Clinical Scorecard: The Many Faces of Tau

At a Glance

Key Highlights

• Distinct tau chemical signatures characterize over 20 neurodegenerative diseases.
• FLEXITau workflow enables precise measurement of pathological tau and its modifications.
• Machine learning identifies key tau modifications for diagnostics and drug development.
• Each tauopathy has a unique combination of post-translational modifications and cleavage patterns.
• Absolute quantification of tau modifications is essential for effective diagnostics and treatment.

Guideline-Based Recommendations

Diagnosis

• Utilize disease-specific tau modifications for accurate diagnostics.

Management

• Target identified post-translational modifications in therapeutic development.

Monitoring & Follow-up

• Quantify pathological tau levels to assess disease progression.

Risks

• Low abundance modifications may not be viable targets for treatment.

Patient & Prescribing Data

Patients diagnosed with tauopathies.

Focus on the most relevant tau modifications for tailored therapeutic approaches.

Clinical Best Practices

• Incorporate quantitative proteomics in diagnostic workflows.
• Apply machine learning to prioritize tau modifications for research and treatment.
• Ensure absolute quantification of molecular targets for effective drug design.

References

• Boston Children's Hospital Study