The causal relationship between GMs and tendinopathy remains a topic of debate. In our study, we examined the potential causative links between 211 GMs and five tendinopathy phenotypes utilizing MR analysis. To support and extend the findings of the MR analysis, bioinformatics analysis was conducted to delve deeper into the genetic underpinnings of these relationships
Traditional epidemiological approaches, such as cohort studies, often face challenges related to confounding factors and ethical constraints, which hinder the establishment of definitive causal connections. Additionally, the results from observational studies might be affected by reverse causality, where the sequence of exposure and outcome is unclear, making it difficult to eliminate confounding influences.
In response to these limitations, our application of MR analysis provided a robust alternative by effectively accounting for confounding variables that traditional statistical methods struggle to address. Further validation through bioinformatics analysis strengthened the credibility of our findings, thereby enhancing the overall reliability of the study.
In our research, we initially employed two-sample MR analysis to explore the causal links between 33 GMs and five distinct phenotypes of tendinopathy. Through this analysis, certain GMs emerged as protective factors, while others were identified as risk factors. Subsequent reverse MR analysis on the outcomes from these 33 assessments uncovered a reverse correlation with Rysipelatoclostridium. Additionally, sensitivity analysis indicated polymorphism in the MR results for Intestinimonas. Consequently, these two bacteria along with three unidentified species were excluded from further analysis.
We then conducted a multivariable MR (MVMR) analysis, integrating classical factors known to contribute to tendinopathy. However, the instability of the results led to questions regarding the reliability of the MVMR outcomes. Following this, bioinformatics analysis was applied to the remaining 28 GMs and the tendinopathy phenotypes. This involved identifying genes associated with the 28 GMs and screening for DEGs associated with tendinopathy. The intersection of these two datasets yielded 13 common gene sets (CGS).Subsequently, a series of bioinformatics analyses were conducted on these 13 CGS. Ultimately, we identified the FN1 gene and four major enrichment pathways, which helped elucidate the interactions between GMs and tendinopathy, providing insight into the underlying biological mechanisms.
Tendinopathy is a distressing and incapacitating ailment marked by the deterioration of tendon tissue, resulting in diminished mechanical characteristics and functionality, potentially culminating in tendon rupture(33, 34). Research has shown that fibronectin (FN) plays a restorative role in various tissues, including tendon tissue(35, 36). Our study focuses on FN1, a critical gene that encodes for FN, as the starting point of our investigation.
Tendons are primarily composed of collagen I(37), and in vitro experiments have demonstrated the spontaneous formation of Type I collagen fibrils, suggesting a potential self-assembling mechanism for collagen fibrillogenesis. However, it is important to note that this process is more complex within a biological system. Specifically, in the absence of FN, there is a noted failure to form fibrils that incorporate collagen I(38), indicating that FN plays a crucial role in the assembly of extracellular matrix (ECM) proteins, including those in tendon tissue(39).
From these findings, we can preliminarily conclude that FN1, our target gene, acts as the primary encoding gene for FN. FN indirectly influences tendon tissue regeneration by modulating collagen I synthesis, a key component of tendons. This mechanism, therefore, contributes to the development of tendinopathy, highlighting the significance of FN1 in tendon health and disease.
The mechanism of action between GMs and tendinopathy can also be elucidated from the perspective of the four gene pathways we have discovered. The impact of GM on skeletal muscle adaptation, particularly in conditions such as sarcopenia and general weakness in the elderly, is linked to dysregulation of intestinal flora. This dysregulation leads to increased intestinal barrier permeability, elevated blood lipopolysaccharide (LPS) levels, activation of the immune system, and reduced insulin sensitivity(40). Animal studies have highlighted that supplementation with strains of Lactobacillus significantly reduces markers associated with muscle atrophy, such as Atrogin-1, MuRF1, LC3 protein, and Cathepsin L. Moreover, supplementation with Lactobacillus plantarum has been shown to increase both muscle mass and strength in mice(41, 42).
Further supporting this, Buigues et al. found that elderly individuals who received a 13-week supplementation with a probiotic mixture containing various strains of Lactobacillus and Bifidobacterium exhibited improvements in endurance and muscular strength(43). Tendons, serving as extensions of skeletal muscles, are influenced by changes in muscle condition; thus, alterations in muscle can trigger changes in tendon structure and function. Proper muscular fitness training has been shown to effectively manage tendinopathy(44), while inappropriate or excessive training may exacerbate the condition(45).
These findings collectively demonstrate GM's significant influence on skeletal muscle adaptability. The interaction between GM and tendinopathy appears to be mediated through two primary pathways: striated muscle adaptation and muscle adaptation. Specifically, GM modulates skeletal muscle adaptability by activating these pathways, impacting tendons as extensions of skeletal muscles and consequently contributing to the development of tendinopathy.
As previously highlighted, tendons primarily comprise collagen, but they also house a sparse population of tendon cells. The two pathways identified—regulation of developmental growth and regulation of cell growth extent—prompt us to speculate that these pathways may govern the growth and development of tendon cells, potentially influencing the incidence of tendinopathy(46, 47). Over the past decade, our understanding of the pathogenesis of tendinopathy has advanced significantly, facilitated by studies using animal models and patient tissue samples. These studies have provided essential insights into the initial cellular and molecular changes that lead to the development of tendinopathy(48).
To further substantiate the hypothesis that alterations in tendon cell counterparts can lead to tendinopathy, several researchers have employed the rat tail tendon as a model to elucidate the underlying mechanisms(49). This approach has been instrumental in dissecting the complex biological processes at play and establishing a clearer link between cellular behavior and tendinopathy outcomes.
Regrettably, the field of research on the interaction between gut microbiota (GM) and tendinopathy is still in its early stages, which presents significant challenges and highlights several shortcomings in our study. Firstly, the tendinopathy phenotypes in the gene expression dataset used in our bioinformatics analysis did not align precisely with the five identified in the MR analysis. While there are notable similarities in gene expression across these phenotypes, the extent of genetic variation in these genes remains unknown. Secondly, although our research outcomes have identified key genes and pathways, and are supported by the existing literature, there is a lack of definitive experimental validation for our results. We plan to conduct targeted experiments in the future to enhance the comprehensiveness and accuracy of our research. Thirdly, to minimize racial bias, our findings primarily involve individuals of European descent, raising concerns about their applicability to other ethnic groups. Future research needs to include a more diverse population to ensure the generalizability of the results. These gaps underscore the need for continued and expansive research to solidify our understanding of the relationship between GM and tendinopathy and to enhance the reliability of the findings across diverse populations.