MALT1 in cerebrospinal fluid: a prognostic biomarker and potential therapeutic target in Alzheimer's disease.

Background: Alzheimer's disease (AD) is a devastating neurodegenerative disorder, and early intervention remains the only reliable strategy to slow its progression. Notably, cerebrospinal fluid (CSF) metabolites play a crucial role in the early diagnosis of AD, making their investigation highly significant. Methods: We integrated two-sample Mendelian randomization (MR), transcriptomic, and machine learning (ML) analyses to identify causal CSF metabolites and their downstream molecular mediators in AD. MR assessed the causal effects of 338 CSF metabolites on AD risk, while integrated GEO datasets (GSE4757, GSE48350, and GSE122063) were analyzed to identify 50 differentially expressed associated genes (DEAGs). Immune infiltration and correlation analyses were performed to characterize immune infiltration. Predictive ML models, including Random Forest (RF), Support Vector Machine (SVM), Generalized Linear Model (GLM), and Extreme Gradient Boosting (XGBoost), were used to screen biomarkers, construct a diagnostic nomogram, and validate findings Results: The MR analysis identified 15 potential CSF metabolites associated with AD. Elevated creatine levels (OR = 0.610, 95% CI: 0.441-0.845, Conclusion: This study demonstrates a causal association between CSF metabolites and AD risk, highlighting MALT1 as a promising biomarker and potential therapeutic target for AD.