Integration of Genomics and Transcriptomics to Predict Sepsis-Associated Acute Lung Injury Genes

Background: Sepsis-induced acute lung injury (SALI) increases morbidity and mortality among patients in the intensive care unit, often progressing to acute respiratory distress syndrome (ARDS) in patients and resulting in death. Exploring the proteomic associations related to SALI can further elucidate its molecular mechanisms and provide novel targets for underlying treatment. Methods: We conducted 2-sample Mendelian randomization (MR) to analyze the relationship between plasma proteins and sepsis. Additionally, differentially expressed genes (DEGs) between the SALI and sepsis groups were identified using the GSE65682 dataset from the Gene Expression Omnibus (GEO) database. By intersecting the plasma proteins analyzed by MR with DEGs related to SALI, we identified and validated the marked plasma proteins, which were accurate and robust according to multiple sensitivity analyses. Results: A total of 541 plasma proteins were significantly associated with sepsis according to 2-sample MR analysis by the inverse-variance-weighted method. Moreover, 206 DEGs between the SALI and sepsis groups from the GSE65682 dataset in the GEO database were identified. By intersecting the 541 plasma proteins with the 206 DEGs, we identified plasma proteins ( CD74 , CDKN2C , CLU , HBQ1 , IL7R , and OLFM4 ) that were negatively associated with SALI risk. According to inverse-variance-weighted analysis, their odds ratios ranged from 0.676 (95% confidence interval [CI] 0.498 to 0.919) for CD74 to 0.889 (95% CI 0.813 to 0.973) for CDKN2C . Enrichment analysis indicated that these proteins were involved primarily in immune responses. From the enriched network, we established the relationships between the above genes and immune receptor activity and the luminal side of the membrane or endoplasmic reticulum membrane. Conclusions: This study revealed that plasma proteins ( CD74 , CDKN2C , CLU , HBQ1 , IL7R , and OLFM4 ) are causally protective against SALI, which contributes to the early identification and accurate treatment of SALI and could decrease the incidence of ARDS or even the risk of death.