Cytokine Profiles of Severe Influenza Virus-Related Complications in Children

Abstract

Rationale: Effective immunomodulatory therapies for children with life-threatening "cytokine storm" triggered by acute influenza infection are lacking. Understanding the immune profiles of children progressing to severe lung injury and/or septic shock could provide insight into pathogenesis.

Objectives: To compare the endotracheal and serum cytokine profiles of children with influenza-related critical illness and to identify their associations with severe influenza-associated complications.

Methods: Children with influenza-related critical illness were enrolled across 32 hospitals in development (N = 171) and validation (N = 73) cohorts (December 2008 through May 2016). Concentrations of 42 cytokines were measured in serum and endotracheal samples and clustered into modules of covarying cytokines. Relative concentrations of cytokines and cytokine modules were tested for associations with acute lung injury (ALI), shock requiring vasopressors, and death/ECMO.

Measurements and main results: Modules of covarying cytokines were more significantly associated with disease severity than individual cytokines. In the development cohort, increased levels of a serum module containing IL6, IL8, IL10, IP10, GCSF, MCP1, and MIP1α [shock odds ratio (OR) = 3.37, family-wise error rate (FWER) p < 10^-4], and decreased levels of a module containing EGF, FGF2, SCD40L, and PAI-1 (shock OR = 0.43, FWER p = 0.002), were both associated with ALI, shock, and death-ECMO independent of age and bacterial coinfection. Both of these associations were confirmed in the validation cohort. Endotracheal and serum cytokine associations differed markedly and were differentially associated with clinical outcomes.

Conclusion: We identified strong positive and negative associations of cytokine modules with the most severe influenza-related complications in children, providing new insights into the pathogenesis of influenza-related critical illness in children. Effective therapies may need to target mediators of both inflammation and repair.

Keywords: acute lung injury; cytokine; inflammation; influenza; septic shock.

Figure 1

Cytokine covariation. (A) Pairwise Pearson’s correlations among log-concentrations of cytokines, chemokines, and growth factors in serum samples (165 patients; 42 cytokines). Cytokines were sorted along both axes to emphasize clusters of cytokines, using hierarchical clustering (complete-linkage). (B) Correlation of cytokines with each patient’s mean cytokine concentrations. Red bars indicate correlation with unadjusted p < 0.05. (C) Pairwise correlations of cytokines after computing relative concentrations adjusted for each patient’s mean cytokine concentration. (D) Correlation of each cytokine in serum versus endotracheal aspirate samples. Red bars indicate correlation with unadjusted p < 0.05.

Figure 2

Modules of blood stream (BS) cytokines based on relative cytokine concentrations. Heatmap of BS cytokine modules. A distance was computed between every pair of cytokines using Pearson’s correlation coefficient estimated across the development cohort. Cytokines were then clustered using complete-linkage hierarchical clustering. The algorithm was repeated 1,000 times, each time resampling the patient cohort with replacement [i.e., patient-level bootstrap clustering (25)]. Finally, cytokines were clustered based on the fraction of times that each pair of cytokines clustered together (heatmap color intensity). Dendrogram shows the separation between clusters, which is the basis of the modules. Stripe of colors indicates the six resultant BS modules used in subsequent analyses.

Figure 3

Cytokine associations with clinical complications. Modules constructed of covarying cytokines from (A) blood stream (BS) or (B) ET samples, were tested for associations with the clinical complications shock, acute lung injury (ALI)-ARDS and ECMO-death. Each cytokine or module is indicated along the rows, grouped by their assigned module. Heatmap color indicates the direction and magnitude of the fold-difference between patients with and without the complication in the development cohort (N = 165). Only associations with false-discovery rate (FDR)-adjusted q-value < 0.2 are colored. Asterisks indicate family-wise error rate (FWER)-adjusted p-values with ***, **, and * indicating p < 0.0005, 0.005, and 0.05, respectively.

Figure 4

Modules associated with clinical complications. (A,B) Box plots of the BS3 and BS4 cytokine module levels for patients with or without shock and acute lung injury (ALI)-ARDS. BS3 levels were significantly different in patients with versus without shock and patients with versus without ALI-ARDS [family-wise error rate (FWER)-adjusted p-values < 0.01]. BS4 levels were significantly different in patients with versus without shock (FWER-adjusted p-value < 0.01). (C–F) Box plots of cytokine module levels in patients for the BS3 (C), BS4 (D), ET2 (E), and ET6 (F) modules grouped by whether or not they died or were on ECMO support (near death). Extents of the box indicate the interquartile range (IQR) with whiskers indicating the most extreme data point within 1.5 times the IQR. Patients who died on study are plotted using a black circle. An asterisk and line indicate a FWER-adjusted p-values < 0.05 (D,E).

Figure 5

Shock-associated serum modules correlate with shock severity. A score based on vasopressor levels was computed at enrollment in a subset of patients (n = 85). Boxplots show the distribution of the levels of the BS3 (A) and BS4 (B) cytokine modules at enrollment (log scale). Module levels are grouped by each patient’s cardiovascular sepsis-related organ failure assessment (CV-SOFA) score at enrollment. Spearman’s rank-based correlation was used to assess correlation between the vasopressor score and cytokine module levels, with the correlation coefficient and p-value annotating each panel.

Figure 6

Evaluation of blood cytokine classifier. To evaluate blood stream (BS) cytokines as a potential biomarker of the most severely ill patients [shock and acute lung injury (ALI)/ARDS] a classifier was developed using L1-regularized logistic regression (i.e., LASSO). The final classifier was based on age and the concentrations of 19 cytokines: TNFα, IFNα2, GMCSF, GRO, IL1β, IL6, IL7, IL8, IL10, MCP1, MCP3, MDC, MIP1β, VEGF, IFNβ, EGF, FGF2, TGFα, and HMGB1. For reference, a classifier based on pediatric risk of mortality (PRISM) score and age alone was also evaluated. Classification performance was evaluated using receiver operating curves (ROC), first on the development cohort [(A), n = 165] and then on the validation cohort [(B), n = 73]. The area under the ROC curve (AUC) and classification accuracy (ACC) are provided in each panel (see Presentation S1 in Supplementary Material for classifier implementation and evaluation details).