Philip Scheltens

INTRODUCTION: The glucagon‐like peptide‐1 receptor agonist semaglutide may impact neuroinflammation and reduce neurodegeneration. We present baseline characteristics of participants enrolled in the evoke (NCT04777396) and evoke+ (NCT04777409) trials, referred to as “evoke (+)” hereafter. METHODS: Evoke (+) are two ongoing global, multicenter, randomized, double‐blind, parallel‐group, placebo‐controlled phase 3 trials investigating semaglutide in participants with early‐stage symptomatic Alzheimer's disease (AD) with confirmed amyloid positivity (by positron emission tomography or cerebrospinal fluid testing). Inclusion criteria are the same for both trials, except that by design, evoke+ also includes participants with significant small vessel pathology. Both trials include a 12‐week screening phase before randomization (1:1) to receive oral semaglutide titrated to 14 mg or placebo for 156 weeks. Baseline data were summarized and analyzed descriptively. Additionally, data were pooled and assessed by five main geographical regions. RESULTS: Evoke (+) recruited 9996 participants from 566 sites in 40 countries. The mean (standard deviation) age of participants was 71.8 (7.1) and 72.6 (7.1) years in evoke and evoke+, respectively; more participants were female than male (female: 53.0% and 51.9%, respectively) and most had a Clinical Dementia Rating (CDR) global score of 0.5 (72.8% and 71.4%; CDR global score of 1: 26.5% and 27.6%). Both trial populations had similar demographics, and clinical and cognitive baseline characteristics, except that 2.8% of participants in evoke+ had magnetic resonance imaging‐documented significant small vessel pathology as per protocol inclusion criteria. Regional‐level data demonstrated some differences in AD treatment characteristics, including cholinesterase inhibitor use of 41.7% in North America versus 61.6% in Asia. DISCUSSION: Evoke (+) are the only large‐scale, phase 3 trials investigating the longer‐term efficacy and safety of semaglutide in early AD as a potential disease‐modifying treatment. The baseline characteristics from evoke (+) reflect a varied, global population with early‐stage symptomatic AD. Primary readouts are expected in the second half of 2025. Highlights: evoke and evoke+ are the only large‐scale randomized controlled trials (RCTs) investigating the longer‐term efficacy and safety of semaglutide in early AD. Baseline characteristics reflect a varied, global population. The trials’ primary readouts are expected in the second half of 2025.

Brains from cognitively intact centenarians offer a unique window into mechanisms of neuroprotection. We quantified 3,448 proteins by LC-MS/MS in middle temporal gyrus(MTG) from 88 Alzheimer's disease (AD) patients, 53 controls (50-99 years) and 49 centenarians (100+). After adjustment for cell type composition, Aβ abundance associated with only five proteins, revealing upregulation of HTRA1, LRP1 and NRXN1 as early AD-associated changes. Conversely, tau abundance associated with ~20% of the quantified proteome, revealing GPRIN1 as the top tau-associated protein. One-third of centenarians had high Aβ abundance, often with Braak neurofibrillary tangle stages IV/V, yet all maintained low local tau abundance. Centenarians showed maintained proteostasis (low ubiquitin peptides, high proteasome components), high PCSK1 (prohormone maturation), high PFKFB2 (glycolysis regulation), mitochondria-coupled lipid β-oxidation and lower APOE levels. Together, these findings suggest a model of neuroprotection in which Aβ facilitates tau seeding, and where proteostatic and metabolic adaptations buffer against additional tau accumulation in centenarians.

Background: Cholesteryl ester transfer protein (CETP) regulates lipid metabolism, mediating the transfer of cholesteryl esters and triglycerides between LDL and HDL cholesterol particles. The CETP inhibitor, obicetrapib, reduces LDL‐C and increases HDL‐C. Genetic evidence and preclinical studies suggest that CETP inhibition might mitigate dementia and Alzheimer’s disease (AD) risk, particularly in individuals carrying the APOE4 allele. Dysfunctional cholesterol transport is a hallmark of AD, characterized by impaired lipidation of ApoE particles leading to neuroinflammation and neurodegeneration. Methods: BROADWAY study (NCT05142722), a Phase 3, double‐blind, placebo‐controlled trial evaluated obicetrapib 10 mg daily versus placebo over 12 months in individuals with established atherosclerosis cardiovascular disease. Participants ( n =1727) were randomized 2:1 to treatment with obicetrapib or placebo. Plasma lipid levels including LDL‐C and HDL‐C were measured at baseline and at 12 months. AD plasma biomarkers, p ‐tau217, p ‐tau181, GFAP, NFL, and p ‐tau217/Aβ42:Aβ40 ratio, were also assessed at both time points. APOE status was determined. Results: The mean age of participants was 65 years, 33% were female. Obicetrapib significantly lowered LDL‐C by 33% and increased HDL‐C by 125% relative to placebo. Obicetrapib demonstrated significant attenuation of increase in the median plasma p ‐tau217 (1.1% obicetrapib vs. 4.8% with placebo; p =0.01) and p ‐tau217/Aβ42:Aβ40 ratio (2.7% obicetrapib vs. 6.5% placebo; p =0.006). At baseline, p ‐tau217 levels were higher in ApoE4 carriers compared with non‐carriers (0.47 pg/ml vs 0.39 pg/ml; ( p n =367) showed greater benefit, with obicetrapib stabilizing p ‐tau217 levels (0% increase vs. 5.7% with placebo; p =0.03) and limiting increases in the p ‐tau217/Aβ42:Aβ40 ratio (2.1% vs. 10.2% placebo; p =0.005). Other AD biomarkers ( p ‐tau181, GFAP, NFL) showed consistent favorable trends. Conclusions: This very large biomarker study showed that obicetrapib significantly slowed the progression of AD biomarkers over a period of 1 year, particularly p ‐tau217 and p ‐tau217/Aβ42:Aβ40 ratio, with most pronounced effects in older individuals carrying the APOE4 allele. These findings support the dual therapeutic potential of obicetrapib in addressing both cardiovascular and neurodegenerative disorders. Given its effects on the early evolution of β‐amyloid and tau pathology, obicetrapib represents a potential advancement in the prevention of AD, particularly in ApoE4 carriers who have an increased risks for both cardiovascular and AD pathologies.

Transcranial direct current stimulation (tDCS) is being investigated as a clinical intervention in Alzheimer’s disease (AD) with the goal of reducing its neurophysiological effects (i.e. oscillatory slowing and loss of functional connectivity). However, progress is hampered by variable outcomes across studies, likely related to both methodological and individual differences. We recently described a virtual brain network simulation method for optimizing tDCS interventions and now propose a novel methodology for further personalizing this approach. While the general model of the AD brain we used for our previous study was based on an average human connectome and brain anatomy, we now created new personalized models for 10 biomarker-confirmed AD patients. We used individual, amplitude envelope correlation (AEC)-based connectivity matrices extracted from magnetoencephalography (MEG) scans and implemented individual structural MRI data for current flow modeling of the tDCS effects. We then assessed a set of previously established stimulation strategies based on their ability to restore relevant neurophysiological outcome parameters in each personalized model, while undergoing AD damage. Personalized tDCS strategies were able to delay neurophysiological deterioration, but in dissimilar ways compared to our previous results. While the general model favored posterior anodal stimulation targeting the precuneus region, the personalized models favored frontal anodal stimulation targeting the dorsolateral prefrontal cortex (dlPFC) region in 90% of the cases. This may be explained by higher connectivity levels of frontal regions in the personalized connectivity matrices, as anodal stimulation of highly connected regions produced more beneficial effects. In this methodological study we propose several ways to improve personalized computational tDCS stimulation prediction modeling. We conclude that connectome-guided personalization of tDCS effects lead to different strategies with potentially better intervention outcomes. For external validation of this model-guided tDCS approach, personalized and general model predictions are currently being tested and compared in a clinical tDCS-MEG trial in AD patients.

Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.

A polygenic score (PGS) for Alzheimer’s disease (AD) was derived recently from data on genome-wide significant loci in European ancestry populations. We applied this PGS to populations in 17 European countries and observed a consistent association with the AD risk, age at onset and cerebrospinal fluid levels of AD biomarkers, independently of apolipoprotein E locus (APOE). This PGS was also associated with the AD risk in many other populations of diverse ancestries. A cross-ancestry polygenic risk score improved the association with the AD risk in most of the multiancestry populations tested when the APOE region was included. Finally, we found that the PGS/polygenic risk score captured AD-specific information because the association weakened as the diagnosis was broadened. In conclusion, a simple PGS captures the AD-specific genetic information that is common to populations of different ancestries, although studies of more diverse populations are still needed to better characterize the genetics of AD.