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

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

  • By

  • Jinquan Zhang

  • Yuwei Zhang

  • Zeyu Liu

  • Xiaona Chen

  • Zhengzheng Yan

  • Zhixia Chen

  • Quan Li

  • June 1, 2026

  • 0 min

Share

Clinical Report: Integrated Multi-Omics Approach in Sepsis and Insomnia

Overview

This study identifies PTPN6 as a critical biomarker linking insomnia to exacerbated acute lung injury in sepsis patients. Utilizing multi-omics and machine learning, it highlights the role of insomnia in increasing susceptibility to sepsis-induced acute lung injury.

Background

Insomnia is a prevalent condition that significantly impacts immune function and increases the risk of severe health outcomes, including sepsis. Sepsis-induced acute lung injury (SALI) is a common and deadly complication, necessitating a deeper understanding of the underlying mechanisms. This study explores the intersection of insomnia and SALI, aiming to clarify their relationship and identify potential biomarkers for risk assessment.

Data Highlights

Remove placeholder text and provide relevant data or state that data is not applicable.

Key Findings

  • Insomnia is identified as a causal determinant for increased susceptibility to sepsis.
  • 1,294 co-dysregulated genes were found to be shared between insomnia and SALI.
  • PTPN6 was prioritized as a promising candidate biomarker through machine learning analysis.
  • PTPN6 expression is predominantly localized to macrophages and modulates the JAK/STAT3 signaling pathway.
  • Functional validation confirmed PTPN6's role in suppressing pro-inflammatory cytokine production.

Clinical Implications

The identification of PTPN6 as a biomarker may aid in the development of targeted interventions for patients with insomnia at risk of SALI. Understanding the molecular pathways involved can enhance clinical strategies for managing sepsis and its complications.

Conclusion

This study underscores the importance of addressing insomnia in sepsis patients to mitigate the risk of acute lung injury. Further research is needed to validate these findings and explore their clinical applications.

Related Resources & Content

  1. Frontiers in Medicine, 2026 -- Construction and internal–external validation of a machine learning-based risk prediction model for multidrug resistance in ICU patients with acute exacerbation of chronic obstructive pulmonary disease
  2. Frontiers in Medicine, 2026 -- Machine Learning Model for Predicting the Risk of AKI in Early Hemodynamically Stable Sepsis Patients: A Study Based on the MIMIC IV Database
  3. npj Digital Medicine, 2025 -- Streamlined machine learning model for early sepsis risk prediction in burn patients
  4. Surviving Sepsis Campaign Adult Guidelines | SCCM
  5. Bidirectional Interaction of Sepsis and Sleep Disorders: The Underlying Mechanisms and Clinical Implications - PubMed
  6. npj Digital Medicine — A multimodal embedding model for sepsis data representation
  7. Guideline on the clinical investigation of medicinal products in the treatment of patients with acute respiratory distress syndrome
  8. Surviving Sepsis Campaign Adult Guidelines | SCCM
  9. An Update on Management of Adult Patients with Acute Respiratory Distress Syndrome: An Official American Thoracic Society Clinical Practice Guideline - PMC
  10. A Focused Update to SCCM PADIS Guidelines for Adult Patients | SCCM
  11. Bidirectional Interaction of Sepsis and Sleep Disorders: The Underlying Mechanisms and Clinical Implications - PubMed
  12. Association of Genetically Predicted Insomnia With Risk of Sepsis: A Mendelian Randomization Study - PMC
  13. Comparative outcomes of corticosteroids, neuromuscular blocking agents, and inhaled nitric oxide in ARDS: a systematic review and network meta-analysis - PMC
  14. Corticosteroids in non-viral acute respiratory distress syndrome (ARDS): recommendations outpace evidence – a concise review | Pneumonia | Springer Nature Link
  15. Conservative Oxygen Therapy in Mechanically Ventilated Critically Ill Adult Patients: The UK-ROX Randomized Clinical Trial - PubMed
  16. Prognostic Significance of Driving Pressure for Initiation and Maintenance of ECMO in Patients with Severe ARDS: A Systematic Review and Meta-analysis - PubMed
  17. The Effect of Early Warning Systems for Sepsis on Mortality: A Systematic Review and Meta-analysis - PubMed

Original Source(s)

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

  • by Jinquan Zhang, Yuwei Zhang, Zeyu Liu, Xiaona Chen, Zhengzheng Yan, Zhixia Chen, Quan Li

  • June 1, 2026

Related Content

Sepsis Care Tied to Home Discharge

Journal pre-proof study of more than 38,000 patients found timely antibiotics and indicated fluid resuscitation were associated with increased odds of returning home

Efficacy analysis of disitamab vedotin (RC-48) in the treatment of HER2-low metastatic breast cancer: a case report

AI Scribes Lag Clinicians on Note Quality

A VHA study across 11 vendors finds AI-generated primary care notes score lower than clinician-written notes, with the largest deficits in thoroughness, organization, and usefulness