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Background <p>Osteomyelitis results principally from endo-/exogenous bacterial infections, whose incidence that complicating bone injuries reaches approximately 30%, with the risk of disability and teratogenicity. Skin microbiota has been found to be clinically linked to osteomyelitis, but substantial evidence is lacking.</p> Methods <p>Mendelian randomization (MR) was applied to unveil the causality between human skin microbiome and osteomyelitis. Genetic data of 1,656 skin microbiota samples were obtained from genome-wide association studies (GWAS), with the outcome of osteomyelitis from UK Biobank (UKB) database.</p> Results <p>Two sample MR confirmed 12 skin microbiota strains that possessed significant causality strength with osteomyelitis, in which asv013 <i>[S. epidermidis]</i> (β = 0.061, <i>P</i> = 0.027), Genus <i>propionibacterium</i> (β = 0.065, <i>P</i> = 0.021), Family micrococcaceae (β = 0.086, <i>P</i> = 0.004), asv003 <i>[Staphylococcus (unc.)]</i> (β = 0.065, <i>P</i> = 0.027), and asv004 <i>[Corynebacterium (unc.)]</i> (β = 0.070, <i>P</i> = 0.016) were drivers of osteomyelitis, whilst the leaving asv037 <i>[C. Glutamicum]</i> (β = -0.041, <i>P</i> = 0.004), asv021 <i>[Micrococcus (unc.)]</i> (β = -0.059, <i>P</i> = 0.019), asv063 <i>[Finegoldia (unc.)]</i> (β = -0.037, <i>P</i> = 0.038), Order clostridiales (β = -0.043, <i>P</i> = 0.013), Class betaproteobacteria (β = -0.061, <i>P</i> = 0.004), Family clostridiales (β = -0.061, <i>P</i> = 0.002), and Order clostridiales (β = -0.063, <i>P</i> = 0.023) could be perceived as protective factors. No heterogeneity or pleiotropy in sensitivity analyses were observed, hinting the robustness of the MR findings.</p> Conclusion <p>This study preliminarily clarified the causal effect of skin microbiome on osteomyelitis. Strains that may significantly trigger or suppress the outcome of osteomyelitis were figured out, which may provide promising insights for the genesis and progression of osteomyelitis, thereby benefiting relevant clinical prevention and treatment.</p>

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Mendelian randomization analysis unveils causal relationships between skin microbiota and osteomyelitis

  • 期刊论文

  • 发表日期：

    2025年6月4日

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  • Yihai Wang,
  • Zhengnan Li

摘要

Background

Osteomyelitis results principally from endo-/exogenous bacterial infections, whose incidence that complicating bone injuries reaches approximately 30%, with the risk of disability and teratogenicity. Skin microbiota has been found to be clinically linked to osteomyelitis, but substantial evidence is lacking.

Methods

Mendelian randomization (MR) was applied to unveil the causality between human skin microbiome and osteomyelitis. Genetic data of 1,656 skin microbiota samples were obtained from genome-wide association studies (GWAS), with the outcome of osteomyelitis from UK Biobank (UKB) database.

Results

Two sample MR confirmed 12 skin microbiota strains that possessed significant causality strength with osteomyelitis, in which asv013 [S. epidermidis] (β = 0.061, P = 0.027), Genus propionibacterium (β = 0.065, P = 0.021), Family micrococcaceae (β = 0.086, P = 0.004), asv003 [Staphylococcus (unc.)] (β = 0.065, P = 0.027), and asv004 [Corynebacterium (unc.)] (β = 0.070, P = 0.016) were drivers of osteomyelitis, whilst the leaving asv037 [C. Glutamicum] (β = -0.041, P = 0.004), asv021 [Micrococcus (unc.)] (β = -0.059, P = 0.019), asv063 [Finegoldia (unc.)] (β = -0.037, P = 0.038), Order clostridiales (β = -0.043, P = 0.013), Class betaproteobacteria (β = -0.061, P = 0.004), Family clostridiales (β = -0.061, P = 0.002), and Order clostridiales (β = -0.063, P = 0.023) could be perceived as protective factors. No heterogeneity or pleiotropy in sensitivity analyses were observed, hinting the robustness of the MR findings.

Conclusion

This study preliminarily clarified the causal effect of skin microbiome on osteomyelitis. Strains that may significantly trigger or suppress the outcome of osteomyelitis were figured out, which may provide promising insights for the genesis and progression of osteomyelitis, thereby benefiting relevant clinical prevention and treatment.