Curr Alzheimer Res [JOURNAL]
Sun
200 papers
Voice Biomarkers: Cognitive Impairment, including Alzheimer's Disease, Dementia, or Mild Cognitive Impairment: Introduction to Peripheral Neuropathy.
Özcan F
Curr Alzheimer Res · 2026 Apr · PMID 41944116 · Publisher ↗
INTRODUCTION/OBJECTIVE: Alzheimer's disease (AD) can cause certain nervous disorders, which in turn can lead to voice disorders and abnormal values for certain acoustic parameters. Mild cognitive impairment (MCI) is prob...
INTRODUCTION/OBJECTIVE: Alzheimer's disease (AD) can cause certain nervous disorders, which in turn can lead to voice disorders and abnormal values for certain acoustic parameters. Mild cognitive impairment (MCI) is probably the early stage of the disease. Dementia is one of the causes of Alzheimer's disease. Whether or not there is a link between these three cognitive impairments, lesions affecting the vocal cords or articulators can be caused by neurological structures that influence phonation. The potential of biomarkers in the detection of cognitive impairment is remarkable. In our study, we will examine vocal biomarkers obtained from the extraction of acoustic features. The aim of this study is to combine vocal biomarkers with cognitive diseases. METHODS: The standardised dataset used has recently been made publicly available. Cognitive impairment, including Alzheimer's disease, dementia, or MCI, is diagnosed from /a/ and diadochokinesis-pataka vocalisations using Mel-Frequency Cepstral Coefficients (MFCCs) transformed into 2D scalogram images. For processing, we will use the pre-trained OpenL3 network, and our less resource-intensive network called Op1Net to classify diseased and healthy groups. RESULTS: A significant difference was observed compared to the control group. For the /a/ vocalisation, classification accuracy across all ages and genders was 82.1%, and the AUC value was 88.3%, while for diadochokinesis-pataka, accuracy was 69.8% and the AUC value was 75.4%. In the group of women over 55 years of age, the accuracy was 80.93%, and the AUC value was 87.12%. DISCUSSION: Performance results clearly show that there is a correlation between the voice and the neurodegenerative disease AD, dementia, or MCI. We can see that the results of the data classification, including all ages and genders, for the sound /a/ are higher than those for the 'pataka' vocalisations. The prolonged vowel provides more information about the disease. CONCLUSION: This preliminary multidisciplinary study clearly demonstrates the existence of a link between neurological disease and the voice, and raises several questions concerning the nervous system, particularly the vagus nerve and associated neuropathy.
Rapidly Progressive Dementia Secondary to Vitamin B12 Deficiency: A Case Report.
Xu R, Wang H, Jiang X … +1 more , Wang L
Curr Alzheimer Res · 2026 Apr · PMID 41935355 · Publisher ↗
INTRODUCTION: While vitamin B12 deficiency is classically associated with hematological abnormalities and subacute combined degeneration, its presentation as rapidly progressive cognitive decline with episodic movement d...
INTRODUCTION: While vitamin B12 deficiency is classically associated with hematological abnormalities and subacute combined degeneration, its presentation as rapidly progressive cognitive decline with episodic movement disorders remains an underrecognized clinical phenomenon. This case highlights the diagnostic challenges posed by such non-classical neurological manifestations and underscores the need for increased clinical suspicion in cases of unexplained cognitive-motor decline. CASE PRESENTATION: A patient presented with rapidly progressive memory impairment and episodic limb tremors in the absence of overt hematological signs. Serum anti-parietal cell antibody (Anti- PCA) was positive (++; titer 1:32), and anti-intrinsic factor antibody (Anti-IFA) was positive (+) in the patient. Extensive diagnostic workup ruled out common neurodegenerative and structural causes, leading to the detection of severe vitamin B12 deficiency. Initiation of high-dose B12 replacement therapy resulted in marked improvement in both cognitive function and tremor control over subsequent weeks. CONCLUSION: This case illustrates that vitamin B12 deficiency can manifest as a rapidly progressive neurocognitive disorder mimicking neurodegenerative conditions. It emphasizes the importance of routinely assessing B12 status in patients with unexplained cognitive and movement abnormalities, as timely intervention can prevent irreversible neurological injury and yield significant clinical improvement.
Glymphatic System Dysfunction in Alzheimer's Disease: Insights into its Mechanisms, Diagnostic Imaging, and Therapeutic Perspectives: A Systematic Review.
Mehrabadi S, Samarghandian S
Curr Alzheimer Res · 2026 Mar · PMID 41928632 · Publisher ↗
INTRODUCTION: 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 path...
INTRODUCTION: 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. METHODS: 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). RESULTS: 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. DISCUSSION: 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. CONCLUSION: 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.
Digital Technology in Cognitive Decline: Bibliometric and Visualization Study.
Huang Y, Zhu X, Yang S … +3 more , Zhang Y, Tan Z, Han S
Curr Alzheimer Res · 2026 Mar · PMID 41928631 · Publisher ↗
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...
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.
Application of Chinese Pre-trained Language Models in Early Detection of Cognitive Impairment: A Comparative Study Based on Spoken Text.
Chen X, Chen J, Mu Y … +2 more , Pan X, Feng S
Curr Alzheimer Res · 2026 Mar · PMID 41928630 · Publisher ↗
INTRODUCTION: 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 th...
INTRODUCTION: 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. MATERIALS AND METHODS: 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. RESULTS: 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. DISCUSSION: 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. CONCLUSION: 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.
Corruption of the Blood-Brain Barrier Literature Identified by 'Tortured Phrases': A Case Study for Bibliometric Neuroethics.
Teixeira da Silva JA, Daly T, Nazarovets S
Curr Alzheimer Res · 2026 Mar · PMID 41928629 · Publisher ↗
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...
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."
Reconciling Divergent Perspectives: A Deep Analysis of Sex Differences in Alzheimer's Disease Mortality Data.
Khan AH, Ubaid B, Perry G
Curr Alzheimer Res · 2026 Mar · PMID 41926311 · Publisher ↗
Abstract loading — click title to view on PubMed.
Effects of DW2009 on BDNF Levels as a Secondary Analysis of a Randomized Controlled Trial Across Sociodemographic Subgroups.
Kim MC, Won DY, Kim H … +3 more , Paik JW, Lee AR, Hwang YH
Curr Alzheimer Res · 2026 Mar · PMID 41926310 · Publisher ↗
INTRODUCTION: The prevalence of neurodegenerative disorders continues to increase with population aging. Brain-derived neurotrophic factor is a biomarker of cognitive function and neuroprotection. Lactobacillus plantarum...
INTRODUCTION: The prevalence of neurodegenerative disorders continues to increase with population aging. Brain-derived neurotrophic factor is a biomarker of cognitive function and neuroprotection. Lactobacillus plantarum C29-fermented soybean (DW2009) has been suggested to enhance cognition by modulating brain-derived neurotrophic factor. This secondary analysis of a randomized, double-blind, placebo-controlled trial investigated the influence of sociodemographic and lifestyle factors on serum brain-derived neurotrophic factor responsiveness to DW2009 supplementation. METHODS: One hundred adults (age: 55-85 years) with mild cognitive impairment were randomized 1:1 to receive DW2009 (800 mg/day) or placebo (800 mg/day) for 12 weeks. The participants were examined, and their cognitive clinical features and serum brain-derived neurotrophic factor (BDNF) levels were measured at baseline and after a 12-week period. RESULTS: We found that DW2009 significantly increased serum BDNF levels, especially in older men (≥ 68 years) and in those with lower educational attainment (≤ 11 years). Subgroup analysis also indicated that the effect of DW2009 was enhanced in participants who performed frequent physical activity (≥ 5 times/week) and those within the normal body mass index range (18.5-22.9 kg/m²). DISCUSSION: Our findings suggest that the increase in serum BDNF after DW2009 supplementation is dependent on baseline characteristics, although this interpretation requires confirmation. CONCLUSION: DW2009 intake was linked to increased serum BDNF levels in individuals with specific sociodemographic and lifestyle characteristics. These findings suggest that personalized supplementation strategies may optimize functional benefits for cognitive health.
Decoding microRNA-Protein Interaction Networks in Alzheimer's Disease: Molecular Mechanisms and Clinical Implications.
Mishra R, Gupta JK
Curr Alzheimer Res · 2026 Mar · PMID 41918207 · Publisher ↗
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 ha...
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.
Amyloid-Beta Immunotherapies for Alzheimer's Disease: Current Progress.
Bazzari FH, Bazzari AH
Curr Alzheimer Res · 2026 Mar · PMID 41918206 · Publisher ↗
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 d...
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.
Associations between Handwriting Decline and Cognitive-Motor Impairment in Dementia.
Chernov Y
Curr Alzheimer Res · 2026 Mar · PMID 41879491 · Publisher ↗
INTRODUCTION: Handwriting reflects the integration of cognitive and motor functions, making it a potential indicator of neurodegenerative changes. Handwriting deterioration often mirrors cognitive and motor decline in de...
INTRODUCTION: Handwriting reflects the integration of cognitive and motor functions, making it a potential indicator of neurodegenerative changes. Handwriting deterioration often mirrors cognitive and motor decline in dementia, particularly Alzheimer's disease (AD). However, objective assessment methods remain limited. This study is based on the AD-HS instrument, which includes 42 handwriting features and three linguistic features. Their assessment is non-trivial. To ensure an objective and reliable evaluation, the features are given exact and unambiguous definitions. The formal, quantitative association of handwriting dimensions with cognitive and motor changes in dementia enriches previously published statistical results. MATERIALS AND METHODS: Handwriting samples from 53 individuals with mild cognitive impairment (MCI) or Alzheimer's disease (AD) were analyzed against a reference group across six dimensions: spatial organization, letter formation, writing dynamics, stroke building, and overall appearance. Statistical analysis determined the significance of each dimension and its contribution to the overall AD-index (ADI). RESULTS: The ADI effectively distinguished dementia samples from the reference group. The strongest diagnostic indicators were found in writing dynamics, followed by letter formation and spatial organization. The characteristics of early deterioration reflect cognitive impairment rather than purely motor impairment, which are less prevalent in the early stages. DISCUSSION: Longitudinal data show that handwriting in early dementia deteriorates gradually, with diagnostic value arising from the combined presence of multiple affected features. The earliest changes appear in dynamic aspects, followed by spatial and organizational deficits, reflecting early cognitive disruption while motor programs remain largely intact. These findings support the validity of the AD-HS instrument for capturing handwriting changes associated with emerging dementia. CONCLUSION: The ADI offers a concise, quantitative measure of handwriting deterioration related to cognitive decline. Future research should focus on collecting longitudinal data and more strictly differentiating between age-related changes and cognitive decline.
Efficacy and Safety of Donanemab in the Treatment of Alzheimer's Disease: A Systematic Review and Meta-Analysis.
Hu G, Zhang M
Curr Alzheimer Res · 2026 Mar · PMID 41879436 · Publisher ↗
INTRODUCTION: 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...
INTRODUCTION: 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. MATERIALS AND METHODS: 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. RESULTS: 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). DISCUSSION: 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). CONCLUSION: 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.
Research on Alzheimer's Disease Risk Assessment Models and Biomarker Screening Based on Bioinformatics Analysis and Machine Learning Algorithms.
Zhang Y, Li Z, Li H … +1 more , Zhang K
Curr Alzheimer Res · 2026 Mar · PMID 41879435 · Publisher ↗
INTRODUCTION: 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...
INTRODUCTION: 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. METHODS: 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. RESULTS: 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. DISCUSSION: 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. CONCLUSION: 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 AD.
EEG Oscillations and the Modulation of tES and TMS in Patients with Mild Cognitive Impairment.
Hu S, Chen Z, Fu Y
Curr Alzheimer Res · 2026 Mar · PMID 41879434 · Publisher ↗
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...
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.
Advancing Smell Disorder Diagnostics: A Comparative Review of Portable Test Kits and Self-Reported Tools.
Ramesh J, Kanakaraj L, Duza MB
Curr Alzheimer Res · 2026 Mar · PMID 41830121 · Publisher ↗
<p> Olfactory Dysfunction (OD) is a prevalent yet underdiagnosed sensory disorder with profound implications for quality of life and for the early detection of neurodegenerative diseases such as Parkinson's and Alzheimer...
<p> Olfactory Dysfunction (OD) is a prevalent yet underdiagnosed sensory disorder with profound implications for quality of life and for the early detection of neurodegenerative diseases such as Parkinson's and Alzheimer's. Beyond its sensory role, OD has emerged as an early, noninvasive biomarker of neurodegenerative pathology, often preceding measurable cognitive decline in Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). Quantitative smell loss correlates with pathological changes in the olfactory bulb and entorhinal cortex, highlighting its diagnostic potential for early screening and longitudinal monitoring. </p><p> Traditional diagnostic tools, though validated, often require specialized personnel, laboratory infrastructure, and extended testing time, limiting accessibility. This review critically examines recent innovations in the detection of olfactory dysfunction, focusing on portable, user-friendly smell test kits and their comparative performance with self-reported tools such as the Mini Olfactory Questionnaire (Self-MOQ) and 4-CAST. We synthesize evidence on diagnostic reliability, usability, and cultural adaptability, evaluating how these methods align with emerging needs in Alzheimer's and dementia research. </p><p> Portable kits such as PT-Smell and SSomix demonstrate high diagnostic precision and cultural adaptability, while self-administered and self-report tools enable scalable deployment in memory clinics and community screening programs. Within Alzheimer's research, these approaches present practical solutions for early identification of sensory biomarkers linked to cognitive decline. </p><p> To optimize diagnostic integration, a two-step framework is proposed: first-line screening with self-administered tools such as Self-MOQ or 4-CAST, followed by confirmatory psychophysical testing with portable kits such as PT-Smell or SSomix. This tiered model supports early AD and MCI detection, enhances accessibility, and promotes digital health integration for widespread olfactory monitoring. </p>.
Early Diagnosis of Alzheimer's: Machine Learning Analysis Leveraging Structural MRI.
Dar SA, Imtiaz N, Dar RA
Curr Alzheimer Res · 2026 Feb · PMID 41764603 · Publisher ↗
INTRODUCTION: Alzheimer's disease (AD) is characterized by significant brain atrophy, detectable via structural MRI. There has been less focus on cortical degeneration in subcortical regional deterioration-particularly d...
INTRODUCTION: Alzheimer's disease (AD) is characterized by significant brain atrophy, detectable via structural MRI. There has been less focus on cortical degeneration in subcortical regional deterioration-particularly during the transition from Mild Cognitive Impairment (MCI) to AD-which remains underexplored. This study aims to identify subcortical regions with progressive atrophy using surface-based morphometry (SBM) and evaluate their potential for early AD diagnosis. METHODS: This longitudinal study collected data from MCI patients (6 months) who later progressed to Alzheimer's within 3 years, alongside healthy controls followed across four time points (6 months-3 years). Reported in line with STARD guidelines, the study aimed to evaluate model performance in distinguishing progressive MCI-to-AD from healthy controls to advance early Alzheimer's diagnosis. The study leveraged the ADNI dataset to analyse 68 subcortical regions in MCI-to-AD converters (MCI-AD) and Healthy Controls (HC) over 6 months to 3 years (i.e., at 6 months, 1 year, 2 years, and 3 years). The groups were classified beforehand using the Clinical Dementia Rating and the Mini-Mental Status Examination scores. Accordingly, three surfacebased morphometry (SBM) metrics-cortical thickness (CTh), gyrification index (GI), and sulcal depth (SD)-were evaluated in the progressive MCI group (individuals with MCI who later converted to Alzheimer's disease) as well as in healthy controls, to quantify morphological changes. Finally, the morphological data were utilized to train and test machine learning models for classification and prediction. RESULTS: Cortical regions exhibiting significant atrophy were identified using paired-samples ttests between 6 months and 3 years. In parallel, machine learning (ML) models were trained and tested on the same dataset to differentiate progressive MCI-to-AD cases from healthy controls across multiple time points (6 months, 1 year, 2 years, and 3 years), and subsequently to predict the progression to Alzheimer's disease. Certain evaluation metrics were considered for the classifier performance, i.e., Accuracy, F1-score, and AUC-ROC. DISCUSSION: Sub-cortical SBM metrics, particularly CTh, are sensitive to early AD-related atrophy, offering potential biomarkers for disease progression. ML models trained on these features enable accurate classification, with performance peaking near diagnosis-highlighting their utility in early intervention. CONCLUSION: SBM-derived subcortical atrophy patterns aid early AD detection and, when combined with ML, offer a scalable predictive framework. Among metrics, CTh showed the greatest decline in MCI-AD, followed by SD and GI. Progressive deterioration was observed in specific subcortical regions, accelerating near diagnosis. Classifiers achieved higher accuracy in distinguishing MCI-AD from HC at later time points, highlighting stage-specific shifts in feature importance.
Preface.
Groen TV
Curr Alzheimer Res · 2026 · PMID 41716064 · Publisher ↗
Abstract loading — click title to view on PubMed.
Molecular and Microstructural MRI of Neuroinflammation in Alzheimer's Disease.
Baniasadipour B, Bagheri F, Hendudari F … +4 more , Koopaee S, Amini SM, Kamalabadi MA, Fatemidokht A
Curr Alzheimer Res · 2026 Feb · PMID 41691696 · Publisher ↗
INTRODUCTION: Alzheimer's disease (AD) is a leading cause of cognitive decline in older adults, often diagnosed late when pathology and symptoms are established, reducing treatment effectiveness. Both AD and mild cogniti...
INTRODUCTION: Alzheimer's disease (AD) is a leading cause of cognitive decline in older adults, often diagnosed late when pathology and symptoms are established, reducing treatment effectiveness. Both AD and mild cognitive impairment (MCI) trigger neuroinflammation, leading to molecular and microstructural changes, including oxidative stress, mitochondrial dysfunction, glial activation, synaptic and neurotransmitter disturbances, myelin degradation, and white matter dysfunction. The blood-brain barrier (BBB) is also compromised. METHODS: Advanced magnetic resonance imaging (MRI) techniques, such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), magnetization- transfer imaging (MTI), chemical exchange saturation transfer (CEST), contrast-enhanced MRI (CE-MRI), and arterial spin labeling (ASL), offer promise for the early detection of Alzheimer's disease (AD)-related molecular and microstructural changes. RESULTS: Based on recent studies, advanced MRI modalities-including magnetic resonance spectroscopy, diffusion imaging, contrast-enhanced imaging, and chemical shift imaging-can highlight metabolic dysfunction, white matter degradation, microstructural disruption, blood-brain barrier dysfunction, cerebral hypoperfusion, vascular dysfunction, and pH alterations caused by neuroinflammation in Alzheimer's patients. DISCUSSION: The integration of advanced MRI modalities into clinical practice could improve the diagnosis and management of Alzheimer's disease (AD). Magnetic resonance spectroscopy and diffusion imaging can identify metabolic and microstructural changes years before brain atrophy occurs, aiding professionals in the early detection of AD. Additionally, perfusion imaging and magnetization transfer imaging can help distinguish between Alzheimer's disease, frontotemporal dementia (FTD), and vascular dementia. Finally, contrast-enhanced MRI can monitor the integrity of the blood-brain barrier to evaluate responses to drug treatments. CONCLUSION: Despite challenges, such as longer scan times and limited specificity, advanced MRIbased approaches are at the forefront of identifying reliable biomarkers for early detection of Alzheimer's disease and determining optimal management and treatment strategies.
Clinical and Medication Factors Associated with Cognitive Decline in Dementia: A Healthcare Database Study.
Chung CC, Chen JH, Chan L … +4 more , Liu HY, Shao JY, Hung YC, Hong CT
Curr Alzheimer Res · 2026 Jan · PMID 41589491 · Publisher ↗
INTRODUCTION: Dementia is the most common neurodegenerative disease, but the risk factors associated with its progression remain incompletely understood. Identifying clinical and medication-related determinants of cognit...
INTRODUCTION: Dementia is the most common neurodegenerative disease, but the risk factors associated with its progression remain incompletely understood. Identifying clinical and medication-related determinants of cognitive decline may inform patient management and guide treatment strategies. MATERIALS AND METHODS: Individuals with dementia who underwent paired Mini-Mental State Examination (MMSE) assessments between 2013 and 2019 were identified from the Taipei Medical University Clinical Research Database. To ensure adequate follow-up, paired assessments were required to be at least 90 days apart, with an actual mean follow-up interval of 21.5 ± 18.0 months. Demographic data, comorbidities, medication prescriptions, and blood biochemistry results were extracted. Generalized estimating equations were applied to evaluate associations between these factors and MMSE changes. RESULTS: A total of 3,054 individuals with dementia were included (mean age 78.0 ± 9.2 years, 61.1% women). The mean baseline MMSE score was 18.5 ± 6.7 and it declined to 16.0 ± 7.5 at follow-up. Male sex was significantly associated with greater MMSE decline (estimate: -0.920, 95% CI: -1.552 to -0.289, p = 0.004). Antidementia medications were significantly associated with less decline in MMSE scores (estimate: 1.245, 95% CI: 0.676 to 1.815, p < 0.001). In contrast, non-aspirin antiplatelet agent use was associated with a greater decline among men (estimate: -1.346, 95% CI: -2.518 to -0.173, p = 0.025). DISCUSSION: These findings highlighted that both clinical and pharmacological factors influence cognitive decline in dementia. Antidementia medications were linked to slower deterioration, supporting their role in disease management. Conversely, the association of non-aspirin antiplatelet agents with faster decline in men suggested potential adverse effects that warrant further investigation. CONCLUSION: In this large real-world cohort, sex and medication use were key determinants of cognitive decline in dementia. Antidementia medications mitigated decline. Notably, only non-aspirin antiplatelet agents, but not aspirin, were associated with greater cognitive decline in men., underscoring the need for personalized treatment approaches.
Targeting Non-coding RNAs in Neurodegeneration: Advances in Therapeutic RNA Modalities and Next-Gen Delivery Technologies.
Thakur A, Chowdhury KR, Kumar A … +2 more , Sharma VV, Bhatia R
Curr Alzheimer Res · 2026 Jan · PMID 41588889 · Publisher ↗
Non-coding RNA (ncRNA)-based therapies represent an emerging and transformative approach in the treatment of neurodegenerative diseases (NDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's dise...
Non-coding RNA (ncRNA)-based therapies represent an emerging and transformative approach in the treatment of neurodegenerative diseases (NDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS)/Motor Neuron Disease (MND). This review explored the potential for targeting microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and exosomal RNAs, reinforced by promising results from clinical trials demonstrating their capacity to modulate disease pathways. The incorporation of cutting-edge computational methodologies, including RNA structure prediction and gene regulatory network analysis, has been at the forefront in enhancing the efficacy of ncRNA-based treatments. Moreover, chemical methods have improved RNA molecules' stability, accuracy, and directed delivery, enhancing their therapeutic effects. Moreover, cutting-edge RNA editing technologies like Clustered Regularly Interspaced Short Palindromic Repeats/CRISPRassociated protein 13 (CRISPR/Cas13) are advancing our ability to directly manipulate ncRNA expression, offering a powerful avenue for addressing the molecular origins of neurodegeneration. Despite these advances, challenges persist, particularly in ensuring the specificity, delivery efficiency, and long-term efficacy of these treatments. Nanotechnology provides innovative solutions to these obstacles, facilitating more efficient and precise RNA delivery, especially to neuronal tissue. In conclusion, ncRNA-based therapies, while still in nascent stages, represent a hopeful frontier in the fight against NDs. With ongoing research and technological advancements, these therapies could not only halt disease progression but also redefine the future of ND treatment, offering new avenues for patients' care and clinical success.
About
- Frequency
- Sun
- Papers found
- 200
- RSS feed
- Subscribe