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| Item Type: | Article |
|---|---|
| Title: | Machine learning identifies microbiome and clinical predictors of sustained weight loss following prolonged fasting |
| Creators: |
Kaufhold, Gelsomina  ORCID: https://orcid.org/0009-0009-0868-3284, Bartolomaeus, Theda U.P. ORCID: https://orcid.org/0000-0002-5156-7184, Schütte, Kristin ORCID: https://orcid.org/0000-0002-4032-5382, Schütte, Till ORCID: https://orcid.org/0000-0003-4869-2766, Kamboj, Sakshi, Löber, Ulrike ORCID: https://orcid.org/0000-0001-7468-9531, Rahn, Gabriele, McParland, Victoria ORCID: https://orcid.org/0000-0003-0731-3272, Braun, Lena, Markó, Lajos ORCID: https://orcid.org/0000-0003-1888-5575, Mammadli, Matanat, Krannich, Alexander ORCID: https://orcid.org/0000-0002-4025-6495, Bahr, Lina S. ORCID: https://orcid.org/0000-0001-7932-8639, Gutmann, Friederike ORCID: https://orcid.org/0000-0001-6763-2270, Paul, Friedemann ORCID: https://orcid.org/0000-0002-6378-0070, Ducarmon, Quinten R., Zeller, Georg, Mesnage, Robin, Wilck, Nicola ORCID: https://orcid.org/0000-0003-3189-5364, Zernecke, Alma, Oefner, Peter J., Gronwald, Wolfram, Müller, Dominik N. ORCID: https://orcid.org/0000-0003-3650-5644, Forslund-Startceva, Sofia K. ORCID: https://orcid.org/0000-0003-4285-6993, Bähring, Sylvia ORCID: https://orcid.org/0000-0001-8734-9755, Bartolomaeus, Hendrik ORCID: https://orcid.org/0000-0003-4288-3828 and Siebert, Nadja ORCID: https://orcid.org/0000-0001-6815-7387
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| Abstract: | BACKGROUND: Prolonged fasting may improve metabolic health, but controlled data in healthy adults with longer follow-up and multi-omics profiling are limited. We investigated the immediate and 12-week follow-up effects of a 5-day fasting intervention on body composition, gut microbiome, and circulating and fecal metabolites, and assessed whether baseline characteristics predict individual weight-loss response. METHODS: In a randomized, waitlist-controlled trial, 38 healthy adults completed a 5-day fasting intervention with 12-week follow-up (LEANER study). Outcomes included body mass index and body composition, gut microbiome composition, and plasma and fecal metabolites. Changes over time and between groups were evaluated using regression-based models and paired non-parametric tests, as appropriate. Additionally, permutation-based multivariate testing was performed on microbiome and metabolome data. Twelve-week body weight response was predicted using data-driven machine learning with cross-validation, followed by external validation in three independent cohorts undergoing prolonged fasting protocols. RESULTS: Fasting reduced body mass index acutely, predominantly driven by loss of fat mass, and these improvements partially persisted at 12 weeks. Fasting induced marked shifts in gut microbiome composition and in plasma and fecal metabolites. Post-fasting and longer-term changes in microbial diversity were associated with baseline microbiome diversity. A model combining baseline microbiome and clinical variables predicted body mass index response at 12 weeks; prominent predictors included an unclassified Faecalibacterium species, Oscillibacter sp. 50_27, low-density lipoprotein cholesterol, and systolic blood pressure. The model generalized to three independent cohorts, including individuals with metabolic syndrome, patients with multiple sclerosis exposed to repeated fasting, and healthy volunteers fasting for 6-12 days. CONCLUSIONS: In healthy adults, a 5-day prolonged fasting intervention produces robust short-term metabolic changes with partial persistence and consistent remodeling of the gut microbiome and metabolite profiles. Baseline microbiome and clinical characteristics can help stratify expected longer-term responses, supporting the development of individualized fasting-based interventions. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04452916. Prospectively registered on June 29, 2020. |
| Keywords: | Body Composition, Body Mass Index, Fasting, Feces, Gastrointestinal Microbiome, Intermittent Fasting, Machine Learning, Metabolome, Microbiota, Multiomics, Predictive Learning Models, Weight Loss |
| Source: | Genome Medicine |
| ISSN: | 1756-994X |
| Publisher: | BioMed Central |
| Volume: | 18 |
| Number: | 1 |
| Page Range: | 136 |
| Date: | 17 September 2026 |
| Official Publication: | https://doi.org/10.1186/s13073-026-01765-0 |
| PubMed: | View item in PubMed |
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