IFN-γ signature in the plasma proteome distinguishes pediatric hemophagocytic lymphohistiocytosis from sepsis and SIRS

Abstract

Hemophagocytic lymphohistiocytosis (HLH) is a syndrome characterized by pathologic immune activation in which prompt recognition and initiation of immune suppression is essential for survival. Children with HLH have many overlapping clinical features with critically ill children with sepsis and systemic inflammatory response syndrome (SIRS) in whom alternative therapies are indicated. To determine whether plasma biomarkers could differentiate HLH from other inflammatory conditions and to better define a core inflammatory signature of HLH, concentrations of inflammatory plasma proteins were compared in 40 patients with HLH to 47 pediatric patients with severe sepsis or SIRS. Fifteen of 135 analytes were significantly different in HLH plasma compared with SIRS/sepsis, including increased interferon-γ (IFN-γ)-regulated chemokines CXCL9, CXCL10, and CXCL11. Furthermore, a 2-analyte plasma protein classifier including CXCL9 and interleukin-6 was able to differentiate HLH from SIRS/sepsis. Gene expression in CD8+ T cells and activated monocytes from blood were also enriched for IFN-γ pathway signatures in peripheral blood cells from patients with HLH compared with SIRS/sepsis. This study identifies differential expression of inflammatory proteins as a diagnostic strategy to identify critically ill children with HLH, and comprehensive unbiased analysis of inflammatory plasma proteins and global gene expression demonstrates that IFN-γ signaling is uniquely elevated in HLH. In addition to demonstrating the ability of diagnostic criteria for HLH and sepsis or SIRS to identify groups with distinct inflammatory patterns, results from this study support the potential for prospective evaluation of inflammatory biomarkers to aid in diagnosis of and optimizing therapeutic strategies for children with distinctive hyperinflammatory syndromes.

Graphical abstract

Figure 1.

Unsupervised analysis does not distinguish HLH from sepsis/SIRS compared with pediatric controls. (A) Heat map displaying unsupervised clustering of all plasma analytes assayed from noninflammatory pediatric controls, HLH, sepsis, and SIRS. Colors representing specific diagnostic groups/subgroups are included in the legend. Cases of secondary HLH (systemic juvenile idiopathic arthritis [JIA], drug reaction with eosinophilia syndrome [DRESS], and cancer) are indicated. (B) These datasets are also presented using principal component analysis. The control cases clearly separate, whereas HLH, severe sepsis, and SIRS have overlapping inflammatory plasma profiles.

Figure 2.

Plasma analytes with significant differences between HLH and sepsis/SIRS. (A) Heatmap demonstrates relative concentration of analytes with significant differential expression (FDR < 0.1) revealed by supervised comparison of HLH and SIRS/sepsis datasets. All subjects in this study are shown with heatmap reflecting relative concentrations of analytes with significant differential expression between HLH and sepsis or SIRS in both training and validation cohorts. (B) Subjects were split into training and validation cohorts, without reference to cytokine values, and analyzed separately. Values of analytes with differential expression between HLH and SIRS/sepsis datasets are displayed for training and validation cohorts.

Figure 3.

IFN-γ–inducible plasma proteins are significantly increased in HLH. Boxplots demonstrate comparisons of specific analyzes in HLH, SIRS/sepsis, and control groups in training (i) and validation (ii) cohorts. Bars with asterisk indicate groups with statistically significant differential expression evaluated using a Mann-Whitney-Wilcoxon test (P < .05). IFN-γ–inducible plasma proteins CXCL9, CXCL10, and CXCL11 are significantly increased in HLH compared with sepsis in training and validation cohorts. IL-6 is relatively increased in SIRS/sepsis compared with HLH, and there is no significant difference in IL-10 concentrations in HLH and SIRS/sepsis in the validation cohort in this study.

Figure 4.

Gene expression signatures validate plasma classifier and point to distinctive T-cell and IFN-γ–driven etiology of HLH. (A) Gene set enrichment plot showing the enrichment score of the ranked gene list in the IFN–γ response signature of CD8⁺ T cells and CD68⁺ monocytes from subjects with HLH and severe sepsis. (B) Genes included in the leading edge analysis of the IFN-γ response signature (A) are presented graphically. The leading edge consists of the subset of genes in the signature where the running sum of the enrichment score reaches its maximum deviation from zero in panel A. The color describes whether the gene is (yellow) or is not (blue) present in leading-edge genes in the CD8 or CD68 datasets. (C) Relative gene expression of the leading edge genes that are significantly enriched in the INF-γ response signature from the CD8 and CD68 subpopulations are presented in a heatmap, with each column representing cell-specific transcriptome from a single subject.

Figure 5.

Protein classifiers to distinguish HLH from sepsis/SIRS. (A) Full (i) and reduced (ii) protein classifiers were developed in a training cohort using a compound covariate predictor to differentiate HLH from SIRS/sepsis and subsequently validated using an independent cohort. The heatmap shows the features used in those classifiers in the combined training and validation sets. (B) Confusion matrices, sensitivities, and specificities of the 2 classifiers in both the training and validation cohorts. (C) Receiver operating curves of both full and reduced classifiers in the training and validation sets. The AUC was calculated for each classifier as an overall diagnostic accuracy.