eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response.

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

A Transcriptomic Approach to Understand Patient Susceptibility to Pneumonia After Abdominal Surgery.

OBJECTIVE: To describe immune pathways and gene networks altered following major abdominal surgery and to identify transcriptomic patterns associated with postoperative pneumonia. BACKGROUND: Nosocomial infections are a major healthcare challenge, developing in over 20% of patients aged 45 or over undergoing major abdominal surgery, with postoperative pneumonia associated with an almost 5-fold increase in 30-day mortality. METHODS: From a prospective consecutive cohort (n=150) undergoing major abdominal surgery, whole-blood RNA was collected preoperatively and at 3 time-points postoperatively (2-6, 24, and 48 h). Twelve patients diagnosed with postoperative pneumonia and 27 matched patients remaining infection-free were identified for analysis with RNA-sequencing. RESULTS: Compared to preoperative sampling, 3639 genes were upregulated and 5043 downregulated at 2 to 6 hours. Pathway analysis demonstrated innate-immune activation with neutrophil degranulation and Toll-like-receptor signaling upregulation alongside adaptive-immune suppression. Cell-type deconvolution of preoperative RNA-sequencing revealed elevated S100A8/9-high neutrophils alongside reduced naïve CD4 T-cells in those later developing pneumonia. Preoperatively, a gene-signature characteristic of neutrophil degranulation was associated with postoperative pneumonia acquisition ( P =0.00092). A previously reported Sepsis Response Signature (SRSq) score, reflecting neutrophil dysfunction and a more dysregulated host response, at 48 hours postoperatively, differed between patients subsequently developing pneumonia and those remaining infection-free ( P =0.045). Analysis of the novel neutrophil gene-signature and SRSq scores in independent major abdominal surgery and polytrauma cohorts indicated good predictive performance in identifying patients suffering later infection. CONCLUSIONS: Major abdominal surgery acutely upregulates innate-immune pathways while simultaneously suppressing adaptive-immune pathways. This is more prominent in patients developing postoperative pneumonia. Preoperative transcriptomic signatures characteristic of neutrophil degranulation and postoperative SRSq scores may be useful predictors of subsequent pneumonia risk.