A new molecular atlas of tau enables precision diagnostics and drug targeting across neurodegenerative diseases

(Press-News.org) Tau protein aggregation is a shared feature in over 20 neurodegenerative diseases (collectively referred to as “tauopathies”). New research led by Boston Children’s Hospital challenges the current "one-size-fits-all" approach to diagnosing and treating these tauopathies.

The team, led by senior authors Judith A. Steen, PhD, and Hanno Steen, PhD, and executed by co–first authors Mukesh Kumar, PhD, Christoph N. Schlaffner, PhD, Shaojun Tang, PhD, and Maaike A. Beuvink, analyzed brain tissue from 203 patients spanning several tauopathies, including Alzheimer’s disease and chronic traumatic encephalopathy (CTE). They used a novel mass spectrometry tool called FLEXITau which enables absolute quantification of pathological tau species, measuring both the identities and abundances of disease-relevant chemical modifications.

Building on previous work on Alzheimer’s Disease, where the Steen team studied disease progression and discovered that tau chemistry changes as the disease advances, and that the p217 Tau modification ranked as the most accurate diagnostic for Alzheimer’s. p217 is now an FDA-approved diagnostic marker for Alzheimer’s Disease.

“For the first time, we can tell diagnostics and drug developers exactly which post-translational modifications to target across tauopathies, where they are on the protein, and how abundant they are in each disease,” said Steen, Director of the Neuroproteomics Laboratory at Boston Children’s. “Instead of guessing which tau forms matter, we now have a precise molecular roadmap.”

While cryo-electron microscopy has revealed disease-specific tau structures, including earlier work by the Steen lab, the chemical composition of tau—its post-translational modifications and cleavage events—has remained largely unknown. Using FLEXITau, the researchers identified 145 post-translational modifications and 195 cleavage sites across tau. Machine-learning models then ranked the molecular features that best distinguished each disease based on quantified chemical changes.

“The machine learning analysis ranks modifications by importance to disease,” said Steen. “This provides a priority list for diagnostics and drug development—the modifications that matter most. Machine learning and other AI tools require high-quality data and standards, and this method, called FLEXIQuant, can standardize measurements of any protein of interest, whether in neurodegeneration or cancer.”

“Knowing how much of a molecular target exists is essential for diagnostic or drug design,” said Steen. “If a modification is rare or low abundance, it’s not a viable target. FLEXITau gives us the quantitative data needed to model dosing, pharmacokinetics, and therapeutic feasibility.”

The findings suggest that distinct enzymatic “writer” and “eraser” pathways drive tau pathology in different diseases. “The chemical signatures reflect specific enzymatic activities,” noted Steen. “This opens new avenues for targeting the enzymes that generate disease-specific tau forms.”

Validated in an independent cohort, this atlas provides a foundation for precision diagnostics, imaging, and therapeutics across tau-mediated neurodegeneration. The FLEXIQuant platform developed can be extended to other proteins in neurodegeneration, such as synuclein in Parkinson’s Disease or TDP43 in ALS, or any protein of interest in other diseases.

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