Current Alzheimer research最新文献

{"title":"Reconciling Divergent Perspectives: A Deep Analysis of Sex Differences in Alzheimer's Disease Mortality Data.","authors":"Abdul Hadi Khan, Bushra Ubaid, George Perry","doi":"10.2174/0115672050450797260211050217","DOIUrl":"https://doi.org/10.2174/0115672050450797260211050217","url":null,"abstract":"","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amyloid-Beta Immunotherapies for Alzheimer's Disease: Current Progress.","authors":"Firas H Bazzari, Amjad H Bazzari","doi":"10.2174/0115672050468315260226041235","DOIUrl":"https://doi.org/10.2174/0115672050468315260226041235","url":null,"abstract":"<p><p>Alzheimer's Disease (AD) is a major global challenge and the most common cause of dementia worldwide. Accumulation of Amyloid-Beta (Aβ) is considered a key factor in AD pathophysiology and progression, and is linked to disruptions of neuronal integrity and the initiation of several downstream neurodegenerative cascades. Immunotherapeutic agents targeting Aβ have emerged as potential disease-modifying drug candidates, and extensive efforts have been dedicated to both active and passive modalities. Early Aβ vaccines demonstrated proof of concept; however, they were later discontinued due to several safety concerns, which, in turn, guided the refinement of epitope design and immune response modulation in the second-generation ones. On the other hand, early monoclonal antibodies have also faced challenges, such as variable efficacy and adverse events, particularly Amyloid-Related Imaging Abnormalities (ARIA), which ultimately led to their discontinuation. Nonetheless, recent regulatory advances have led to the approvals of Aduhelm® (Aducanumab), Leqembi® (Lecanemab), and Kisunla® (Donanemab), each of which has demonstrated the ability to reduce Aβ burden and slow cognitive decline. Despite these advancements, challenges persist regarding patient selection, biomarker-guided monitoring, ARIA risk reduction, long-term outcomes, and global accessibility. Notably, the clinical benefits observed to date remain modest, and it remains uncertain whether the currently approved Aβ-targeted immunotherapies achieve meaningful long-term disease modification. Collectively, the evolution of Aβ-targeted immunotherapies has provided further insights into the complexity of AD pathology and the challenges associated with future progress toward achieving effective disease modification. This paper aims to provide a comprehensive review of all Aβ-directed immunotherapies, both active and passive agents, that have advanced into clinical trials, including those currently approved, discontinued, or undergoing late-stage evaluation.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147597341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding microRNA-Protein Interaction Networks in Alzheimer's Disease: Molecular Mechanisms and Clinical Implications.","authors":"Ravindra Mishra, Jeetendra Kumar Gupta","doi":"10.2174/0115672050451919260313061818","DOIUrl":"https://doi.org/10.2174/0115672050451919260313061818","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory loss, cognitive decline, and neuronal dysfunction. Despite thorough research efforts, effective disease-modifying treatments have yet to be discovered. MicroRNAs (miRNAs), small noncoding RNAs that control gene expression after transcription, have become key factors in AD development. Changes in miRNA levels influence critical molecular pathways such as amyloid precursor protein (APP) processing, tau phosphorylation, oxidative stress, neuroinflammation, and synaptic plasticity, all of which contribute to neuronal damage. By increasing β-secretase (BACE1) activity, downregulation of miR-29a/b and miR-107 encourages the buildup of amyloid-β (Aβ) and the development of plaques. Through the deregulation of the CDK5 and MAPK pathways, overexpression of miR-125b and decreased levels of miR-132/212 lead to tau hyperphosphorylation. While oxidative stress-associated miRNAs like miR-34a and miR- 21 worsen mitochondrial malfunction and neuronal death, pro-inflammatory miRNAs like miR-146a and miR-155 cause NF-κB-mediated signalling and glial activation. Circulating miRNAs found in blood and cerebral fluid are potential, minimally invasive indicators for tracking the course of a disease and making early diagnoses. Additionally, therapeutic manipulation with antagomiRs or miRNA mimics has the potential to prevent neurodegeneration and restore normal gene regulation. This review deciphers the molecular mechanisms underlying miRNA dysregulation in AD and explores their translational potential as biomarkers and therapeutic targets. A comprehensive understanding of miRNA-protein interaction networks could facilitate the development of targeted, precision- based interventions for Alzheimer's disease.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147597318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Glymphatic System Dysfunction in Alzheimer's Disease: Insights into its Mechanisms, Diagnostic Imaging, and Therapeutic Perspectives: A Systematic Review.","authors":"Shima Mehrabadi, Saeed Samarghandian","doi":"10.2174/0115672050428286260225033532","DOIUrl":"https://doi.org/10.2174/0115672050428286260225033532","url":null,"abstract":"<p><strong>Introduction: </strong>The glymphatic system, a perivascular network that facilitates cerebrospinal fluid (CSF)-mediated clearance of metabolic waste, including amyloid-β (Aβ) and tau, has emerged as a critical player in the pathophysiology of Alzheimer's disease (AD). Growing evidence suggests that an impaired glymphatic function may contribute to the onset and progression of AD by disrupting brain homeostasis and facilitating neurotoxic protein accumulation. This systematic review aims to synthesize current evidence from preclinical and clinical studies investigating the role of glymphatic system dysfunction in Alzheimer's disease, with a focus on its imaging biomarkers, clearance mechanisms, cognitive implications, and therapeutic interventions.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted in PubMed, Scopus, and Web of Science to identify studies published up to June 2025. Thirteen eligible studies were included: five preclinical experiments, eight human imaging or biomarker studies, and one clinical trial protocol. All studies examined glymphatic system function in relation to Aβ or tau clearance, neuroimaging markers (e.g., DTI-ALPS, PVS, PET), cognitive outcomes, or therapeutic modulation (e.g., exercise, sensory stimulation).</p><p><strong>Results: </strong>Preclinical models demonstrate that impaired aquaporin-4 (AQP4) polarization and reduced CSF-interstitial fluid exchange promote Aβ accumulation and plaque formation. Human imaging studies consistently report reduced glymphatic activity in AD and mild cognitive impairment (MCI), often measured via diffusion MRI (ALPS index) and associated with increased amyloid burden, reduced cognitive performance, and altered sleep. Emerging interventions, such as aerobic exercise and 40 Hz gamma sensory stimulation, appear to enhance glymphatic clearance and reduce Aβ levels in experimental settings. A recently published trial protocol is currently evaluating the effects of exercise on glymphatic function in MCI/AD.</p><p><strong>Discussion: </strong>The current body of evidence supports a probable association between glymphatic dysfunction and Alzheimer's disease pathology. Disruption of perivascular clearance pathways may serve as an early biomarker of AD and a novel therapeutic target. Future longitudinal and interventional studies are needed to establish causal relationships and evaluate clinical applications.</p><p><strong>Conclusion: </strong>Glymphatic system impairment plays a significant role in AD pathogenesis, contributing to the accumulation of neurotoxic proteins and cognitive decline. Therapeutic strategies targeting glymphatic function enhancement, such as lifestyle interventions and neuromodulation, hold promise for early prevention and disease modification.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corruption of the Blood-Brain Barrier Literature Identified by 'Tortured Phrases': A Case Study for Bibliometric Neuroethics.","authors":"Jaime A Teixeira da Silva, Timothy Daly, Serhii Nazarovets","doi":"10.2174/0115672050460224260206052444","DOIUrl":"https://doi.org/10.2174/0115672050460224260206052444","url":null,"abstract":"<p><p>Patients living with a neurological disease depend on the integrity of the neuroscience literature to improve the probability of effective treatments becoming available to them. The BloodBrain Barrier (BBB) is one of the key components of the nervous system, and its dysfunction is implicated in different neurological diseases. Non-standardized terms (or 'tortured phrases'; TP) to describe the BBB have emerged in the indexed and non-indexed literature, and their use is suggestive of low-quality science or even misconduct. A total of 13 variants of BBB TPs were initially discovered on Google Scholar on 18-20 April 2024, followed by new variants and cases on 21-30 May 2025. In total, 260 documents (220 journal papers, 26 book chapters, eight conference proceedings, and six preprints), with and without a DOI, were identified. The three most common variants (i.e., TPs) of BBB were blood-brain obstruction, blood-brain boundary, and blood-cerebrum boundary/hindrance, identified in 84, 58, and 31 documents, respectively. Only two variants (bloodmind boundary and blood-brain obstruction) were found in the Tortured Phrase Detector of the Problematic Paper Screener, while a total of four and one documents in Scopus and Web of Science Core Collections databases, respectively, contained any of these BBB TPs. The existence of these 19 variants of TPs suggests the corruption of the associated BBB literature. This study provides a methodological case study for neuroethicists wishing to use bibliometric methods to identify problematic instances of low-quality or insufficiently vetted neuroscience research via an approach that we term \"bibliometric neuroethics.\"</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Technology in Cognitive Decline: Bibliometric and Visualization Study.","authors":"Yihan Huang, Xuejiao Zhu, Shulan Yang, Yunhao Zhang, Zhelu Tan, Shinan Han","doi":"10.2174/0115672050420571260126043841","DOIUrl":"https://doi.org/10.2174/0115672050420571260126043841","url":null,"abstract":"<p><p>With an increasing prevalence of cognitive decline diseases around the world, digital technologies are becoming an important tool for their prevention, diagnosis, and treatment. In this study, we present a comprehensive bibliometric study on the application of these digital technologies in the field of cognitive decline. This study intends to examine the trends of development and research hotspots of digital technology in cognitive decline field by bibliometric analysis. The literature has been analyzed in a systematic way. Bibliometrix R-package and VOSviewer were used to investigate publication tendency, country contribution, scholar influence, and research hotspots. A total of 1661 articles from 2006 to 2023 were analyzed. Results show an exponential increase in the number of annual publications on digital technologies applications and cognitive decline. The top journals, by volume of publication, are Alzheimer's & Dementia, the Journal of Alzheimer's Disease, and Neurology. The US is the dominant contributor of literature to this field, and the key countries for author impact include Greece, the USA, and Italy. Current research hotspots include virtual reality, machine learning, and artificial intelligence, based on analysis of keywords. This study characterizes the overall research progress and reveals research hotspots, trends, and the collaboration status among countries, on the utilization of digital technologies for cognitive decline. Moving forward, we call on researchers to increase developed/developing countries collaboration, to further implement digital technologies to counteract the public health burden of cognitive decline.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Chinese Pre-trained Language Models in Early Detection of Cognitive Impairment: A Comparative Study Based on Spoken Text.","authors":"Xuanshu Chen, Jiaxuan Chen, Yujie Mu, Xindi Pan, Shiwen Feng","doi":"10.2174/0115672050434686260214223520","DOIUrl":"https://doi.org/10.2174/0115672050434686260214223520","url":null,"abstract":"<p><strong>Introduction: </strong>Degenerative cognitive disorders, such as Alzheimer's Disease (AD), impose a substantial burden on societies and families worldwide. Currently, no definitive treatments or curative medications exist, and the academic consensus emphasizes the critical importance of early detection and intervention to mitigate disease progression. With advancements in artificial intelligence, particularly the rapid evolution of Natural Language Processing (NLP) technologies, novel approaches for the early identification of cognitive impairments have emerged. Text embeddings derived from Pre-Trained Language Models (PLMs) offer a promising means to classify spoken language samples, enabling objective assessment of cognitive status. However, research on the application of Chinese PLMs in this domain remains relatively scarce.</p><p><strong>Materials and methods: </strong>Six representative Chinese Pre-Trained Language Models (PLMs) were used as feature extractors to generate text embeddings from transcribed spoken texts. The corpus included 45 healthy young adults, 46 elderly individuals with Mild Cognitive Impairment (MCI), and 48 patients diagnosed with Alzheimer's Disease (AD). These embeddings were combined with four classic machine learning algorithms, Support Vector Machines (SVM), Random Forests (RF), K-Nearest Neighbors (KNN), and Logistic Regression (LR), to conduct classification experiments.</p><p><strong>Results: </strong>Results showed RoBERTa performed best, achieving 95.71% accuracy with SVM, followed by BERT. MacBERT, SimCSE, ERNIE, and BGE had decreasing performance. Among classifiers, SVM and LR outperformed RF and KNN.</p><p><strong>Discussion: </strong>The results of this study not only verify the strong ability of Chinese pre-trained language models in mining semantic degradation features but also indicate that traditional machine learning algorithms still have competitiveness in scenarios with small samples and high-dimensional data. Compared with traditional methods that rely on manually designed language features, the text embedding-based classification strategy in this study undoubtedly shows higher performance.</p><p><strong>Conclusion: </strong>These findings highlight the potential of Chinese PLMs in facilitating early detection of cognitive impairment, providing a technical foundation for developing accessible screening tools for Chinese-speaking populations.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Alzheimer's Disease Risk Assessment Models and Biomarker Screening Based on Bioinformatics Analysis and Machine Learning Algorithms.","authors":"Yazhi Zhang, Ziwei Li, Hanrui Li, Kuixing Zhang","doi":"10.2174/0115672050425330260122093903","DOIUrl":"https://doi.org/10.2174/0115672050425330260122093903","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Introduction: &lt;/strong&gt;Alzheimer's Disease (AD) is among the most prevalent neurodegenerative disorders globally, yet effective early diagnostic strategies remain lacking. Advances in multi-omics technologies and the integration of artificial intelligence into medicine have created new opportunities for developing predictive models for AD. Biomarker-based models hold significant promise for enhancing early detection. In this study, we integrated multi-omics data to identify core risk genes with potential causal links to AD and developed an early diagnostic model, thereby providing a theoretical framework for precision intervention.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We integrated Mendelian Randomization (MR), differential expression analysis, and Weighted Gene Co-Expression Network Analysis (WGCNA) to identify candidate genes with potential causal relevance to AD. Functional enrichment analyses using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), along with immune infiltration profiling, were performed to investigate the biological roles of these genes. We then applied eight machine learning algorithms to evaluate gene importance scores and selected the most diagnostically informative features to construct the Nomogram predictive model. The model's performance was validated in an independent external cohort. Finally, Gene Set Enrichment Analysis (GSEA) was conducted to further elucidate the mechanistic involvement of core risk genes in AD pathogenesis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Integrated analyses using multiple machine learning models (all with AUC values exceeding 0.88) identified VASP, PIP4K2A, RRP36, METTL7A, and AP2M1 as key diagnostic feature genes. The nomogram constructed based on these five genes demonstrated robust diagnostic performance in the validation cohort (AUC = 0.964). Notably, RRP36 and PIP4K2A consistently emerged as core risk genes across diverse machine learning approaches. GSEA results further suggested that RRP36 may contribute to neurodegeneration by modulating cytoskeletal remodeling and neuroinflammatory responses, while PIP4K2A may be implicated in synaptic dysfunction.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Discussion: &lt;/strong&gt;This study is the first to integrate MR, differential gene expression, and WGCNA for systematic AD risk gene discovery, combined with a multi-algorithm machine learning strategy to enhance model robustness and translational potential. RRP36 and PIP4K2A, as core risk genes, may drive AD progression by orchestrating cytoskeletal reorganization, neuroinflammation, and synaptic impairment, offering promising targets for future mechanistic investigations and therapeutic development.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study identified and validated RRP36 and METTL7A as core risk genes for AD. The resulting nomogram, based on a five-gene panel, exhibited high diagnostic accuracy and provides new biomarkers and methodological support for the early screening and precise intervention of","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EEG Oscillations and the Modulation of tES and TMS in Patients with Mild Cognitive Impairment.","authors":"Sheng Hu, Zhuangfei Chen, Yu Fu","doi":"10.2174/0115672050430368260120052142","DOIUrl":"https://doi.org/10.2174/0115672050430368260120052142","url":null,"abstract":"<p><p>Mild cognitive impairment (MCI) is characterized by objective cognitive decline that does not severely impact daily independence. This clinical stage may stem from various underlying causes, including Alzheimer's disease pathology. MCI provides a valuable opportunity to study interventions that could slow cognitive decline. Individuals with MCI show alterations in neural oscillations linked to cognitive impairment. Non-invasive brain stimulation (NIBS) techniques, including transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), along with their major forms, transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), can effectively modulate neural oscillations and improve cognition in MCI patients. Due to the potential of NIBS in the treatment of MCI, this review focuses on EEG abnormalities of neural oscillations in MCI patients and examines how repetitive TMS (rTMS), tDCS, and tACS improve cognitive function by targeting specific EEG frequency bands. A literature review was conducted for this study using the PubMed database, including studies published up to May 2025. Studies demonstrated that MCI patients have significant changes in EEG activity, with increases in the low-frequency band (δ-θ, 0.5-8 Hz) and decreases in the high-frequency band (β-γ, 12-100 Hz), and there are few reports on changes in mid-frequency α (8-12 Hz) EEG activity. Notably, tDCS improves cognition in MCI patients by decreasing low-frequency and increasing highfrequency EEG activity, whereas rTMS and tACS achieve similar effects mainly by increasing highfrequency EEG activity. Overall, this review provides an understanding of the role of NIBS in modulating neural oscillations and improving cognition in MCI, which may guide future therapeutic strategies. Future studies could explore the specific molecular pathways of neural oscillatory dysfunction in MCI and investigate the correlation between neural oscillations and other biomarkers, such as amyloid plaques and tau tangles, for a more comprehensive understanding of the disease.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147518154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and Safety of Donanemab in the Treatment of Alzheimer's Disease: A Systematic Review and Meta-Analysis.","authors":"Guanqun Hu, Meiyun Zhang","doi":"10.2174/0115672050425914260119063736","DOIUrl":"https://doi.org/10.2174/0115672050425914260119063736","url":null,"abstract":"<p><strong>Introduction: </strong>Donanemab is a monoclonal antibody targeting amyloid-β plaques. This study aims to quantify donanemab's consistent cognitive benefits, biomarker efficacy, and safety risks by pooling data from all available RCTs.</p><p><strong>Materials and methods: </strong>Systematic searches were conducted in PubMed, the Cochrane Library, Web of Science, and Embase. Phase II/III randomized controlled trials comparing donanemab with placebo in amyloid-positive early Alzheimer's disease were included. After screening 133 records, two trials met the inclusion criteria.</p><p><strong>Results: </strong>Donanemab significantly reduced cognitive decline (iADRS +2.93; 95% CI: 1.52- 4.33; P < 0.0001) and functional progression (CDR-SB -0.66; 95% CI: -0.90 to -0.42; P < 0.00001), with amplified benefits in low/medium tau burden patients (iADRS +3.80; 95% CI: 2.10- 5.50). Amyloid clearance was dramatically higher with donanemab (risk ratio (RR) = 234.46; 95% CI: 68.17-806.38; P < 0.00001), with 76.4% achieving amyloid-negative status. There were significantly elevated risks of ARIA-E (RR = 12.90; 95% CI: 8.15-20.43; P < 0.00001), ARIA-H (RR = 2.86; 95% CI: 1.61-5.06; P = 0.0003), and treatment discontinuation (RR = 3.26; 95% CI: 2.38- 4.47; P < 0.00001), whereas all-cause mortality was not significantly different (RR = 1.44; 95% CI: 0.69-3.00).</p><p><strong>Discussion: </strong>Donanemab showed statistically significant cognitive benefits, but its clinical meaningfulness warrants careful interpretation. The iADRS improvement of 2.93 points and the CDRSB reduction in all patients of 0.66 points did not approach their minimal clinically important difference (MCID).</p><p><strong>Conclusion: </strong>Donanemab provides statistically significant but modest benefits in early AD, particularly in low-tau subgroups. However, the magnitude of cognitive and functional improvement did not approach the threshold for a MCID in the overall population, which requires stringent safety monitoring for ARIA. Clinical implementation should prioritize PET stratification and APOEguided surveillance.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147518159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}