A machine learning integrated multi-omics framework for risk prediction and target discovery in insomnia aggravated sepsis induced acute lung injury - PubMed
3 hours ago
- #insomnia
- #PTPN6 biomarker
- #sepsis-induced acute lung injury
- Insomnia was identified as a causal factor increasing susceptibility to sepsis through Mendelian randomization.
- Multi-omics and machine learning identified 1,294 genes co-dysregulated in insomnia and sepsis-induced acute lung injury (SALI), enriched in immune-related pathways.
- ISG20, MYO1F, and PTPN6 were selected as hub genes via machine learning, with PTPN6 prioritized as the most promising diagnostic and prognostic biomarker.
- PTPN6 is predominantly expressed in macrophages and modulates the JAK/STAT3 pathway, suppressing pro-inflammatory cytokine production and M1 polarization.
- Experimental validation showed that PTPN6 overexpression in macrophages reduces inflammation and STAT3 phosphorylation, linking insomnia to aggravated SALI.