D6. Other (e.g., host response biomarkers, molecular imaging, metabolomics/proteomics, etc.)
Oral Abstract Submission
Miguel Reyes, BS
Graduate Student
Massachusetts Institute of Technology
Cambridge, MA
Disclosure: Nothing to disclose
Roby P. Bhattacharyya, MD, PhD
Assistant in Medicine
Massachusetts General Hospital
Boston, MA
Disclosure: Nothing to disclose
Michael Filbin, MD
Assistant Professor
Massachusetts General Hospital
Boston, Massachusetts
Disclosure: Nothing to disclose
Thomas Eisenhaure, BS
Research Scientist
Broad Institute
Cambridge, MA
Disclosure: Nothing to disclose
Deborah T. Hung, MD, PhD
Assistant Professor
Broad Institute
Cambridge, MA
Disclosure: Nothing to disclose
Rebecca Baron, MD
Assistant Professor
Harvard Medical School
Boston, MA
Disclosure: Nothing to disclose
Marcia B. Goldberg, MD
Physician and Professor of Medicine and Microbiology
Massachusetts General Hospital
Boston, MA
Disclosure: Nothing to disclose
Background :
Despite intense efforts to understand the immunopathology of sepsis, no clinically reliable diagnostic biomarkers exist. Multiple whole-blood gene expression studies have sought sepsis-associated molecular signatures, but these have not yet resolved immune phenomena at the cellular level. Using single-cell RNA sequencing (scRNA-Seq) to profile peripheral blood mononuclear cells (PBMCs), we identified a novel cellular state enriched in patients with sepsis.
Methods :
We performed scRNA-Seq on PBMCs from 26 patients with sepsis and 47 controls at two hospitals (mean age 57.5 yrs, sd 16.6; 54% male; 82% white), analyzing >200,000 single cells in total on a 10x Genomics platform. We identified immune cell states by stepwise clustering, first to identify the major immune cell types, then clustering each cell type into substates. Substate abundances were compared between cases and controls using the Wilcoxon rank-sum test.
Results :
We identified 18 immune cell substates (Fig 1a), including a novel CD14+ monocyte substate (MS1) that is enriched in patients with sepsis (Fig 1b). The fractional abundance of the MS1 substate alone (ROC AUC 0.88) outperformed published bulk transcriptional signatures in identifying sepsis (AUC 0.68-0.82) across our clinical cohorts. Deconvolution of publicly available bulk transcriptional data to infer abundance of the MS1 substate externally validated its accuracy in predicting sepsis of various etiologies across diverse geographic locations (Fig 1c), matching the best previously identified bulk signatures. Flow cytometry using cell surface markers unique to MS1 confirmed its marked expansion in sepsis, facilitating quantitation and isolation of this substate for further study.
Conclusion :
This study demonstrates the utility of scRNA-Seq in discovering disease-associated cytologic signatures in blood and identifies a cell state signature for sepsis in patients with bacterial infections. This novel monocyte substate matched the performance of the best bulk transcriptional signatures in classifying patients as septic, and pointed to a specific cell state for further molecular and functional characterization of sepsis immunopathogenesis.
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