Sex‐adjusted blood biomarkers differentiate AD from LATE

Background Alzheimer’s disease (AD) is a complex neurodegenerative disorder that affects cognition, memory, and behavior, while limbic-predominant age-related TDP-43 encephalopathy (LATE) recently defined common mimics the clinical symptoms of AD (Table 1). At present, there are no effective diagnostic biomarkers for LATE which can mainly be confirmed by autopsy. Method We applied machine learning algorithms to identify informative blood differentiating from LATE. To blood-based discriminating based on imbalanced data, we proposed an innovative integrated feature selection-based approach, Preprocessing, Environmental factor analysis, Feature selection, Validation (PEFV). Result focused association analysis markers differentiate and/or AD, ROSMAP (Figure 1), considering factors including medication diet. pre-identified some sensitive dietary factors, then these performed sex-stratified group analyses. identified 3 small sets distinguish adjusted each case, All, Male, Female. In addition, analyzed scenarios case: pure vs. LATE+AD, AD+LATE, (Tables 2-4). While usually, single biomarker cannot achieve high accuracy reliability due complexity both LATE, set scenario was small. For example, in Male 8 were needed LATE+AD with rate 61%, improvement about 10% over using all test features; 77%, 23% 4 75%, 22% features. Conclusion this study, tests, explored data our approach PEFV used it discover distinguishing