Landscape of multiple tissues' gene expression pattern associated with severe sepsis: Genetic insights from Mendelian...

Sepsis, a systemic syndrome often culminating in multiple organ failure (MOF), poses a substantial global health threat. However, the gene expression pattern of various tissues associated with severe sepsis remains elusive.

Applying the summary data-based Mendelian randomization (SMR) method, we integrated sepsis genome-wide association study (GWAS) data and expression quantitative trait loci (eQTLs) summaries. This facilitated the investigation of gene causality across 12 tissue types within 26 cohorts linked to adverse sepsis outcomes, including critical care and 28-day mortality. Additionally, trans-omics analyses, including blood transcriptome and single-cell RNA sequencing, were conducted to examine cellular origins and gene functions. The effects of ST7L on sepsis were validated in vivo and in vitro.

We identified 127 genes associated with severe sepsis across diverse tissues. Cross-tissue analysis highlighted ST7L as a significant pan-tissue risk factor for severe sepsis, displaying significance across 11 tissues for both critical care sepsis (meta OR 1.19, 95 % CI: 1.14-1.25, meta p < 0.0001) and 28-day-death sepsis (meta OR: 1.22, 95 % CI: 1.17-1.27, meta p < 0.0001). Notably, independent blood single-cell RNA sequencing data showed specific expression of ST7L in dendritic cells (DCs). ST7L⁺ DCs were elevated in non-surviving sepsis patients and exhibited an augmented inflammatory molecular pattern compared to ST7L^- DCs. Both transcription and translation level of ST7L in DCs exhibited a dose-dependent pattern with LPS. Knocking down ST7L by siRNA was sufficient to alleviate the inflammation phenotype of DCs, including inhibiting p65/NF-kB pathway and inflammatory factors.

Our findings underscore ST7L as a pan-tissue risk factor for severe sepsis, specifically manifested in DCs and associated with an inflammatory phenotype. These results offer essential insights into the gene expression profiles across multiple tissues in severe sepsis, potentially identifying therapeutic targets for effective sepsis management.