01/2026 journal articles
EDITORIAL: WHAT CAN ARTIFICIAL INTELLIGENCE BRING TO ALZHEIMER’S DISEASE CLINICAL TRIALS? A FIRST PERSPECTIVE
Lefkos T Middleton, Sandrine Andrieu
J Prev Alz Dis 2026;1(13)
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CITATION:
Lefkos T Middleton ; Sandrine Andrieu (2025): Editorial: What can artificial intelligence bring to Alzheimer’s disease clinical trials? A first perspective. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100423
EDITORIAL: ARTIFICIAL INTELLIGENCE AND THE ACCELERATION OF ALZHEIMER’S RESEARCH - FROM PROMISE TO PRACTICE
Gregory J. Moore, Niranjan Bose, Husseini K. Manji, Eric M. Reiman, Reisa Sperling
J Prev Alz Dis 2026;1(13)
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CITATION:
Gregory J. Moore ; Niranjan Bose ; Husseini K. Manji ; Eric M. Reiman ; Reisa Sperling (2025): Editorial: Artificial intelligence and the acceleration of Alzheimer’s research - From promise to practice. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100421
A BENCHMARK OF TEXT EMBEDDING MODELS FOR SEMANTIC HARMONIZATION OF ALZHEIMER\'S DISEASE COHORTS
Tim Adams, Yasamin Salimi, Mehmet Can Ay, Diego Valderrama, Marc Jacobs, Holger Fröhlich
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: Harmonizing diverse healthcare datasets is a challenging task due to inconsistent naming conventions. Manual harmonization is time- and resource-intensive, limiting scalability for multi-cohort Alzheimer's Disease research. Large Language Models, or specifically text-embedding models, offer a promising solution, but their rapid development necessitates continuous, domain-specific benchmarking, especially since general established benchmarks lack clinical data harmonization use cases.
OBJECTIVES: To evaluate how different text-embedding models perform for the harmonization of clinical variables.
DESIGN AND SETTING: We created a novel benchmark to assess how well different Language Model embeddings can be used to harmonize cohort study metadata with an in-house Common Data Model that includes cohort-to-cohort mappings for a wide range of Alzheimer’s Disease cohorts. We evaluated five different state-of-the-art text embedding models for seven different data sets in the context of Alzheimer’s disease.
PARTICIPANTS: No patient data were utilized for any of the analyses, as the evaluation was based on semantic harmonization of cohort metadata only.
MEASUREMENTS: Text descriptions of variables from different modalities were included for the analyses, namely clinical, lifestyle, demographics, and imaging.
RESULTS: Our benchmark results favored different models compared to general-purpose benchmarks. This suggests that models fine-tuned for generic tasks may not translate well to real-world data harmonization, particularly in Alzheimer’s disease. We propose guidelines to format metadata to facilitate manual or model-assisted data harmonization. We introduce an open-source library (https://github.com/SCAI-BIO/ADHTEB) and an interactive leaderboard (https://adhteb.scai.fraunhofer.de) to aid future model benchmarking.
CONCLUSIONS: Our findings highlight the importance of domain-specific benchmarks for clinical data harmonization in the field of Alzheimer’s disease and motivate standards for naming conventions that may support semi-automated mapping applications in the future.
CITATION:
Tim Adams ; Yasamin Salimi ; Mehmet Can Ay ; Diego Valderrama ; Marc Jacobs ; Holger Fröhlich (2025): A benchmark of text embedding models for semantic harmonization of Alzheimer's disease cohorts. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100420
TOWARDS AN AI BIOMEDICAL SCIENTIST: ACCELERATING DISCOVERIES IN NEURODEGENERATIVE DISEASE
Kaleigh F. Roberts, Eric C. Landsness, Justin Reese, Donald Elbert, Gabrielle Strobel, Elizabeth Wu, Yixin Chen, Albert Lai, Zachary B. Abrams, Mingfang Zhu, Justin Melendez, Srinivas Koutarapu, Sihui Song, Yun Chen, Robert Lazar, Payam Barnaghi, John F. Crary, Sergio Pablo Sardi, Marc D. Voss, Rajaraman Krishnan, Joel W. Schwartz, Ron Mallon, Gustavo A. Jimenez-Maggiora, Chenguang Wang, Thomas Sandmann, Niranjan Bose, Mukta Phatak, Gayle Wittenberg, Yannis G. Kevrekidis, Cassie S. Mitchell, Ludovico Mitchener, Cassie S. Mitchell, Ludovico Mitchener, Towfique Raj, Luca Foschini, Gregory J. Moore, Randall J. Bateman
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryDespite major advances in Alzheimer’s disease and related diseases (ADRD) research, the translation of discoveries into impactful clinical interventions remains slow. Overwhelming data complexity, fragmented knowledge, and prolonged research cycles hinder progress in understanding and treating neurodegenerative diseases. Artificial intelligence (AI) offers a promising path forward, particularly when developed as a scientist-in-the-loop system that collaborates with researchers throughout the scientific discovery process. This paper introduces the concept of an AI Biomedical Scientist, an intelligent platform designed to support literature synthesis, hypothesis generation, experimental design, and data interpretation. This platform aims to function as a holistic scientific partner, integrating diverse biomedical data and expert reasoning to accelerate discovery. We review commercial and academic efforts and introduce targeted Minimum Viable Products (MVPs) needed for general biomedical research lab utilization of AI, such as robust and accurate tools for literature and data analysis, negative data models, and virtual peer review, with a longer-term vision of foundation models trained directly on biomedical datasets. In AD and neurodegeneration research, such tools are anticipated to deliver efficiency gains ranging from modest improvements in specific research tasks to potential multi-fold accelerations in discovery workflows as systems mature and scale. This review examines the technical foundations, challenges, and anticipated impacts of AI and aims to inform and engage researchers in utilizing these systems to transform biomedical discovery, starting with AD and extending to other complex conditions.
CITATION:
Kaleigh F. Roberts ; Eric C. Landsness ; Justin Reese ; Donald Elbert ; Gabrielle Strobel ; Elizabeth Wu ; Yixin Chen ; Albert Lai ; Zachary B. Abrams ; Mingfang Zhu ; Justin Melendez ; Srinivas Koutarapu ; Sihui Song ; Yun Chen ; Robert Lazar ; Payam Barnaghi ; John F. Crary ; Sergio Pablo Sardi ; Marc D. Voss ; Rajaraman Krishnan ; Joel W. Schwartz ; Ron Mallon ; Gustavo A. Jimenez-Maggiora ; Chenguang Wang ; Thomas Sandmann ; Niranjan Bose ; Mukta Phatak ; Gayle Wittenberg ; Yannis G. Kevrekidis ; Cassie S. Mitchell ; Ludovico Mitchener ; Towfique Raj ; Luca Foschini ; Gregory J. Moore ; Randall J. Bateman (2025): Towards an AI biomedical scientist: Accelerating discoveries in neurodegenerative disease. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100398
AI MODELS, BIAS AND DATA SHARING EFFORTS TO TACKLE ALZHEIMER\'S DISEASE AND RELATED DEMENTIAS
Vijaya B. Kolachalama, Vijay Sureshkumar, Rhoda Au
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryArtificial intelligence (AI), often seen as a harbinger of future innovation, also presents a dilemma: it can perpetuate existing human biases. However, this issue is not novel or unique to AI. Humans have long been the progenitors of biases, and AI, as a product of human creation, often mirrors these inherent tendencies. Here, we present a perspective on the development and use of AI, recognizing it as a tool influenced by human input and societal norms, rather than an autonomous entity. Modern efforts to technologically enabled data collection approaches and model development, particularly in the context of Alzheimer’s disease and related dementias, can potentially reduce bias in AI. We also highlight the importance of data sharing from existing legacy cohorts to help accelerate ongoing AI model development efforts for greater scientific good and clinical care.
CITATION:
Vijaya B. Kolachalama ; Vijay Sureshkumar ; Rhoda Au (2025): AI models, bias and data sharing efforts to tackle Alzheimer's disease and related dementias. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100400
MINING THE GAPS: DECIPHERING ALZHEIMER’S BIOLOGY THROUGH AI-DRIVEN RECONCILIATION
Cory C. Funk, Tom Paterson, Alex Bangs, David M. Cannon, George Savage, Eric Ringger, Lee Hood
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryAlzheimer’s disease remains one of the most complex and contested domains in biomedicine, characterized by fragmented findings, competing hypotheses, and limited translational success. We propose that AI can offer not just technical acceleration but a deeper epistemic contribution: reconciliation. Rather than optimizing predictive performance or replicating existing assumptions, the goal is to align disparate data, methods, and mechanistic insights into coherent models that explain how the disease emerges, progresses, and can be treated. This approach centers on digital twins, not as monolithic models, but as flexible, testable architectures grounded in homeostasis, destabilization, and multiscale coherence. Through an iterative, interoperable AI architecture, digital twins integrate evidence, resolve contradictions, and highlight where critical gaps remain. This framework moves beyond incremental progress within the prevailing model to catalyzing a paradigm shift in how Alzheimer’s is understood. Reconciliation, in this sense, is not a method but a guiding principle for transforming both the science and its applications.
CITATION:
Cory C. Funk ; Tom Paterson ; Alex Bangs ; David M. Cannon ; George Savage ; Eric Ringger ; Lee Hood (2025): Mining the gaps: Deciphering Alzheimer’s biology through AI-driven reconciliation. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100402
MULTI-MODAL DATA ANALYSIS FOR EARLY DETECTION OF ALZHEIMER’S DISEASE AND RELATED DEMENTIAS
Liming Wang, Jim Glass, Lampros Kourtis, Rhoda Au
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryUntil recently, accurate early detection of clinical symptoms associated with Alzheimer’s disease (AD) and related dementias (ADRD) has been difficult. Digital technologies have created new opportunities to capture cognitive and other AD/ADRD related behaviors with greater sensitivity and specificity. Speech captured through digital recordings has shown recent promise at feasible levels of scalability because of the widespread penetration of smartphones. One such study is described in detail to illustrate the depth in which artificial intelligence (AI) analytic approaches can be used to amplify the value of audio recordings. Another modality that has also attracted research interest are ocular scans that have near term potential for validation as a digital biomarker and a point of entry for clinical care workflows. Single modality measures, however, are rapidly giving way to multi-modality sensors that are embedded in all smartphones and other internet-of-things connected devices. Artificial intelligence (AI) driven analytic approaches are able to divine clinical signals from these high dimensional digital data streams. These data driven findings are setting the stage for a future state in which AD/ADRD detection will be possible at the earliest possible stage of the neurodegenerative process and enable interventions that would significantly attenuate or alter the trajectory, preventing disease from reaching the clinical diagnosis threshold.
CITATION:
Liming Wang ; Jim Glass ; Lampros Kourtis ; Rhoda Au (2025): Multi-modal data analysis for early detection of alzheimer’s disease and related dementias. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100399
REINVENTING “N” IN THE A/T/N FRAMEWORK: THE CASE FOR DIGITAL
Rhoda Au, Zachary Popp, Spencer Low, Nicholas J. Ashton, Henrik Zetterberg
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBreakthroughs in biomarkers for amyloid (A), tau (T), and neurodegeneration (N) have advanced the prospects of accurate Alzheimer’s disease (AD) diagnosis. However, presence of pathology does not always translate into clinical expression and there are still clear knowledge gaps as to whether someone with AD biological indicators will lead to clinically apparent disease necessary to warrant drug treatments that carry toxicity risk. Reliance on decades-old assessment tools inhibits detection and monitoring at preclinical and early disease stages when new treatments could prove most effective. Evidence has accumulated that digital measures provide accurate detection of disease at early stages. We call for a re-evaluation of the A/T/N diagnostic framework, with digital evaluation measures complementing non-AD specific neurodegeneration markers, and even potentially replacing those non-specific to AD, to provide a clinically relevant feature critical to clinical trial advances and treatment decisions. Achieving this will only be possible if further research into novel digital evaluation tools is pursued with the same support and consideration as amyloid and tau.
CITATION:
Rhoda Au ; Zachary Popp ; Spencer Low ; Nicholas J. Ashton ; Henrik Zetterberg (2025): Reinventing “N” in the A/T/N framework: The case for digital. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100395
THE EVOLUTION OF ALZHEIMER’S TARGET IDENTIFICATION: TOWARDS A FUSION OF ARTIFICIAL AND CELLULAR INTELLIGENCE
Gayle Wittenberg, Fiona Elwood, Andrea Houghton, Tommaso Mansi, Bart Smets, Simon Lovestone
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryDecades of advances unfolding in parallel across diverse domains have delivered to science rapid rises in the scale of multiplexing, population-level cohort sizes, global computational capacity, massive-scale artificial intelligence (AI) models, and advanced human cellular modeling capabilities. These have generated unprecedented volumes of data, allowing researchers to explore Alzheimer’s disease (AD) biology at a depth and scale never before possible. The explosion of multi-omics datasets and computational power heralds an era in which the complexity of AD can be meaningfully dissected and reconstructed leveraging AI. These can be applied to advance our understanding of the root causes of disease, fundamentally a forward problem, tracing how dysfunction emergence from interactions across genes, cells and environments over time. On the other hand, therapeutic discovery requires addressing the inverse problem, working back from the diseased state to pinpoint upstream interventions that restore health. Human induced pluripotent stem cells (iPSCs) and other human cell models play a pivotal role in this process, naturally computing the mapping from perturbation to phenotype at scale. By recreating human-relevant biology, this cellular intelligence enables validation of targets predicted by AI and testing of interventions that drive therapeutic progress. We look to the next horizon in Alzheimer’s research as a collaboration, a convergence of three forms of intelligence: human, artificial and cellular. In unison, these complementary forces will shape a new frontier for AD research where scientific innovation and human ingenuity work together bringing hope for meaningful advances and new therapies.
CITATION:
Gayle Wittenberg ; Fiona Elwood ; Andrea Houghton ; Tommaso Mansi ; Bart Smets ; Simon Lovestone (2025): The evolution of Alzheimer’s target identification: Towards a fusion of artificial and cellular intelligence. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100417
SOLVING THE \'GOLDILOCKS PROBLEM\' IN DEMENTIA CLINICAL TRIALS WITH MULTIMODAL AI
Andrew E. Welchman, Zoe Kourtzi
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryThe development of effective therapeutics for Alzheimer’s Disease and related dementias (ADRD) has been hindered by patient heterogeneity and the limitations of current diagnostic tools. New treatments have no chance of working if given to patients who cannot benefit from them. This perspective explores how advances in Artificial Intelligence (AI), particularly multimodal machine learning, can solve the ‘Goldilocks problem’ of identifying patients for inclusion in clinical trials and support precision treatment in real-world healthcare settings. We examine the challenges of patient stratification, grounded by a conceptual framework of identifying each person’s stage and subtype of dementia. We review data from several clinical trials of Alzheimer’s disease therapeutics, to explore how AI-guided patient stratification can improve trial outcomes, reduce costs and improve recruitment. Further, we discuss the integration of AI into clinical workflows, the importance of model interpretability and generalizability, and ethical imperative to address algorithmic bias. By combining AI with scientific insight, clinical expertise, and patient experience, we argue that intelligent analytics can accelerate the discovery and delivery of new diagnostics and therapeutics, ultimately transforming dementia care and improving outcomes for patients around the globe.
CITATION:
Andrew E. Welchman ; Zoe Kourtzi (2025): Solving the 'Goldilocks problem' in dementia clinical trials with multimodal AI. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100397
AI-AUGMENTED FRAMEWORKS FOR ENHANCING ALZHEIMER’S DISEASE CLINICAL TRIALS: A MEMORY CLINIC PERSPECTIVE
Francesco K. Yigamawano, Aubrey R. Odom, Chonghua Xue, Hemant K. Pandey, Vijaya B. Kolachalama
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryAlzheimer’s disease (AD) clinical trials continue to face major hurdles in patient identification, resulting in delayed timelines, underpowered studies, and escalating costs. This perspective explores these challenges through the lens of a memory clinic, where hundreds of cases often translate into only a handful of enrollments. We highlight the potential of artificial intelligence (AI) to address this gap by powering chatbots for awareness and pre-screening, decision support tools for case identification, and algorithms for matching patients to trial-specific criteria, automating and streamlining the recruitment process. We also examine critical considerations in developing such AI-driven tools, including data standardization, privacy protections, and ethical safeguards. With thoughtful implementation, these innovations could accelerate more inclusive and efficient AD trials, ultimately bringing therapies to patients faster.
CITATION:
Francesco K. Yigamawano ; Aubrey R. Odom ; Chonghua Xue ; Hemant K. Pandey ; Vijaya B. Kolachalama (2025): AI-augmented frameworks for enhancing Alzheimer’s disease clinical trials: A memory clinic perspective Author links open overlay panel. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.1003968
EFFECT OF OBICETRAPIB, A POTENT CHOLESTERYL ESTER TRANSFER PROTEIN INHIBITOR, ON P-TAU217 LEVELS IN PATIENTS WITH CARDIOVASCULAR DISEASE
Michael H Davidson, Michael Szarek, Philip Scheltens, Everard Vijverberg, Andrew Hsieh, Marc Ditmarsch, Douglas Kling, Danielle Curcio, Stephen J Nicholls, Kausik K Ray, Jeffrey L. Cummings, John JP Kastelein
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: Cholesteryl ester transfer protein (CETP) inhibition reduces low density lipoprotein-cholesterol (LDL-C) while simultaneously increasing high density lipoprotein-cholesterol (HDL-C) levels and improving HDL-particle functionality. These lipoprotein modifications may provide a novel pathway for Alzheimer disease (AD) prevention through effects on lipid modulation, antioxidant activity, and neuro-inflammation. This approach could prove particularly beneficial for APOE4 carriers, who face elevated risks for both AD and atherosclerotic cardiovascular disease (ASCVD).
OBJECTIVES: To examine the effects of obicetrapib, an oral CETP inhibitor, on biomarker changes indicative of AD pathology among patients with ASCVD
DESIGN: This was a pre-specified substudy of the BROADWAY trial, a phase 3, double-blind, placebo-controlled pivotal registration trial to evaluate the LDL-C lowering efficacy of obicetrapib in adult patients with established ASCVD and/or heterozygous familial hypercholesterolemia (HeFH), whose LDL-C was not adequately controlled, despite being on maximally tolerated lipid-lowering therapy.
SETTING: The trial was conducted across 188 sites in China, Europe, Japan, and the United States. Participants were recruited from cardiology clinics and lipid specialty centers from 2021 to 2024.
PARTICIPANTS: Participants with ASCVD in BROADWAY who had known ApoE status and phosphorylated tau-217 (p-tau217) measured at baseline and 12 months.
INTERVENTION: Participants in BROADWAY were randomized 2:1 to receive oral obicetrapib 10 mg daily or placebo for 12 months.
MEASUREMENTS: AD plasma biomarkers were measured at baseline and 12 months using standardized SIMOA assays. The key outcome measure of interest was change in plasma p-tau217 from baseline to 12 months. Other outcome measures included changes in p-tau217/(Aβ42:40), p-tau181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL).
RESULTS: The analysis population consisted of 1535 (61 %) of the 2530 BROADWAY participants. Median age was 67 years and 67.0 % were male. Baseline p-tau217 levels varied significantly by ApoE subgroups, with ApoE4 carriers generally having higher concentrations and ApoE4/E4 participants exhibiting the highest median concentration (0.56 pg/mL). Obicetrapib significantly attenuated p-tau217 increases compared to placebo (adjusted mean 2.09 % vs 4.94 %; P = 0.025). Treatment differences were most pronounced in ApoE4 carriers, where adjusted mean increases were 1.92 % and 6.91 %, for obicetrapib and placebo, respectively (P = 0.041). Furthermore, among ApoE4/E4 participants, there was a 7.81 % adjusted mean decrease in p-tau217 with obicetrapib compared to a 12.67 % increase with placebo, representing a 20.48 % treatment difference (P = 0.010). Positive trends were observed across secondary biomarkers, with obicetrapib also significantly limiting increases in the p-tau217/Aβ42:40 ratio compared to placebo (2.51 % vs 6.55 %; P = 0.004). In addition, among ApoE4/E4 participants, obicetrapib demonstrated significant effects on GFAP (-6.39 % vs +8.85 %; P = 0.006) and NfL (-10.49 % vs +6.82 %; P = 0.020). Strong correlations were observed between end-of-study obicetrapib plasma concentrations and biomarker improvements (r=-0.64), suggesting CETP inhibition as a potential mechanism, although other drug effects may also contribute to these changes.
CONCLUSIONS: Obicetrapib significantly slowed AD biomarker progression over 12 months in participants with ASCVD, with the greatest effects in ApoE4 carriers. Among ApoE4/E4 participants, obicetrapib reduced p-tau217 levels by a placebo-adjusted 20.48 % and demonstrated consistent effects across multiple AD biomarkers. These findings represent the first demonstration of an oral intervention capable of reducing both beta-amyloid and tau pathology biomarkers in ApoE4 carriers, offering a potential preventive strategy for this high-risk population who currently have no effective prevention options. Future research will need to establish whether these biomarker changes translate to clinical benefits in dedicated AD prevention trials.
CITATION:
Michael H Davidson ; Michael Szarek ; Philip Scheltens ; Everard Vijverberg ; Andrew Hsieh ; Marc Ditmarsch ; Douglas Kling ; Danielle Curcio ; Stephen J Nicholls ; Kausik K Ray ; Jeffrey L. Cummings ; John JP Kastelein (2025): Effect of obicetrapib, a potent cholesteryl ester transfer protein inhibitor, on p-tau217 levels in patients with cardiovascular disease. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100394
DIETARY INDEX FOR GUT MICROBIOTA (DI-GM) AND COGNITIVE FUNCTION: NHANES FINDINGS AND VALIDATION IN A HONG KONG COHORT WITH METAGENOMIC DATA
Hui Jiang, Jiashuo Zhang, Shuyi Li, Timothy Kwok, Siew C Ng, Allen Ting Chun Lee, Zhilu Xu
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: The diet-gut-microbiota-brain axis is critical for maintaining brain health. The Dietary Index for Gut Microbiota (DI-GM), comprising beneficial and unfavorable components, may serve as a proxy for this connection, yet its association with cognition remains underexplored.
METHODS: This study examined the relationship between DI-GM, its components, and cognitive function in older adults using data from the National Health and Nutrition Examination Survey (NHANES). Findings were validated in an independent Hong Kong osteoporosis cohort (OS cohort) with gut metagenomic data to assess of microbiota’s mediating role in diet-cognition relationship. Cognitive assessment in NHANES utilized the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST), while the OS cohort employed the Hong Kong version of the Montreal Cognitive Assessment (HK-MoCA). DI-GM was calculated from 24-hour dietary recalls. The diet-cognition associations were assessed by weighted multivariate regressions, supplemented by restricted cubic spline (RCS), subgroup, correlation network, and mediation analyses.
RESULTS: Higher DI-GM was significantly associated with better performance on DSST (OR=0.90; 95 % CI: 0.82, 0.99; p = 0.033). The beneficial-to-gut-microbiota score (BGMS) associated with lower psychometric mild cognitive impairment (p-MCI) risk (OR=0.88; 95 % CI: 0.80, 0.98; p = 0.022) and better CERAD immediate and delayed recall and DSST (all p < 0.05). The beneficial-to-gut-microbiota components like dietary fiber demonstrated protective effects across cognitive domains, while refined grains was associated with poorer cognition. In the OS cohort, higher dietary fiber intake correlated with higher HK-MoCA score (p < 0.05) and increased abundance of fermenting bacteria. Among these species, Eubacterium ventriosum mediated the beneficial effect of dietary fiber intake on dementia risk reduction, with an indirect effect of -0.014 (95 % CrI: -0.040, -0.001), accounting for approximately 12.7 % of the total effect.
CONCLUSION: Higher adherence to beneficial-to-gut-microbiota dietary patterns, as reflected by DI-GM, was associated with better cognitive function in older adults. These findings highlight the importance of a gut-microbiota-targeted diet in maintaining cognitive health.
CITATION:
Hui Jiang ; Jiashuo Zhang ; Shuyi Li ; Timothy Kwok ; Siew C Ng ; Allen Ting Chun Lee ; Zhilu Xu (2025): Dietary index for gut microbiota (DI-GM) and cognitive function: NHANES findings and validation in a Hong Kong cohort with metagenomic data. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100319
CARDIOVASCULAR-KIDNEY-METABOLIC HEALTH, GENETIC SUSCEPTIBILITY, AND THE RISK OF DEMENTIA: A PROSPECTIVE COHORT STUDY
Yi-Peng Zhang, Jing-Wei Gao, Guang-Hong Liao, Qing-Yuan Gao, Ze-Gui Huang, Chuan-Rui Zeng, Yang-Wei Cai, Yong-Xiang Ruan, Zhi-Teng Chen, Yang-Xin Chen, Jing-Feng Wang
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: The joint effect of cardiovascular-kidney-metabolic (CKM) health and genetic susceptibility on dementia remains unclear.
METHODS: This prospective cohort study utilized data from the UK Biobank. CKM syndrome was characterized by the presence of metabolic risk factors, cardiovascular disease, and chronic kidney disease. We employed Cox proportional hazards models to examine the association between CKM syndrome and dementia incidence, while also investigating the influence of genetic risk via polygenic risk score (PRS) and apolipoprotein E (APOE) ε4 status. We also examined the association between CKM syndrome and cognitive function via linear regression model.
RESULTS: Among 331,731 participants (mean ± SD age, 56.53 ± 8.1 years; 156,762 [47.26 %] male), 4413 (1.33 %) developed dementia during a mean follow-up of 12.8 years. Advanced CKM syndrome correlated with higher risk of dementia; compared to stage 0, HRs for dementia were 1.19 (95 % CI 1.01–1.39, P = 0.036), 1.26 (95 % CI 1.09–1.45, P = 0.002), and 2.06 (95 % CI 1.77–2.39, P < 0.001) for stages 1, 2, and 3–4, respectively. Genetic susceptibility further strengthened this association, and the synergistic effect of CKM syndrome, dementia PRS, and APOE ε4 status surpasses the individual contributions of any single factor. These findings remained robust in a series of subgroups and sensitivity analyses. Individuals in the later stages of CKM syndrome demonstrated poorer performance on cognitive function tests.
CONCLUSIONS: Poor CKM health was independently associated with cognitive impairment and an increased risk of dementia. The association between CKM syndrome and risk of dementia could be further strengthened by genetic susceptibility.
CITATION:
Yi-Peng Zhang ; Jing-Wei Gao ; Guang-Hong Liao ; Qing-Yuan Gao ; Ze-Gui Huang ; Chuan-Rui Zeng ; Yang-Wei Cai ; Yong-Xiang Ruan ; Zhi-Teng Chen ; Yang-Xin Chen ; Jing-Feng Wang (2025): Cardiovascular-kidney-metabolic health, genetic susceptibility, and the risk of dementia: A prospective cohort study. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100325
PLASMA AND NEUROSTRUCTURAL BIOMARKERS IN THE CLINICAL-BIOLOGICAL CHARACTERIZATION OF EARLY STAGES OF THE ALZHEIMER\'S DISEASE CONTINUUM: FINDINGS FROM THE COMPOSTELA AGING STUDY
Montserrat Zurrón, Arturo Xosé Pereiro, Ana Isabel Rodriguez-Perez, Santiago Galdo-Álvarez, Juan José Ansede, Cristina Lojo-Seoane, Mónica Lindín, David Facal, Miguel Ángel Rivas-Fernández, María Campos-Magdaleno, Ángel Carracedo, José Luis Labandeira-Garcia, Fernando Díaz
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryRecent technical advances in peripheral blood analysis have enabled precise quantification of Alzheimer´s Disease (AD) biomarkers in the early stages of the AD continuum, in an economical, non-invasive and safe manner. The main objective of this study was to contribute to the clinical-biological characterization of the initial stages of cognitive impairment by measurement of blood and neurostructural AD biomarkers in groups of participants classified according to their cognitive clinical phenotype.
Plasma concentrations of p-tau217, p-tau181, total tau, neurofilament light chain and amyloid-β 42/40 ratio biomarkers were measured along with APOE gene variants, hippocampal volume and cortical thickness of the AD signature regions. The cohort of 329 participants included Cognitively Unimpaired (CU), Subjective Cognitive Decline (SCD), single-domain amnestic Mild Cognitive Impairment (sd-aMCI), multidomain aMCI (md-aMCI), and single-domain non-amnestic MCI (sd-naMCI) groups.
P-tau217 concentrations were significantly higher in the md-aMCI and sd-aMCI groups than in the CU, SCD and sd-naMCI groups. P-tau181 concentrations were significantly higher in md-aMCI group than in CU, SCD and sd-naMCI groups. Hippocampal volume and AD signature cortical thickness were significantly lower in the md-aMCI group than in the CU, SCD and sd-naMCI groups. No across group differences were found in the distribution of carriers/non-carriers of APOE-ε4. Mediation analysis revealed that hippocampal volume and AD signature cortical thickness mediated the relationship between p-tau217 and p-tau181 levels and cognitive performance.
Sd-aMCI and md-aMCI represent two distinct and sequential clinical-biological stages of the AD continuum. Conversely, sd-naMCI does not appear to be associated with AD pathology. Finally, the SCD group does not seem to display a higher risk of progression along the AD continuum than the CU group.
CITATION:
Montserrat Zurrón ; Arturo Xosé Pereiro ; Ana Isabel Rodriguez-Perez ; Santiago Galdo-Álvarez ; Juan José Ansede ; Cristina Lojo-Seoane ; Mónica Lindín ; David Facal ; Miguel Ángel Rivas-Fernández ; María Campos-Magdaleno ; Ángel Carracedo ; José Luis Labandeira-Garcia ; Fernando Díaz (2025): Plasma and neurostructural biomarkers in the clinical-biological characterization of early stages of the Alzheimer's disease continuum: findings from the Compostela Aging Study. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100331
BRAIN LYMPHATIC DRAINAGE PATHWAYS, DEEP CERVICAL LYMPHATIC SURGERY, AND CURRENT INSIGHTS: A SYSTEMATIC REVIEW
Theodore Lahmar, Francois Thuau, Gaelle Pinard, Claire Boutoleau-Bretonniere, Pierre Perrot, Ugo Lancien
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryThe discovery of the glymphatic system and the later rediscovery of the meningeal lymphatic network have significantly changed our understanding of central nervous system (CNS) waste clearance. Aging is linked to a gradual decline in these clearance pathways, resulting in waste buildup. As a result, therapeutic strategies targeting cerebral lymphatic function have garnered growing interest, with lymphatic surgery emerging as a promising option.
We conducted a review until July 2025, providing an overview of the potential of lymphatic surgical techniques to enhance CNS metabolic waste clearance pathways as a therapeutic approach for brain lymphatic system disorders.
Currently available data are limited, nine publications addressing this approach. These studies explore an innovative technique involving lymphatico-venous anastomoses (LVA) targeting deep cervical lymphatic vessels to promote clearance for the treatment of Alzheimer’s or Parkinson’s diseases.
Cerebral lymphatic drainage is critical for effective brain waste elimination such as amyloid-β, phosphorylated tau, and α-synuclein, which are linked to neurodegenerative diseases. Viewing these lymphatic dysfunctions as a form of “cerebral lymphedema,” LVA, already used in treating peripheral lymphedema, shows potential as a therapeutic approach. Although clinical evidence is still limited, lymphatic supermicrosurgery presents promising therapeutic possibilities for neurodegenerative diseases and other conditions related to impaired CNS lymphatic outflow.
CITATION:
Theodore Lahmar ; Francois Thuau ; Gaelle Pinard ; Claire Boutoleau-Bretonniere ; Pierre Perrot ; Ugo Lancien (2025): Brain lymphatic drainage pathways, deep cervical lymphatic surgery, and current insights: A systematic review. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100335
ASSOCIATIONS BETWEEN TRAUMATIC BRAIN INJURY AND THE PREVALENCE OF ALZHEIMER’S DISEASE DEMENTIA AND BEHAVIORAL AND PSYCHOLOGICAL SYMPTOMS OF DEMENTIA: A RETROSPECTIVE COHORT STUDY
Han-Kyeol Kim, Sojeong Park, Sung-Woo Kim, Yeonju Jin, Hokyung Lee, Jin Yong Hong, Ickpyo Hong, Min Seok Baek
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: Traumatic brain injury is an environmental risk factor that may accelerate the progression of Alzheimer’s disease and behavioral and psychological symptoms of dementia in patients with mild cognitive impairment.
OBJECTIVES: To investigate whether traumatic brain injury in patients with mild cognitive impairment is associated with an increased risk of progression to Alzheimer’s disease dementia and behavioral and psychological symptoms of dementia.
DESIGN: A retrospective cohort study using the Korean National Health Insurance Service database.
SETTING: National-level health data covering healthcare utilization, diagnoses, prescriptions, and procedures in South Korea from January 2012 to December 2021.
PARTICIPANTS: Patients diagnosed with mild cognitive impairment between January 1, 2013, and December 31, 2016, were followed until Alzheimer’s disease dementia diagnosis, behavioral and psychological symptoms of dementia occurrence, death, or December 31, 2021. These patients were classified into two groups according to the presence of traumatic brain injury during the follow-up period.
MEASUREMENTS: Age at the time of mild cognitive impairment diagnosis, sex, income level, the presence of several chronic conditions, presence of traumatic brain injury, progression of Alzheimer’s disease dementia, and behavioral and psychological symptoms of dementia
RESULTS: We assessed 452,718 patients (mean age: 67.16 years). Traumatic brain injury was significantly associated with an increased risk of Alzheimer’s disease dementia progression (hazard ratio = 1.252, 95 % confidence interval: 1.206–1.301), particularly among patients aged <65 years (hazard ratio = 1.560, 95 % confidence interval: 1.391–1.749), and was linked to a higher risk of behavioral and psychological symptoms of dementia following Alzheimer’s disease dementia diagnosis (hazard ratio = 1.300, 95 % confidence interval: 1.181–1.431).
CONCLUSIONS: Our results underscore the importance of traumatic brain injury prevention in patients with mild cognitive impairment for mitigating the progression and neuropsychiatric complications of Alzheimer’s disease.
CITATION:
Han-Kyeol Kim ; Sojeong Park ; Sung-Woo Kim ; Yeonju Jin ; Hokyung Lee ; Jin Yong Hong ; Ickpyo Hong ; Min Seok Baek (2025): Associations between traumatic brain injury and the prevalence of Alzheimer’s disease dementia and behavioral and psychological symptoms of dementia: A retrospective cohort study. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100360
ALZHEIMER’S DISEASE PREVENTION BY FLAVONOLS AND THEIR ANALOGS
George Uhl, Balaji Kannan, Joungil Choi, Ian Henderson
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryFour studies now document reduced incidence of Alzheimer’s disease (AD) or dementia diagnoses in aging individuals who report higher dietary intake of flavonols (or their glycosides) years prior to diagnosis vs those with lower intake. These effects are large, almost 50 %, for individuals at higher genetic risk for AD, providing a robust gene x environment interaction. They display a specific structure-activity relationship. These benefits are driven by modest-to-moderate differences in the quantity of flavonol (glycoside) consumed. These data contrast with the failure of late life supplementation with flavonol-rich ginko extract to alter progression to AD in groups of individuals who are not selected for genotype or dietary pattern. Studies of mouse AD models support benefits of the flavonol quercetin. In vitro and in vivo results add the receptor type protein tyrosine phosphatase PTPRD to the list of oxidative and other targets or mechanisms to which flavonol benefits are attributed. The magnitude of flavonol protection for individuals who would otherwise be especially vulnerable to AD, the ease of supplementation strategies with currently-available nutraceuticals and the opportunities for development of improved flavonol analogs all support further exploration of flavonol-based strategies for reducing the incidence of AD with aging.
CITATION:
George Uhl ; Balaji Kannan ; Joungil Choi ; Ian Henderson (2025): Alzheimer’s disease prevention by flavonols and their analogs. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100361
FOLIC ACID SUPPLEMENTATION IMPROVES COGNITION FUNCTION IN PARTICIPANTS WITH CEREBRAL SMALL VASCULAR DISEASE-RELATED COGNITIVE IMPAIRMENT: A RANDOMIZED CONTROLLED TRIAL
Yinyue Liu, Yinyue Liu, Zhengjun Cai, Li Zhao, Yu Wang, Yajie Guo, Xiaonan Su, Yuli Miao, Bin Yi, Yanhong Wang, Xumei Zhang
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: The potential improvement of cognitive function through folic acid (FA) supplementation in patients with vascular cognitive impairment (VCI) remains unclear, and no randomized controlled trials (RCTs) have been conducted specifically in populations with cerebral small vessel disease-related cognitive impairment (CSVD-CI).
OBJECTIVE: This study aimed to explore the effects of FA supplementation on cognitive function and angiogenesis-related indicators in patients with CSVD-CI.
DESIGN: Double-blinded, parallel group, randomized controlled trial, with a six-month follow-up period.
SETTING: Department of neurology and neurosurgery in Shanxi, China.
PARTICIPANTS: 220 CSVD-CI patients.
INTERVENTIONS: The intervention consisted of FA tablets (0.4 mg/tablet) administered orally at a dose of two tablets daily for six months, while the placebo tablets were identical in appearance and administration but lacked FA.
MEASUREMENTS: The primary outcome was the Montreal Cognitive Assessment (MoCA) score at six months assessed in the intention-to-treat (ITT) population. Secondary outcomes included Mini-Mental State Examination (MMSE) score, Trail Making Test (TMT), Tinetti Performance Oriented Mobility Assessment (POMA), and five-level EuroQol five-dimensional questionnaire (EQ-5D-5 L).
RESULTS: MoCA and MMSE scores improved significantly in the FA group compared to placebo (both P < 0.05). Additionally, the FA group had statistically significant increases in serum folate and decreases in serum homocysteine (Hcy) (both P < 0.001). Matrix metalloproteinase-9 (MMP-9) expression decreased significantly in the FA group compared with placebo (P < 0.05).
CONCLUSIONS: FA improved cognitive outcomes in CSVD-CI, accompanied by a reduction in serum Hcy levels and MMP-9 expression. Early FA supplementation could help prevent vascular-related cognitive decline in CSVD-CI patients.
CITATION:
Yinyue Liu ; Zili Yu ; Zhengjun Cai ; Li Zhao ; Yu Wang ; Yajie Guo ; Xiaonan Su ; Yuli Miao ; Bin Yi ; Yanhong Wang ; Xumei Zhang (2025): Folic acid supplementation improves cognition function in participants with cerebral small vascular disease-related cognitive impairment: a randomized controlled trial. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100369
ASSOCIATIONS OF CIRCULATING C-REACTIVE PROTEIN LEVELS WITH CENTRAL ALZHEIMER’S DISEASE BIOMARKERS
Hye Ji Choi, Min Soo Byun, Dahyun Yi, Hyejin Ahn, Gijung Jung, Sangyong Park, Joon Hyung Jung, Musung Keum, Bo Kyung Sohn, Yu Kyeong Kim, Hongyoon Choi, Yun-Sang Lee, Jun-Young Lee, Koung Mi Kang, Chul-Ho Sohn, Yen-Ning Huang, Andrew J. Saykin, Kwangsik Nho, Dong Young Lee, KBASE Research Group
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: C-reactive protein (CRP) is well-known marker of inflammation and immune response. Its potential role in Alzheimer’s disease (AD) pathophysiology remains unclear, particularly in relation to central AD biomarkers, including beta-amyloid (Aβ), tau, and neurodegeneration.
OBJECTIVES: To investigate the associations between circulating CRP levels and central AD biomarkers-including Aβ deposition, tau, and AD-signature neurodegeneration-in nondemented older adults.
DESIGN, SETTING, PARTICIPANTS: This cross-sectional observational study analyzed data from a Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer Disease conducted from 2014 to 2020. A total of 417 nondemented older adults underwent comprehensive evaluations, including blood sampling and multimodal neuroimaging for measuring of Aβ and AD-signature neurodegeneration. A subset of participants (N = 123) also underwent tau positron emission tomography (PET) scan.
MEASUREMENTS: The primary outcomes were A/T/N biomarkers of AD, including brain Aβ and tau deposition measured via amyloid and tau PET, as well as AD-signature neurodegeneration measured by fluorodeoxyglucose (FDG)-PET. Associations between CRP levels and these biomarkers were analyzed while adjusting for CRP-decreasing allele scores, as well as other confounders, including age, sex, vascular risk score, body mass index, nonsteroidal anti-inflammatory drug (NSAID) usage, smoking status, and APOE ε4 carrier status.
RESULTS: The mean (SD) age of participants was 70.57 (8.00) years, with 179 (42.9 %) females. Circulating CRP levels showed non-linear associations with A/T/N biomarkers of AD, showing a U-shaped relationship with Aβ and tau deposition and an inverted U-shaped association with neurodegeneration. Threshold effect analyses revealed that CRP was inversely associated with Aβ deposition (B = -0.081; 95 % CI, -0.153 to -0.007; p = 0.031) below 0.63 mg/L, after adjusting for all confounding variables. In contrast, higher CRP levels were associated with lower cerebral glucose metabolism in AD-signature regions, indicative of greater AD-related neurodegeneration, when above 2.15 mg/L (B = -0.056; 95 % CI, -0.112 to -0.001; p = 0.042).
CONCLUSIONS: Our study revealed differential associations between circulating CRP levels and central AD biomarkers that varied according to the CRP concentration. Further studies are necessary to elucidate the mechanisms underlying the inverse relationship between circulating CRP and brain Aβ within the clinically normal range, as well as potential aggravating effects of elevated CRP on Aβ-independent neurodegeneration.
CITATION:
Hye Ji Choi ; Min Soo Byun ; Dahyun Yi ; Hyejin Ahn ; Gijung Jung ; Sangyong Park ; Joon Hyung Jung ; Musung Keum ; Bo Kyung Sohn ; Yu Kyeong Kim ; Hongyoon Choi ; Yun-Sang Lee ; Jun-Young Lee ; Koung Mi Kang ; Chul-Ho Sohn ; Yen-Ning Huang ; Andrew J. Saykin ; Kwangsik Nho ; Dong Young Lee ; KBASE Research Group (2025): Associations of circulating c-reactive protein levels with central Alzheimer’s disease biomarkers. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100368
TRENDS IN COGNITIVE IMPAIRMENT AMONG OLDER ADULTS IN CHINA FROM 2002 TO 2022: EVALUATING THE IMPACT OF THE COVID-19 PANDEMIC
Lei Feng, Kaisy Xinhong Ye, Qiushi Feng, Yan Mo, Zuqi Cai, Chunbo Li, Jintai Yu, Bin Li, Andrea B. Maier, Yi Zeng, Zhenglian Wang
J Prev Alz Dis 2026;1(13)
Show summaryHide summaryBACKGROUND: Cognitive impairment is a growing public health concern, particularly in aging populations. While trends in CI prevalence in China were studied up to 2018, no previous research has explored how the COVID-19 pandemic has affected these trends.
OBJECTIVES: This study aims to extend the analysis to 2022, examining the impact of the pandemic on cognitive impairment prevalence.
PARTICIPANTS: The Chinese Longitudinal Healthy Longevity Survey (CLHLS) data across multiple waves (2002 to 2022) was used (n=64,872).
MEASUREMENTS: Cognitive impairment was assessed using a Chinese version of the Mini-Mental State Examination (MMSE). The rural/urban-sex-single age-specific prevalence of cognitive impairment across different waves were estimated using the DemoRates R package. Cognitive impairment trends before and after the onset of the COVID-19 pandemic were compared to identify any significant changes.
RESULTS: In 2018 and previous waves, an average of 16,191 participants per wave were surveyed (four waves), with a cognitive impairment prevalence of 4.3%. In 2022, post–COVID-19, the survey included 14,022 participants and showed a significant increase in CI prevalence to 6.8%. The observed trends were independent of gender, age group, and residential environment (P-trend < 0.001). However, a significant decrease in mean calf circumference, increase in proportion of overweight participants, and increases in daily fruit and vegetable intake and regular physical activity were notable after the pandemic.
CONCLUSION: The study suggests that the COVID-19 pandemic may have contributed to the observed increase in cognitive impairment prevalence in China, underscoring the importance of further research into the long-term cognitive effects of global health crises. These findings highlight the need to strengthen healthcare systems to support cognitive health in an aging population, while considering both pandemic-related and ongoing factors in the management of cognitive impairment.
CITATION:
Lei Feng ; Kaisy Xinhong Ye ; Qiushi Feng ; Yan Mo ; Zuqi Cai ; Chunbo Li ; Jintai Yu ; Bin Li ; Andrea B. Maier ; Yi Zeng ; Zhenglian Wang (2025): Trends in cognitive impairment among older adults in China from 2002 to 2022: Evaluating the impact of the COVID-19 pandemic. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100370
LETTER TO THE EDITOR : COGNITIVE DECLINE AMONG CHINESE OLDER ADULTS: FINDINGS FROM THE CHINESE LONGITUDINAL HEALTHY LONGEVITY SURVEY (CLHLS)
Kaisy Xinhong Ye, Lei Feng, Tih-Shih Lee, Yi Zeng, Zhengliang Wang
J Prev Alz Dis 2026;1(13)
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CITATION:
Kaisy Xinhong Ye ; Lei Feng ; Tih-Shih Lee ; Yi Zeng ; Zhengliang Wang (2025): Letter to the Editor: Cognitive decline among Chinese older adults: Findings from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100393
ERRATUM TO “RESULTS OF THE FIRST-IN-HUMAN, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, SINGLE- AND MULTIPLE-ASCENDING DOSE STUDY OF BIIB113 IN HEALTHY VOLUNTEERS” [THE JOURNAL OF PREVENTION OF ALZHEIMER\'S DISEASE VOLUME 12 (2025) 100302]
Flavia C. Nery, Maciej Kaliszczak, Ben Suttle, Lori Jones, Shuang Wu, Jing Xie, Gioacchino Curiale, Esin Yesilalan, Beth Hirschhorn, Denisa Wilkes, Dave Singh, Martin Bolin, Sangram Nag, Andrea Varrone, Per Stenkrona, Anton Forsberg Morén, Christer Halldin, Jeffrey Yachnin, H. Moore Arnold, Szofia Bullain, Jaren Landen, Diana Gallagher, Heike Hering
J Prev Alz Dis 2026;1(13)
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CITATION:
Flavia C. Nery ; Maciej Kaliszczak ; Ben Suttle ; Lori Jones ; Shuang Wu ; Jing Xie ; Gioacchino Curiale ; Esin Yesilalan ; Beth Hirschhorn ; Denisa Wilkes ; Dave Singh ; Martin Bolin ; Sangram Nag ; Andrea Varrone ; Per Stenkrona ; Anton Forsberg Morén ; Christer Halldin ; Jeffrey Yachnin ; H. Moore Arnold ; Szofia Bullain ; Jaren Landen ; Diana Gallagher ; Heike Hering (2025): Erratum to “Results of the first-in-human, randomized, double-blind, placebo-controlled, single- and multiple-ascending dose study of BIIB113 in healthy volunteers” [The Journal of Prevention of Alzheimer's Disease volume 12 (2025) 100302]. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100425