Journal of Alzheimer's Disease最新文献

{"title":"Memory improvements among older adults with memory complaints and mild cognitive impairment after lifestyle intervention: An uncontrolled trial.","authors":"Zihan Ding, Tiffany Wing-Yin Pang, Agnes S Chan","doi":"10.1177/13872877251360209","DOIUrl":"https://doi.org/10.1177/13872877251360209","url":null,"abstract":"<p><p>BackgroundAlzheimer's disease (AD) is associated with various modifiable lifestyle risk factors, making lifestyle intervention a potentially viable approach to prevent or delay the onset of AD.ObjectiveTo investigate whether a one-month smartphone app-aided lifestyle medicine program could improve memory of older adults at risk of AD, including those with subjective memory complaints (SMC) and mild cognitive impairment (MCI).Methods158 community-dwelling older adults aged 60-80 years were recruited, including 31 older adults with normal cognition (NC), 104 with SMC, and 23 with MCI. The three groups were matched in age, education level, and gender. All the participants attended four weekly face-to-face workshops and completed daily homework with guidance from a smartphone app. Verbal learning and memory were assessed using Hong Kong List Learning Test (HKLLT) before and after intervention. This study was an uncontrolled trial.ResultsAfter the intervention, older adults improved significantly in learning and memory, with MCI benefiting the most. 94% of amnestic MCI cases showed clinically significant improvements in verbal memory. Besides, a substantial proportion of the MCI group (57% - 77%) and the SMC group (54% - 63%) demonstrated improvements in learning and memory that fulfilled the reliable and clinically significant change criteria, suggesting that the positive effects were not solely attributable to practicing effect. The extents of improvements were significantly predicted by baseline performance, gender, and/or compliance rate.ConclusionsImproved verbal learning and memory were observed in older adults with SMC and MCI after the smartphone app-supported lifestyle medicine program.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251360209"},"PeriodicalIF":3.4,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized sequential classification models for mild cognitive impairment screening based on handwriting and speech data.","authors":"Qizhe Tang, Xiaoya Zhang, Chu Zhang, Qing Lang, Hengnian Qi, Lina Wang","doi":"10.1177/13872877251359874","DOIUrl":"https://doi.org/10.1177/13872877251359874","url":null,"abstract":"<p><p>BackgroundHandwriting and speech are served as reliable signatures for detecting cognitive decline, playing a pivotal role in the early diagnosing Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, current unimodal approaches for diagnosing AD and MCI have demonstrated constraints in classification accuracy, potentially overlooking the synergistic value of combining handwriting and speech data.ObjectivePresenting an innovative multi-modal screening classification model, that harnesses handwriting and speech analysis to enhance MCI detection, aiming to overcome the constraints of single-modality approaches by integrating data from both modalities, thereby improving diagnostic accuracy.MethodsProposing a multimodal classification model based on gated recurrent unit (GRU) and attention mechanism, treating handwriting and speech data as sequence inputs. The model was constructed and tested on a dataset of 41 participants, including 20 MCI patients and 21 cognitively normal (CN) individuals. To mitigate the risk of overfitting due to the small sample size, we employed a 10-fold cross-validation strategy to ensure the robustness of the results.ResultsOur multimodal classification model achieved an accuracy of 95.2% for MCI versus CN individuals, which shows a significant improvement compared to the results of single-modality. This result indicates the effectiveness of the cross-fusion model in enhancing classification performance, offering a promising approach for the early diagnosis of neurodegenerative diseases.ConclusionsThe proposed GRU_CA effectively improves early MCI detection by fusing handwriting and speech data, outperforming a single modality. It shows strong potential for deployment in primary healthcare settings and establishes a foundation for future research on more complex diagnostic tasks, including CN, MCI, and AD classification, as well as longitudinal studies.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251359874"},"PeriodicalIF":3.4,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between digital speech features of automated cognitive tasks and trajectories of brain atrophy and cognitive decline in early Alzheimer's disease.","authors":"Qingyue Li, Stefanie Koehler, Alexandra Koenig, Martin Dyrba, Elisa Mallik, Nicklas Linz, Josef Priller, Eike Spruth, Slawek Altenstein, Jens Wiltfang, Inga Zerr, Claudia Bartels, Franziska Maier, Ayda Rostamzadeh, Emrah Duezel, Wenzel Glanz, Enise I Incesoy, Michaela Butryn, Christoph Laske, Sebastian Sodenkamp, Matthias Hj Munk, Bjoern Falkenburger, Antje Osterrath, Ingo Kilimann, Melina Stark, Luca Kleineidam, Michael T Heneka, Annika Spottke, Michael Wagner, Frank Jessen, Gabor C Petzold, Fedor Levin, Stefan Teipel","doi":"10.1177/13872877251359967","DOIUrl":"https://doi.org/10.1177/13872877251359967","url":null,"abstract":"<p><p>BackgroundSpeech-based features extracted from telephone-based cognitive tasks show promise for detecting cognitive decline in prodromal and manifest dementia. Little is known about the cerebral underpinnings of these speech features.ObjectiveTo examine associations between speech features, brain atrophy, and longitudinal cognitive decline in individuals at risk for Alzheimer's disease (AD).MethodsHealthy volunteers, individuals with subjective cognitive decline, and those with mild cognitive impairment completed phonebot-guided semantic verbal fluency (SVF) and 15-word verbal learning task (VLT). Speech features were automatically extracted, and a global cognitive score (SB-C score) was computed. We analyzed data from 161 participants for cognitive trajectories, 141 for cross-sectional brain atrophy, and 102 for longitudinal brain changes. Analyses were conducted using multiple linear regressions, mixed-effects models, and voxel-based morphometry.ResultsThe SB-C score was associated with bilateral hippocampal volumes, SVF features were primarily associated with left hemisphere regions, including the inferior frontal, parahippocampal, and superior/middle temporal gyri (<i>p</i>_uncorr < 0.001). SB-C score, SVF correct counts, and VLT delayed recall were associated with atrophy rates in the hippocampal/parahippocampal gyrus and left middle/inferior temporal gyri (<i>p</i>_FDR < 0.05). These features were also associated with cognitive decline assessed via Preclinical Alzheimer's Cognitive Composite 5, SVF, and Wordlist learning delayed recall (<i>p</i>_FDR < 0.01). Word frequency and temporal cluster switches showed varying associations with cognitive trajectories. Other features did not show robust associations.ConclusionsIn this study, we highlight the potential of digital speech features for identifying brain atrophy and cognitive decline over time in at-risk AD populations.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251359967"},"PeriodicalIF":3.4,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing an accessible dementia assessment tool: Leveraging a residual network, the trail making test, and demographic data.","authors":"Jingmei Yang, Samad Amini, Boran Hao, Seho Park, Cody Karjadi, Lance San Souci, Vijaya B Kolachalama, Stephanie Cosentino, Stacy L Andersen, Rhoda Au, Ioannis Ch Paschalidis","doi":"10.1177/13872877251359889","DOIUrl":"10.1177/13872877251359889","url":null,"abstract":"<p><p>BackgroundThe global burden of Alzheimer's disease and related dementias is rapidly increasing, particularly in low- and middle-income countries where access to specialized healthcare is limited. Neuropsychological tests are essential diagnostic tools, but their administration requires trained professionals, creating screening barriers. Automated computational assessment presents a cost-effective solution for global dementia screening.ObjectiveTo develop and validate an artificial intelligence-based screening tool using the Trail Making Test (TMT), demographic information, completion times, and drawing analysis for enhanced dementia detection.MethodsWe developed: (1) non-image models using demographics and TMT completion times, (2) image-only models, and (3) fusion models. Models were trained and validated on data from the Framingham Heart Study (FHS) (<i>N</i> = 1252), the Long Life Family Study (LLFS) (<i>N</i> = 1613), and the combined cohort (<i>N</i> = 2865).ResultsOur models, integrating TMT drawings, demographics, and completion times, excelled in distinguishing dementia from normal cognition. In the LLFS cohort, we achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 98<i>.</i>62%, with sensitivity/specificity of 87<i>.</i>69%/98<i>.</i>26%. In the FHS cohort, we obtained an AUC of 96<i>.</i>51%, with sensitivity/specificity of 85<i>.</i>00%/96<i>.</i>75%.ConclusionsOur method demonstrated superior performance compared to traditional approaches using age and TMT completion time. Adding images captures subtler nuances from the TMT drawing that traditional methods miss. Integrating the TMT drawing into cognitive assessments enables effective dementia screening. Future studies could aim to expand data collection to include more diverse cohorts, particularly from less-resourced regions.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251359889"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing structure-function coupling in subjective memory complaints of preclinical Alzheimer's disease.","authors":"Cunsheng Wei, Jianing Wang, Yingying Xue, Junying Jiang, Meng Cao, Shenghua Li, Xuemei Chen","doi":"10.1177/13872877251360259","DOIUrl":"https://doi.org/10.1177/13872877251360259","url":null,"abstract":"<p><p>BackgroundSubjective cognitive decline (SCD) is recognized as an early phase in the progression of Alzheimer's disease (AD).ObjectiveTo explore the abnormal patterns of morphological and functional connectivity coupling (MC-FC coupling) and their potential diagnostic significance in SCD.MethodsThe data of 52 individuals with SCD and 51 age-gender-education matched healthy controls (HC) who underwent resting-state functional magnetic resonance imaging and high-resolution 3D T₁-weighted imaging were retrieved to build the MC and FC of gray matter. Support vector machine (SVM) methods were used for differentiating between SCD and HC.ResultsSCD individuals exhibited MC-FC decoupling in the frontoparietal network compared with HC (p = 0.002, 5000 permutations). Using these adjusted MC-FC coupling metrics, SVM analysis achieved 74.76% accuracy, 64.71% sensitivity, and 92.31% specificity (p < 0.001, 5000 permutations). Additionally, the stronger MC-FC coupling of the left inferior temporal gyrus (r = 0.294, p = 0.034) and right posterior cingulate gyrus (r = 0.372, p = 0.007) in SCD individuals was positively correlated with subjective memory complaint performance.ConclusionsThe findings of this study provide insight into the idiosyncratic feature of brain organization underlying SCD from the prospective of MC-FC coupling and highlight the potential of MC-FC coupling for the identification of the preclinical stage of AD.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251360259"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural flexibility is higher in Alzheimer's disease and predicts Alzheimer's disease transition.","authors":"Eleanna Varangis, Jun Liu, Yuqi Miao, Xi Zhu, Yaakov Stern, Seonjoo Lee","doi":"10.1177/13872877251360025","DOIUrl":"https://doi.org/10.1177/13872877251360025","url":null,"abstract":"<p><p>BackgroundNeural flexibility (NF), a measure of dynamic functional connectivity, was associated with psychiatric diseases but has not yet been studied in Alzheimer's disease (AD).ObjectiveWe aim to evaluate whether AD is associated with alterations in NF and probe its predictive utility for AD conversion.MethodThe study included 862 older adults (461 cognitively normal (CN), 294 mild cognitive impairment (MCI), 107 AD) with valid resting-state fMRI data from the Alzheimer's Disease Neuroimaging Initiative. We defined the NF of a node as the number of times that a node changed its community assignment across the sliding windows, normalized by the total number of possible changes. We computed global NF and 12 functional network-specific NFs, then performed linear mixed models on NFs separately to explore the differences in these measures between our three groups. Finally, we evaluated the predictive utility of NF on dementia transition using survival analysis.ResultsNF is significantly higher in AD than CN on global NF (β = 0.002, 95% CI 0.001 to 0.004), and NF in six networks, and NF is significantly higher in MCI than CN in the visual network. Among n = 617 non-demented participants at baseline, n = 53 (8.6%) participants converted to dementia during the follow-up visits. Higher NF in the visual network was positively associated with AD transition (HR = 1.323, 95%CI 1.002 to 1.747, p = 0.049, per 1 SD in NF), controlling for age, gender, and education.ConclusionsWe found that NF during rest was higher in AD patients and predicted dementia transition. Thus, NF may be a valuable biomarker of AD; however, more validation and mechanistic studies need to be performed.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251360025"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of resistance exercise on cognitive function, neurotrophic factors, brain structure, and brain function in older adults: A narrative review.","authors":"Wanting Jiang, Xing Wang, Lijuan Mao","doi":"10.1177/13872877251359630","DOIUrl":"https://doi.org/10.1177/13872877251359630","url":null,"abstract":"<p><p>Cognitive decline is age-specific or related to dementia and Alzheimer's disease (AD), which poses great concern to older adults. Exercise contributes to cognitive gains, with aerobic exercise (AE) being the most commonly studied type. However, other types, such as resistance exercise (RE), have received less attention in exercise-cognition research. This narrative review aims to synthesize evidence addressing the effects of RE, including the influence of its various parameters on cognitive function in older adults. It also examines the adaptations of neurotrophic factors, brain structure, and brain function in response to RE and explores the relationship between these adaptive responses and cognitive function. A comprehensive search of PubMed databases was conducted up to Jan 2025, identifying 41 randomized controlled trials for inclusion. RE may effectively improve executive function, memory function, and global cognition in older adults with and without cognitive impairment. However, optimal exercise parameters, such as intensity, frequency, and length, remain to be established. Evidence suggests that RE may elevate peripheral insulin-like growth factor 1 levels, increase gray matter thickness, mitigate hippocampal atrophy, and enhance brain activation, all of which appear to contribute to cognitive improvements. Collectively, these studies advance our understanding of the potential role of RE in promoting cognitive and brain health during aging.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251359630"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Baseline and longitudinal changes in cortical thickness and hippocampal volume predict cognitive decline.","authors":"Gengsheng Chen, Nicole S McKay, Brian A Gordon, Nelly Joseph-Mathurin, Jingxia Liu, Suzanne E Schindler, Jason Hassenstab, Stephanie Doering, Andrew J Aschenbrenner, Qing Wang, Pamela J LaMontagne, Sarah J Keefe, Parinaz Massoumzadeh, Carlos Cruchaga, Chengjie Xiong, John C Morris, Tammie Ls Benzinger","doi":"10.1177/13872877251352202","DOIUrl":"https://doi.org/10.1177/13872877251352202","url":null,"abstract":"<p><p>BackgroundAs we transition to disease-modifying treatment for Alzheimer's disease (AD), identifying individuals most at risk for future cognitive decline is crucial. Amyloid PET, cerebrospinal fluid and more recently blood-based biomarkers can identify the first stage of AD. However, changes detectable by PiB-PET may precede the onset of the dementia by 20-30 years. MRI is a widely available tool for detecting longitudinal changes in brain structure, such as cortical thickness and hippocampal volume and may provide additional insight into which patients are at greatest risk to develop cognitive decline.ObjectiveTo determine how well the hippocampal volume and cortical thickness, without specific AD biomarkers, can predict cognitive decline.MethodsMRI data from 344 participants (cognitively unimpaired or mild cognitive impairment, age 50-86) were used to evaluate if changes in cortical thickness and hippocampal volume predict cognitive decline, measured by a global cognitive composite score. A random coefficient model was employed to calculate longitudinal changes in cortical thickness and hippocampal volume and assess their ability to predict cognitive decline.ResultsBaseline cortical thickness as well as hippocampal volume predicted cognitive decline, regardless of baseline cognitive status. In individuals unimpaired at baseline, decreases in cortical thickness and hippocampal volume independently predicted cognitive decline. For participants with baseline mild impairment, decreases in hippocampal volume predicted further cognitive decline.ConclusionsThese findings indicate that MRI could serve as an effective tool for identifying individuals at elevated risk of cognitive decline, a growing public health concern as global populations continue to age.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251352202"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amyloid-β protein precursor modulates mitophagy and mitochondrial function through its cellular localization.","authors":"Taylor A Strope, Benjamin Troutwine, Brittany M Hauger, Keith P Smith, Russell H Swerdlow, Heather M Wilkins","doi":"10.1177/13872877251360243","DOIUrl":"https://doi.org/10.1177/13872877251360243","url":null,"abstract":"<p><p>BackgroundAmyloid-β (Aβ) is generated from amyloid-β protein precursor (AβPP) via secretase enzymes. While AβPP processing and its localization are well understood, the function of AβPP is largely unknown. AβPP has been shown to localize to mitochondria, but the consequence of this is not understood.ObjectiveWe examined the consequences of modulating mitochondrial AβPP content on mitochondrial function.MethodsWe measured mitochondrial AβPP localization in postmortem human brain from non-demented and AD subjects. To understand the effects of mitochondrial localization of AβPP on mitochondria, we leveraged AβPP constructs with increased (D23A) or decreased (3 M) mitochondrial localization compared to a wild-type (WT) construct. We measured mitochondrial function including dynamics and mitophagy.ResultsWe observed increased AβPP mitochondrial localization in postmortem brain of sporadic AD subjects. Increased or decreased mitochondrial AβPP content led to reduced electron transport chain (ETC) activities, reduced ATP levels, increased mitochondrial superoxide production, hyperpolarized mitochondrial membrane potential, and increased mitochondrial calcium content. Reduced mitochondrial AβPP content reduced mitophagy flux, while increased mitochondrial AβPP content increased mitophagy flux. Increased or decreased mitochondrial AβPP content reduced mitochondrial biogenesis. We identified interactions between AβPP and mitophagy/autophagy proteins. We next examined if a specific motif in AβPP was responsible for alterations in mitochondrial function and mitophagy. Mitophagy flux was inhibited with expression of ΔCT AβPP, suggesting a role for the C-terminus of AβPP in mitophagy induction.ConclusionsOverall, these findings highlight a critical role of AβPP in mitochondrial physiology. Alterations to AβPP mitochondrial content can lead to mitochondrial dysfunction.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251360243"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational screening of repurposed drugs targeting lactoferrin for neurodegenerative diseases.","authors":"Mohammed Alrouji, Mohammed S Alshammari, Fahad Alhumaydhi, Moyad Shahwan, Sharaf E Sharaf, Sami Saad Alghamdi, Akhtar Atiya, Anas Shamsi","doi":"10.1177/13872877251359648","DOIUrl":"https://doi.org/10.1177/13872877251359648","url":null,"abstract":"<p><p>BackgroundLactoferrin (LTF), a conserved glycoprotein, plays a pivotal role in iron homeostasis, oxidative stress management, and anti-inflammatory responses. Its high iron-binding affinity and protective actions make it a promising therapeutic target for neurodegenerative diseases, including Alzheimer's and Parkinson's, characterized by oxidative damage and disrupted metal homeostasis.ObjectiveThis study aimed to identify FDA-approved drugs that can be repurposed to modulate LTFs activity, providing a cost-effective therapeutic strategy for neurodegenerative diseases.MethodsWe employed molecular docking to screen a library of ∼3500 FDA-approved drugs for binding affinity to LTF. Drug profiling and PASS analysis were used to predict biological activities. Molecular dynamics (MD) simulations evaluated the stability of LTF-drug complexes, with key parameters such as RMSD, RMSF, radius of gyration, solvent-accessible surface area, and hydrogen bonding assessed. Principal component analysis and free energy landscape mapping further explored protein-ligand interactions and conformational stability.ResultsTen drugs with high binding affinities were identified, among which Mosapramine and Quinupramine emerged as promising candidates based on their drug profiling and PASS activities. These drugs demonstrated stable binding to LTFs iron-binding pocket, as confirmed by MD simulations. Drug profiling indicated neuroprotective properties, including anti-inflammatory and cognitive-enhancing activities. PCA and free energy analyses revealed conformational stability of the LTF-drug complexes.ConclusionsThis study highlights Mosapramine and Quinupramine as potential modulators of LTF for neurodegenerative diseases. The findings underscore the efficacy of computational screening in repurposing drugs, paving the way for further experimental validation and therapeutic development.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":" ","pages":"13872877251359648"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}