Genetically-influenced HDL concentration, composition and modulation and the risk of sepsis: a Mendelian Randomization Study

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Abstract

Purpose: A growing body of evidence suggests a protective role for high-density lipoprotein (HDL) in the development and progression of sepsis. However, evidence favoring causality between HDL and sepsis remains limited. Here we investigated, by using Mendelian randomization (MR), the potential causal link between HDL particle concentration or HDL-related proteins, and the risk of developing sepsis. Methods: Two-sample MR analyses were conducted to investigate association between genetically-influenced HDL particle concentration, HDL-related proteins, and the risk of sepsis. We utilized a genome-wide association study (GWAS) comprising 10,154 sepsis cases and 452,764 controls as outcome. Inverse-variance weighted (IVW) analyses were employed as primary analyses. Protein-protein interaction (PPI) network analyses were used to identify key regulators for concentration of HDL particles and ApoA1. Results: Based on the IVW analyses, we found evidence for an association between genetically-influenced higher HDL particle concentration and lower risk of sepsis (odds ratio (OR): 0.86, 95% confidential interval (CI): 0.77-0.96). Similarly, genetically-influenced higher ApoA1 concentration was associated with a lower risk of sepsis (OR: 0.90, 95% CI: 0.85 - 0.96). Through PPI network analyses, we identified cholesteryl ester transfer protein (CETP) as one of the key players in regulating the concentration of HDL particles and ApoA1, and sepsis risk as such. Conclusion: Our MR study provides evidence for an inverse relationship between HDL particle concentration or ApoA1, and the susceptibility to sepsis. We anticipate that CETP inhibitory strategies may increase HDL particle concentration and apoA1 to lower sepsis susceptibility and potentially prevent the risks associated with sepsis. Keywords: High density lipoprotein; sepsis; apolipoprotein A1; cholesteryl ester transport protein; Mendelian randomization

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