A machine learning integrated multi-omics framework for risk prediction and target discovery in insomnia aggravated sepsis induced acute lung injury.

Objective: This study aims to identify critical biomarkers and clarify how insomnia exacerbates sepsis-induced acute lung injury (SALI). We used integrative multi-omics approaches and machine learning. Methods: A causal association between sepsis and insomnia was established using Mendelian randomization (MR). We used weighted gene co-expression network analysis (WGCNA) to identify genes linked to both insomnia and SALI. We used machine learning techniques (Random Forest, SVM, KNN) with SHAP interpretability modeling to refine gene signatures. The diagnostic and prognostic value of these genes was investigated. To elucidate the underlying molecular pathways, functional enrichment analyses, including KEGG, GO, PPI, and GSEA were performed. To validate gene expression patterns and cellular localization, transcriptomic profiling, single-cell RNA sequencing (scRNA-seq), and Results: MR analysis identified insomnia as a causal determinant in susceptibility to sepsis. Complementary pathological evidence from preclinical sleep deprivation models further confirmed its role in exacerbating progression of SALI. The WGCNA revealed 1,294 co-dysregulated genes shared between insomnia and SALI. These genes were significantly enriched in biological processes, including immune regulation and phagocytic vesicle formation, as well as KEGG pathways such as tuberculosis infection and chemokine signaling. Among these,102 genes exhibited differential expression in a murine SALI model induced by LPS. Through machine learning analysis, ISG20, MYO1F, and PTPN6 were identified as robust hub genes. Further diagnostic stratification and prognostic evaluation prioritized PTPN6 as the most promising candidate. Immune infiltration analysis, scRNA-seq profiling and GSEA collectively demonstrated that PTPN6 expression is predominantly localized to macrophages and functionally involved in modulating the JAK/STAT3 signaling pathway. Functional validation via PTPN6 overexpression in macrophages confirmed its suppressive effects on pro-inflammatory cytokine production, STAT3 phosphorylation, and M1 polarization. Conclusion: This work identifies PTPN6 as a critical biomarker mechanistically linking insomnia to an exacerbation of SALI, potentially through the amplification of pro-inflammatory responses and JAK/STAT3-dependent macrophage polarization. These findings enhance our understanding of the molecular processes underlying this pathogenic axis; however, further mechanistic investigations and comprehensive clinical validation are required to fully elucidate the complex regulatory network involved.