Multi-Omics Data for Insomnia-Aggravated Sepsis-Induced Acute Lung Injury

1,294 co-dysregulated genes were identified linking insomnia and sepsis-induced acute lung injury (SALI). Machine learning analysis prioritized three hub genes, with PTPN6 validated as a key biomarker. The dataset, authored by Jinquan Zhang and last updated in 2026, supports research into the molecular mechanisms of this condition.

Use Cases

• Validate causal links between insomnia and sepsis susceptibility based on Mendelian randomization results.
• Train diagnostic classifiers for acute lung injury using the identified gene signatures like ISG20, MYO1F, and PTPN6.
• Investigate immune regulation pathways in sepsis using the enriched KEGG and GO terms from the analysis.
• Study macrophage polarization and JAK/STAT3 signaling using the single-cell RNA sequencing and immune infiltration data.

Strengths

• Integrates multiple analysis methods including Mendelian randomization, WGCNA, and three machine learning algorithms.
• Includes experimental validation via in vivo and in vitro models, as well as single-cell RNA sequencing.
• Identifies a specific causal biomarker (PTPN6) with demonstrated functional role in macrophage polarization.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Integrative multi-omics analysis and machine learning applied to genetic and transcriptomic data.

Freshness

Last updated 2026-06-01 04:17:32; freshness should be verified.