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

Clicks: 1
ID: 338233
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #191 of 192 articles by views in qjm : monthly journal of the association of physicians

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 192 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Reference Key
openalex_W7225077697 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Simone Baldi, Alessio Rotelli, Francesco Cei, Sara Bertorello, Azzurra Bongianni, Marta Menicatti, Antonino Salvatore Calabrò, Fabio Cianchi, Barbara Colombini, Francesco Sofi, Elena Niccolai, Bartolucci Gianluca, Ernesto Iadanza, Amedeo Amedei
Are you one of these authors? Claim your profile
Journal qjm : monthly journal of the association of physicians
Year 2026
DOI
10.1093/qjmed/hcag306
URL
https://doi.org/10.1093/qjmed/hcag306
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.