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Osteoarthritis treatment via the GLP-1–mediated gut-joint axis targets intestinal FXR signaling
Open accessAbstract
Whether a gut-joint axis exists to regulate osteoarthritis is unknown. In two independent cohorts, we identified altered microbial bile acid metabolism with reduced glycoursodeoxycholic acid (GUDCA) in osteoarthritis. Suppressing farnesoid X receptor (FXR)—the receptor of GUDCA—alleviated osteoarthritis through intestine-secreted glucagon-like peptide 1 (GLP-1) in mice. GLP-1 receptor blockade attenuated these effects, whereas GLP-1 receptor activation mitigated osteoarthritis. Osteoarthritis patients exhibited a lower relative abundance of Clostridium bolteae , which promoted the formation of ursodeoxycholic acid (UDCA), a precursor of GUDCA. Treatment with C. bolteae and Food and Drug Administration–approved UDCA alleviated osteoarthritis through the gut FXR–joint GLP-1 axis in mice. UDCA use was associated with lower risk of osteoarthritis-related joint replacement in humans. These findings suggest that orchestrating the gut microbiota–GUDCA–intestinal FXR–GLP-1–joint pathway offers a potential strategy for osteoarthritis treatment.
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“Gut dysbiosis has been implicated in RA-associated immune activation, whereas modulation of microbial BA metabolism and glucagon-like peptide-1 secretion has emerged as a potential therapeutic route in OA [130].”
From Interorgan Communications in Skeletal Pathophysiology: From Molecular Pathways to Multidisciplinary Therapies (2026) · cites this paper as [130]
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Research works printed but not linked: 1
- S. Hawley A. Delmestri A. Judge C. J. Edwards C. Cooper N. K. Arden D. Prieto-Alhambra “Total Hip and Knee Replacement Among Incident Osteoarthritis and Rheumatoid Arthritis Patients Within the UK Clinical Practice Research Datalink (CPRD) Compared to Hospital Episode Statistics (HES): A Validation Study ” paper presented at International Conference on Pharmacoepidemiology & Therapeutic Risk Management Dublin Ireland 25 to 28 August 2016.
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Antiinflammatory actions of glucagon-like peptide-1–based therapies beyond metabolic benefits
Wong, C. K., & Drucker, D. J. (2025) · Journal of Clinical Investigation · doi:10.1172/jci194751 · Cited by 112
Osteoarthritis as a systemic disease
Collins, K. H., Haugen, I. K., Neogi, T., & Guilak, F. (2025) · Nature Reviews Rheumatology · doi:10.1038/s41584-025-01332-8 · Cited by 58
“Although initial studies aimed to understand the role of the gut microbiome as a link between diet and OA 135–138 , data now indicate that the gut microbiota–GLP1 axis could be a highly attractive drug target for OA 47 .”
Emerging Frontiers in GLP-1 Therapeutics: A Comprehensive Evidence Base (2025)
Patel, S., & Niazi, S. K. (2025) · Pharmaceutics · doi:10.3390/pharmaceutics17081036 · Cited by 48
“It demonstrated that GLP-1 RAs can modulate intestinal farnesoid X receptor (FXR) signaling to improve joint health [168].”
Glucagon-like peptide-1 receptor agonists in arthritis: current insights and future directions
Karacabeyli, D., & Lacaille, D. V. (2025) · Nature Reviews Rheumatology · doi:10.1038/s41584-025-01302-0 · Cited by 31
“People with OA have lower serum GLP-1 levels 63 , and intra-articular liraglutide injection alleviates pain 55 and attenuates cartilage degradation in OA mouse models 63 .”
Influential3D bioprinting bone/cartilage organoids: construction, applications, and challenges
Gao, D., Li, R., Pan, J., Li, C., Zhang, W., Qin, L., & Lai, Y. (2025) · Journal of Orthopaedic Translation · doi:10.1016/j.jot.2025.08.008 · Cited by 22
“Epidemiological data from the World Health Organization reveal that osteoarthritis alone affects over 500 million individuals globally, with prevalence rates surpassing 20 % in populations aged 65 years and older [4].”
Self-citation
Metadata
- Authors
- Yang, Y., Hao, C., Jiao, T., Yang, Z., Li, H., Zhang, Y., Zhang, W., Doherty, M., Sun, C., Yang, T., Li, J., Wu, J., Zhang, M., Wang, Y., Xie, D., Wang, T., Wang, N., Huang, X., Li, C., Gonzalez, F. J., Wei, J., Xie, C., Zeng, C., & Lei, G.
- Affiliations
- Central South University (CN)
- Chinese Academy of Sciences (CN)
- Harvard University (US)
- University of Nottingham (GB)
- Nanjing University of Chinese Medicine (CN)
- University of Toronto (CA)
- National Institutes of Health (US)
- Corresponding author
- Yang, Yuanheng
- Hao, Cong
- Jiao, Tingying
- Yang, Zidan
- Li, Hui
- Wei, Jie
- Xie, Cen
- Zeng, Chao
- Lei, Guanghua
- ORCID
- Venue
- Science
- Published
- 2025-04-04
- Volume
- 388
- Issue
- 6742
- Pages
- eadt0548-eadt0548
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4409176469
- Cited by
- 160
- References
- 91
- Citations by year
- 2026: 110 · 2025: 50
- FWCI
- 47.42
- Type
- journal article
- Language
- en
- Open access
- Licence
- cc-by
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (82 372 474, 2022YFC2505500, 81930071, 2022YFC3601900)
- Peking University
- Xiangya Hospital, Central South University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Rheumatology › Osteoarthritis Treatment and Mechanisms
- Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
- Keywords
- osteoarthritis, gut-joint axis, glucagon-like peptide-1, farnesoid X receptor, glycoursodeoxycholic acid, bile acid metabolism, gut microbiota, Clostridium bolteae, ursodeoxycholic acid, GLP-1 receptor, joint replacement, microbiota-targeted therapy
- MeSH terms
- Glucagon-Like Peptide-1 Receptor, Gastrointestinal Microbiome, Receptor, Farnesoid X-Activated, Animals, Bile Acids and Salts, Clostridium, Female, Humans, Male, Mice, Inbred C57BL, Osteoarthritis, Ursodeoxycholic Acid, Signal Transduction, Receptors, Cytoplasmic and Nuclear, Mice, Glucagon-Like Peptide 1
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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