Causal associations between human gut microbiota and osteomyelitis: a mendelian randomization study

doi:10.21203/rs.3.rs-3639048/v1

Background: Recent studies have illuminated the potential association between gut microflora and osteomyelitis. Despite these advancements, the underlying causal relationship remains elusive.

Methods: In this research, we utilized the largest genome-wide association study (GWAS) meta-analysis available from the MiBioGen consortium to date (n=13,266) and employed a two-sample Mendelian randomization study (TSMR) framework. We conducted a detailed investigation into the causal relationship between gut flora and osteomyelitis using inverse variance weighting, MR-Egger, weighted median, and weighted modeling approaches. Additionally, Cochran's Q statistic was applied to measure the heterogeneity of the instrumental variable (IV).

Results：Our study demonstrated that an increased abundance of Bacilli, Bacteroidia, Bacteroidales, Butyricimonas, Coprococcus3, and Tyzzerella3 was positively associated with the risk of osteomyelitis, while Lachnospira was negatively associated. Sensitivity analyses revealed no evidence of heterogeneity or pleiotropy.

Conclusion：This study marks the first to provide suggestive evidence of beneficial or detrimental causal effects of gut microbiota on the risk of osteomyelitis through the application of MR methods. These insights may offer critical information regarding the pathogenesis of gut flora-mediated osteomyelitis and inform strategies for its prevention and treatment.

osteomyelitis

gut microbiota

Mendelian randomization

causal effect

genetic association

Osteomyelitis, an inflammatory bone disease primarily caused by microbial infections leading to bone destruction, involves the invasion of various skeletal areas, including the bone marrow, bone cortex, periosteum, and surrounding soft tissues [1]. In the United States, the incidence of osteomyelitis has been on the rise, increasing from 11.4 cases per 100,000 person-years between 1969 and 1979 to 24.4 cases per 100,000 person-years between 2000 and 2009. This trend is particularly pronounced in males and older age groups [2]. This increase is also indicative of the profound influence of environmental factors on the risk of osteomyelitis. Typically, osteomyelitis results from infections with various microorganisms. However, in special cases, such as chronic non-bacterial osteomyelitis, the disease manifests as an autoinflammatory bone disorder, precluding the possibility of infection. The pathogenesis of this form remains poorly understood, but certain studies have identified strong environmental and genetic correlations [3].

The largest known commensal microbial community in the human body, the gut microbiota, comprises bacteria, fungi, viruses, and protozoa [4]. It encompasses approximately 4 trillion microorganisms [5] and 150,000 microbial genomes [6]. The gut microbiota is integral to human metabolism, immune regulation, and the stability of the intestinal mucosal barrier [7]. Recent strides in microbiome research suggest that the host microbiota either maintains dynamic homeostasis with the host organism or exacerbates infectious states. This understanding has led to the hypothesis that gut microbiota may play a significant role in various infectious diseases, osteomyelitis included [8]. Over recent years, high-throughput sequencing technologies have deepened our grasp of the relationship between gut microbiota and osteomyelitis. For instance, an animal study demonstrated that modulating the gut microflora diversity in rats using oligofructose significantly increased the population of the anti-inflammatory bacterium Bifidobacterium pseudolongum. This change markedly reduced the severity of osteomyelitis, impeding the onset and progression of hyperinflammation [9]. Moreover, several clinical studies have indicated that antibiotic use disrupts gut microflora, potentially heightening the risk of bloodstream infections and severe health states [10, 11]. Despite these findings, most current research is observational, often limited by small sample sizes and vulnerability to confounding factors. Although these studies imply an association between gut microflora and osteomyelitis, they do not establish a direct causal link.

Presently, a substantial volume of research attests to the gut microbiota's extensive involvement in human diseases. It has become evident that the gut microbiota, and specific microbial metabolites, influence not just local processes such as the host's inflammatory responses, nutrient absorption, and intestinal barrier function, but also broader systems including the immune system, glucose homeostasis, lipid metabolism, energy balance, nonalcoholic fatty liver disease, obesity, and associated comorbidities, along with other metabolic disorders. This is particularly true for autoinflammatory diseases like asthma, arthritis, colitis, diabetes, and lupus [12–15]. Therefore, strategies targeting the regulation of gut flora could offer novel perspectives and approaches for treating autoimmune diseases. Previous studies have also confirmed a link between gut flora and the development of osteomyelitis [16].

Mendelian randomization (MR) employs single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) to explore causal relationships between exposures and outcomes [17]. In contrast to observational studies, MR capitalizes on the random assortment of alleles during inheritance to circumvent confounders and reverse causation, thereby mirroring the design of randomized controlled trials [17, 18]. Although MR has been used in several studies to investigate potential causal relationships between gut microbiota and various diseases [19–21], it has not yet been applied to explore the possible causal connections between gut microbiota and osteomyelitis risk.

Consequently, in this study, we employed Mendelian randomization analysis to comprehensively investigate the potential causal relationship between gut microbiota and osteomyelitis, aiming to identify specific bacterial taxa that may contribute to pathogenesis or confer protection.

2.1.Study design

Mendelian Randomization (MR) is a methodological tool in human genetics that utilizes the random distribution properties of genetic variants during gamete formation and fertilization to deduce causality. It aims primarily to evaluate the causal relationship between exposures and outcomes that have been empirically observed, circumventing the confounding biases inherent in traditional epidemiological studies. For the derivation of reliable results, as illustrated in Fig. 1A, a two-sample MR must satisfy three critical assumptions [18]: (1) the selected single nucleotide polymorphisms (SNPs) exhibit significant associations with gut microbiota; (2) these SNPs operate independently of any potential confounders between the exposure and the outcome; and (3) the SNPs are associated with the outcome (osteomyelitis) solely through their association with gut microbiota, excluding any direct associations.

2.2 Data selection

2.2.1 Exposure Genome-Wide Association Study (GWAS): Gut Microbiota

The exposure data for this study was derived from a large-scale, multi-ethnic, genome-wide meta-analysis focusing on associations between human genetic autosomal variants and gut microbes, facilitated by the MiBioGen Consortium. This analysis involved the collection of 16S rRNA gene sequencing profiles and genotyping data from 18,340 individuals across 11 countries in Asia and Europe. Subsequent localization analyses were conducted to identify genetic loci influencing the relative abundance or presence of microbial taxa—all of which are included in the human genome-wide association study (GWAS) data [22].

In pursuit of result accuracy, we filtered the data procured from MiBioGen, culminating in the inclusion of 211 genera of gut microbiota. Criteria were imposed based on the P-value and linkage disequilibrium conditions (P < 5×10^-8, R^2 < 0.1), recognized as thresholds for ensuring there's no instrumental variable bias. Furthermore, SNP loci with F-statistics ≤ 10 were excluded to preclude weak instrumental variable bias in the Mendelian randomization study [24]. The F-statistics for the valid SNPs are documented in Supplementary Table 2.

2.2.2Regarding the Outcome GWAS: Osteomyelitis

Summary statistics for osteomyelitis were sourced from the MRC Institute of Genetics and Molecular Medicine's IEU Open GWAS database (https://gwas.mrcieu.ac.uk/), which serves as a repository for publicly available GWAS summary data. While considering factors like sample size, sequencing depth, ethnicity, and the timing of data updates, we opted for the article equivalent to the 2021 publication of the comprehensive genomic osteomyelitis genetic dataset. This dataset encompasses 486,484 European subjects (4,836 cases and 481,648 controls) [25].

2.2.3 Mendelian Randomization Analysis

We adopted inverse variance weighting (IVW) as our primary method for Mendelian randomization analysis to ascertain the causal relationship between human gut microbiota and osteomyelitis (P < 0.05) [26]. Simultaneously, we engaged three other methods—MR-Egger, weighted median, and weighted mode—as supplementary analyses [27]. A spectrum of sensitivity analyses was also executed, encompassing Cochran's Q test, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. Specifically, heterogeneity was assessed through Cochran's Q test. The intercept derived from the MR-Egger regression was used to gauge horizontal pleiotropy. Leave-one-out analyses were undertaken to verify if the causal estimates were unduly influenced by any specific SNPs. The procedure for this study is depicted in Fig. 1B.

Through Mendelian randomization analysis, we identified 7 intestinal microflora with a reliable causal association with osteomyelitis, as detailed in Table 1 and illustrated through a forest plot in Fig. 2. When classified by taxonomy—kingdom, phylum, order, family, genus, species—the analysis yielded significant p-value results for 2 orders: Bacilli (OR = 1.34, 95% CI,1.10 to 1.63, P = 0.04) and Bacteroidia (OR = 1.29, 95% CI 1.04 to 1.59, P = 0.021); 1 order, specifically, Bacteroidales (OR = 1.29, 95% CI 1.04 to 1.59,P = 0.021); and 4 genera: Butyricimonas (OR = 1.23,95% CI,1.03 to 1.46, P = 0.021), Coprococcus3 (OR = 1.37, 95% CI 1.03 to 1.82, P = 0.023), Lachnospira (OR = 0.77, 95% CI, 0.61 to 0.98, P = 0.032), and Tyzzerella3 (OR = 1.15, 95% CI, 1.01 to 1.30, P = 0.036). This data points to a notable overlap of anamorphic effect values at higher taxonomic levels such as phyla and orders. Our findings indicate that Lachnospira acts as a protective factor against the development of osteomyelitis. In contrast, the remaining identified microflora groups—Bacilli, Bacteroidia, Bacteroidales, Butyricimonas, Coprococcus3, and Tyzzerella3—show a positive correlation with osteomyelitis incidence, implicating them as predisposing factors. Figure 3 further elaborates by demonstrating the scatterplot (A), funnel plot (B), forest plot (C), and sensitivity analysis (D) of the causal relationship between Coprococcus3 and osteomyelitis. Additionally, the results of Mendelian randomization analysis of all 211 intestinal microflora associated with osteomyelitis are provided in Fig. 4, highlighting significant flora in red (IVW results, P < 0.05)), while detailed information of all flora is presented in Supplementary Table 1.

Table 1

MR results of causal links between gut microbiota and osteomyelitis risk (P < 1×10 − 5)
Classification		Nsnp	SE	P-value	OR (95% CI)	Pleiotropy			Heterogeneity
Classification		Nsnp	SE	P-value	OR (95% CI)	Egger intercept	SE	P- value	Q	P-value
UKB
Class	Bacilli	16	0.101	0.004	1.34(1.10 to 1.63)	0.03	0.019	0.141	15.8	0.399
	Bacteroidia	13	0.109	0.021	1.29(1.04 to 1.59)	0.042	0.018	0.044	8.19	0.77
Order	Bacteroidales	13	0.109	0.021	1.29(1.04 to 1.59)	0.042	0.018	0.044	8.19	0.77
Genus	Butyricimonas	13	0.090	0.023	1.23(1.03 to 1.46)	-0.006	0.027	0.839	11.4	0.494
	Coprococcus3	7	0.145	0.029	1.37(1.03 to 1.82)	0.006	0.032	0.853	3.09	0.797
	Lachnospira	15	0.120	0.032	0.77(0.61 to 0.98)	-0.039	0.035	0.281	10.75	0.706
	Tyzzerella3	12	0.064	0.036	1.15(1.01 to 1.30)	-0.023	0.05	0.651	8.97	0.625

Heterogeneity tests revealed no significant discrepancy among individuals for these SNPs (P > 0.05). Moreover, the MR-Egger regression intercept suggests it’s unlikely that horizontal pleiotropy significantly impacts the effect of gut microflora on osteomyelitis.

In this MR study, we initially explored potential causal associations between gut microbiota and osteomyelitis risk by utilizing large-scale summary statistics of gut microbiota GWAs and osteomyelitis GWAs. Remarkably, a total of seven bacterial traits were identified as having a noteworthy causal association with osteomyelitis risk.

We delineated three main pathways through which gut flora affects distant organs: modulation of nutrient absorption, alteration of the immune system in intestinal endothelial cells, and translocation across the endothelial barrier into the systemic circulation by gut flora or their metabolites [28]. Evidence indicates that diet significantly influences the composition and abundance of intestinal flora in mice. By evaluating the specific responses to inflammation and immunity in mice subjected to varied diets, researchers have deduced that the intestinal flora correspondingly modulates its biological functions [29]. This hypothesis gained further support from a study by Phillips et al. They observed that osteomyelitis mice fed a high-fat diet exhibited a higher proportion of Lactobacillus and Prevotella in their gut microbiome. In contrast, a greater presence of Prevotella was documented in the cohort on a standard diet, which subsequently developed osteomyelitis. Furthermore, high-fat diet mice demonstrated reduced IL-1b levels in their pedis relative to those on a standard diet. Crucially, fecal microflora transplantation from high-fat-diet mice to standard-diet mice prior to disease onset not only inhibited Prevotella proliferation but also decreased IL-1b synthesis, thereby averting osteomyelitis. This underscores the proposition that diet-induced shifts in gut microbiota, through interactive modulation, can influence both the initiation and advancement of osteomyelitis [16]. Within the human gastrointestinal tract, the intestinal epithelial barrier serves as a crucial defense against detrimental antigens and pathogens, concurrently housing the gut microbiota. This barrier is pivotal for nutrient absorption and immune defense. Under typical conditions, tight junction (TJ) proteins securely seal the intestinal epithelium, providing a protective function. However, during intestinal dysbiosis, the gut microbiota can disrupt TJ proteins' expression and localization, consequently increasing intestinal permeability and precipitating extensive inflammatory reactions, including severe skeletal inflammations like osteomyelitis [30]. Moreover, research focusing on the gut-bone axis has revealed that short-chain fatty acids, gut microbiota metabolites, are instrumental in fostering regulatory T cells (Tregs) development, impeding Th17 cell production, diminishing inflammatory cytokines synthesis, encompassing cellular inflammatory mediators such as IL-6, IL-17, and IL-23, and preserving the systemic immune equilibrium [31].

Bacilli represent a category of Gram-positive bacteria, notable for their production of resistant endospores, exhibiting broad-spectrum bacillary activity, and synthesizing bacteriocins. They are prevalently found in various biological environments and constitute a significant component of the human intestinal flora. While most Bacilli are non-invasive, exceptions exist, with Bacillus cereus being a prime example. According to a report by Veysseyre et al., Bacillus cereus was responsible for 57 infections, of which 10 involved bones and joints. This phenomenon leads us to conjecture that such infections might arise when intestinal flora or their metabolic byproducts breach the endothelial barrier, entering the bloodstream, initiating an inflammatory response, and eventually precipitating a systemic inflammatory reaction [32]. In a related study, Bradley et al. discovered that Bacillus cereus can compromise the human intestinal barrier via a binary protein mechanism. This mechanism entails bacteria and their toxins disrupting the human intestinal barrier by achieving receptor-mediated endocytosis and employing the AB toxin complex for cellular intoxication, composed of ADP-ribosyltransferase (A) and cell-binding (B) components. This finding lends credence to the hypothesis that such disruptions could theoretically underpin the pathogenesis of osteomyelitis [33].

Our findings demonstrate that both Bacteroidia and Bacteroidales are positively associated with the risk of developing osteomyelitis. Furthermore, Bacteroidales, a member of the Gram-negative bacteria, represent an important cornerstone of the intestinal flora and boast one of the most complex polysaccharide-pod systems known in bacteria, comprising at least eight different polysaccharides (PSA- PSH). In a different spectrum, the lipopolysaccharides of the genus Anabaena, which lack O antigens, exhibit a virulence approximately 1000 times greater than that of E. coli lipopolysaccharides. Contrastingly, the fragile anaplasma toxin, a critical virulence factor within the Anaplasma genus, manifests in three isoforms (BFT-1, BFT-2, BFT-3), with BFT-2 identified as the prime facilitator of tissue damage. This super-potent toxin, BFT-2, has the potential to traverse the intestinal epithelial barrier, enter the bloodstream, and consequentially initiate hematogenous osteomyelitis. Moreover, the proficiency in withstanding oxidative stress significantly contributes to pathogenic virulence. Through the regulation of various oxidoreductases production and transport, including catalase, peroxidase, and thioredoxin under the governance of the transcription factor OxyR, bacterial flora acquire resilience against the host's oxidative responses, thus achieving enhanced tolerance [34].

In an intriguing case study, Panagiota et al. documented two instances of vertebral osteomyelitis attributable to Bacillus fragilis, with no detectable infection foci elsewhere in the body. This observation propels the hypothesis of a potential correlation with enterobacteria, offering valuable insights for forthcoming investigations [34]. The disproportion, characterized by the overgrowth of certain microorganisms and the depletion of others, disrupts the intestinal microbial ecosystem, leading to the forfeiture of crucial physiological functions, a condition termed gut microbiota dysbiosis [35]. This aberration in the gut flora composition is speculated to influence the progression and manifestation of osteomyelitis significantly. It does so primarily by orchestrating the production of short-chain fatty acids (SCFAs), modulating intestinal permeability, and adjusting immune and inflammatory responses. Among the SCFAs, butyrate stands out as a predominant component, chiefly generated through the enzymatic breakdown of dietary fibers within the intestinal conduit and serving as a principal energy substrate for intestinal epithelial cells [21]. Noteworthy producers of butyrate encompass bacteria like rumen Coccidioides, Vibrio butyronucleicus, and Aeromonas butyricola. Butyrate executes a diverse array of functions by engaging with G protein-coupled receptors (GPACs) and partaking in both local and extensive signaling networks. Such interactions facilitate the fortification of intestinal barrier function, mucosal immunity, and intestinal homeostasis, potentially optimizing energy metabolism, fostering weight reduction, attenuating inflammation, and restoring the equilibrium of the gut-brain axis. However, a decline or alteration in the population of Aeromonas butyric acidophilus can compromise the body's defensive mechanisms, resulting in an imbalanced immune system and heightened inflammatory processes.

Furthermore, our research identified a potential link between the genera Tyzzerella3 and Coprococcus3 and the susceptibility to osteomyelitis. Particularly, Coprococcus3, an inhabitant of the human intestinal flora and recognized commensal bacterium, has drawn attention due to the escalating imbalance within the genus triggered by antibiotic misuse. This imbalance has been associated with elevated inflammatory levels in some Coprococcus3 species, with emerging evidence suggesting their role in virulence and increasing antibiotic resistance. In the context of early-stage osteomyelitis, where clinical symptoms may be inconspicuous or where there is indiscriminate administration of anti-infective antibiotics, there's a postulation that these factors may exert a pronounced effect on this genus, thereby intensifying the onset and progression of osteomyelitis.

Conversely, Lachnospira, the sole genus identified as a potential protective agent in our study, falls under the phylum of Thick-walled Bacteria. It's posited that Trichoderma, a likely beneficial bacterium, engages in the metabolism of diverse carbohydrates, producing essential substances like acetic acid and butyric acid to energize the host [36]. Identified primarily in early infant populations, Lachnospira's prevalence has been linked to increased concentrations of short-chain fatty acids (SCFAs). These SCFAs play pivotal roles, particularly in sustaining the integrity of the intestinal barrier and harboring anti-inflammatory attributes. This not only guarantees efficient nutrient absorption but also acts as a safeguard against the infiltration of deleterious substances (such as bacterial endotoxins) into the systemic circulation, consequently mitigating the risk of hematogenous osteomyelitis [37].

The innovative methodology of this study lays the groundwork for the first Mendelian Randomization (MR) analysis to ascertain a causal relationship between gut microbiota and osteomyelitis. By eradicating confounding elements, it earmarks candidate bacteria for future functional explorations. Furthermore, the implications of the MR findings are far-reaching in the realm of public health. They supplement previous research on the gut microbiota-osteomyelitis nexus by introducing a novel viewpoint at the genetic stratum. From a preventive medicine perspective, these insights could guide osteomyelitis prevention strategies through timely gut microbiota modulation. Diagnostically, they underscore the necessity for heightened vigilance in osteomyelitis screening and early detection among individuals with gut microbiota anomalies.

However, this study presents several limitations. Firstly, the pool of SNPs accessible for analysis was constrained, a result of adhering to a stringent genome-wide significance criterion (P < 5×10 − 8). We included only those SNPs that fulfilled the stipulated significance benchmark (P < 1×10 − 5), a factor that might undermine the robustness and exactitude of our outcomes. Additionally, the gut microbiota GWAS data employed are in their preliminary phases in terms of sample magnitude and the extent of currentness. Moreover, the dataset utilized was derived solely from European ancestries, not accounting for variables such as gender and ethnicity, thereby curtailing the extrapolation of our insights to broader populations. It's also vital to acknowledge that our research narrowly concentrated on bacteria, overlooking the substantial diversity of eukaryotic viruses and prokaryotic phages within the human microbiota [38]. This necessitates further inquiries to delve into their potential implication in osteomyelitis' onset and evolution. Ultimately, the connection between the human microbiota and its host, in states of both health and disease, doesn't adhere to a simplistic unidirectional "cause and effect" paradigm [39]. Consequently, ensuing research ought to take into account the intricate interplay and intercommunication amidst the host and gut microbiota to deepen our grasp of their interrelation with various diseases.

In conclusion, for the first time, we have unveiled compelling evidence suggesting the gut microbiota's substantial influence on osteomyelitis (OM). Identifying several key bacterial groups, such as Bacilli, Bacteroidia, Bacteroidales, Butyricimonas, Coprococcus3, Tyzzerella3, and Lachnospira, our research proposes these taxa as potential novel biomarkers. These critical insights herald a new era in osteomyelitis treatment and prevention strategies. Nonetheless, it is crucial to pursue further studies to not only elucidate the explicit nexus between the gut microbiota and OM but also to comprehensively understand the specific underlying mechanisms that drive this connection.

MR, Mendelian randomization; GWAS, Genome-wide association study; TSMR,a two-sample Mendelian randomization study IV, Instrumental variable; SNP, Single nucleotide polymorphism; IVW, Inverse variance weighted;; OR, Odds ratio; CI, Confidence interval; SCFAs, Short-chain fatty acids; PSA- PSH ,polysaccharide-pod ; GPACs,G protein-coupled receptors

Acknowledgments

We express our sincere gratitude to the participants and investigators of BioBank UK and the MiBioGen consortium for their invaluable contributions.

Author contributions

WX and ZW conceptualized and designed the study. The manuscript was initially drafted by WX, YH, DJ, HS, JT, and FH. All authors engaged in critical revision of the manuscript and gave their final approval for the version to be published.

Declaration of competing interest

The authors affirm that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest..

Funding

This research received financial support from the Guangdong Provincial Administration of Traditional Chinese Medicine, under Grant Number 20231163, and the National Studio Construction Projects for Experts in Traditional Chinese Medicine (Huang Feng Studio N75, 2022).

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

Supplementarydocuments.zip

Causal associations between human gut microbiota and osteomyelitis: a mendelian randomization study

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials and methods

2.1.Study design

2.2 Data selection

2.2.1 Exposure Genome-Wide Association Study (GWAS): Gut Microbiota

2.2.2Regarding the Outcome GWAS: Osteomyelitis

2.2.3 Mendelian Randomization Analysis

3. Results

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1