Tau extent outperforms tau load as a predictor of neurodegeneration in Alzheimer's disease

Mol Neurodegener. 2026 Jun 4. doi: 10.1186/s13024-026-00945-1. Online ahead of print.

ABSTRACT

BACKGROUND: In Alzheimer's disease (AD), tau pathology is more strongly linked to neurodegeneration than amyloid-β and better predicts brain atrophy. The spatial extent of tauopathy (SEOT) has shown promise as an earlier and more sensitive marker of AD severity than tau load, but how these complementary dimensions relate to neurodegeneration remains unclear. Here, we compared the in vivo associations of tau-PET extent versus load with cross-sectional and longitudinal neurodegeneration.

METHODS: We studied 367 participants across the healthy-aging to AD continuum (mean age 69.3 years; 61% female) from the TRIAD cohort who underwent [¹⁸F]MK-6240 tau-PET. Tau load was quantified as regional standardized uptake value ratio (SUVR), and SEOT as the proportion of abnormal voxels, within a temporal meta-region of interest (ROI) and a full-cortex ROI. Neurodegeneration markers included cortical thickness, hippocampal volume (HCV), medial temporal atrophy (MTA) visual ratings, plasma neurofilament light (NfL), and CSF total tau (t-tau). Cross-sectional associations were evaluated using multiple linear regression or covariate-adjusted Spearman correlations. We also compared local correlations of tau load and extent with cortical thickness across all cortical regions. Longitudinal predictive value for neurodegeneration was tested using linear mixed-effects models.

RESULTS: Cross-sectionally, all tau-PET metrics were significantly associated with neurodegeneration across imaging and fluid biomarkers. Full-cortex SEOT provided the best model fit for cortical thinning. SEOT outperformed tau load for associations with HCV and for predicting MTA, whereas SEOT and SUVR showed comparable associations with plasma NfL and CSF t-tau. Tau extent was equal or superior to tau load in its correlation with local cortical thickness across all cortical regions. Longitudinally, baseline full-cortex SEOT best predicted future cortical thinning, while temporal SEOT best predicted future hippocampal atrophy.

CONCLUSIONS: Across cross-sectional and longitudinal analyses, tau extent provided superior predictive value for imaging-based neurodegeneration compared with tau load. By enabling a spatially unbiased, whole-brain assessment of tau burden that accommodates heterogeneous topographies, SEOT represents a promising complementary tau-PET metric for staging and tracking disease progression in AD.

PMID:42243971 | DOI:10.1186/s13024-026-00945-1