Transcriptomic profiles of multiple organ dysfunction syndrome phenotypes in pediatric critical influenza

BackgroundInfluenza virus is responsible for a large global burden of disease, especially in children. Multiple Organ Dysfunction Syndrome (MODS) is a life-threatening and fatal complication of severe influenza infection.MethodsWe measured RNA expression of 469 biologically plausible candidate genes in children admitted to North American pediatric intensive care units with severe influenza virus infection with and without MODS. Whole blood samples from 191 influenza-infected children (median age 6.4 years, IQR: 2.2, 11) were collected a median of 27 hours following admission; for 45 children a second blood sample was collected approximately seven days later. Extracted RNA was hybridized to NanoString mRNA probes, counts normalized, and analyzed using linear models controlling for age and bacterial co-infections (FDR q<0.05).ResultsComparing pediatric samples collected near admission, children with Prolonged MODS for ≥7 days (n=38; 9 deaths) had significant upregulation of nine mRNA transcripts associated with neutrophil degranulation (RETN, TCN1, OLFM4, MMP8, LCN2, BPI, LTF, S100A12, GUSB) compared to those who recovered more rapidly from MODS (n=27). These neutrophil transcripts present in early samples predicted Prolonged MODS or death when compared to patients who recovered, however in paired longitudinal samples, they were not differentially expressed over time. Instead, five genes involved in protein metabolism and/or adaptive immunity signaling pathways (RPL3, MRPL3, HLA-DMB, EEF1G, CD8A) were associated with MODS recovery within a week.ConclusionThus, early increased expression of neutrophil degranulation genes indicated worse clinical outcomes in children with influenza infection, consistent with reports in adult cohorts with influenza, sepsis, and acute respiratory distress syndrome

Cytokines and signaling molecules predict clinical outcomes in sepsis.

Inflammatory response during sepsis is incompletely understood due to small sample sizes and variable timing of measurements following the onset of symptoms. The vasopressin in septic shock trial (VASST) compared the addition of vasopressin to norepinephrine alone in patients with septic shock. During this study plasma was collected and 39 cytokines measured in a 363 patients at both baseline (before treatment) and 24 hours. Clinical features relating to both underlying health and the acute organ dysfunction induced by the severe infection were collected during the first 28 days of admission.Cluster analysis of cytokines identifies subgroups of patients at differing risk of death and organ failure.Circulating cytokines and other signaling molecules were measured using a Luminex multi-bead analyte detection system. Hierarchical clustering was performed on plasma values to create patient subgroups. Enrichment analysis identified clinical outcomes significantly different according to these chemically defined patient subgroups. Logistic regression was performed to assess the importance of cytokines for predicting patient subgroups.Plasma levels at baseline produced three subgroups of patients, while 24 hour levels produced two subgroups. Using baseline cytokine data, one subgroup of 47 patients showed a high level of enrichment for severe septic shock, coagulopathy, renal failure, and risk of death. Using data at 24 hours, a larger subgroup of 81 patients that largely encompassed the 47 baseline subgroup patients had a similar enrichment profile. Measurement of two cytokines, IL2 and CSF2 and their product were sufficient to classify patients into these subgroups that defined clinical risks.A distinct pattern of cytokine levels measured early in the course of sepsis predicts disease outcome. Subpopulations of patients have differing clinical outcomes that can be predicted accurately from small numbers of cytokines. Design of clinical trials and interventions may benefit from consideration of cytokine levels

Logistic regression results for predicting patient subgroup with cytokine product models.

<p>Coefficients are reported with standard errors and p-values for coefficients being non-zero in round brackets.</p

Levels of signaling molecules at 24 hours.

<p>Patient subgrouping, survival and features are indicated on the top colored rows. The <i>24 hr groups</i> are the Low and High subgroups based on 24 hour cytokines. The <i>Baseline groups</i> are the corresponding subgroups the patients are in using baseline data.</p

Cytokine levels at 24

<p>Concentrations of cytokines are shown for those having highest ratio between patient subgroups. Values are median, and interquartile ranges in pM. Ratio is the ratio of medians of High and Low cytokine subgroup values. The p-value is from t-test on log10-transformed cytokine values adjusted for multiple testing. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079207#pone.0079207.s002" target="_blank">Table S2</a> for full list.</p

Patient subgroup transitions.

<p>Numbers of patients found in each combination of subgroups based on baseline cytokines and 24 hr cytokines. Mortality at 28 days is reported and p-value for the difference between the survival curve for the patients transition versus the survival curve of the subgroups based on the baseline and 24 hr cytokines.</p

Survival curves for patients in Low, Medium and High subgroups using cytokines at baseline.

<p>P-values<0.001 for difference in curves between Low and High as well as Medium and High , but not significant between Low and Medium.</p

Features of patients enriched in High subgroup using cytokines at 24 hours.

<p>Enrichments are all significant at p<0.05, adjusted for multiple testing. Comparison was to overall (entire) patient population in the study.</p