This large-scale cross-consortium MR study of 26 musculoskeletal diseases revealed suggestive evidence linking the gut microbiota with MSDs. Notably, our analysis revealed a significant negative correlation between gut microbiota and rheumatoid arthritis, calcific tendonitis of the shoulder and rotator cuff syndrome, while highly plausible positive associations between gut microbiota and osteoporosis were shown. However, for the majority of conditions examined, we did not establish a definitive causal relationship, whether positive or negative, between gut microbiota and MSDs, underscoring the complexity of the gut-microbiome-musculoskeletal nexus. Emerging studies have suggested a pivotal role of gut microbiota in various diseases, potentially influencing musculoskeletal system functioning. However, establishing direct causal links at the genetic level is challenging (Fan and Pedersen 2021; Behera et al. 2020). By leveraging MR and Bayesian modeling, our study created a comprehensive gut-microbiota-musculoskeletal-disorder library, validating direct relationships and identifying future pathways involved in the microbial-musculoskeletal axis.

Two studies by Zhao et al. (2022a) and Zhang et al. (2022) showed that the gut microbiota influences calcium absorption and osteoclast differentiation through carbohydrate metabolism and short-chain fatty acid production, contributing significantly to the understanding of how the gut microbiota affects bone health. Our findings align with these studies, revealing a robust association between gut microbiota and an increased risk of osteoporosis. Furthermore, a cohort study by Zhang et al. also revealed that Chinese herbal medicine may promote recovery in osteoporosis patients by modifying the structure and function of the gut microbiota (Zhang et al. 2023). For osteoporosis (Beta = 0.011), the narrow CI (0.001–0.021) suggests a consistent but small effect, potentially meaningful at the population level. In light of this, we believe that gut microbiota modulation may be a promising candidate target for new therapeutic treatments for fairly common systemic bone diseases such as osteoporosis. For osteoporosis, gut microbiota may modulate bone mineral density via vitamin D metabolism and SCFA-mediated inhibition of osteoclastogenesis. Specifically, butyrate reduces RANKL/OPG ratio in osteoblasts, suppressing bone resorption (Zhao et al. 2022a, 2022b; Lucas et al. 2018).

Osteonecrosis, characterized by an ischemic skeletal condition, and osteomyelitis, a bone infection, contrast with juvenile osteochondrosis, which manifests through noninflammatory disruptions in the ossification of articular cartilage (Lewis et al. 2019; McCabe et al. 2015; West and Jaramillo 2019). Notably, an experimental study on mouse models highlighted the potential therapeutic role of Ligilactobacillus animalis in mitigating osteonecrosis through mechanisms such as enhanced angiogenesis and osteogenesis and reduced apoptosis (Chen et al. 2022b). Although these findings derived from animal studies offer limited direct applicability to human health, they support the concept that we have mechanisms of influence mediated by other factors that may be undetected by our studies, such as the pathways of bone mineral resorption (Zhang et al. 2022). However, this may also lead to a debate on whether the onset of skeletal diseases stems directly from gut microbiota derivatives or whether dysbiosis within the gut microbiota itself triggers skeletal pathologies (Zhao et al. 2022a; McCabe et al. 2015). Our MR findings align with Zhao et al., who reported Bifidobacterium lactis improved bone density in postmenopausal osteoporosis. However, unlike their probiotic trial, our study identified Bacteroides as a risk factor, possibly due to population-specific microbiota interactions or unmeasured confounders (e.g., vitamin D status) in observational studies (Zhao et al. 2022a). These observations underscore the necessity of further research to elucidate the specific pathways through which the gut microbiota impacts skeletal health, potentially revolutionizing our understanding and treatment of these conditions (Lewis et al. 2019).

In our comprehensive cross-study analysis, we explored the causal relationships between gut microbiome variations and muscle diseases, notably muscular dystrophy and low back pain, but we did not identify significant associations. This finding contrasts with recent research by Qiu et al. (2023), which posited a microbiome-muscular dystrophy linkage mediated through inflammatory processes or microbial abundance shifts. Moreover, contemporary literature has begun to highlight the transformative role of gut microbiota in the progression of muscular dystrophy (Ziemons et al. 2021). Animal studies further support a causal link between gut microbiota and low back pain, suggesting that Lacticaseibacillus paracasei administration can mitigate inflammatory responses and influence serum metabolomics and gut microbiota composition in relevant models (Wang et al. 2021).

Collectively, in contrast to the current literature and previous inconclusive small-scale studies, although our MR analyses did not yield a potential relationship between them, as validated by the Bayesian model we constructed, it is reasonable to assume that this paradox occurs because muscle atrophy and low back pain are the result of gut microbiota potentially influencing the onset of such muscle disorders via a non-gene-mediated pathway (Ticinesi et al. 2019). Muscle atrophy is classified as neurological or physiological atrophy, while low back pain may be caused by lumbar muscle strain or spinal canal pathology (Ziemons et al. 2021; Diarbakerli et al. 2022). Although the results of our analyses are biologically plausible, further subgroup analyses of causality may not be possible due to the lack of individual data in the original studies we chose to group such genetic data (Ticinesi et al. 2019). Repeated validation in independent cohorts, clinical follow-up analyses, or the use of stronger GWAS datasets in future studies are needed to draw definitive conclusions.

While established risk factors for cervicobrachial syndrome include smoking and sex (Yi et al. 2020), research on the etiology of cervicobrachial syndrome by Yi et al. highlighted atlantoaxial subluxation at the C1/C2 level as a critical etiological factor (Vesela et al. 2005). However, cervical spinal stenosis, a subtype of neurogenic cervical spondylosis, is also associated with cervicobrachial syndrome, but its pathogenesis remains poorly investigated. This adds a layer of complexity to our understanding of cervicobrachial syndrome (Aboushaala et al. 2023; Allam et al. 2018). With the discovery of the mechanism by which cerebral activin affects neurogenic cervical spondylosis, whether and how gut microbiota can affect this process requires more targeted research (Yi et al. 2020; Allam et al. 2018). In the present study, the association with spinal stenosis was not statistically significant after correction for multiple analyses, but thoracolumbar spinal stenosis also causes "scoliosis" in clinical practice (Toyoda et al. 2023). In contrast to the above spinal disorders, one systematic review provided evidence that the gut microbiota influences the development and progression of scoliosis and ankylosing spondylitis through aberrant immune responses and complex bacterial-host cell-miRNA interactions (Aboushaala et al. 2023; Tavasolian and Inman 2021). Therefore, even if we obtain nonsignificant results after Bayesian analysis, if we blindly conclude that there is no genetic correlation between all spinal diseases and gut microbiota, we need to use the gut microbiota as an entry point to launch more targeted research on its immunology and etiology (Aboushaala et al. 2023).

Classification with the ICD-10 (World Health Organization 2016) was based on genome analyses that were originally performed in the FinnGen database (https://r9.risteys.finngen.fi/). The spondylolisthesis data included in this study included juvenile spondylolisthesis (Calvi's disease, Scheuermann's disease) and adult spondylolisthesis. Similarly, although we did not find a direct or indirect genetic association between gut microbiota and osteochondromatosis of the spine, the paucity of such studies suggests that our study could be expanded to include randomized controlled clinical trials in the future to further clarify the etiology and mechanism of spinal disorders (Behera et al. 2020; Tavasolian and Inman 2021).

After rigorous analysis and exploration of our MR analysis and constructed Bayesian model, our findings on the protective effect of the gut microbiome on rheumatoid arthritis (RA) are in agreement with those of Sun et al., who clearly verified by immunohistochemistry (IHC) and micro-CT that the gut microorganism P. distasonis and its metabolites are effective therapeutic targets for the treatment of rheumatoid arthritis (Sun et al. 2023). While the Beta value for rheumatoid arthritis (− 0.016) appears modest, it corresponds to a 1.6% reduction in disease risk per standard deviation increase in protective microbiota abundance. Extrapolated to population-level shifts in microbiome composition (e.g., via probiotics), this could translate to a 10–15% risk reduction, aligning with interventions such as Sun’s Lacticaseibacillus supplementation in clinical trials (Sun et al. 2023). Moreover, according to the available data, the gut microbiome is not only able to influence systemic autoimmune diseases such as RA, but it can also modulate disease progression through metabolites such as short-chain fatty acids, secondary bile acids and taurodeoxycholic acid (Castro-Mejía et al. 2020; McCabe et al. 2015; Liu et al. 2023; Chen et al. 2022c). However, our systematic literature review suggested that this pathway may be genetically mediated, as indicated by secondary metabolite or protein expression in the gut microbiota involved in the amelioration of RA (Guan et al. 2023; Hu et al. 2022). In rheumatoid arthritis, Parabacteroides distasonis may suppress Th17 differentiation through IL-10 induction, while Prevotella copri exacerbates synovitis via molecular mimicry of human citrullinated peptides (Sun et al. 2023; Chen et al. 2022c; Wu et al. 2016). Our MR results suggest that microbial-targeted therapies for treating autoimmune joint diseases are a relatively effective therapeutic avenue and research direction (Aboushaala et al. 2023).

According to the ICD-10 classifications, there are several other joint disorders: gout, which is also known as metabolic arthritis; primary arthropathy, which refers to spontaneous joint pathology other than sports injuries; and meniscal structural disorders, which refer to disorders of various forms (degeneration, detachment, and preservation) of the knee meniscus structure (World Health Organization 2016). The gut microbiota has been found to be directly related to hyperuricemia and can even lead to systemic inflammation, leading to arthritis (Guan et al. 2023; Zhao et al. 2022b). However, probably due to reverse causality or multiple effects of selected IVs, our study did not establish significant correlations with other joint diseases, suggesting the complexity of interactions within the gut-joint axis (Chen et al. 2023; Zuber et al. 2023). We posit that the gut microbiota may exert differential effects on various joint pathologies, a hypothesis that warrants further explicit experimental analyses to elucidate the intricate underlying mechanisms involved.

We calculated estimates of the existence of nominal causal effects of the gut microbiota on rotator cuff syndrome and calcific tendonitis of the shoulder using MR methods and Bayesian modeling and concluded that there is a negative correlation between gut microbiota and the two soft tissue disorders of the shoulder joint. The currently identified cause of calcific tendonitis of the shoulder is calcium hydroxyapatite deposition due to insufficient blood perfusion to the shoulder joint, which eventually leads to glenohumeral osteoarthritis (Guan et al. 2023; Compagnoni et al. 2021). Diabetes mellitus was identified as a risk factor for calcific tendonitis of the shoulder in a large-scale cohort study (Su et al. 2021). Delving into the intricate relationship between gut microbiota and rheumatoid arthritis provides insight into the potential relationship between the gut microbiota and calcific tendonitis. This connection is hypothesized to stem from the’failure of macrophages to phagocytose calcific deposits, the induction of inflammation driven by inflammatory cytokines, or the influence of gut-derived metabolites on collagen deposition and fibroblast activity, leading to the’manifestation of the disease (Compagnoni et al. 2021; Mateos et al. 2021). To further substantiate this potential causal link, a transcriptome analysis utilizing RNA sequencing by Cho et al. revealed differentially expressed genes and matrix metalloproteinases implicated in calcific tendonitis at the genetic level, supporting the existence of the proposed gene–gut-microbiota–soft-tissue-disease axis (Cho et al. 2020). To our knowledge, this is the first MR study linking gut microbiota to rotator cuff pathology. Retrospective studies by Cho et al. implicated MMP-9 dysregulation in tendon calcification; our findings suggest gut-derived metabolites (e.g., LPS) may modulate MMP activity, offering a novel therapeutic axis for microbiome-targeted anti-inflammatory therapies (Cho et al. 2020). Given the nascent state of research on calcific tendonitis pathogenesis, a directed effort toward identifying specific bacterial species or metabolites related to this condition is imperative. Such an approach could yield alternatives to conventional treatments such as arthroscopic lithotripsy or extracorporeal shockwave therapy (Compagnoni et al. 2021; Youn et al. 2023). In juxtaposition, rotator cuff syndrome, characterized by pain and muscle atrophy due to the complete or partial tear of the rotator cuff or supraspinatus muscle, is negatively correlated with certain gut microbial compositions (World Health Organization 2016). For rotator cuff syndrome (Beta =  − 0.007, 95% CI: − 0.013 to − 0.001), the CI’s proximity to zero suggests caution in interpretation. While statistically significant, clinical translation requires validation in cohorts with longitudinal microbiome data. This suggests a protective role of the microbiota, potentially through the reduction of systemic inflammatory markers or a direct impact on shoulder tendon structures, illuminating the multifaceted influence of gut microbiota on soft tissue pathologies (Guan et al. 2023; Sun et al. 2023; Hu et al. 2022). Notably, rotator cuff syndrome showed FDR significance despite failing Bonferroni correction, suggesting its association with gut microbiota may warrant further investigation. This nuanced exploration underlines the critical need for further comprehensive studies to unravel the complex interactions at play, potentially revealing novel microbiome-targeted therapeutic strategies for managing soft tissue disorders (Chen et al. 2022a).

However, we lacked significant findings for other soft tissue disorders, including trigger finger, synovial and tendon disorders; shoulder bursitis; lateral epicondylitis; shoulder impingement syndrome; carpal tunnel syndrome; and adhesive capsulitis, for which our study did not find significant associations. With this as a point of intervention, we can fully speculate that the mechanism behind this correlation may originate from the gut microbiome-distant soft tissue inflammation axis, whereby an immune response triggered by gut microbial profiles leads to inflammation at extremities and joints of extremities, particularly in the shoulder joint or rotator cuff tendons (Aboushaala et al. 2023). Our research has fully dissected the importance of the complex microbial-host interactions that lead to soft tissue pathologies. Modulation of the gut microbiota through diet, probiotics or prebiotics may be a new strategy to control rotator cuff syndrome or prevent diseases such as calcific tendonitis of the shoulder (Castro-Mejía et al. 2020; Kragsnaes et al. 2024). Therefore, we believe that future studies should aim to identify the specific microbial species or metabolites responsible for these correlations and that more clinical trials are needed to explore this therapeutic avenue.

In the present study, by leveraging the extensive sample size available in GWASs and employing a Bayesian regression framework for joint modeling, we investigated the causal relationships between gut microbiota and 26 common MSDs. A key advantage of MR is that genetic variants are immutable from birth and are randomly inherited by offspring. Therefore, scholars have posited that genetic variants are free from confounding and reverse causality issues (Hartley et al. 2022; Burgess et al. 2023). Nonetheless, we could not entirely eliminate the possibility of confounding factors, such as those within the study population and geographical factors, during the research process. We incorporated comprehensive and sufficiently authentic GWAS summary statistics, in which the original cohort study stratified and corrected the population (Kurilshikov et al. 2021; Sadat-Ali 2023; Kurki et al. 2023). Our research solely included European population cohorts, significantly reducing potential population bias and genetic heterogeneity (Kurilshikov et al. 2021; Sadat-Ali 2023). Moreover, with the use of powerful tools to estimate heritability, we found that the gut microbiome does not appear to contribute directly to most of the muscle and bone disease outcomes studied. Compared to smaller cohort studies, our research still provides genetic-level causal inferences unaffected by confounding factors (Burgess et al. 2023). We are satisfied that therapies targeting genetic modification of gut microbiota do not directly lead to a reduced risk of most of the outcomes investigated or to better symptom management. Previous MR studies were predominantly limited to single or a few outcomes without a systematic analysis of MSDs (Chen et al. 2023). Our study surpasses most previous research in terms of comprehensiveness and persuasiveness by employing joint modeling of multiple outcomes using a sparse Bayesian Gaussian copula regression framework to detect causal effects while estimating the residual correlation between summary-level outcomes, i.e., correlations not explained by exposures. Therefore, our study offers more accurate causal effect estimations (Zuber et al. 2023; Zou et al. 2024).

However, our study also has limitations. First, our selection of available IVs from the available gut microbiota data was limited relative to the human genome, potentially leading to type I errors in our findings (Burgess et al. 2023; Zuber et al.