# Gut Microbiota Composition is related to AD Pathology Summary: Author tries to investigate the associations between gut microbiota composition and AD biomarkers using ML models in patients with AD, MCI and SCD. Methods: Statistical Inference and Machine Learning. Machine Learning Model used: XGBoost (Extreme gradient boosting trees). Then, use logistic regression to obtain effect sizes of associations (between highest ranked microbes and outcome of 3 ML models (predictors)). Statistical Analysis: ANOVA, Kruskal-Wallis tests, Chi-square. PERMANOVA. Conclusion: Were able to find associations, lower abundance of SCFA-producing microbes was associated with higher odds of AD pathology. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://tianyi0216.gitbook.io/blog/reading-notes/stats-other/microbiome-ml/gut-microbiota-composition-is-related-to-ad-pathology.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.