Table 1_Quantitative mapping of gut microbiota feature importance to TCM syndrome elements in clinical T2DM stages.xlsx

Support vector machine (SVM) models with SHAP values quantified microbial feature importance for individual syndrome elements, revealing progressive evolution from dampness, qi deficiency, and spleen (pre-diabetes) to dampness, phlegm, heat, and kidney (complications). Bacteroides and Faecalibacterium showed the highest feature importance for spleen (4.9% each), Veillonella showed the highest feature importance for dampness (3.4%), and Bifidobacterium was the top feature for phlegm (1.0%).

Fecal microbiota transplantation (FMT) in 34 patients provided interventional evidence consistent with the model: 26.7% of post-FMT differentially abundant genera (4 of 15) and 7.5% of differentially abundant species (8 of 106) overlapped with top-ranking SVM features.</p>Discussion<p>This proof-of-concept study provides the first quantitative mapping of gut microbiota feature importance to TCM syndrome elements, establishing an integrated framework combining MR-based causal prioritization, ML-based feature importance mapping, and FMT-based intervention validation for micro-syndrome differentiation.</p>