CSF total tau as a proxy of synaptic degeneration
Aug 29, 2025·,,,,,,,,,
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0 min read
Carolina Soares
Bruna Bellaver
Pamela C. L. Ferreira
Guilherme Povala
Cristiano Schaffer Aguzzoli
João Pedro Ferrari-Souza
Hussein Zalzale
Firoza Z. Lussier
Francieli Rohden
Sarah Abbas
Guilherme Bauer-Negrini
Douglas Teixeira Leffa
Andréa L. Benedet
Rebecca Langhough
Tobey J. Betthauser
Bradley T. Christian
Rachael E. Wilson
Dana L. Tudorascu
Pedro Rosa-Neto
Thomas K. Karikari
Henrik Zetterberg
Kaj Blennow
Eduardo R. Zimmer
Sterling C. Johnson
Tharick A. Pascoal
Abstract
Cerebrospinal fluid (CSF) total tau (t-tau) is considered a biomarker of neuronal degeneration alongside brain atrophy and fluid neurofilament light chain protein (NfL) in biomarker models of Alzheimer’s disease (AD). However, previous studies show that CSF t-tau correlates strongly with synaptic dysfunction/degeneration biomarkers like neurogranin (Ng) and synaptosomal-associated protein 25 (SNAP25). Here, we compare the association between CSF t-tau and synaptic degeneration and axonal/neuronal degeneration biomarkers in cognitively unimpaired and impaired groups from two independent cohorts. We observe a stronger correlation between CSF t-tau and synaptic biomarkers than neurodegeneration biomarkers in both groups. Synaptic biomarkers explain a greater proportion of variance in CSF t-tau levels compared to neurodegeneration biomarkers. Notably, CSF t-tau levels are elevated in individuals with abnormalities only in synaptic biomarkers, but not in individuals with abnormalities only in neurodegeneration biomarkers. Our findings suggest that CSF t-tau is a closer proxy for synaptic degeneration than for axonal/neuronal degeneration.
Type
Publication
Nature Communications
Status
Peer-reviewed

Authors
Biomedical Data Scientist
Computational neuroscientist working at the intersection of machine learning, biomedical
imaging, and human genetics in neurodegenerative disease. My work applies deep learning to
high-dimensional medical images, harmonizes imaging measurements across sites and acquisition
protocols, and integrates imaging with genomic, proteomic, and longitudinal clinical data to
characterise Alzheimer’s disease and related dementias, with particular focus on fluid and
imaging biomarkers of neurodegeneration.