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Enregistrement W4414192449 · doi:10.1101/2025.09.13.25335690

Tau-Connectome Subtypes and Solanezumab Response in Preclinical Alzheimer’s Disease

2025· preprint· en· W4414192449 sur OpenAlexaboutno aff
Hamid Abuwarda, Wen‐Xiang Tsai, Shengxian Ding, Mohammed Elhassan, Xilin Shen, Yize Zhao, R. Todd Constable, Carolyn Fredericks

Notice bibliographique

RevuemedRxiv · 2025
Typepreprint
Langueen
DomaineMedicine
ThématiqueAlzheimer's disease research and treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésClinical trialDiseaseBiomarkerCognitionDementiaClinical Dementia RatingClinical endpointFunctional magnetic resonance imagingTime point

Résumé

récupéré en direct d'OpenAlex

Abstract Importance This study identifies clinically meaningful subtypes within preclinical Alzheimer’s disease (AD) using the functional connectome and introduces tau-predictive functional connectivity as a new tool to stratify risk and treatment response. Objective To determine whether fMRI–derived functional connectivity can identify subgroups with differential cognitive outcomes and treatment responses among amyloid-positive, cognitively unimpaired adults. Design, Setting and Participants A post-hoc analysis of the Anti-Amyloid in Asymptomatic Alzheimer’s disease (A4) study, a randomized, double-blinded, placebo-controlled clinical trial. The A4 trial was a multi-center clinical trial in the United States, Canada, Australia, and Japan. This trial enrolled cognitively unimpaired adults aged 65-85, of whom 1,490 had successful functional magnetic resonance imaging data preprocessing: A β -(n = 445) and A β + (n = 1045). Longitudinal data were drawn from both the primary trial and the open-label time period (up to 455 weeks). Hierarchical clustering was performed on baseline functional connectivity patterns, followed by spline-based generalized linear modeling to evaluate differences in longitudinal clinical and biomarker outcomes. Intervention(s) or Exposure(s) Tau-predictive functional connectivity, derived from previously generated connectome-based tau predictive models, was used to cluster individuals at baseline. Subsequent analyses compared longitudinal outcomes within the placebo-only group and within the treatment group. Main Outcome(s) and Measure(s) For the original A4 trial, the primary endpoint was the Preclinical Alzheimer’s Cognitive Composite (PACC) score, with secondary clinical outcomes including the Clinical Dementia Rating Sum of Boxes (CDR-SB), Cognitive Function Index (CFI), and Activities of Daily Living (ADL). Secondary biomarker endpoints included plasma phosphorylated tau-217 (pTau-217) and cortical amyloid SUVR (Standardized Uptake Value Ratio). We assessed significance using either permutation testing or bootstrapped models (n=5000). All confidence intervals were defined by bootstrapped models. Results Hierarchical clustering of connectivity data revealed two distinct subgroups among amyloid-positive individuals in the A4 trial. Individuals had distinct tau PET spatial distributions: one subgroup (Cluster 1, n=618) with a typical limbic-predominant distribution, and the other (Cluster 2, n=427) showing an atypical cortical-predominant distribution. In the placebo arm, the cortical-predominant group exhibited significantly more cognitive decline on both PACC (marginal mean difference: -3.5, 95% CI: -6.4 to -0.6, p = 0.009) and secondary cognitive and clinical outcomes (CDR-Sum of Boxes: +1.8 (+0.6 to +3.1), p =0.005; Activities of Daily Living: - 8.7 (-16.5 to -1.2), p = 0.010; Cognitive Function Index: +4.4 (+1.1 to +7.9) p=0.010; Plasma pTau-217 not significant: p = 0.67; FDR-adjusted for 4 tests) at the end of the study (Week 455). Remarkably, in the cortical-predominant cluster, those treated with solanezumab had significantly improved PACC scores compared to placebo counterparts (marginal mean difference at 455 weeks: +3.3, 95% CI: +0.4 to +6.4, p = 0.03). This corresponds to 48% less cognitive decline, equivalent to a 103-week difference in modeled cognitive trajectories over the 9-year study period, despite the trial’s overall null results. Secondary clinical outcomes were not significant in either cluster. In typical tau group, solanezumab showed no effect in secondary outcomes (CDR-SB: -0.1, 95% CI: –0.8 to +0.7; p=0.80; ADL: +0.9, 95% CI: –3.3 to +5.1 p=0.80; CFI: –0.2, 95% CI: –2.1 to +1.5, p=0.80; FDR-adjusted for 5 tests). In the cortical-predominant group, effects trended in favor of solanezumab on CDR-SB: -1.1, 95% CI: –0.4 to +2.8; p=0.20; ADL: +2.5, 95% CI: –6.4 to +12.1; p=0.60; CFI: –2.5, 95% CI: –6.4 to +0.8; p=0.20; FDR-adjusted for 5 tests) but none reached significance. Amyloid clearance was significantly reduced in both groups at equal levels (Typical tau Solanezumab-Placebo Δ SUVR: -0.06, 95% CI: -0.08 to -0.04, p =<0.001; Cortical-predominant tau Solanezumab-Placebo Δ SUVR: -0.05, 95% CI: -0.08 to -0.02, p = 0.008; FDR-adjusted for 5 tests). There was a significant reduction in plasma pTau-217 for cortical-predominant solanezumab patients (-0.29; 95% CI: -0.49 to -0.11, p=0.008; FDR-adjusted for 5 tests), while the typical group showed no associated differences (-0.08; 95% CI: -0.22 to +0.05, p = 0.63; FDR-adjusted for 5 tests). Conclusions and Relevance We show that baseline clustering using tau-predictive functional connectivity identified an AD subtype with worse overall outcomes and stronger responsiveness to solanezumab. These findings highlight the potential of the functional connectome to personalize interventions in AD and in future clinical trials. Key Points Question Can tau-predictive functional connectome patterns derived from baseline functional magnetic resonance imaging (fMRI) identify clinically meaningful subgroups in preclinical Alzheimer’s disease? Findings We performed a post-hoc analysis of the Anti-Amyloid in Asymptomatic Alzheimer’s (A4) study, a clinical trial of solanezumab in preclinical Alzheimer’s patients. Hierarchical clustering of baseline tau-predictive functional connectome signatures identified two distinct subgroups. Groups showed no baseline differences in demographic or biomarker variables, except for a modest difference in racial distribution. Spatial tau distributions differed among the groups, with one group showing a classical limbic-predominant pattern and the other having a cortical-predominant tau pattern. Among participants in the placebo arm, the cortical-predominant subgroup demonstrated poorer longitudinal scores on the A4 trial’s primary endpoint, the Preclinical Alzheimer’s Cognitive Composite (-3.3 points; lower score indicates greater cognitive impairment), relative to the other group. Importantly, within the treatment arm, individuals belonging to the cortical predominant subgroup exhibited positive treatment effects relative to the placebo group, despite the trial’s overall null results. Meaning Our clustering analyses used the baseline fMRI-derived functional connectome to identify a vulnerable subgroup in preclinical AD individuals that benefited from the drug in the A4 null trial of solanezumab. These findings support the use of fMRI-based biomarkers for patient stratification and the development of more personalized treatments in future clinical trials of Alzheimer’s disease.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,073
Tête enseignante GPT0,391
Écart entre enseignants0,319 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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