Genetic correlations and causal associations between BMI, HDL-C, and postoperative infections: a two-sample Mendelian...

Infections are serious postoperative complications, and strongly affects the mortality and prognosis of patients. Body mass index (BMI) and lipids are factors in postoperative infection, but a causal relationship has not been know. In this Mendelian randomization (MR) study, we utilized genome-wide association study (GWAS) data from the Global Lipids Genetics Consortium and FinnGen database, treating lipids and BMI as exposures. Postoperative infection GWAS data from the UK Biobank served as the outcome. We utilized linkage disequilibrium score regression (LDSC) analysis to evaluate the genetic correlations between lipids, BMI, and postoperative infections. We employed univariate and reverse MR analyses to explore the causal relationships between exposure and outcome factors. The analysis primarily utilized the inverse variance weighted method, supplemented by MR-Egger and weighted median methods. The MR-PRESSO method was used to detect horizontal pleiotropy and potential outliers. Additionally, stepwise mediation MR analysis was employed to investigate indirect factors potentially influencing the relationships between lipids, BMI, and postoperative infections. The genetic covariance analysis indicates that there is no sample overlap among all the GWAS conducted. In the LDSC analysis, genetic correlations (GC) were found between BMI(GC = 0.430, P < 0.05), HDL-C(GC = - 0.414, P < 0.05), nonHDL-C(GC = 0.137, P < 0.05), TG(GC = 0.417, P < 0.05), and postoperative infection. HDL-C showing a negative genetic association with postoperative infection, while other phenotypes showed positive associations. In MR analysis, causal relationships were identified between BMI and postoperative infection (OR = 1.36, 95% CI = 1.16-1.60, P < 0.05) and HDL-C and postoperative infection (OR = 0.87, 95% CI = 0.78-0.96, P < 0.05), with BMI showing a positive causal association and HDL-C showing a negative causal association with postoperative infection. These findings are consistent with the LDSC results. In the reverse MR analysis, there was no significant causal relationship identified between postoperative infection and both BMI and lipids. Stepwise mediation MR analysis excluded the impact of potential mediating factors between exposure and outcomes. In this study, through LDSC and MR analyses, we identified genetic correlations and causal links between BMI, HDL, and postoperative infection. It was found that BMI might increase the risk of postoperative infection, whereas HDL could potentially lower the risk of developing postoperative infection.