Table 1_A synergistic multi-omics approach: causal sepsis drivers identified in activated

Jun Zhou published a dataset on 2026-05-28 containing results from a multi-omics study of sepsis. The data likely contains statistical results from single-cell RNA sequencing and Mendelian randomization analyses. It identifies four causal gene drivers in activated CD4+ T cells.

Use Cases

• Validate causal gene signatures for sepsis risk based on the identified four-gene set (RPLP0, CD52, RPS15A, RPS18).
• Investigate the 'Metabolism–Proteostasis–Immunity' regulatory axis in immune cell pathology.
• Benchmark single-cell RNA-seq findings from activated CD4+ T cells against other sepsis studies.
• Perform secondary Mendelian randomization analyses using the provided genetic association statistics.
• Design targeted therapeutic strategies based on the identified pathogenic and protective gene programs.

Strengths

• Dataset is licensed CC-BY-4.0 for open sharing and reuse.
• Analysis integrates two distinct methodologies: single-cell RNA sequencing and Mendelian randomization.
• Findings were validated via qPCR in a clinical cohort of 5 sepsis patients and 5 healthy controls.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small at 70.7 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Analysis of public datasets (GSE175453, ieu-b-4980, eQTLGen) combined with original qPCR validation.

Freshness

Last updated 2026-05-28 04:43:38; freshness should be verified.