An Endotoxin Tolerance Signature Predicts Sepsis and Organ Dysfunction at Initial Clinical Presentation - GSE63311

Background: Sepsis involves aberrant immune responses to infection, but the exact nature of this immune dysfunction remains poorly defined. Bacterial endotoxins like lipopolysaccharide (LPS) are potent inducers of inflammation, which has been associated with the pathophysiology of sepsis, but repeated exposure can also induce a suppressive effect known as endotoxin tolerance or cellular reprogramming. It has been proposed that endotoxin tolerance might be associated with the immunosuppressive state that was primarily observed during late-stage sepsis. However, this relationship remains poorly characterised. Here we clarify the underlying mechanisms and timing of immune dysfunction in sepsis. Methods: We defined a gene expression signature characteristic of endotoxin tolerance. Gene-set test approaches were used to correlate this signature with early sepsis, both newly and retrospectively analysing microarrays from 593 patients in 11 cohorts. Then we recruited a unique cohort of possible sepsis patients at first clinical presentation in an independent blinded controlled observational study to determine whether this signature was associated with the development of confirmed sepsis and organ dysfunction. Findings: All sepsis patients presented an expression profile strongly associated with the endotoxin tolerance signature (p < 0.01; AUC 96.1%). Importantly, this signature further differentiated between suspected sepsis patients who did, or did not, go on to develop confirmed sepsis, and predicted the development of organ dysfunction. Interpretation: Our data support an updated model of sepsis pathogenesis in which endotoxin tolerance-mediated immune dysfunction (cellular reprogramming) is present throughout the clinical course of disease and related to disease severity. Thus endotoxin tolerance might offer new insights guiding the development of new therapies and diagnostics for early sepsis.

For the RNA-Seq study reported here, 73 patients were recruited with deferred consent at the time of first examination in an emergency ward based on the opinion of physicians that there was a potential for the patient's condition to develop into sepsis. These were retrospectively divided into groups based on clinical features and compared to 11 non-urgent surgical controls.

Sepsis (2021 ICD-10-CM code* = A41)

Raw basecall data was converted to FASTQ sequence files using Off-Line Basecaller 1.9.4 (Ilumina) and a custom Perl script.Reads were aligned to the hg19 human genome with TopHat version 2.06 and Bowtie2 2.0.0-beta6Reads were initially mapped to Ensembl transcripts with the search for novel junctions disabled. Genomic coordinates were then transformed into counts of protein-coding Ensembl genes. To do this, a chimeric gene-model was first defined by merging all protein-coding transcripts for a given gene. Transcripts that had reads in less than 50% of their exons in all samples were defined as not expressed and were excluded from the chimeric transcriptome.Reads that overlapped the chimeric genes were counted using the htseq-count script in the intersection-nonempty mode (http://www-huber.embl.de/users/anders/HTSeq/doc/count.html). The script discards multi-mapped reads as well as reads that overlap multiple distinct genes, to generate a file of uniquely mapped gene counts.Genome_build: hg19Supplementary_files_format_and_content: comma-delimited csv files includes mapped count values for each Sample

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE63311