Beyond the Stool: Circulating Short-Chain Fatty Acids Better Predict Human Gut-Related Diseases

Short-chain fatty acids (SCFAs) mediate host-microbiota interactions and are typically measured in feces as markers of gut microbial activity. However, whether fecal SCFAs adequately reflect disease-associated host-microbiota dysfunction remains unclear. We hypothesized that circulating SCFAs, which integrate microbial production, intestinal absorption, barrier function, and host metabolism, provide a more informative representation of gut-related diseases.

Seven fecal and serum SCFAs were quantified by gas chromatography-mass spectrometry in 193 individuals, including patients with colorectal cancer (CRC, n = 30), celiac disease (CD, n = 35), obesity (OB, n = 33), and healthy controls (HCs, n = 95). We developed an interpretable machine-learning framework combining stacking ensembles, bootstrap validation, permutation testing, SHAP and LIME analyses. Cross-compartment predictive modeling was used to assess the reciprocal informativeness of fecal and circulating SCFAs.

Circulating SCFAs exhibited markedly stronger disease-associated signatures than fecal SCFAs across all groups. Serum-based models achieved excellent classification performance (95% accuracy; multiclass ROC-AUC 1.00), whereas fecal SCFAs provided substantially lower predictive power (59% accuracy). Combining serum and fecal datasets yielded only marginal improvement (97.4% accuracy), indicating most diagnostic relevant information was already captured in circulation. Valeric, propionic, 2-methylbutyric, and isovaleric acids were consistently identified as the main contributors to disease discrimination. Cross-compartment modeling revealed weak predictive relationships between fecal and serum SCFAs, indicating these pools are largely non-redundant and reflect distinct biological processes.

Circulating SCFAs outperform fecal SCFAs as biomarkers of gut-related diseases, capturing the integrated effects of microbial activity and host physiology. These findings support blood-based SCFA profiling as a promising approach for precision diagnostics in microbiota-associated disorders.