Abstract
Background:
Obesity is a major risk factor for musculoskeletal disorders. Glucagon-like peptide-1 receptor (GLP-1R)–based agonists facilitate weight loss and may influence musculoskeletal health. However, whether GLP-1R based agonists are associated with the musculoskeletal adverse events during the treatment remains unclear.
Objectives:
To assess the association between the use of GLP-1R agonists (GLP-1RA) and the spontaneous reports of musculoskeletal adverse events based on RCT safety data.
Design:
A systematic review and meta-analysis of RCTs.
Methods:
PubMed, Embase, the Cochrane Center Register of Controlled Trials for Studies, and Clinicaltrial.gov website were searched for RCTs of GLP-1R–based agonists from the inception to June 2025. The primary endpoint was the association between GLP-1R–based agonists and the reported musculoskeletal adverse events, expressed as risk ratio with the 95% confidence interval (CI) using a random-effect model.
Results:
A total of 43 RCTs with 100,488 participants were included. No significant difference was observed between users of GLP-1RAs and the control group in the reporting of the prespecified musculoskeletal adverse events, including gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic fracture, synovitis, or intervertebral disc protrusion. However, a higher proportion of male participants was associated with fewer reports of osteoarthritis (β = −0.015, 95% CI, −0.029 to −0.001) in GLP-1R–based agonist users.
Conclusion:
GLP-1RAs were not associated with the spontaneously reported events of gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic fracture, synovitis, or intervertebral disc protrusion. A higher percentage of male participants was associated with fewer reports of osteoarthritis among GLP-1RA users.
Plain Language Summary
Keywords
Introduction
Obesity, one of the major risk factors for mortality and morbidity in recent years, 1 is a growing public health problem. By 2030, nearly one in two adults in the U.S. will have obesity. 2 Obesity significantly impacts the prevalence, severity, and treatment responses of musculoskeletal diseases, 3 with an array of musculoskeletal disorders being identified as complications associated with obesity. 1 The underlying mechanisms might include the biomechanical stress generated by excess weight, cellular overnutrition in the synovium, which destroys the articular integrity, 4 and the increased activation of innate immune cells. 5 Thus, weight loss might be able to hinder the risks and progression of musculoskeletal disorders.
As novel anti-obesity medications, the potential benefits of glucagon-like peptide-1 receptor (GLP-1R)–based agonists have been indicated in lowering the risk of musculoskeletal disorders. First, the anti-inflammatory effects of GLP-1R–based agonists could alleviate the symptoms of osteoarthritis. 6 Moreover, GLP-1R–based agonists could stimulate osteoblast differentiation, inhibit osteoclast activity, and reduce oxidative stress in bone tissue, thus improving bone remodeling and reducing the risk of bone fracture. 7
However, the clinical impact of GLP-1R–based agonists on musculoskeletal health is very complex. Beyond the potential protective mechanisms, there are concerns regarding possible drug-related adverse events, such as gout flares and arthralgia, which may be linked to rapid metabolic shifts. 8 Consequently, preceding clinical studies exploring the influence of GLP-1R–based agonists on osteoarthritis6,9–11 or rheumatoid arthritis have generated divergent conclusions.12–14 This inconsistency underscores a critical knowledge gap: the absence of a comprehensive and quantitative synthesis of high quality from RCTs to clarify these associations. Therefore, we conducted this systematic review and meta-analysis of RCTs to comprehensively evaluate the association between GLP-1R agonists (GLP-1RA) and the spontaneously reported musculoskeletal adverse events.
Methods
Study registration
This systematic review and meta-analysis were designed and implemented conforming to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-analyses protocol. Registration was completed on the International Prospective Register of Systematic Reviews (PROSPERO) platform as CRD420251075768. No amendments were made to the review protocol subsequent to its registration on PROSPERO.
Data sources and searches
We conducted a systematic literature retrieval in PubMed, Embase, Web of Science, the Cochrane Central Register of Controlled Trials, and the Clinicaltrials.gov website for RCTs investigating GLP-1R–based agonists in patients with obesity or overweight, according to the recommendations from the Cochrane Handbook for Systematic Reviews for meta-analysis. The investigation included studies published from the inception date to June 2025. Literature searches were conducted by the strategy of both medical subject headings and free terms. The retrieval terms were as follows: GLP-1RA, Glucagon-Like Peptide-1/Glucose-Dependent Insulinotropic Polypeptide dual receptor agonist (GLP-1/GIP dual receptor agonist), Glucagon-Like Peptide-1/Glucagon dual receptor agonist (GLP-1/GCG dual receptor agonist), Glucagon-Like Peptide-1/Glucose-Dependent Insulinotropic Polypeptide/Glucagon triple receptor agonist (GLP-1/GIP/GCG triple receptor agonist), semaglutide, liraglutide, dulaglutide, exenatide, lixisenatide, albiglutide, tirzepatide, cotadutide, efpeglenatide, oxyntomodulin, survodutide, bamadutide, orforglipron, mazdutide, efinopegdutide, retatrutide, RCT, placebo, obesity, and overweight (Table S1).
Study selection and data extraction
The inclusion criteria of this meta-analysis were: (1) RCT; (2) studies conducted in patients with obesity or overweight; (3) studies comparing GLP-1R–based agonists with placebo; (4) studies with reports of musculoskeletal disorder events. The exclusion criteria were: (1) studies conducted in patients under 18 years old; (2) observational studies or reviews; (3) studies that did not report musculoskeletal disorder events.
Two investigators (M.C. and C.L.) independently screened titles, abstracts, and full texts, excluded duplicates, and assessed risk of bias with the Cochrane tool. Another pair of investigators (F.L. and W.Y.) independently verified every inclusion decision and re-checked all extracted data. Discrepancies were resolved by consensus and, when required, by a senior investigator (X.C.). The extracted data included study design, drug exposure, study duration, sample size in experimental and control groups, publication data (first author and published year), characteristics of patients (mean age, sex ratio, diabetes duration, glycosylated hemoglobin (HbA1c), body mass index (BMI), HbA1c change, and weight change), musculoskeletal disorder events including gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic diseases, synovitis, and intervertebral disc protrusion. Musculoskeletal disorder events and other data were primarily abstracted from the original text or Supplemental Files attached. The Clinicaltrials.gov website would be the subsequent source of musculoskeletal events if data were not available in either articles or Supplemental Files.
Risk of bias assessment
The risks of bias in enrolled RCTs were assessed with the Cochrane Collaboration’s tool. 15 The evaluating measurements include random sequence generation, allocation concealment, blinding of participants and caregivers, missing outcome data, selective outcomes reporting, and other bias. Each domain was evaluated by degrees as to whether the risks of bias exist, including “definitely yes,” “probably yes,” “definitely no,” and “probably no” according to the instructions. 16 To further ensure the quality of the included parallel-design RCT, we re-assessed them with the Cochrane Risk of Bias 2 (RoB 2) tool (developed by the Cochrane Collaboration, UK). For each trial, we generated separate RoB 2.0 judgments for the outcome “skeletal-muscle adverse events.” The five fixed domains—bias arising from the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result—were rated as “low,” “some concerns,” or “high” risk of bias following the algorithm supplied in the RoB 2.0 guidance. 17
Data synthesis and analysis
The primary endpoint was the association between GLP-1RA treatment and the spontaneously reported musculoskeletal adverse events, including gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic fracture, synovitis, and intervertebral disc protrusion. Results of the meta-analysis were expressed as risk ratios with the 95% confidence intervals (CIs), and the random-effects model was adopted in the statistical analysis. The heterogeneity of included studies was evaluated by Higgens I2 statistics. Publication bias was assessed with the Egger’s test and funnel plot. Statistical significance was considered at p < 0.05. Moreover, to further evaluate the influence of potential influencing factors, including age, male percentage, baseline BMI, follow-up duration, weight change, HbA1c change, weight change differences, and HbA1c change differences between experimental groups and control groups, we conducted sensitivity analyses and meta-regression analyses. 18 Statistical analyses were conducted by Review Manager statistical software package (Version 5.3; Nordic Cochrane Center, Copenhagen, Denmark), and STATA version 16.0 (STATA, College Station, TX, USA).
Results
Baseline characteristics of the included studies
A total of 43 RCTs with 100,488 participants were included (Figure 1), involving 9 subtypes of GLP-1R–based agonists, including: liraglutide, semaglutide, dulaglutide, lixisenatide, exenatide, efpeglenatide, albiglutide, tirzepatide, and cotadutide. Baseline characteristics of included studies were summarized in Table S2.

Flow chart of the included studies.
Quality evaluation of included studies and generated evidence
The quality assessments of included studies were performed with Cochrane collaborative tools, which are summarized in Table S3. The RoB2 tool indicated that there were four RCTs with high risks of bias in missing outcome data. None of the 43 RCTs had high risks of selective outcome reporting, randomization sequence generation, allocation concealment, bias in masking patients and caregivers, or bias in masking assessors and adjudicators (Figure S1). The pooled estimates for the musculoskeletal outcomes were rated with moderate to high confidence. The Egger’s tests suggested potential small-study effects only for rheumatoid arthritis (p = 0.018) while the funnel plots generally displayed even distribution, which indicated no significant sign of publication bias (Table S4).
The association between GLP-1R–based agonists and the spontaneous reports of musculoskeletal disorders
Overall, no significant difference was observed between users of GLP-1RAs and the control group in the reporting of the prespecified musculoskeletal adverse events, including gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic fracture, synovitis, or intervertebral disc protrusion (Figure 2 and Table S5).

The association between GLP-1R–based agonists and the spontaneous reports of musculoskeletal disorders in patients with obesity or overweight.
Subgroup analyses indicated no difference in reports of the six prespecified musculoskeletal adverse events among subgroups stratified by age, male percentage, BMI, follow-up duration, the presence of diabetes, and types of GLP-1R–based agonists (Figure S2).
The meta-regression analyses revealed that higher male percentage was associated with fewer reports of osteoarthritis in patients using GLP-1R based agonists (β = −0.0149, 95% CI, −0.0289 to −0.0008; Figure 3). None of the remaining covariates showed a significant impact on the associations (Table S6).

Meta-regression analysis for the association between the proportion of male participants and the spontaneous reports of osteoarthritis in GLP–1R–based agonist–treated individuals.
Discussion
According to this meta-analysis, GLP-1RAs were not associated with spontaneously reported musculoskeletal adverse events, including gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic diseases, synovitis, and intervertebral disc protrusion. However, regression analysis showed that a higher male percentage was associated with fewer reports of osteoarthritis.
These findings provide novel insights into the potential benefits GLP-1R–based agonists might generate in musculoskeletal disorders and may serve as references for further investigations concerning the associations among GLP-1R–based agonists and specific musculoskeletal disorders.
Preclinical and mechanistic evidence suggest that GLP-1R–based agonists could influence the pathological processes underlying various forms of arthritis through multiple pathways. First, obesity could promote the development of different types of arthritis through the excess release of proinflammatory adipokines in adipose tissue.19,20 And the weight loss induced by GLP-1R–based agonists may attenuate such an inflammatory status. Second, GLP-1R–based agonists could directly inhibit inflammation by reducing proinflammatory cytokine expression.21,22 Third, GLP-1R–based agonists could also modulate immune response through promoting M2 macrophage polarization. 23 Fourth, GLP-1R–based agonists were shown to promote stabilization of mitochondria, thus alleviating oxidative stress. 7 Moreover, GLP-1R–based agonists could improve the extracellular matrix in cartilage. 24 Overall, theoretically, the weight loss effect,19,20 the anti-inflammation, and immune modulation effect of GLP-1R–based agonists could reduce the risks of different types of arthritis. 7 These systemic mechanisms are supported by evidence of GLP-1R–based agonists’ efficacy in diverse pathologies, including dementia, asthma, and certain cancers.25–27 However, as our investigation revealed, the associations between GLP-1R–based agonists and reported events were not uniform across the arthritis subtypes (gouty, rheumatoid, and osteoarthritis), warranting a more detailed, subtype-specific discussion.
In terms of osteoarthritis, our study did not reveal a significant association between GLP-1R–based agonists and osteoarthritis. However, previous experiments showed that GLP-1R–based agonists could inhibit the progression of osteoarthritis through weight loss, anti-inflammation effects, 28 and cartilage extracellular matrix improvement. 24 Despite the protective impacts of GLP-1R–based agonists on osteoarthritis discovered by experimental research, clinical studies on the impact of GLP-1R–based agonists on osteoarthritis generated divergent conclusions. 7 One clinical study conducted among 39,394 patients using semaglutide, tirzepatide, and liraglutide showed that GLP-1R–based agonists were related to a 27% lower risk of osteoarthritis, and the lowest risk was observed in tirzepatide users. However, liraglutide was associated with a slightly increased risk of osteoarthritis in the same study. 29 Another study reported increased incidence of adverse joint outcomes in obese, pre-osteoarthritis-naïve patients treated with GLP-1R–based agonists. 10 In individuals with diabetes, the association between GLP-1R–based agonists and a higher risk of osteoarthritis progression and joint injections has also been reported. 9 However, an RCT conducted among 407 patients with obesity and knee osteoarthritis showed that semaglutide treatment was significantly associated with great reductions in pain related to knee osteoarthritis compared with placebo. 11 Thus, the exact impact of GLP-1R–based agonists on osteoarthritis requires further investigation. In regression analysis, a higher male percentage was associated with fewer reports of osteoarthritis. The fact that women are more susceptible to knee osteoarthritis due to the greater mechanical stresses in female joints might be a possible explanation. 30
Meanwhile, the anti-inflammatory and metabolic improvement effects of GLP-1R–based agonists could potentially inhibit the development and progression of rheumatoid arthritis. 13 Two studies reported improved symptoms associated with GLP-1R–based agonists in patients with rheumatoid arthritis.13,14 A retrospective cohort study reported no elevated risks of rheumatoid arthritis associated with GLP-1R–based agonists. 12 However, our study found no significant association between the use of GLP-1R–based agonists and spontaneous reports of rheumatoid arthritis. The associations between GLP-1R–based agonists and rheumatoid arthritis require further exploration.
GLP-1R–based agonists could improve gout-relevant risk factors, including obesity and renal dysfunction, thus probably reducing the risk of gout. 31 Accordingly, a meta-analysis containing 17 clinical trials reported a modest but significant reduction in serum uric acid levels associated with GLP-1R–based agonists. 32 However, several studies reported that GLP-1R–based agonists were associated with higher risks of gout compared to SGLT2 treatment, while SGLT2 was associated with significantly lower risks of gout.33–35 Therefore, the effect of GLP-1R–based agonists themselves on the risk of gout or gouty arthritis remained inconclusive. 7
As for osteoporotic diseases, GLP-1R–based agonists could improve bone remodeling, 7 potentially reducing risks of bone fracture. However, an experiment conducted in diabetic mice implicated that short-term exposure to GLP-1RAs neither generated significant protective effects against, nor a marked increase in fracture risk. 36 Four meta-analyses consistently found an association between GLP-1R–based agonists and fewer reports of osteoporotic diseases.37–40 However, one meta-analysis and a post hoc analysis revealed no significant association between GLP-1R–based agonists and reported events of osteoporotic diseases.41,42 Thus, the exact impact of GLP-1R–based agonists on osteoporotic fracture diseases is not definite yet.
There are several limitations in our study. First, it is crucial to emphasize that our analysis is based on spontaneously reported adverse events collected during the safety monitoring of the included RCTs. These events were not prospectively defined, systematically adjudicated, or uniformly diagnosed as outcomes of interest. Some important details—such as who reported them (patient vs clinician), what they signify (new diagnosis vs exacerbation), or how they were diagnosed—are unavailable. In addition, the included trials were not designed to investigate new-onset musculoskeletal disorders and generally did not exclude participants with preexisting conditions. Therefore, our results could not be viewed as evidence for an impact on the incidence of musculoskeletal disorders. Instead, they should be interpreted as indicating an association between GLP-1RAs and the frequency of spontaneous reporting of musculoskeletal adverse events.
Second, the research data were derived from studies with varied designs and populations, which would inevitably introduce heterogeneity into this meta-analysis. To cope with this situation, we have conducted multiple sensitivity analyses to evaluate the consistency of the results and meta-regression to deal with the residual heterogeneity.
Third, given the slow-developing nature of musculoskeletal disorders, the duration of observation in enrolled studies may not be long enough. Accordingly, we performed a sensitivity analysis focusing on the duration of follow-up. No significant difference between studies with follow-up periods below and exceeding 52 weeks was observed, conforming to the main findings from the overall analysis. Still, studies with extended follow-up are required to validate our findings in the future.
Fourth, the enrolled population may not be fully representative of all demographic groups, which may restrict the applicability of our findings.
Fifth, since the included studies did not take musculoskeletal disorders as the primary outcome, the results of the meta-analysis should be interpreted as exploratory. The dedicated RCTs with the primary outcome of musculoskeletal disorders should further validate these findings in the future.
Finally, future studies could benefit from adopting more precise and Artificial Intelligence-driven body composition assessments. Such tools can transcend BMI’s limitations with personalized data, offering a clearer view of the relationship between obesity and musculoskeletal disorders. 43
Conclusion
The use of GLP-1R–based agonists was not associated with the spontaneously reported events of gouty arthritis, rheumatoid arthritis, osteoarthritis, osteoporotic fracture disease, synovitis, or intervertebral disc protrusion. A higher percentage of male participants was associated with fewer reports of osteoarthritis among GLP-1RA users.
Supplemental Material
sj-docx-1-tab-10.1177_1759720X261428147 – Supplemental material for The association between glucagon-like peptide-1 receptor agonists and reported musculoskeletal adverse events: a systematic review and meta-analysis of randomized controlled trials
Supplemental material, sj-docx-1-tab-10.1177_1759720X261428147 for The association between glucagon-like peptide-1 receptor agonists and reported musculoskeletal adverse events: a systematic review and meta-analysis of randomized controlled trials by Meng Cao, Chu Lin, Xiaoling Cai, Fang Lv, Wenjia Yang and Linong Ji in Therapeutic Advances in Musculoskeletal Disease
Supplemental Material
sj-docx-2-tab-10.1177_1759720X261428147 – Supplemental material for The association between glucagon-like peptide-1 receptor agonists and reported musculoskeletal adverse events: a systematic review and meta-analysis of randomized controlled trials
Supplemental material, sj-docx-2-tab-10.1177_1759720X261428147 for The association between glucagon-like peptide-1 receptor agonists and reported musculoskeletal adverse events: a systematic review and meta-analysis of randomized controlled trials by Meng Cao, Chu Lin, Xiaoling Cai, Fang Lv, Wenjia Yang and Linong Ji in Therapeutic Advances in Musculoskeletal Disease
Footnotes
Acknowledgements
We thank the doctors, nurses, and technicians for their practical work during the study at Department of Endocrinology and Metabolism in Peking University People’s Hospital.
Declarations
Supplemental material
Supplemental material for this article is available online.
Declaration of generative AI in scientific writing
No generative AI or AI-assisted technologies were used in the creation of this manuscript. The authors are solely responsible for the entire scientific content, accuracy, and originality of the work.
References
Supplementary Material
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