Cross talk between skin microbiota and post-traumatic wound infection: a bidirectional mendelian randomization analysis

Author:

Chen Qingsong1,Zhang Yuke2,Huang Guangbin3,Zhang Bohao4,Cheng Yuan5,Shi Li3,Li Jianxiao3,Li Hui3,Zhang Qi3,He Ping3,Li Yongming1,Du Dingyuan3

Affiliation:

1. School of Microelectronics and Communication Engineering of Chongqing University, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, China

2. Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan

3. Department of Traumatology, National Regional Trauma Center, Traumatic Research Center of Chongqing University, Chongqing University Central Hospital (Chongqing Emergency Medical Center)

4. Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning

5. Department of Hepatobiliary Surgery, Traditional Chinese Medicine Hospital of Dianjiang Chongqing, Dianjiang Hospital of Chongqing College of Traditional Chinese Medicine, Chongqing

Abstract

Abstract

Background Post-traumatic wound infection (PTWI) is a major challenge in trauma, burns, and surgeries. The skin microbiota is crucial for defense and may influence PTWI occurrence, though the relationship is unclear. This study explores the causal link between the skin microbiome and PTWI using bidirectional two-sample Mendelian randomization (MR) analysis. Methods A two-sample MR analysis was conducted using genome wide association studies (GWAS) data of 147 skin microbiota taxa and PTWI. The inverse-variance weighted (IVW) method was the primary analysis technique, while the MR-Egger and weighted median were used as supplementary analysis methods. Cochran’s Q test was used to perform heterogeneity analysis. The MR-Egger intercept test and MR-PRESSO were employed to assess potential horizontal pleiotropy. The leave-one-out method was utilized to evaluate the impact of individual SNPs on the overall causal effect. Results The two-sample MR analysis identified significant causal relationships between 12 skin microbiota species and PTWI. Five species were potentially beneficial: asv045 [Acinetobacter (unc.)] (OR = 0.971, P = 0.044), asv092 [C. kroppenstedtii] (OR = 0.966, P = 6.88e − 03), asv093 [Staphylococcus (unc.)] (OR = 0.911, P = 0.044), genus Finegoldia (OR = 0.965, P = 0.043), and genus Kocuria (OR = 0.95, P = 0.025). Seven species were potentially harmful: asv001 [P. acnes] (OR = 1.187, P = 0.041), asv005 [P. granulosum] (OR = 1.259, P = 6.06e − 03), family Micrococcaceae (OR = 1.24, P = 0.014), family Neisseriaceae (OR = 1.161, P = 0.038), genus Enhydrobacter (OR = 1.039, P = 0.013; OR = 1.202, P = 0.017), and order Bacteroidales (OR = 1.202, P = 0.012). PTWI may also induce skin microenvironment changes, disrupting homeostasis and increasing the likelihood of pathogenic microbiota, such as class Betaproteobacteria, genus Chryseobacterium, asv007 [Anaerococcus (unc.)], and family Flavobacteriaceae. Conversely, PTWI might promote beneficial microbiota, like asv005 [P. granulosum]. Conclusions This study provides strong evidence of a causal link between the skin microbiome and PTWI, emphasizing their complex interactions. These findings offer new insights for preventing and treating PTWI. Further research on the underlying mechanisms and similar studies in different populations are essential.

Publisher

Springer Science and Business Media LLC

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