Whole blood transcriptomics identifies subclasses of pediatric septic shock

Abstract

Background: Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.

Methods: The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.

Results: Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires.

Conclusions: Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Keywords: Adaptive immunity; Gene expression; RNA-Seq; Sepsis; Subclassification.

Fig. 1

Flowchart of patients in this study after applying exclusion and inclusion criteria. All septic shock cases were diagnosed with sepsis and were started on inotropes < 72 h from blood sampling. All controls had no documented diagnosis of sepsis or pneumonia, no positive cultures, and no inotrope use, and were started on mechanical ventilation < 72 h from blood sampling

Fig. 2

Gene network displaying functional enriched terms with associated DEGs between septic shock cases and controls (A). Upregulated pathways in septic shock cases compared to controls (B). Downregulated pathways in septic shock cases compared to controls

Fig. 3

Heatmaps A Heatmap depicting the expression of all 840 differentially expressed genes (DEGs) between septic shock cases and controls. Each row represents a DEG; blue indicates that a gene is downregulated, while red indicates that a gene is upregulated. Each column is a patient, so each column depicts the transcriptomic signature of each patient. The dendrogram at the top shows unsupervised hierarchical clustering of the patients such that the patients with similar transcriptomic signatures are clustered together. B This heatmap depicts the same patients and genes as in Fig. 2A, but now the controls are sorted on the left, and the cases sorted on the right. Clustering based on each patient’s transcriptomic signature was performed within each group

Fig. 4

Gene network displaying functionally enriched terms with associated DEGs between Subclass 1 and Subclass 2. A Upregulated Pathways in Subclass 1 compared to Subclass 2 B Downregulated Pathways in Subclass 1 compared to Subclass 2

Fig. 5

A Box plot depicting differences in whole blood cell type abundances between Subclass 1 and 2. Subclass 1 has significantly lower percentages of CD4 T cells (0.9 ± 1.5 vs. 5.2 ± 4.3; p < 0.001) and B cells (2.7 ± 2.0 vs. 4.6 ± 3.3; p = 0.024), and a higher percentage of endothelial cells compared to Subclass 2 (4.8 ± 0.7 vs. 4.2 ± 0.6). There were no significant differences in percentages of CD8 T cells between the two subclasses. B Number of TCR reads per 1 million RNA-Seq reads in septic shock subclasses. Subclass 1 had significantly fewer TCR reads normalized per RNA sequencing reads than Subclass 2 (3.91 ± 4.30 vs. 10/03 ± 8.46; p = 0.001). C Subclass 1 had significantly fewer mean clonotypes than Subclass 2 (59.70 ± 59.49 vs. 155.96 ± 138.4; p = 0.002). D Inverse Simpson index, a measure of mean diversity of the T cell repertoire, between Subclass 1 versus Subclass 2. Subclass 1 had a less diverse mean T cell repertoire than Subclass 2 on the Inverse Simpson index (43.84 ± 45.11 vs. 114.45 ± 108.8; p = 0.002)