Tau-Clinical Mismatch Identifies Individuals with Co-Pathology and Predicts Clinical Trajectory

Area of Science:

• Neuroscience
• Biomarkers
• Alzheimer's Disease Research

Background:

• Predicting individual Alzheimer's disease (AD) trajectories is challenging due to disease heterogeneity.
• This prediction is crucial for the effective use of disease-modifying therapies.
• A gap exists in clinically practical tools for identifying individuals with co-pathology and varied disease courses.

Purpose of the Study:

• To evaluate tau-clinical mismatch for identifying resilient and vulnerable individuals with AD.
• To compare co-pathology levels and clinical trajectories between these identified groups.

Main Methods:

• Utilized data from ADNI, Penn-ADRC, and Penn-ATM cohorts (all amyloid-β positive).
• Classified participants into canonical, resilient, or vulnerable groups based on clinical assessment (CDR-SB) and tau burden (Tau-PET or plasma p-tau217).
• Assessed neurodegeneration markers (TDP-43, α-synuclein) and longitudinal cognitive decline (CDR-SB).

Main Results:

• Tau-clinical mismatch models classified participants as canonical (55.6-57.1%), resilient (23.7-24.7%), or vulnerable (19.3-19.7%).
• Vulnerable groups exhibited earlier cognitive impairment and higher co-pathology (TDP-43, α-synuclein), while resilient groups showed later impairment.
• Models were validated in an independent dataset and demonstrated utility in predicting cognitive trajectories during anti-amyloid therapy.

Conclusions:

• Tau-clinical mismatch is a valuable tool for identifying individuals with AD at higher risk of co-pathology and divergent clinical courses.
• Plasma-based tau biomarkers offer a practical alternative to Tau-PET, with replicable results.
• These models can enhance individualized prognosis and potentially monitor therapeutic responses in clinical practice.