Abstract
Patients with sepsis complicated by acute respiratory distress syndrome (ARDS) face a significantly increased risk of in-hospital death. This study aimed to identify sepsis-associated genes involved in ARDS pathogenesis and discover candidate biomarkers for its diagnosis. Gene expression profiling data from the Gene Expression Omnibus database were analyzed to identify key septic ARDS genes using differential expression analysis and weighted gene co-expression network analysis. Functional enrichment and connectivity map analyses were performed to explore underlying mechanisms and potential therapeutic drugs. Machine learning algorithms were applied to screen biomarkers and construct a diagnostic nomogram. Receiver operating characteristic, calibration, and decision curve analyses evaluated its diagnostic performance. Single-sample gene set enrichment analysis and peripheral blood mononuclear cell sequencing were used to assess immune cell infiltration. We identified 49 key genes linked to septic ARDS, enriched in inflammatory response regulation, reactive oxygen biosynthesis, and immune suppression. Connectivity map analysis suggested etoposide as a potential ARDS treatment. Three hub genes, ATPase plasma membrane Ca2⁺ transporting 1 (ATP2B1), retinol binding protein 7 (RBP7), and absent in melanoma 2 (AIM2), were selected as candidate biomarkers for nomogram construction, demonstrating ideal diagnostic performance. Immune cell infiltration analysis revealed immune downregulation in ARDS, with ATP2B1, RBP7, and AIM2 significantly associated with immune dysregulation. This study uncovered inflammatory immune pathways in ARDS and developed an ATP2B1/RBP7/AIM2-based nomogram for septic ARDS diagnosis, offering new insights for diagnosis and therapeutic interventions.