Optimal Transport‐Based Transcriptomic Mapping Revealed Atypical Disease Progression Subtypes in Living Alzheimer’s Disease Patients

Through a deep transfer learning-based approach on the blood and brain transcriptomic data, we successfully identified the atypical disease progression subgroups among live AD patient cohorts in ADNI and ANMerge with promising biomarkers/gene signatures. The molecular signatures identified in this study not only enhance our comprehension of the underlying pathophysiological mechanisms but also hold promise for developing early prognosis and effective personalized treatments for AD and related tauopathies.