Routine and accessible plasma measures can be leveraged to recover reproducible, biologically distinct progression modules that improve characterization of heterogeneous AD and have practical value for risk stratification, trial enrichment, or treatment monitoring.
Alzheimers disease pathology and cognitive outcomes frequently diverge, yet current single-axis definitions cannot identify resilient (high pathology, preserved cognition) and resistant (high risk, low pathology) subgroups reliably at scale, obscuring the mechanisms that uncouple pathological burden from cognitive decline. Here, we developed a multivariate blood-based framework integrating 19 molecular assays and six risk instruments in the Bio-Hermes-001 cohort (n=1,009). Unsupervised clustering identified resilient (n=91) and resistant (n=81) subgroups, together comprising 17% of the cohort, with distinct amyloid, tau, and neurodegeneration profiles. Amyloid-PET yielded convergent but only partially overlapping classifications. Proteomic, cytokine, and polygenic profiling further distinguished resistance through an APOE-centred genomic signature and resilience through neuroinflammatory markers associated with progression toward clinical Alzheimers disease. A four-biomarker panel (A{beta}40, p-tau217, p-tau181, NfL) reproduced subgroup assignments with 83% accuracy. These findings support resilience and resistance as molecularly distinct subgroups and provide a scalable framework for pathology-informed stratification and mechanistic investigation.
K. Mavromati, C. Dalby, A. Dibble et al.· medRxiv· 0 citations
A stratified approach based on amyloid status is essential for the optimal application of blood-based biomarkers in monitoring disease progression and evaluating therapeutic efficacy in future clinical trials and precision medicine.
Keun You Kim, Hyunsun Ham, E. Yoon et al.· The journal of prevention of...· 0 citations
Most plasma proteomic studies in Alzheimer's disease (AD) compare cases and controls cross-sectionally, leaving unresolved which AD-associated proteins mark diagnostic states and which are linked to disease progression. Using longitudinal SomaScan profiling from the Global Neurodegeneration Proteomics Consortium (13,449 participants, 17,269 samples, 7,362 aptamers), we separated baseline AD differences from AD-specific change over time. Linear mixed-effects models requiring concordant baseline and AD-by-time effects defined a 30-protein signature. We prioritized proteins across five evidence domains: clinical progression, AD biomarker alignment, cerebrospinal fluid concordance, independent prospective replication in UK Biobank and genetic support from Mendelian randomization and rare-variant burden. Thirteen proteins were supported in two or more domains and six in three. EDA2R, HPGDS, ITGAV and CLEC3B converged across clinical, biomarker and prospective evidence. Signature proteins aligned more strongly with tau and neuronal-injury markers than with Ab42/40. ANTXR1 showed direction-concordant plasma pQTL Mendelian randomization and nominal rare-variant burden signals, supporting its prioritization within the longitudinal AD signature. By distinguishing diagnostic-state markers from progression-linked changes, this longitudinal, multi-domain approach prioritizes proteins for validation as markers of AD progression and for mechanistic and therapeutic follow-up.
Junyoung Park, Y. le Guen, A. Peña-Tauber et al.· medRxiv· 0 citations
Structural brain changes during the earliest asymptomatic stages of Alzheimer’s disease (AD) remain poorly understood. Previous research in preclinical AD shows heterogeneous findings, reporting both subtle neuronal loss and paradoxical increases in grey matter (GM) volume. This study applies an extensive cerebrospinal fluid (CSF) biomarker panel to better understand the biological processes underlying longitudinal GM changes in cognitively unimpaired (CU) adults, spanning the amyloid/tau (AT) continuum.
We analysed data from 627 CU individuals from three longitudinal cohorts (ALFA+, Wisconsin ADRC, WRAP), with repeated MRI (3.5 ± 0.9 years) and baseline CSF biomarkers from the NeuroToolKit panel (Roche Diagnostics). Using non-negative matrix factorization, we decomposed the CSF biomarker levels into six latent components, reflecting amyloid-β (Aβ) pathology, tau-related pathophysiology with synaptic injury, neuroaxonal injury, microglial reactivity, astrocytic reactivity, and cytokine signalling. We tested associations between component weights and voxel-wise longitudinal GM volume changes using single-component and a joint-all components model. Analyses were performed across the full sample and stratified by AT status. Associations with longitudinal cognitive performance (PACC) were assessed using linear mixed-effects models.
The Aβ pathology component was the strongest and most widespread predictor of longitudinal GM atrophy, predominantly in temporal and frontal regions, also when controlling for tau pathophysiology, neuroaxonal injury, or neuroinflammatory components. Higher Aβ pathology scores were also associated with cognitive decline. The component capturing tau-related pathophysiology and synaptic injury initially associated with GM loss but lost significance after accounting for other biomarker components. In contrast, components reflecting microglial reactivity, astrocytic reactivity, and cytokine signalling were associated with longitudinal GM volume increases, with effects varying by AT stage.
In this large longitudinal sample of asymptomatic individuals, the Aβ-dominant biomarker component showed the strongest association with longitudinal GM atrophy and cognitive decline, beyond the effects of tau pathophysiology and neuroaxonal injury. While glial and inflammatory processes may contribute to transient GM increases in preclinical AD. A better understanding of these dynamic relationships between structural brain changes and various biological pathways at the earliest stages of AD is crucial to inform the development of interventions before irreversible neurodegeneration occurs.
W. Pelkmans, R. Cacciaglia, Michalis Kassinopoulos et al.· Molecular Neurodegeneration· 0 citations
Higher plasma YKL‐40 was associated with greater white matter hyperintensity (WMH), whereas higher plasma GFAP was related to increased 18F‐florbetapir (FBP) standardized uptake value ratio (SUVR) and higher plasma p‐tau217 was associated with reduced MTL cortical thickness and hippocampal volume.
Batool Rizvi, Jenna N. Adams, Alison R. Bamford et al.· Alzheimer's & Dementia· 1 citation
The introduction of blood-based biomarkers (BBMs) for Alzheimer’s disease (AD) represents one of the most transformative advances in neurodegenerative disease research over the past decade. 1,2 For the first time, biological evidence of AD pathology can be obtained through a minimally invasive, scalable blood test, opening new opportunities for early diagnosis, patient triage, and implementation of disease-modifying therapies. 3 Among the available biomarkers, phosphorylated tau (p-tau) species, particularly plasma p-tau217, have consistently shown excellent diagnostic performance across the AD continuum, recently culminating in regulatory approval of plasma p-tau217-based assays in both the USA and Europe. 4–6 Despite this remarkable clinical success, a fundamental paradox remains. Plasma tau biomarkers work
Lucilla Parnetti, L. Gaetani· EBioMedicine· 0 citations
