Gemma Salvadó

The medial temporal lobe (MTL) is a key region in Alzheimer’s disease (AD) pathogenesis, affected early by tau pathology. While female sex and APOE-ε4 are two known risk factors that affect tau levels, whether these factors drive tau in the MTL via amyloid-dependent or amyloid-independent mechanisms remains unclear. We investigated these relationships in two large neuropathological cohorts comprising 2550 participants from the Religious Orders Study/Memory and Aging Project (ROS/MAP; n =1587, main cohort) and Arizona Study of Aging and Neurodegenerative Disorders (AZSAND; n=963, replication cohort) covering the whole AD continuum. Neuropathological assessments of global neocortical and regional MTL amyloid-β burden were used to determine the extent to which amyloid-β pathology mediated associations of APOE-ε4 carriership and sex with MTL tau burden. In both cohorts, APOE-ε4 carriership and female sex were associated with significantly greater MTL tau pathology (all p p ≤0.024). However, after jointly accounting for global and MTL amyloid-β burden, the association between APOE-ε4 and MTL tau was no longer significant in either cohort ( p ≥0.19), whereas the association between female sex and MTL tau remained robust ( p ≤0.004). Models incorporating both global and regional MTL amyloid-β explained substantially more variance in MTL tau burden than models including only global amyloid-β, and results were replicated when further adjusting for diagnostic group or neocortical tau burden. These findings suggest that APOE-ε4 and female sex influence MTL tau accumulation through partially distinct pathogenic pathways, supporting an additional contribution of regional amyloid-β to the APOE-ε4-associated MTL tau burden while implicating additional amyloid-independent mechanisms in female vulnerability to tau accumulation.

Among soluble tau biomarkers, tau phosphorylation at position T205 (p-tau205) has been suggested to distinctly emergence across Alzheimer’s disease (AD) continuum compared to other p-tau and non-phosphorylated tau forms, and a moderate relationship with both amyloid-β and tau aggregated pathologies. To evaluate this and further expand the characterization of this biomarker, we measured cerebrospinal fluid (CSF) p-tau205 using an in-house developed immunoassay in a total of 2069 samples from the BioFINDER-2 ( n = 1364) and BioFINDER-1 ( n = 705) cohorts. These two cohorts spanned the full AD continuum and were analyzed to assess cross-sectional and longitudinal associations with imaging and clinical measures. CSF p-tau205 levels were elevated in both biologically and clinically advanced disease stages. In Aβ-positive individuals, baseline p-tau205 levels correlated with Aβ-PET (R² = 0.28), tau-PET (medial temporal: R ² = 0.35, neocortical: R² = 0.29), cortical atrophy (R² = 0.15) and cognition (MMSE, R² = 0.15). Baseline p-tau205 predicted subsequent Aβ accumulation (R² = 0.44) and tau-accumulation measured by PET (R² = 0.33). Longitudinal p-tau205 levels increased more steeply longitudinally in Aβ-positive than Aβ-negative participants (β[95%CI] = 0.16[0.12–0.21], p < 0.001). Longitudinal p-tau205 changes were associated with cortical thinning (R² = 0.32) and cognitive decline (R² ≥ 0.41). When incorporating Aβ42/40, p-tau217 and p-tau205 into a conceptual CSF-based staging model, the final p-tau205-positive stage showed the strongest association with cortical atrophy, cognitive impairment, and risk of progression to dementia (HR = 6.40[4.28–9.59]). These findings support CSF p-tau205 as a biomarker of Alzheimer’s disease pathology and progression with potential value for biological staging.

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

This scientific commentary refers to ‘Modelling the temporal evolution of plasma p-tau217, amyloid PET, tau PET and cognition’, by Cogswell et al. (https://doi.org/10.1093/brain/awag075).

INTRODUCTION: Early Alzheimer's disease (AD) involves subtle cortical changes that may precede atrophy. Magnetic resonance imaging (MRI) microstructural markers may detect earlier pathology than classical morphometry. METHODS: We analyzed cross‐sectional MRI and amyloid‐β (Aβ) positron emission tomography (PET) data from 1323 non‐demented AMYPAD participants. Cortical volume, thickness, gray–white matter contrast (GWC), and mean diffusivity (MD) were related to global Aβ burden and estimated time to Aβ‐positivity using regression, correlation, and change‐point analyses. RESULTS: Microstructural measures showed stronger age associations than macrostructural measures, whereas all measures were unaffected by apolipoprotein E ( APOE) ‐ε4 carriership. GWC and MD showed minimal overlap with volume and thickness. Higher Aβ burden was most strongly associated with reduced GWC and cortical thinning. Change‐point analyses showed GWC alterations preceded Aβ‐positivity by several years. DISCUSSION: Cortical microstructural MRI, particularly GWC, changes earlier than atrophy and may serve as an early in vivo marker of AD pathology.

Importance: Biological staging of Alzheimer disease (AD) can improve diagnostic accuracy and prognostic assessment. However, existing approaches often require invasive procedures and specialized infrastructure, limiting their routine clinical use. Objective: To develop and validate a plasma-based biological staging model that closely mirrors an amyloid and tau positron emission tomography (PET)–based staging system. Design, Setting, and Participants: This observational longitudinal study included the research BioFINDER-2 cohort as the main cohort and the Knight Alzheimer Disease Research Center (ADRC) cohort as an independent validation cohort, with data acquired from November 2019 to January 2025 and from September 2007 to March 2020, respectively. Participants ranged from cognitively unimpaired (CU) to experiencing mild cognitive impairment (MCI) and dementia with AD or other neurodegenerative diseases. All individuals had both plasma biomarkers available. A Knight ADRC subsample had neuropathological data available. Data were analyzed from December 2024 to July 2025. Exposures: Plasma endogenously cleaved microtubule-binding region tau containing residue 243 (eMTBR-tau243) and phosphorylated tau at threonine 217 expressed as a percentage of its unphosphorylated form (%p-tau217). Main Outcome and Measures: The primary outcomes were PET-based biological staging according to the revised Alzheimer’s Association criteria, clinical criteria, and biomarker levels assessed cross-sectionally and longitudinally. Results: The BioFINDER-2 main cohort included 872 participants, with an additional 156 participants in the Knight ADRC cohort for independent validation. In the BioFINDER-2 cohort, participants included 383 CU participants, 182 participants with MCI, 151 with AD dementia, and 156 participants with non-AD neurogenerative diseases (mean [SD] age, 72.8 [9.2] years; 438 women [50.2%]; 516 [59.2%] apolipoprotein E [ APOE-E4 ] carriers). A plasma-based model with %p-tau217 and eMTBR-tau243 was derived, which demonstrated high concordance with established PET-based stages (C index, 0.91; 95% CI, 0.90-0.92) and was associated with clinical stage within the AD continuum (C index, 0.84; 95% CI, 0.82-0.86). In the validation cohort, concordance with PET-based stages was high (C index, 0.91; 95% CI, 0.87-0.94), as was concordance with clinical stage (C index, 0.86; 95% CI, 0.82-0.89). Concordance between fluid- and PET-based staging models was higher with this study’s %p-tau217 and eMTBR-tau243 model than with a staging model using %p-tau217 alone, especially improving the intermediate or C stage (A+T _MOD +) classification. In the neuropathology subsample, plasma staging was strongly aligned with autopsy-confirmed AD pathology using the Alzheimer Disease Neuropathologic Change scale (area under the curve, 0.96; 95% CI, 0.91-1.00). Conclusions and Relevance: In this longitudinal study, a plasma-based biological staging model incorporating %p-tau217 and eMTBR-tau243 showed strong concordance with PET-based staging, correlated with clinical severity and biomarker progression, and aligned with neuropathological categorization. This scalable, minimally invasive approach could facilitate broader implementation of biological staging in clinical practice and could enhance participant selection for disease-modifying treatments and clinical trials.

To efficiently implement plasma and cerebrospinal fluid (CSF) biomarkers for staging and prognosis of Alzheimer disease (AD), we must understand their dynamics across disease progression. We analyzed participants from the Swedish BioFINDER-2 study with mass spectrometry measurements of plasma and CSF tau species, including eMTBR-tau243/MTBR-tau243 and phosphorylation occupancies (%p-tau). Disease duration was estimated using Aβ-PET and tau-PET with the SILA algorithm. Bootstrapped LOESS models showed that %p-tau217 changes earliest, increasing just before Aβ-PET positivity. Other p-tau species changed later, with smaller dynamic ranges and earlier ceiling effects. %p-tau205 and MTBR-tau243 changes aligned with tau-PET positivity onset, while MTBR-tau243—especially plasma eMTBR-tau243—tracked cortical tau burden in later stages. Non-phosphorylated mid-region tau may serve as a late-stage biomarker. Taken together, concurrent assessments of plasma or CSF %p-tau217, %p-tau205, and (e)MTBR-tau243 provides information about different biological events in the disease cascade, which can benefit clinical trials and patient management in clinical practice.

In Alzheimer’s disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale, biologically informed disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional β-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.