–42 Hz activity after non-flickering 40 Hz light stimulation, with additional absolute-power support for the right temporal finding. These findings remain preliminary given the uncontrolled design and small sample. Full article

Background: Acetylcholinesterase (AChE) demonstrates non-enzymatic actions attributable to a 14mer bioactive peptide derived from its sixth exon, ‘T14’, a pivotal agent driving Alzheimer’s disease (AD). Methods: To investigate this possible parallel between development and neurodegeneration, we tracked the expression and timeline of T14 in embryonic and neonatal rodent brain tissue in relation to the expression of its parent molecule, AChE, benchmarked against markers of neural maturation (NeuN) and neurodegenerative pathology (pTau) using sedimentation profiling, Western blotting, and qPCR. Results: We report two key findings: Firstly, while overall AChE activity, expression, and oligomeric assembly in the developing rodent cortex predominantly reflect AChE-T, endogenous T14 appear to selectively correspond with the AChE-R variant (r = 0.936, p = 0.0639), peaking at P7 before declining in tandem with NeuN and pTau. Secondly, application of exogenous peptide to cultured SHSY-5Y cells triggers the selective upregulation of this same variant, AChE-R (F_(3,18) = 9.320, p < 0.05). This effect is blocked by cotreatment with either mTORC1 inhibitor rapamycin or NBP14, an antagonist of T14. Conclusions: We conclude that in development, T14 and AChE-R are closely linked, that both are involved in a developmental mechanism most active in the embryonic brain, and that inappropriate reactivation of this mechanism in the mature brain could be the driver in the progression of AD. Full article

Viral infections have been associated with multiple sclerosis (MS), Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS), but the associations may reflect different relationships to the disease process. This review evaluates evidence for viral involvement in disease initiation, modification of established disease, impaired viral control secondary to disease or treatment, and incidental detection. The strongest temporal evidence concerns Epstein–Barr virus (EBV) and MS. Prospective data place EBV seroconversion before clinical onset and the first observed increase in serum neurofilament light chain, while mechanistic studies link EBV infection, B-cell biology, and CNS-directed immunity. However, evidence that ongoing EBV activity modifies established MS remains limited. In AD, experimental studies support interactions between herpesviruses and AD-associated proteins, while the reduced incidence of all-cause dementia after herpes zoster vaccination suggests that viral or immunological pathways may be modifiable, without establishing that a specific herpesvirus initiates AD. Viral associations in PD rely mainly on epidemiological, experimental, and postmortem findings. Human pegivirus detection in a subset of PD brains remains a candidate association requiring independent confirmation and evidence of biological activity. Evidence in ALS is similarly limited. Enterovirus detection has been inconsistent, and altered human endogenous retrovirus K (HERV-K) expression in postmortem tissue does not establish an acquired viral infection. Stronger inference across these diseases will require longitudinal studies relating viral activity and antiviral immunity to subsequent disease-related changes, together with intervention studies that document the intended effect on the implicated viral process and separately assess subsequent disease risk or progression. Full article

Traumatic brain injury (TBI) is a significant public health concern, often resulting in long-term impairments. TBI is also a known risk factor for Alzheimer’s disease (AD), with both conditions sharing features such as inflammasome dysregulation. Inflammasome proteins are carried in extracellular vesicles (EVs) derived from blood plasma and serum. Our previous work showed that TBI in the context of AD acutely increases inflammasome activation and accelerates pathology. However, chronic effects of TBI in AD, particularly regarding sex differences, remain poorly characterized. Here, we used 3xTg-AD mice and wild-type (WT) controls, which underwent moderate controlled cortical impact (CCI) or sham surgery at 5 months of age. Mice were sacrificed at 3 months post-injury for biochemical and histopathological analysis. Cortical and hippocampal lysates were analyzed for inflammasome proteins and inflammatory cytokines via immunoblotting, while pathological markers were assessed using Ella Simple Plex technology and histopathology. In a separate cohort, 3xTg mice received moderate CCI and were sacrificed 7 days post-injury to evaluate sex differences. Cortical lysates were tested for pro-inflammatory cytokines and pathological markers via electrochemiluminescent immunoassay, and EVs were analyzed using mass spectrometry. AD-TBI mice showed increased expression of inflammasome proteins, pro-inflammatory cytokines, and glial fibrillary acidic protein (GFAP). TBI mice displayed elevated neurofilament light in the cortex, with both GFAP and neurofilament light co-localizing with inflammasome proteins in the perilesional cortex. Moreover, AD-TBI mice exhibited reduced cortical and hippocampal volumes compared to WT-TBI mice. In the sex differences cohort, EVs from male and female AD-TBI mice showed distinct patterns in upstream regulators and signaling pathways. Female-derived EVs showed greater activation of AD-related pathways. Sex-specific differences were also observed in cortical pro-inflammatory cytokine expression, although GFAP and amyloid-β levels were not significantly different between sexes. This study demonstrates that AD leads to changes in chronic inflammasome expression and neurodegenerative pathology, with marked sex-dependent differences in inflammatory and signaling responses in AD with TBI. These findings underscore the importance of considering both AD comorbidity and biological sex in the evaluation of TBI outcomes and therapeutic strategies. Full article

Background/Objectives: Alzheimer’s disease is one of the most prevalent forms of dementia and is accompanied by progressive anatomical changes within the brain. However, large-scale analyses that compare global and local anatomical differences across age, sex, diagnosis, and repeated scans remain limited. Methods: We constructed a cohort of 1385 total participants, with 3593 scans, who were diagnosed as cognitively normal or with Alzheimer’s at entry into the study. Global and medial temporal brain volumes from 3T MRI scans were normalized to intracranial volume, and we used a linear mixed-effects model to analyze the association between participants’ age, sex, and diagnosis while also accounting for multiple follow-up scans. Diagnosis-dependent relationships between global and medial temporal structures, brain parenchymal and hippocampal fractions, and body mass index were also calculated. Results: Older age was associated with a decrease in normalized brain volume across each region of interest. In general, AD participants had significantly lower volumes than cognitively normal individuals, with a greater degree of difference in medial temporal regions. Global measures did have different degrees of separation, with gray matter showing greater separation than white matter. Exponential model equations showed that the AD group generally had a greater age-associated percentage decrease across-ROI/ICV association. BMI nor BMI x diagnosis was significantly associated with brain volumes within the model, while the exploratory pooled pTau217 analysis showed it was 4.6 times higher in AD and negatively associated with most morphometric areas. Conclusions: This large, integrated analysis supports the use of MRI morphometry as a valuable tool to directly compare AD-associated differences across global and medial temporal areas and also evaluate diagnosis-dependent relationships across anatomically related structures. Findings indicate that medial temporal measures provide a greater AD vs. CN separation than global measures, with GM being more sensitive than WM. Plasma pTau217 also gives biological context, which helps suggest that MRI results should be interpreted with multiple clinical and biological factors. Full article

Background/Objectives: The accelerating integration of machine learning (ML) with molecular, imaging, and physiological data is transforming Alzheimer’s disease (AD) research. Methods & Results: Recent studies demonstrate that multimodal, AI-assisted platforms can enhance early diagnosis, predict biomarker trajectories, and identify novel therapeutic targets. This mini-review covers the evolving AD diagnostic and biomarker frameworks, current therapeutic strategies including recently approved anti-amyloid immunotherapies, and advances from contemporary studies employing ML across diverse data streams, ranging from cerebrospinal fluid (CSF) and plasma proteomics to Raman spectroscopy, neuroimaging, transcriptomics, and microbiome signatures. Conclusions: Collectively, they illustrate how artificial intelligence (AI) has shifted A biomarker discovery from univariate to network-based inference, achieving clinically relevant accuracy while emphasizing model interpretability. We discuss biological insights, translational implications, and persisting challenges related to validation, bias, and regulatory integration. Full article

Alzheimer’s disease (AD) is an unremitting neurodegenerative disorder characterized by the presence of extracellular β-amyloid (Aβ)-containing neuritic plaques, intracellular tau-positive neurofibrillary tangles and loss of selected neurons in the brain. Evidence suggests that aggregation of Aβ and tau via synergistic interactions initiates a cascade of events, leading to development of AD pathology. Thus, many studies are being pursued to develop small molecules/drugs that can target both Aβ and tau as an effective AD treatment strategy. In this study, we evaluated effects of native PLGA nanoparticles on tau-mediated Aβ1-42 aggregation using biophysical, structural, spectroscopic and biochemical approaches. Our results show that 0N4R tau seeds enhanced Aβ1-42 aggregation, and that this effect is mitigated by native PLGA. Additionally, PLGA inhibited Aβ1-42 aggregation induced by both 0N4R and 2N4R tau isoforms. The presence of PLGA during the formation of tau seeds or pretreatment of tau seeds with PLGA attenuates subsequent Aβ1-42 aggregation. Interestingly, monomeric 0N4R tau, unlike 0N4R tau seeds, suppressed Aβ1-42 aggregation, which is diminished further by PLGA nanoparticles. However, we have not addressed the implications of native PLGA on tau/Aβ1-42 interaction using any cellular or animal models of AD. Nevertheless, our results reveal that tau seeds and monomeric tau can differentially influence Aβ1-42 aggregation, which is mitigated by native PLGA under in vitro conditions, providing a rationale to study it further under an in vivo paradigm to examine its significance in AD pathogenesis. Full article

Alzheimer’s disease (AD) is associated with both mild and moderate to severe traumatic brain injury (TBI). This narrative review gives an account of the association of TBI and AD and highlights possible cellular and molecular pathways linking these pathologies. Following TBI, the immune system of the brain is rapidly activated and gives rise to acute neuroinflammation. While neuroinflammation is protective in nature, it may persist chronically in the case of less-controlled prolonged responses, triggering neuroprotective loss and neurotoxicity. Moreover, reduced clearance of amyloid-beta may occur, along with its overproduction and aggregation. Tau protein regulation is also altered by kinase and phosphatase enzymes, resulting in the accumulation of hyperphosphorylated tau protein in neurons and glial cells and the emergence of intracellular tau neurofibrillary tangles. More to the point, vascular impairment following TBI has been reported to contribute to cognitive decline and AD. Blood–brain barrier breakdown following TBI allows for infiltration of peripheral immune cells and blood-derived proteins into the brain, which exacerbates neuroinflammation, interrupts synaptic signaling, and promotes oxidative stress. The neuroinflammatory response, dynamic alterations in amyloid and tau biology, and vascular impairment are thought to interact within a broader network of processes associated with AD neurodegeneration, rather than acting as isolated mechanisms. Full article

Tauopathies comprise a heterogeneous group of neurological and systemic disorders characterized by pathological tau dysregulation, traditionally including Alzheimer’s disease (AD), traumatic brain injury (TBI), and chronic traumatic encephalopathy (CTE). Emerging evidence suggests that tauopathy may also occur in selected vascular and systemic disease contexts, including ischemic stroke, vascular dementia (VaD), and preeclampsia (PE), although the strength and clinical significance of this evidence vary among these conditions. Compelling evidence suggests that the Pin1-cis phosphorylated tau (cis P-tau) axis may represent a convergent molecular mechanism linking these conditions. Pin1 is a phosphorylation-specific peptidyl-prolyl cis-trans isomerase that protects against tauopathy and cognitive impairment by catalyzing conversion of pathological cis P-tau to the physiological trans conformation at phosphorylated Thr231-Pro motifs. Under stress conditions such as oxidative stress, hypoxia, inflammation, mechanical injury, or aging, Pin1 activity becomes impaired through oxidation, phosphorylation, sequestration, or transcriptional downregulation, resulting in the accumulation of neurotoxic cis P-tau. cis P-tau is proposed to initiate a pathogenic cascade termed cistauosis in neurons, characterized by axonal microtubule collapse and transport failure, mitochondrial dysfunction, synaptic degeneration, neuroinflammation, neuronal death, and prion-like spread. Importantly, cis P-tau appears rapidly after insults long before overt neurofibrillary tangle (NFT) formation in several experimental and clinical contexts, supporting its role as an upstream pathogenic driver and early biomarker. Crucially, conformation-specific monoclonal antibodies targeting cis P-tau selectively eliminate pathological cis P-tau while sparing physiological trans P-tau, demonstrating promising therapeutic effects in preclinical models of TBI, vascular injury, AD-related tauopathy, and PE. This review summarizes the molecular basis of the Pin1–cis P-tau axis, examines its role across conventional and unconventional tauopathies, evaluates its biomarker potential, and highlights cis-specific immunotherapy as a potentially broad therapeutic strategy for neurodegenerative, traumatic, and vascular cognitive disorders. Full article

Brain aging is accompanied by changes in RNA homeostasis, intercellular communication, and stress responses that increase vulnerability to neurodegenerative diseases. The neuronal protein HuD (ELAVL4) and the broadly expressed HuR (ELAVL1) regulate RNA stability, translation, localization, and selected microRNA (miRNA) activities. Recent studies further show that HuD can promote export of let-7a and miR-125b during differentiation of PC12 cells, whereas HuR can bind selected miRNAs and engage endosomal export or intracellular buffering mechanisms in other cellular contexts. These observations support an emerging ELAVL–miRNA–extracellular vesicle (EV) framework. They do not yet establish an integrated HuD/HuR-dependent neuron–glia pathway in aging human brain or Alzheimer’s disease (AD). We therefore distinguish direct, model-specific findings from hypotheses that age-, amyloid-, or inflammation-associated changes in ELAVL abundance, localization, or RNA binding could redistribute miRNAs between intracellular pools and EVs. Testing this framework in primary human neural cells, induced pluripotent stem cell-derived systems, organoids, and in vivo models may identify context-specific mechanisms and therapeutic opportunities. Full article

Background/Objectives: Alzheimer disease (AD) causes progressive cognitive and functional loss and substantial caregiver and healthcare burden. Anti-amyloid monoclonal antibodies represent a shift toward biology-directed treatment in biomarker-confirmed early symptomatic AD, but modest clinical effects must be balanced against amyloid-related imaging abnormalities (ARIA), intensive monitoring, and implementation burden. Heterogeneity in trial populations, endpoints, dosing, stopping rules, and follow-up complicates interpretation. This narrative review critically integrates efficacy, safety, durability, biomarker, and implementation evidence for lecanemab and donanemab while preserving study-family relationships and avoiding unsupported cross-trial superiority claims. Methods: For this revised narrative review, a targeted PubMed/MEDLINE search covering the period from database inception was initially conducted before manuscript submission and was subsequently updated through 21 August 2026, supplemented by reference-list and citation tracking. Search terms combined Alzheimer disease with lecanemab, donanemab, anti-amyloid monoclonal antibody, ARIA, APOE, amyloid PET, open-label extension, real-world, clinical meaningfulness, implementation, and access. Sixty-two sources were purposively selected for a comprehensive narrative synthesis; no meta-analysis or formal certainty grading was performed. Results: Pivotal trials demonstrated statistically significant but modest average slowing of decline: Clarity AD showed a 0.45-point between-group difference in CDR-SB worsening at 18 months, and TRAILBLAZER-ALZ 2 showed a 3.25-point iADRS difference in the low/medium-tau population at 76 weeks. ARIA-E occurred in 12.6% of lecanemab-treated and 24.0% of donanemab-treated participants in the pivotal trials, with higher risk in APOE ε4 carriers. Extensions and biomarker analyses suggest persistent biological effects but are less secure for causal inference, and real-world evidence is currently more mature for lecanemab. Conclusions: Both antibodies substantially reduce amyloid and modestly slow average clinical decline in selected patients, but neither restores lost function, greater amyloid clearance does not establish greater individual benefit, and cross-trial superiority cannot be inferred. Treatment requires biomarker-guided selection, APOE-informed risk counseling, serial MRI, infusion and ARIA-management capacity, and shared decision-making that incorporates cost, access, and patient/caregiver burden. Full article

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder and a leading cause of dementia worldwide, characterized by progressive cognitive decline, memory impairment, and functional deterioration. With the rapid growth of the aging population, AD has become a major global health challenge, imposing substantial burdens on patients, families, and healthcare systems. Despite extensive research, early and accurate diagnosis of AD remains challenging due to disease heterogeneity, overlapping clinical manifestations, and the lack of easily accessible, highly sensitive, and specific diagnostic markers. Recent advances in biomedical technologies, including neuroimaging, multi-omics profiling, electronic health records, and digital health tools, have generated large-scale and heterogeneous datasets, providing new opportunities for improving AD diagnosis. However, extracting clinically meaningful information from these complex data sources remains difficult using conventional statistical approaches. Artificial intelligence (AI) has progressively transformed AD diagnosis by evolving from traditional machine learning (ML) approaches based on handcrafted feature engineering to deep learning (DL) models capable of automated representation learning and multimodal information integration. More recently, large language models (LLMs) have further expanded the scope of AI-driven AD diagnosis by enabling contextual understanding of unstructured clinical information, knowledge-guided reasoning, and integration of multimodal biomedical evidence. This transition reflects a shift from feature-based prediction toward more flexible and intelligent diagnostic frameworks. This review synthesizes recent advances in AI-based AD diagnosis, tracing the evolution from traditional ML to DL and LLMs. Particular emphasis is placed on the emerging role of LLMs in extracting disease-related information from speech and clinical narratives, integrating heterogeneous biomedical data sources, and enabling multimodal frameworks for AD assessment. Full article

Conventional qualitative eye movement examinations may miss subtle abnormalities, complicating early and accurate diagnosis of progressive supranuclear palsy (PSP). Quantitative oculography, represented by video-oculography (VOG), provides an objective digital assessment of eye movements. This review summarizes abnormalities in advanced eye movement tasks in PSP, including prosaccades (ProSs), antisaccades (ASs), memory-guided saccades (MGSs), predictive saccades (PSs), overlap saccades (OSs) and gap saccades (GSs), and considers their underlying pathophysiological mechanisms. Quantitative metrics from these tasks may help distinguish PSP subtypes and PSP from other neurodegenerative diseases, such as Parkinson’s disease (PD), multiple system atrophy (MSA), corticobasal degeneration (CBD) and Alzheimer’s disease (AD). Advanced eye movement measures are therefore promising candidate biomarkers for PSP diagnosis and longitudinal disease monitoring. Full article