Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive deficits, amyloid-beta (Aβ) plaque deposition, tau hyperphosphorylation, oxidative stress, and chronic neuroinflammation. Therapeutic strategies are at present mainly symptomatic and do not modify the course of the disorder. Natural chalcones, precursors of flavonoids, are emerging as multi-target agents for neuroprotection since they have the ability to protect neurons and exert anti-inflammatory and antioxidant activities. A systematic literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar utilizing keywords that associate chalcones with Alzheimer's disease. Studies were included if they reported in silico docking, in vitro assays, or mechanistic insights on AD-related targets (AChE, BACE1, GSK-3β, NF-κB). Data extraction included information about the compound's identity, structural changes, docking scores, enzyme inhibition, oxidative stress, and cytokine modulation. The findings were synthesized both qualitatively and quantitatively, with structure-activity relationship (SAR) analysis emphasizing patterns of hydroxylation and methoxylation. These helped in the rational design of chalcone derivatives, which showed potential as multi-target agents against AD pathology. Several chalcones exhibited potent inhibition against AChE and BACE1, besides reducing reactive oxygen species (ROS) generation and preventing the release of pro-inflammatory cytokines. These findings demonstrate their potential to mitigate cholinergic deficits and neuroinflammatory signaling. SAR studies revealed a significant enhancement in bioactivity for certain hydroxylation and methoxylation substituents. This provides insights into the rational design of improved chalcone derivatives. Chalcones display multifunctional properties and are able to modulate several AD pathological signatures, suggesting potential application in the prevention of AD symptoms. Their therapeutic importance is emphasized by their combined ability to target cholinergic dysfunction, oxidative stress, and neuroinflammation. The SAR analysis further supports the focused development of chalcone-based derivatives with improved potency. The present study provides insights into the mechanistic basis of the neuroprotective activity of chalcones and paves the way for subsequent preclinical evaluation. The chalconebased strategy holds promise for the development of potential drug candidates for the treatment of neurodegenerative diseases such as Alzheimer's disease by addressing the multi-target nature of this complex disease.
Membrane type 5-matrix metalloproteinase (MT5-MMP, MMP-24), an η-secretase involved in amyloid precursor protein processing, is a promising but unexplored target in Alzheimer's disease. We report here the identification of a first nonpeptidic hit for MT5-MMP through a structure-guided approach. A homology model of the MT5-MMP catalytic domain was built from the MT3-MMP/batimastat structure and validated by both docking and experimental inhibition data obtained with batimastat (IC50 = 3 nM). To account for binding-site plasticity, especially that of the S1' pocket, molecular dynamics and ensemble docking were applied to a zinc-binding group (ZBG)-focused library of 3851 compounds. Although the initial screening campaign yielded only weakly active candidates, analysis of docking poses identified a relevant scaffold for optimization. Replacement of a carboxylic acid ZBG by a hydroxamic acid led to compound 17, which inhibited MT5-MMP with an IC50 of 6 μM and established a first nonpeptidic hit for future optimization.
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BackgroundPeople living with Alzheimer's disease often require support from their relatives, who may face emotional and physical challenges in their role. Up to 90% of people living with cognitive impairment experience unmet needs such as wandering.ObjectiveThe aim of the study was to analyze the narrative of relatives of people living with Alzheimer's disease experiencing unsatisfied behavioral needs and whether this has a relationship with levels of burden.MethodsRelatives who cared for a family member with Alzheimer's disease at home participated in a structured interview with a psychologist and completed the Zarit Burden Interview to assess caregiver burden. An analysis was conducted of the frequency of words used in the relatives' responses to the question "What is your experience of your loved one's wandering?".ResultsA total of 15 relatives participated in the study. Relatives with higher levels of burden related to their role as caregivers were more likely to use words such as "disorder" (on average once per interview), "problem" (on average three times per interview), and "difficulty" (on average twice per interview), than people with low levels of burden. For people with low levels of burden, the word "need" appeared as a significant expression (on average four times per interview).ConclusionsRelatives who experience less burden are more likely to understand the reasons behind their loved ones' need or desire to wander. They are less likely to perceive this behavior as a problem and restrict the person's freedom of movement for their own safety.
Single-cell RNA sequencing (scRNA-seq) enables high-resolution characterization of cellular heterogeneity, but its rich, complementary structure across cells and genes remains underexploited, especially in the presence of technical noise and sparsity. Effectively leveraging this multi-scale structure is essentially an information fusion problem that requires integrating heterogeneous graph-based views of cells and genes into robust low-dimensional representations. In this paper, we introduce GatorSC, a unified representation learning framework that models scRNA-seq data through multi-scale cell and gene graphs and fuses them with a mixture-of-experts architecture. GatorSC constructs a global cell-cell graph, a global gene-gene graph, and a local gene-gene graph derived from neighborhood-specific subgraphs, and learns graph neural network embeddings that are adaptively fused by a gating network. To learn noise-robust and structure-preserving embeddings without labels, we couple graph reconstruction and graph contrastive learning in a unified self-supervised objective applied to both cell- and gene-level graphs. We evaluate GatorSC on 19 publicly available scRNA-seq datasets covering diverse tissues, species, and sequencing platforms. Experiments showed that GatorSC consistently outperforms state-of-the-art deep generative, graph-based, and contrastive methods for cell clustering, gene expression imputation, and cell-type annotation. The learned embeddings are used for accurate trajectory inference, recovery of canonical marker gene programs, and cell-type-specific pathway signatures in an Alzheimer's disease single-nucleus dataset. GatorSC provides a flexible foundation for comprehensive single-cell transcriptomic analysis and can be readily extended to multi-omic and spatial modalities.
Reduced brain energy metabolism, mitochondria dysfunction, and extracellular tau oligomer buildup characterize Alzheimer's disease (AD), but how these phenomena cooperatively promote neurodegeneration is poorly understood. We now report that tau oligomers (TauOs) pathologically coordinate mitochondrial metabolism with increased expression of a plasma membrane (PM) tau receptor. Mitochondrial energy metabolism was recorded using two-photon fluorescence lifetime microscopy of mitochondrial nicotinamide adenine dinucleotide phosphate (NADPH) in live human neurons and PS19 mouse brain. Recombinant or human brain-derived TauOs upregulate expression of the mitochondrial NAD+ kinase, mitochondrial NAD kinase 2 (NADK2), and by extension, de novo NADPH synthesis. This process controls expression of low-density lipoprotein receptor-related protein 1 (LRP1), a major PM receptor for tau, thereby establishing a vicious cycle for further TauO internalization. Upregulation of the NADK2-NADPH pathway was detected in live presymptomatic PS19 mouse brains and in AD patient-derived neurons. Upregulation of mitochondrial NADK2-dependent NADPH controls a key step in TauO toxicity and may represent an early stage in human AD.
Proprotein convertase subtilisin-kexin type 9 (PCSK9) has recently emerged as a significant mediator that links metabolic dysfunction to neurodegeneration related to Alzheimer's disease (AD). It is a well-known and crucial component involved in cholesterol homeostasis. However, its function in the central nervous system (CNS) is still in its early stages. Normally, it is engaged with the breakdown of cholesterol in the body, but within the brain, PCSK9 has been seen to disrupt the homeostasis of cholesterol and its uptake. Receptors such as LDL receptor-related protein-1 (LRP-1) and low-density lipoprotein receptor (LDLR) are crucial for the survival of neurons, as they are responsible for the clearance of amyloid-β (Aβ) and peripheral lipid control. Elevated PCSK9 activity may promote degradation of these receptors, which eventually leads to deposition of Aβ near synapses along with reduced uptake of cholesterol by neurons, which may contribute to neurotoxicity and neuronal dysfunction. This review aims to explore the effect of elevated PCSK9 levels on the development as well as exacerbation of AD via different molecular mechanisms. Along with cholesterol dyshomeostasis, PCSK9 is found to be involved in glucose dysregulation, mechanistic target of rapamycin (mTOR) dysregulation, increased oxidative stress, neuroinflammation, reduced neurogenesis, affected Wnt-β-catenin signaling, and cholinergic signaling. Together, these mechanisms may contribute to AD progression. Preclinical studies show that pharmacological therapies targeting PCSK9 can give promising results by reducing neuroinflammation, modulating lipid homeostasis, and lowering Aβ accumulation. Therefore, modulation of PCSK9 represents a promising therapeutic strategy that warrants further mechanistic and clinical investigation in AD.
Alzheimer's disease (AD) has been linked to impaired clearance of metabolic waste, and glymphatic dysfunction is increasingly considered a potential contributor to its pathogenesis. The diffusion tensor imaging-based analysis along the perivascular space (ALPS) index has been proposed as a non-invasive imaging marker, although findings across clinical studies remain inconsistent. We systematically searched PubMed, Embase, Web of Science, Scopus, CENTRAL, and PEDro up to August 2025 in accordance with PRISMA guidelines. Studies reporting ALPS index values in adults with AD, mild cognitive impairment (MCI), or cognitively normal controls (NC) were included. Risk of bias was assessed using the AHRQ checklist, and the certainty of evidence was evaluated with GRADE. Fifteen studies involving 1,756 participants were included in the meta-analysis. Pooled results showed a stepwise decrease in ALPS values, with significantly lower values in AD compared with NC (mean difference -0.20, I 2 = 93%) and MCI (-0.09, I 2 = 78%), as well as in MCI compared with NC (-0.11, I 2 = 92%). Subgroup and sensitivity analyses supported the stability of these findings despite methodological heterogeneity. The ALPS index shows a progressive decrease across the AD continuum, which is consistent with the presence of glymphatic alterations during disease progression. As a non-invasive MRI-derived marker, ALPS may have potential for use in early detection and monitoring; however, further validation with standardized imaging protocols and longitudinal studies is required before clinical application. https://www.crd.york.ac.uk/PROSPERO/view/CRD420251119624, PROSPERO, CRD420251119624.
The etiology of Alzheimer's disease (AD) remains unclear but is likely driven by gene-environment interactions. We present a multi-organ untargeted metabolomics atlas (n = 2,271) paired with metagenomics data (n = 666) from two AD transgenic mouse models (3xTg and 5xFAD) under colonized and germ-free conditions. Systems-level analyses revealed clusters of dysregulated molecules across tissues, including carnitines, bile acids, B vitamins, neurotransmitters, and N-acyl lipids. Metabolic shifts were associated with the depletion of Akkermansia muciniphila and enrichment of Mucispirillum schaedleri in the 3xTg model. We identify previously unexplored carnitines linked to microbial metabolism of phenylalanine. Using tissueMASST-a mass spectrometry search tool we developed to translate animal-model findings into a human clinical context-we trace phenylacetyl-carnitine in human plasma and serum samples (n = 1,470) from independent cohorts, revealing associations with aging, cognitive impairment, and diminished memory performance. This public resource and associated tools will aid future research in AD etiology.
Investigating the relationship of circulating lipidome profiles with cross-sectional and longitudinal changes of central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD pathophysiology. In this study, we quantified a total of 749 plasma lipid species at baseline using liquid chromatography-mass spectrometry and performed cross-sectional and longitudinal association analysis of plasma lipidome profiles with longitudinal A/T/N biomarkers for AD in the Alzheimer's Disease Neuroimaging Initiative cohort (N = 1395). We identified several lipid species, classes, and network modules of correlated lipids that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers. Notably, we identified lysoalkylphosphatidylcholine (LPC(O)) as associated with cross-sectional "A/N" biomarkers at the lipid species, class, and module levels. Also, Phosphatidylethanolamine (PE) ethers were associated with A/T/N biomarkers in the species level and with "N" biomarkers in the class and module levels. GM3 ganglioside showed association with cross-sectional and longitudinal changes of "N" biomarkers at the species and class levels. Furthermore, 20 lipid species, out of all 57 species identified as associated with "less severe" AD biomarkers, contained docosahexaenoic acid (DHA), indicating that the previously reported beneficial effects of DHA on AD were significant at the central biomarker level. In conclusion, our approach linking peripheral metabolic changes with brain metabolic, structural, and functional states strengthens evidence from previous studies that were performed using only clinical AD diagnosis. Importantly, our study also enabled identification of novel lipids that play potential roles in progression of AD pathophysiology, suggesting dysregulation of lipid metabolic pathways as precursors to AD development and progression.
Provided herein are novel compounds as TREM2 modulators, pharmaceutical compositions, use of such compounds in treating Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and Nasu-Hakola disease, and processes for preparing such compounds.
Alzheimer's disease (AD) is associated with the aggregation of β-amyloid (Aβ) peptides and oxidative stress, two interconnected processes that contribute to neuronal dysfunction and cognitive decline. Natural polyphenols such as oleuropein and its metabolite hydroxytyrosol display antioxidant and anti-amyloidogenic properties, but oleuropein suffers from limited stability due to glycosidic hydrolysis. To develop more robust and potent oleuropein analogs, we synthesized a series of hydroxytyrosol-based esters in which the secoiridoid glucoside scaffold of oleuropein was replaced by lipophilic substituents designed to enhance molecular stability and interactions with Aβ peptide. The compounds were evaluated for their ability to interact with Aβ40 using ESI-MS, circular dichroism (CD), and thioflavin-T fluorescence (ThT), along with complementary antioxidant assays. Most of the compounds formed stable non-covalent complexes with Aβ40, inhibited early aggregation events, and prevented the peptide's conformational transition from random coil to β-sheet. To assess biological efficacy and safety in vivo, the most promising analog (3b) was evaluated in Caenorhabditis elegans models of amyloid-β toxicity. Treatment with 3b exhibited no detectable toxicity in wild-type animals, as evidenced by normal development, growth, and reproductive efficacy. Importantly, 3b rescued lifespan shortening and locomotor deficits in transgenic nematodes expressing human Aβ42 pan-neuronally, while having no effect on control strains lacking Aβ42 expression. These findings demonstrate that 3b confers functional protection against amyloid-induced toxicity in vivo. Overall, our results identify the newly synthesized hydroxytyrosol-derived esters as promising multifunctional scaffolds that combine potent anti-aggregation activity with strong antioxidant properties and in vivo neuroprotective efficacy, supporting their further development as anti-amyloidogenic agents for AD therapy.
The rapid progression of Alzheimer's disease (AD) is primarily caused by compromised neurotrophin functions and decreased tropomyosin receptor kinase expression in the basal forebrain area. The two main pathogenic features of AD are cholinergic-dependent cognitive dysfunctions and amyloidogenic-induced neurodegeneration. Concurrent stimulation of major neurotrophin signalling pathways, such as tropomyosin receptor kinases receptor A and B (TrkA and TrkB), may reduce amyloid-β-mediated neurotoxicity and cholinergic denervation in the basal forebrain, improving cognitive performance and re-establishing neuronal communication. The development of new medications with dual agonist action towards TrkA and B receptors holds enormous therapeutic potential for managing the symptoms of neurodegenerative diseases. This study aims to develop novel dual TrkA/TrkB receptor agonists for the treatment of AD by enhancing neurotrophin signalling, reducing cholinergic denervation, and mitigating amyloid-β-induced neurotoxicity. An in silico drug discovery pipeline was employed, involving homology and pharmacophore modelling of amitriptyline, virtual screening of ChEMBL compounds, molecular docking, ADMET, MM/GBSA analysis, DFT calculations and molecular dynamics (MD) simulations for 100 and 300 ns to assess ligand stability and binding behaviour of the ligand-protein complexes. Six novel optimised quinoline analogues (OP-1 to OP-6) were identified as computationally predicted dual TrkA/TrkB agonists by molecular docking (-8.90 to -5.07 kcal/mol), MM/GBSA (-40.47 to -30.71 kcal/mol), ADMET and DFT analysis. Furthermore, OP-1, OP-2, and OP-3 exhibit stable binding interactions over 300 ns of MD simulations. The optimised compounds demonstrated favorable computational binding profiles, predicted pharmacokinetic properties, and stable receptor-ligand interactions, identifying them as promising candidates for further experimental validation as potential dual TrkA/TrkB modulators in Alzheimer's disease.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder evident by cognitive decline and neuropathological hallmarks such as amyloid-β (Aβ) plaques and tau protein hyperphosphorylation. Recent evidence links gut microbiota dysbiosis to AD pathogenesis through the microbiota-gut-brain axis (MGBA), a complex bidirectional communication system entailing neural, immune, and metabolic pathways. This study aims to explore the mechanistic relationship between gut microbiota alterations and AD development and to assess the therapeutic potential of microbiota modulation through dietary, probiotic, and metabolite-based interventions. A thorough analysis was undertaken, blending evidence from preclinical animal models and clinical investigations. The effects of bacterial metabolites, microbial components (e.g., lipopolysaccharides, microbial amyloids), and interventions like probiotics, dietary fibers, and polyphenols were examined. Emphasis was placed on neuroinflammatory markers, Aβ deposition, blood-brain barrier integrity, and behavioral outcomes. Findings revealed that gut dysbiosis contributes to increased neuroinflammation, microglial activation, reduced short-chain fatty acid (SCFA) levels (especially butyrate), and compromised blood-brain barrier function. Bacterial LPS and amyloids may enhance Aβ aggregation and tau hyperphosphorylation. Probiotic supplementation and high-fiber/polyphenol-rich diets were noticed to restore microbial balance, increase SCFA production, attenuate Aβ deposition, and improve cognitive functions in animal models. Modulating gut microbiota shows potential as a complementary strategy for delaying or managing AD. Restoration of microbial equilibrium via dietary or probiotic approaches can mitigate neurodegeneration by targeting inflammation, microbial metabolite production, and immune responses. Further mechanistic studies and longitudinal human trials are needed to validate the clinical efficacy of MGBA-targeted therapies. Personalized microbiome-based interventions may pave the way for novel, non-invasive strategies to combat AD progression.
Characterizing the association between survival time and the dynamic patterns of a longitudinal covariate trajectory is of particular interest in many studies. Classical time-dependent survival models focus mainly on the link between the concurrent covariate value and the instantaneous hazard function. Consequently, the conditional survival function is often not properly defined on the whole time range, which causes difficulty in model estimation and interpretation. In this article, we propose a novel semiparametric joint modeling approach, in which the observed longitudinal trajectory is modeled as a random realization of a latent functional pattern. We assume each latent pattern uniquely indexes a global survival function via a log-linear functional regression model. Because the observational time interval of the longitudinal data depends on the survival time, we propose to jointly model the longitudinal and survival data. By using the latent pattern as an infinite-dimensional shared parameter, our approach extends the classical parametric joint modeling method to a semiparametric setting. We show that the proposed estimator achieves the semiparametric efficiency bound. Simulation studies and a real data application demonstrate the advantageous finite sample performances of our new approach.
Observational studies suggest an association between sleep apnea and dementia, but causality and directionality are unclear. This study investigated bidirectional causal relationships between sleep apnea and various dementia types using two-sample Mendelian randomization (MR). This study used summary-level data from genome-wide association studies (GWAS). Sleep apnea (including obstructive sleep apnea (OSA) and generalized sleep apnea) exposure data were from a European ancestry study. Dementia (general, Alzheimer's, vascular, etc.) outcome/exposure data were from the Finnish FinnGen consortium. The inverse variance weighted (IVW) method was used as the primary analysis, supplemented by multiple analyses (MR-Egger, weighted median, weighted mode). Robustness was assessed using several sensitivity analyses, including MR-PRESSO, Cochran's Q test, and leave-one-out analysis. Forward analysis, after MR-PRESSO outlier correction, showed that OSA was associated with reduced unspecified dementia risk (IVW, OR = 0.830, 95% CI = 0.700-0.970). Reverse analysis, after outlier removal, indicated that general dementia was associated with reduced OSA risk (IVW, OR = 0.9399, 95% CI = 0.9187-0.9615) and generalized sleep apnea risk (IVW, OR = 0.9141, 95% CI = 0.8863-0.9427). Alzheimer's dementia was also associated with reduced OSA and generalized sleep apnea risk. Sensitivity analyses did not reveal significant horizontal pleiotropy for the main findings, and heterogeneity was generally within acceptable limits. This MR study revealed complex, bidirectional genetic associations between sleep apnea and dementia subtypes. These findings provide new genetic insights into the complex interplay between sleep apnea and dementia, highlighting subtype-specific associations.
Identification of natural compounds that delay aging and prevent age-related neurodegeneration is a key goal in gerontology. Fucoxanthin, a marine-derived xanthophyll, exhibits potent antioxidant properties, yet its effects on organismal aging and specific molecular mechanisms remain underexplored. Here, we investigated the pro-longevity and neuroprotective effects of fucoxanthin using Caenorhabditis elegans. Fucoxanthin supplementation significantly extended the mean lifespan of wild-type nematodes by 12.1% and improved health span, as evidenced by delayed age-related motility decline and enhanced resistance to oxidative stress. Notably, this lifespan extension occurred without compromising reproductive fitness. Genetic analysis revealed that the beneficial effects of fucoxanthin require the FOXO transcription factor DAF-16 and the autophagy-essential gene bec-1. Furthermore, fucoxanthin treatment increased autophagic flux and upregulated the expression of SKN-1/Nrf2-dependent detoxification genes, hsp-16.2 and gst-4. In nematode models of Alzheimer's and Parkinson's disease, fucoxanthin significantly ameliorated Aβ-induced paralysis and protected against dopaminergic neurodegeneration and α-synuclein accumulation in a DAF-16-dependent manner. Collectively, our findings demonstrate that fucoxanthin acts as a multitarget geroprotector that promotes healthy aging through the coordinated activation of DAF-16 and autophagy, suggesting its potential as a therapeutic intervention for age-related decline.
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Mood disorders are frequent in memory clinic populations, but their association with language difficulties in the context of cognitive decline is not well understood. The study aimed to examine the association of cognitive decline and mood disorders with two aspects of language performance: verbal fluency and confrontation naming. A total of 183 participants were included in the study. Specifically, 92 individuals with a prior mood disorder diagnosis were categorized by cognitive status into two groups: 48 with mild cognitive impairment (MCI) and 44 neurotypical adults. A random sample of 91 individuals (44 with MCI and 47 without MCI) formed the control group. Two regression models were tested for each variable: verbal fluency and naming. Model A included cognitive status, mood disorder diagnosis, and demographic variables, while Model B further incorporated the Geriatric Depression Scale (GDS) as a measure of depressive symptom severity. Two additional regression models, identical in predictor structure to Model A, were estimated for phonemic and semantic fluency. The results indicate that cognitive decline was the strongest predictor of both verbal fluency and naming, with demographic factors influencing verbal fluency performance. Older age and lower education were associated with poorer performance. In separate models, cognitive status predicted both phonemic and semantic fluency, whereas mood disorder diagnosis was associated with phonemic but not category fluency. Depression severity did not independently predict either outcome. These findings highlight the central role of cognitive status in driving language performance, including both naming and verbal fluency. In contrast, mood disorder diagnosis was selectively associated with phonemic fluency, which relies more on executive control. Current depressive symptom severity did not add explanatory value beyond diagnostic and demographic variables. Assessing these tasks separately may help clinicians distinguish mood-related cognitive difficulties from early cognitive decline.
Age-related macular degeneration (AMD) is caused by the degeneration of photoreceptors and retinal pigment epithelium (RPE) along with drusen deposition and is the leading cause of vision loss in older adults. Both these structures within the central nervous system (CNS) utilize common neuro-inflammatory mechanisms because the retina is an outgrowth of the brain. Like the brain, the eye has its own physical characteristics and surface molecules as well as a tendency towards specific immune reactions. Numerous distinct neurodegenerative diseases like Alzheimer's disease (AD), Parkinson's disease (PD), Amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and Frontotemporal dementia (FTD) that impact the brain present as eye symptoms, and the conventional diagnosis of these neurodegenerative disorders (NDs) is often preceded by ocular symptoms. Furthermore, several eye-specific disorders have characteristics in common with other CNS disorders. NDs and AMD share common key features, such as tau and amyloid-β deposits, oxidative stress response, chronic inflammation, and dysregulation of microglia and müller glia. Common pathological mechanisms include complement activation, amyloid aggregation, neuroinflammation, vascular impairment, and cell death, providing a basis for a convergent neuroimmune axis between retinal and cerebral degeneration. Comparing these age-related diseases will facilitate the identification of shared risk factors, convergent molecular pathways, and potential cross-applicable therapeutic strategies, such as anti-inflammatory, anti-complementary, anti-apoptotic, and anti-VEGF-based approaches. This knowledge may enhance understanding of neurodegenerative diseases, help identify early biomarker development for diagnosis, and enable the design of targeted therapeutic strategies.