An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Abstract

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.

Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis

“…The authors proposed that patients classified as Mars1 were the most clinically relevant group with consistently increased mortality. Comparisons with the SRS revealed an overlap between the low-risk groups SRS2 and Mars3, but not the expected enrichment of Mars1 patients within SRS1 (Scicluna et al, 2017;Cano-Gamez et al, 2022). One explanation could be the primarily leukocyte-based training data for SepstratifieR differing from the whole blood-derived RNA used for MARS signatures.…”

“…Frontiers in Genetics frontiersin.org a continuum which is a better descriptor of molecular profiles compared to classes (Cano-Gamez et al, 2022).…”

“…At the gene level though, similarities in differential expression and active pathways were observed. Moreover, classification of MARS patients into SRS endotypes showed that SRS1 had a higher proportion of septic shock and elevated Sequential Organ Failure Assessment (SOFA) scores, but not increased mortality, reflecting the presence of unobserved variables preventing the severe sequelae of sepsis (Cano-Gamez et al, 2022).…”

“…The studies described all present a refined panel of genes or proteins as input for their classifiers, but the extent of refinement should be determined by the final assay choice for use in the clinic. Notably, some of the attempts to apply tests to new populations find further model training is required, including the addition of more genes (Burnham et al, 2017;Cano-Gamez et al, 2022). This is perhaps to be expected given the heterogeneity of human samples and the complexity of the clinical problems.…”

“…The model for Oncotype DX, approved for clinical use, was ultimately derived from pooling three clinical trials' results (Paik et al, 2014). In the case of sepsis, attempts to use publicly available data to improve robustness may similarly prove fruitful (Sweeney et al, 2018a;Sweeney et al, 2018b;Cano-Gamez et al, 2022). Likewise, more groups taking steps to ensure their analyses can be reproduced and applied to new populations, by sharing code and data, should also hasten this process (Heil et al, 2021).…”