Progressive structural brain changes are a hallmark of neurodegenerative conditions like Alzheimer's disease (AD), frontotemporal dementia (FTD), multiple sclerosis (MS), and Parkinson's disease (PD). The brain-predicted age difference (brain-PAD) has emerged as a promising biomarker to quantify these alterations, yet its unique clinical contribution relative to conventional measures of global brain atrophy such as the brain parenchymal fraction (BPF) remains underexplored. In this transdiagnostic study across AD, FTD, MS, and PD, we systematically evaluated brain-PAD's capacity to distinguish patients from controls, its cross-sectional and longitudinal associations with cognition, and its voxel-wise structural correlates. We benchmarked brain-PAD against BPF to determine its added explanatory value. Brain-PAD successfully distinguished patients from controls, adding to BPF alone, in AD, FTD, and MS, but not PD. Across disorders, higher brain-PAD correlated with worse cognition, showing clear added value beyond BPF particularly in AD and MS. Baseline brain-PAD also independently predicted subsequent cognitive changes in AD, FTD, and MS, over and above BPF. Voxel-wise analyses revealed spatial features underlying brain-PAD including, beyond global tissue loss, specific regional atrophy matching each disease's characteristic pattern. Collectively, these findings demonstrate that brain-PAD is a clinically meaningful, transdiagnostic biomarker of neurodegeneration that complements conventional volumetric measures like the BPF.
The Alzheimer's disease (AD) brain is characterized by dysregulated expression of multiple microRNAs (miRNA), positioning them as promising diagnostic and therapeutic targets. The levels of glia-enriched miR-223 are abnormal in the brains and plasma of AD patients and miR-223 is neuroprotective in models of stroke. However, whether miR-223 can be beneficial in AD is not known. Here, we report that intracerebroventricular (ICV) injection of miR-223 oligonucleotide mimic alleviated cognitive impairment, reduced amyloid beta (Aβ) pathology, and ameliorated the defects in synaptic marker expression in App NL-G-F AD model mice. Mechanistically, miR-223 induced microglial clustering around Aβ plaques with a concomitant upregulation of microglial phagocytic receptors AXL, TREM2 and CD11c, while pharmacological microglial depletion abolished the plaque-clearance phenotype. Moreover, in human iPSC-derived microglia miR-223 directly targeted multiple genes in the endo-lysosomal pathway, including AD risk gene SPPL2A , indicating that it acts as a major regulator of microglial phenotype. Lastly, long-term AAV-mediated overexpression of miR-223 recapitulates its beneficial effects on cognition, pathology, and synaptic marker expression. Our study demonstrates a novel approach for the treatment of AD using miR-223 and highlights the potential of RNAi-based therapeutics in neurodegenerative disease.
Scaling laws describe how model performance improves as the amount of training data increases, and recent theories such as the zeta law suggest that scaling behavior is influenced by the eigenspectrum of the model's latent representation. Here, we evaluated whether the distribution of discriminative signals across spectral modes predicts the future scaling behavior, for MRI transformers trained for disease classification. We trained three supervised 3D vision transformers (ViT3D, MINiT, and NIT) for Alzheimer's disease classification using 2,822 training scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI); we compared their encoder spectra with that of a frozen self-supervised DINO ViT-B/16 encoder adapted to 3D MRI. The supervised models learned highly concentrated representations, with 90-96% of CLS-token variance captured by a single principal component, whereas DINO distributed signal across many latent directions. Via spectral expansion of the Mahalanobis signal, we found that supervised training concentrated disease information into a single dominant mode, while self-supervised training produced a richer spectral geometry with higher effective rank and discoverability. This led to different scaling behavior: supervised models exhibited flatter AUC( N ) curves, yet DINO continued to improve as sample size increased, gaining 11.0 percentage points from N=50 to N=2,822. Overall, the spectral distribution of the discriminative signal, for these different encoder types, influenced how much performance remained discoverable as sample size increased. Distributed representations may retain signal across many latent modes and continue to improve with additional data, whereas concentrated representations tend to exhaust most of the discoverable signal at much lower sample sizes.
Mutations in the gene encoding the microtubule-associated protein tau (MAPT) that are causal for frontotemporal dementia result in nuclear envelope deformation and disrupted nucleocytoplasmic transport when expressed in human neurons. A small-molecule inhibitor of the acetyltransferase NAT10 has been shown to correct similar nuclear membrane defects in Hutchinson-Gilford progeria syndrome, primarily by modulating microtubule dynamics. We report here that NAT10 inhibition and loss of function correct nuclear membrane abnormalities in human MAPT-mutant neurons. Similarly, NAT10 inhibition and haploinsufficiency correct neuronal nuclear shape defects and extend lifespan in vivo in a Drosophila model of tauopathy. NAT10 inhibition changes microtubule dynamics and corrects aberrant nucleocytoplasmic transport, and NAT10 directly interacts with regulators of microtubule dynamics in human MAPT-mutant neurons. We conclude that NAT10 mediates neuronal pathologies in tauopathies and is a potential therapeutic target in these diseases.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, oxidative stress, neuroinflammation, and cholinergic dysfunction. Increasing evidence suggests that gut microbiota disturbances contribute to AD progression, encouraging the investigation of microbiota-modulating approaches such as probiotics and paraprobiotics. This study evaluated the effects of Lactobacillus casei probiotic and its thermally inactivated paraprobiotic on cognitive, behavioral, oxidative, cholinergic, and inflammatory alterations in a sporadic AD model induced by intracerebroventricular streptozotocin (STZ-ICV; 3 mg/3 μL/site) in female rats. From day 4, animals received daily oral treatment with probiotic L. casei (1 × 109 CFU), paraprobiotic (100 mg/kg), or saline for 14 days. Behavioral assessments of memory and exploratory activity were performed alongside biochemical analyses of oxidative stress markers, antioxidant defenses, acetylcholinesterase (AChE) activity, and neuroinflammatory parameters in central and peripheral tissues. STZ-ICV administration induced impairments in working and long-term memory, increased oxidative stress and neuroinflammation, elevated AChE activity, and promoted intestinal and behavioral alterations. Both probiotic and paraprobiotic treatments attenuated memory deficits, reduced lipid peroxidation, inhibited AChE activity, and decreased inflammatory markers. However, their effects differed in magnitude and tissue specificity. The probiotic mainly improved peripheral antioxidant defenses, whereas the paraprobiotic exerted broader neuroprotective effects, reducing cerebral oxidative stress, restoring non-enzymatic antioxidant levels in the hippocampus and colon, improving jejunal catalase activity, and attenuating hippocampal astrogliosis. These findings demonstrate that modulation of the gut-brain axis through L. casei-based interventions mitigates key pathological features of sporadic AD, with paraprobiotics emerging as a promising and stable alternative with enhanced neuroprotective potential independent of bacterial viability.
Neurobiobanks focused on the study of major cognitive impairment constitute a strategic infrastructure for translational research and personalized medicine in the neurosciences. In Mexico and the Dominican Republic, the National Dementia Biobank (BND) at the Universidad Politécnica de Pachuca and the National Brain Bank at the Universidad Nacional Pedro Henríquez Ureña (BNC-UNPHU) have developed integrated mechanisms for the collection, processing, and preservation of human brain tissue, as well as other tissues such as kidney, liver, intestine, pancreas, and skin, intended exclusively for biomedical research. Both institutions share research lines centered on the molecular pathological study of the tau protein and the amyloid-β peptide, key markers of Alzheimer's disease and other dementias. Protocols for immunohistochemistry, silver staining, single and multiple immunofluorescences, as well as staining with fluorochromes such as thiazine red and thioflavin-S, have been standardized for the precise detection of neuropathological lesions. Transgenic animal models, including the triple transgenic mouse with mutations in presenilin-1, amyloid-β protein precursor, and tau, have served as complementary tools to dissect the temporal sequence of protein aggregation. In parallel, both institutions have implemented sustained scientific outreach programs, including a traveling museum of neurodegenerative diseases, Brain Awareness Week, Alzheimer's fairs, and media campaigns, aimed at reducing stigma, promoting altruistic tissue donation, and building public trust. Collectively, these neurobiobanks represent an emerging model of research contextualized within Latin American populations, with the potential to integrate into regional and international networks that contribute to reducing knowledge gaps in neurodegeneration.
Against the backdrop of accelerating population aging, the risk of neurodegenerative diseases (NDDs) has risen significantly. While brain structure plays a critical role in NDDs, the interplay between them remains unclear. This study employed Mendelian randomization (MR) to investigate potential causal relationships between brain structure, region-specific gene expression, and four NDDs - Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS) - providing new directions and genetically informed hypotheses for disease research. MR analyses were conducted using inverse-variance weighted (IVW), MR-Egger, weighted median, weighted mode, and Wald ratio methods. Summary-data-based MR (SMR) was applied to identify brain genes influencing NDDs. We calculated F-statistics, 95% confidence intervals (CIs), odds ratios, and p-values. Sensitivity analyses included the heterogeneity I2 statistic, Cochran's Q test, Egger intercept test, MR-PRESSO, and leave-one-out validation. Data from 512 unsupervised deep-learning imaging phenotypes (UDIPs) were analyzed. Thirty-four UDIPs showed associations consistent with a potential causal role in AD, 56 in PD, 22 in ALS, and 92 in MS. After false discovery rate (FDR) correction, 4 remained significant for AD and PD, 3 for ALS, and 28 for MS (p < 0.05). Brain regions (excluding the cervical spinal cord C-1) exhibited shared causal genetic features across all four NDDs, primarily involving HLA-class genes. This study provides genetic evidence suggestive of potential causal associations between UDIPs, brain gene expression, and NDDs. These findings offer genetically predicted evidence that may generate hypotheses and inform future mechanistic research into NDD pathogenesis.
The objective of this study is to address conflicting evidence that chronic inflammation may increase the risk of dementia in patients with rheumatoid arthritis (RA). Retrospective population-based study using longitudinally linked administrative health data over a 30-year period for ever hospitalised patients with RA (n = 14,041, age 64 years, 67.2% female) and controls (n = 33,785, age 65 years, 65.6% female). Dementia was defined by the International Classification of Diseases codes for Alzheimer's disease (AD), vascular dementia, and nonspecific dementia subtypes. Dementia incidence rate (IR) and mortality rate (MR) per 1000 person-years and comorbidities are reported. During 9.6 years of follow-up, 1463 (10.4%) of patients with RA and 3701 (11%) of controls were diagnosed with dementia at respective age of 83 vs 84 years (P = .01). The IR was 12.07 (95% CI: 11.15-12.71) in patients with RA and 11.59 (95% CI: 11.22-11.97) in controls corresponding to an IR ratio of 1.04 (95% CI: 0.98-1.11, P = .21), which did not change significantly over 3 decades. Traditional risk factors for dementia were equal in both groups, but patients with RA with dementia were less likely to be classified as AD (odds ratio = 0.59, 95% CI: 0.48-0.73, P < .001). Hospitalisation rates after dementia diagnosis were higher for patients with RA, and the crude MR (overall 91.8 vs 90.4, P = .64) remained similar before or after 2000 for both groups. There was no difference in temporal incidence and MRs for dementia between patients with RA and matched controls. These data suggest that there is minimal impact of RA on the frequency and outcome of dementia.
Monitoring microglial activation mediators remains challenging in neurodegeneration. Few imaging studies track amyloid-β (Aβ)-linked microglial dynamics across a wide field of view with high spatiotemporal resolution. Leveraging the triggering receptor expressed on myeloid cells 2 (TREM2), a pivotal Alzheimer's disease (AD) biomarker that enhances Aβ clearance while suppressing neuroinflammation, we developed a dual-modal probe, TREM2-ICG, by conjugating a TREM2-specific antibody with indocyanine green (ICG), an FDA-approved dye, for robust in vivo photoacoustic and near-infrared-II (NIR-II) fluorescence imaging. Multi-wavelength photoacoustic microscopy imaged AD pathology at 532 nm (hemoglobin, vasculature), 559 nm (Aβ probe AOI987), and 780 nm (TREM2-ICG for peri‑plaque microglia). Time-resolved NIR-II imaging (30 frames/sec) tracked Aβ-oligomer-induced microglial displacement at ∼50 µm resolution, showing a rapid chemotaxis phenomenon. Immunofluorescence-verified TREM2-microglia plaque engagement demonstrates AD pathogenesis. Overall, our multiscale photoacoustic-fluorescence imaging resolved cortex-wide Aβ-microglial interactions, combining wide-field, high-speed, and deep-penetration to overcome confocal depth and two-photon field of view limits. This enabled in vivo tracking of microglial responses to Aβ, revealing potential for investigating AD-specific mechanisms.
BackgroundAlzheimer's disease (AD) is characterized by amyloid-β (Aβ) accumulation with impaired lymphatic clearance, yet therapies targeting lymphatic dysfunction remain underexplored. The Neurolymphatic Formula (NLF), a traditional Chinese medicine, demonstrates lymphatic modulation potential, but its mechanistic role in AD remains unknown.ObjectiveThis study aimed to elucidate NLF's therapeutic efficacy in AD and investigate whether it enhances central and peripheral lymphangiogenesis via VEGF receptor 3 (VEGFR3) activation.MethodsWe evaluated NLF's pharmacological effects on behavior and AD pathology in APP/PS1 mice, including sunitinib-induced lymphatic impairment models. Underlying mechanisms were explored using network pharmacology, molecular docking, and in vitro assays on human lymphatic endothelial cells (HLECs).ResultsIn APP/PS1 mice, 4-week NLF treatment reduced Aβ plaque burden by 43% (p < 0.01) and improved spatial memory latency by 35% (p < 0.05). NLF restored meningeal and mesenteric lymphatic density in sunitinib-treated mice to 82% and 133% of baseline, respectively (p < 0.01), while upregulating serum VEGFR3 2.3-fold (p < 0.01). To validate NLF's molecular basis, coptisine was identified as a representative VEGFR3 ligand (-7.1 Kcal/mol). In vitro, coptisine (25 μM) enhanced HLEC viability by 60%, accelerated wound closure 2.5-fold, and increased tube junctions by 75% (all p < 0.01) alongside VEGFR3 upregulation.ConclusionsNLF alleviates AD pathology by promoting Aβ clearance through VEGFR3-mediated dual modulation of central and peripheral lymphatic systems. The in vitro efficacy of its constituent, coptisine, mechanistically validates this pro-lymphangiogenic pathway, highlighting NLF's therapeutic potential as a holistic lymphatic-targeted AD treatment.
Cerebral Small vessel disease (cSVD) is a prevalent feature of Alzheimer's disease (AD) pathology. Whether this pathology is a late consequence of amyloid and tau accumulation or an early, direct effect of PSEN1 dysfunction has remained unresolved. We found that it is more severe in familial AD (FAD) caused by E280A mutation in presenilin 1 (PSEN1). These cases present with a distinctive proteomic signature, associated with pathological features, more dysregulated in the occipital cortex (OC) compared to the frontal cortex (FC), and characterized by multiple dysregulated proteins involved in extracellular matrix (ECM) and RNA-associated processes. This proteomic fingerprint was associated with abnormal collagen build up, ECM disorganization, and signatures of aberrant angiogenesis. Six months old transgenic knock-in mice homozygous for Psen1 E280A mutation (PSEN1Ki) also showed a similar phenotype with microvascular tortuosity and proteomic changes. Critically, these mice develop neither Aβ plaques nor tau tangles, indicating that the shared microvascular and RNA-associated changes are direct consequences of PSEN1 dysfunction rather than downstream effects of amyloid pathology. Remarkably, dysregulated RNA-associated protein networks overlapped between FAD and PSEN1Ki mice. Cerebral microvessels microstructure in PSEN1Ki mice at two months and six months showed abnormal astrocytic end-feet with lamellar deposits implicating blood-brain barrier damage. Finally, single nuclei transcriptomic analysis of AD patients and controls showed similar abnormal astrocytes in both sporadic and familial variants, but FAD astrocytes expressed dysregulated genes identified in the proteomic analyses, such as GLUL, APOE, and CLU. Our findings suggest that cSVD is an early pathological event in PSEN1 FAD and that is driven by abnormal RNA-associated processes and astrocytic dysfunction.
International data transfer rules, designed to protect individuals, often create barriers to collaborative research by imposing constraints misaligned with modern data ecosystems. Frameworks like GDPR and UK GDPR can unintentionally hinder scientific progress by failing to recognise the safeguards provided by emerging technologies. More nuanced legal approaches are needed to preserve privacy while enabling responsible international research. We will examine how privacy-enhancing technologies (PETs) can help address these challenges. Informed by insights from pilot projects under the Alzheimer's Disease Data Initiative which seek to address critical dementia questions, while expanding dataset access. With dementia cases projected to rise globally from 57 million to 153 million by 2050, this work demonstrates the urgent need for cross-border data sharing in brain health research. Specifically, we will explore how PETs offer pathways through regulatory barriers, and how Trusted Research Environments (TREs), aligned with the Five Safes Framework, provide strong safeguards to prevent identifiable data disclosure. We will demonstrate how remote querying techniques enable international analysis without data transfers, as researchers receive only aggregate results. The presentation will address persistent challenges: under European Data Protection Board guidance, even viewing data across borders constitutes a transfer, meaning TRE access may trigger complex compliance requirements despite technical safeguards. We will explore the rapidly evolving landscape through new UK legislation, the European Health Data Space, and emerging case law. Finally, we will discuss whether PETs can bridge the gap between privacy protection and scientific progress, and what regulatory adaptations are required to recognise the protections they provide.
The importance of advanced practice nurses (APNs) in improving emergency care for patients with Alzheimer's disease is a reality. APNs play a crucial role by providing advanced clinical skills and an approach centered on Naomi Feil's Validation®, a non-pharmacological therapy. This method involves empathetic acknowledgment and affirmation of patients' emotions and experiences, which helps build a relationship of trust and address their specific needs. By collaborating with other healthcare professionals, APNs ensure high-quality care tailored to the emergency situations faced by vulnerable patients.
Chronic neuroinflammation is a major driver of cognitive decline, vascular cognitive impairment, and Alzheimer's disease. However, the spatial lipidomic alterations underlying neuroinflammatory brain injury remain poorly defined. Oxidative stress and sphingolipid dysregulation have been implicated, but their regional distribution and interplay in the brain are not well characterized. We performed positive-ion mode matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) on coronal brain sections from middle-aged spontaneously hypertensive rats (SHR), a model of chronic neuroinflammation, and normotensive Wistar-Kyoto (WKY) controls. Spatial distributions and relative abundances of multiple lipid classes, including phosphatidylcholines (PCs), sphingomyelins (SMs), hexosylceramides (HexCers), ceramides, phosphatidylserines (PSs), phosphatidylinositols (PIs), phosphatidylethanolamines (PEs), phosphatidic acids (PAs), and sulfatides, were mapped and compared between genotypes. Region-of-interest analysis was used to quantify changes across cortex, hippocampus, and white-matter tracts. SHR brains exhibited a coordinated lipidomic signature characterized by pronounced oxidative stress and membrane remodeling. Oxidized and short-chain PCs were markedly upregulated (up to 11.6-fold), while major structural diacyl PCs were broadly downregulated. Concurrently, sphingolipids were significantly altered, with robust upregulation of SM(d36:1) (7.5-fold) and multiple HexCer species (1.5-1.9-fold), accompanied by accumulation of ceramides. These changes were accompanied by heterogeneous redistribution of PS, PI, and PE species, particularly within the hippocampus. Sulfatide patterns in white-matter tracts were also altered, suggesting myelin remodeling. Region-of-interest analysis confirmed that the most pronounced lipid alterations were concentrated in the hippocampus and white-matter regions. Chronic neuroinflammation induces a spatially organized, multi-class lipid remodeling response in the brain, driven by advanced oxidative membrane damage and a shift toward a pro-apoptotic sphingolipid profile. The convergence of these pathways creates a vicious cycle of membrane injury, mitochondrial dysfunction, and sustained neuroinflammation that is especially prominent in the hippocampus and white matter. These spatially resolved findings provide direct evidence that oxidative stress and sphingolipid dysregulation are central, interrelated mechanisms contributing to neurovascular injury and increased risk of cognitive impairment. The study highlights the power of MALDI-MSI to uncover region-specific lipid pathology and identifies potential lipid-based targets for therapeutic intervention in neuroinflammatory brain disease.
Aging-related neurological disorders, including stroke, Alzheimer's disease (AD), Parkinson's disease (PD), epilepsy, and various neuroinflammatory conditions, affect over three billion individuals worldwide and constitute leading causes of morbidity, disability, and socioeconomic burdens. Aging contributes not only to the increased incidence of these disorders but also to their progression through interconnected mechanisms, including endothelial dysfunction, oxidative stress, chronic inflammation, mitochondrial dysfunction, cellular senescence, metabolic imbalance, and gut microbiota dysbiosis. These processes collectively impair neuronal survival, synaptic plasticity, and cognitive and motor functions. Traditional Chinese medicine (TCM), with its characteristic multi-component and multi-target therapeutic strategies, has emerged as a promising approach to counteract age-associated neurological decline. Accumulating preclinical studies suggest that TCM interventions may exert neuroprotective, anti-inflammatory, and antioxidant effects, modulate autophagy, restore metabolic homeostasis, and potentially delay cellular senescence. However, high-quality clinical evidence on safety and efficacy remains limited. This review summarizes current insights into the molecular interplay between aging and neurological disorders and highlights the therapeutic potential of TCM in targeting hallmarks of aging, providing perspectives for integrative prevention and treatment strategies for neurodegenerative and neurovascular diseases.
The biomarker-based amyloid/ tau/ neurodegeneration (A/T/N) framework has become a popular staging method for Alzheimer's disease (AD) research. Previous studies use the framework either as a rule-based or data-driven approach but typically sacrifice either adaptivity or interpretability. We present an interpretable, hybrid method, called Neurosymodal Data Fusion, for predicting incident AD in the ADNI dataset. Specifically, we encode the A/T/N framework as a logic program, where the input biomarker features are extracted by one or more neural networks. Our pipeline predicted four-year incident AD with a sensitivity of up to 0.84. Additionally, our models learned scores for each A/T/N profile, denoting relative importances to model predictions. These scores also indicated that empirically-derived cut-off values for the A and T criteria might be uninformative for the ADNI data. Our pipeline provides a novel way to use the A/T/N framework that could potentially improve early AD screening years before clinical manifestations.
BackgroundPhysical exercise is widely recognized for its cognitive benefits; however, the effect of menopausal status in modulating the cognitive effects of exercise is not definitively established.ObjectiveTo examine the cognitive benefits of two 6-month physical exercise programs in cognitively healthy older women across adulthood, and whether menopause status moderates these benefits.MethodsIn a post hoc analysis of a randomized controlled trial, 93 cognitively healthy women (aged 20-67; 43% at post-menopause) were assigned to either aerobic exercise (AE) or stretching/toning (ST) 4 days a week for six months. Neuropsychological assessment, cardiorespiratory exercise test, and blood draw were performed at baseline, 3-months, and 6-months. Linear mixed-effects regression models assessed whether menopausal status moderated the impact of exercise on executive functions and processing speed.ResultsSeventy-six participants (81.7%) completed the intervention. A time-by-group-by-menopause interaction emerged after 3 months (β = -0.89; p = 0.001) and 6 months (β = -0.67, p = 0.016). Post-menopausal women in the AE group showed greater improvement in executive functions compared to the ST group and pre-menopausal women. Models controlled for age, education, and baseline cognitive performance.ConclusionsOur results provide novel evidence that AE improves cognition with pronounced executive functions benefits in post-menopausal women, a population at higher risk for dementia. Since women are at a higher risk of developing Alzheimer's disease compared to men, these findings support AE as a relevant strategy to promote women's brain health. Although this is a secondary analysis, it may inform future exercise trials targeting women.
The Diabetes Prevention Program (DPP) was a randomized clinical trial designed to prevent type 2 diabetes (T2D) in adults with prediabetes. The DPP Outcomes Study (DPPOS) is the 30-year follow-up of this cohort, focusing on T2D, prediabetes, and related complications. Cognitive assessments began in 2009 and expanded in 2022 to examine cognitive impairment, including Alzheimer's disease (AD) and AD related dementias (ADRD), in the surviving cohort. To support these aims, the National Alzheimer's Coordinating Center Uniform Data Set version 3 (NACC-UDSv3), the standardized framework used by Alzheimer's Disease Research Centers, was implemented in DPPOS in 2022 to enable data sharing with NACC. These forms were complemented by cognitive tests administered in DPPOS. We aimed to integrate the NACC-UDSv3 into the existing longitudinal DPPOS framework while maintaining fidelity to its structure and developing automated reports to streamline cognitive outcomes adjudication. Items from the 16 NACC-UDSv3 data forms were compared with those already collected within DPPOS to integrate overlapping similar items, add missing NACC-UDSv3 items, and create a dataset harmonized with NACC-UDSv3. Forms were adapted for electronic data capture (EDC) using the MIDAS (Multimodal Integrated Data Acquisition System, George Washington University). Automated reports integrated current and prior neuropsychological scores to support adjudications. In the first wave of the DPPOS-AD/ADRD study, 1561 cognitive adjudications were successfully completed using the harmonized DPPOS and NACC-UDSv3 data implemented into MIDAS. The DPPOS-AD/ADRD project demonstrated that NACC-UDSv3 can be successfully integrated into a long-standing longitudinal cohort not originally designed for AD/ADRD research. The harmonization, electronic capture, and automated adjudication processes may provide a practical framework for other cohorts seeking to incorporate NACC-UDSv3 to align with national AD/ADRD research standards.
Neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD), are major causes of disability and mortality worldwide. Emerging evidence suggests that chronic peripheral inflammation and microbial dysbiosis may contribute to neurodegenerative processes. The oral-brain axis has recently gained attention as a biological framework linking oral microbial communities, systemic inflammatory responses, immune regulation, and central nervous system function. Within this context, periodontitis, a prevalent chronic inflammatory disease driven by oral dysbiosis, has been proposed as a potential modifiable risk factor for neurodegeneration. This narrative review examines current evidence supporting the oral-brain axis and its role in the relationship between periodontitis and neurodegenerative disorders. Key mechanisms include systemic dissemination of periodontal pathogens and their virulence factors, persistent inflammatory signaling, blood-brain barrier dysfunction, neuroimmune activation, oxidative stress, and protein aggregation. Particular attention is given to the contribution of Porphyromonas gingivalis and associated virulence factors to neuroinflammation, amyloidogenesis, and neuronal injury. Epidemiological, clinical, and experimental studies linking periodontal disease with cognitive decline, Alzheimer's disease, and Parkinson's disease are also discussed. Current evidence supports a biologically plausible association between periodontal disease and neurodegeneration through interconnected microbial, inflammatory, and vascular pathways. Although causality remains to be established, the oral-brain axis provides valuable insight into potential mechanisms underlying this relationship. Improved understanding of these interactions may facilitate the development of preventive and therapeutic strategies that integrate oral healthcare with approaches aimed at preserving neurological health and reducing the burden of neurodegenerative diseases.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and behavioral alterations. However, the complex etiology and pathogenesis of AD have thus far precluded the development of satisfactory therapeutic agents. Traditional Chinese medicine (TCM) has garnered increasing recognition for its potential in AD management due to its multicomponent, multitarget therapeutic strategy. Metabolomics, an advanced analytical methodology for investigating metabolic alterations in biological systems, has yielded significant insights into both the therapeutic efficacy and mechanistic underpinnings of TCM interventions for AD. This review synthesizes recent metabolomic findings associated with TCM approaches to AD treatment, identifying key metabolic pathways across diverse biological specimens, including brain tissue, blood, urine, and feces. Through systematic elucidation of these metabolic networks, metabolomics offers substantial potential to facilitate the advancement of TCM-derived therapeutics for AD, potentially enhancing global patient outcomes.