Transcriptomic Profiles in Children With Septic Shock With or Without Immunoparalysis

Identification of CRTH2 as a New PPARγ-Target Gene in T Cells Suggested CRTH2 Dependent Conversion of Th2 Cells as Therapeutic Concept in COVID-19 Infection

Background

COVID-19 is a serious viral infection, which is often associated with a lethal outcome. Therefore, understanding mechanisms, which affect the immune response during SARS-CoV2 infection, are important.

Methods

To address this, we determined the number of T cells in peripheral blood derived from intensive care COVID-19 patients. Based on our previous studies, evaluating PPARγ-dependent T cell apoptosis in sepsis patients, we monitored PPARγ expression. We performed a next generation sequencing approach to identify putative PPARγ-target genes in Jurkat T cells and used a PPARγ transactivation assay in HEK293T cells. Finally, we translated these data to primary T cells derived from healthy donors.

Results

A significantly reduced count of total CD3+ T lymphocytes and the CD4+ and CD8+ subpopulations was observed. Also, the numbers of anti-inflammatory, resolutive Th2 cells and FoxP3-positive regulatory T cells (Treg) were decreased. We observed an augmented PPARγ expression in CD4+ T cells of intensive care COVID-19 patients. Adapted from a next generation sequencing approach in Jurkat T cells, we found the chemoattractant receptor-homologous molecule expressed on T helper type 2 cells (CRTH2) as one gene regulated by PPARγ in T cells. This Th2 marker is a receptor for prostaglandin D and its metabolic degradation product 15-deoxy-∆12,14-prostaglandin J2 (15d-PGJ2), an established endogenous PPARγ agonist. In line, we observed an increased PPARγ transactivation in response to 15d-PGJ2 treatment in HEK293T cells overexpressing CRTH2. Translating these data to primary T cells, we found that Th2 differentiation was associated with an increased expression of CRTH2. Interestingly, these CRTH2+ T cells were prone to apoptosis.

Conclusion

These mechanistic data suggest an involvement of PPARγ in Th2 differentiation and T cell depletion in COVID-19 patients.

Risk assessment with gene expression markers in sepsis development

Infection is a commonplace, usually self-limiting, condition but can lead to sepsis, a severe life-threatening dysregulated host response. We investigate the individual phenotypic predisposition to developing uncomplicated infection or sepsis in a large cohort of non-infected patients undergoing major elective surgery. Whole-blood RNA sequencing analysis was performed on preoperative samples from 267 patients. These patients developed postoperative infection with (n = 77) or without (n = 49) sepsis, developed non-infectious systemic inflammatory response (n = 31), or had an uncomplicated postoperative course (n = 110). Machine learning classification models built on preoperative transcriptomic signatures predict postoperative outcomes including sepsis with an area under the curve of up to 0.910 (mean 0.855) and sensitivity/specificity up to 0.767/0.804 (mean 0.746/0.769). Our models, confirmed by quantitative reverse-transcription PCR (RT-qPCR), potentially offer a risk prediction tool for the development of postoperative sepsis with implications for patient management. They identify an individual predisposition to developing sepsis that warrants further exploration to better understand the underlying pathophysiology.

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness

BACKGROUND

Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification of genes associated with a persistent MODS trajectory may shed light on underlying biology and allow for accurate prediction of those at-risk.

METHODS

Secondary analyses of publicly available gene-expression datasets. Supervised machine learning (ML) was used to identify a parsimonious set of genes associated with a persistent MODS trajectory in a training set of pediatric septic shock. We optimized model parameters and tested risk-prediction capabilities in independent validation and test datasets, respectively. We compared model performance relative to an established gene-set predictive of sepsis mortality.

FINDINGS

Patients with a persistent MODS trajectory had 568 differentially expressed genes and characterized by a dysregulated innate immune response. Supervised ML identified 111 genes associated with the outcome of interest on repeated cross-validation, with an AUROC of 0.87 (95% CI: 0.85-0.88) in the training set. The optimized model, limited to 20 genes, achieved AUROCs ranging from 0.74 to 0.79 in the validation and test sets to predict those with persistent MODS, regardless of host age and cause of organ dysfunction. Our classifier demonstrated reproducibility in identifying those with persistent MODS in comparison with a published gene-set predictive of sepsis mortality.

INTERPRETATION

We demonstrate the utility of supervised ML driven identification of the genes associated with persistent MODS. Pending validation in enriched cohorts with a high burden of organ dysfunction, such an approach may inform targeted delivery of interventions among at-risk patients.

FUNDING

H.R.W.'s NIHR35GM126943 award supported the work detailed in this manuscript. Upon his death, the award was transferred to M.N.A. M.R.A., N.S.P, and R.K were supported by NIHR21GM151703. R.K. was supported by R01GM139967.

Whole blood transcriptomics identifies subclasses of pediatric septic shock

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.

Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock

Background

Sepsis is a highly heterogeneous syndrome, that 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 29 March 2012.

Immunoparalysis in critically ill children

Immunoparalysis is associated with poorer outcomes in the paediatric intensive care unit (PICU) setting. We aimed to determine the group of patients with higher chances of immunoparalysis and correlate this status with increased risks of nosocomial infection and adverse clinical parameters. We conducted an exploratory study with prospective data collection in a university-affiliated tertiary medical, surgical, and cardiac PICU. Fifteen patients with multiple organ dysfunction syndrome were included over a period of 6 months. Monocyte's human leucocyte antigen (HLA)-DR expression and tumour necrosis factor (TNF)-α and interleukin (IL)-6 production were measured by flow-cytometry at three time points (T1 = 1-2 days; T2 = 3-5 days; T3 = 6-8 days). Using the paediatric logistic organ dysfunction-2 score to assess initial disease severity, we established the optimal cut-off values of the evaluated parameters to identify the subset of patients with a higher probability of immunoparalysis. A comparative analysis was performed between them. Sixty per cent were males; the median age was 4.1 years. Considering the presence of two criteria in T1 (classical monocytes mean fluorescence intensity [MFI] for HLA-DR ≤ 1758.5, area under the curve (AUC) = 0.775; and frequency of monocytes producing IL-6 ≤ 68.5%, AUC = 0.905) or in T3 (classical monocytes MFI of HLA-DR ≤ 2587.5, AUC = 0.675; and frequency of monocytes producing TNF-α ≤ 93.5%, AUC = 0.833), a variable to define immunoparalysis was obtained (100% sensitivity, 81.5% specificity). Forty per cent of patients were assigned to the immunoparalysis group. In this: a higher frequency of nosocomial infection (p = 0.011), vasoactive inotropic score (p = 0.014) and length of hospital stay (p = 0.036) was observed. In the subgroup with the diagnosis of sepsis/septic shock (n = 5), patients showed higher percentages of non-classical monocytes (p = 0.004). No mortality was recorded. A reduction in classical monocytes HLA-DR expression with lower frequencies of monocytes producing TNF-α and IL-6 during the first week of critical illness, appears to be a good marker of immunoparalysis; these findings relate to an increased risk of nosocomial infection and deleterious outcomes. The increased frequency of non-classical monocytes in patients with sepsis/septic shock is suggestive of a better prognosis.

Utility of monocyte HLA-DR and rationale for therapeutic GM-CSF in sepsis immunoparalysis

Sepsis, a heterogeneous clinical syndrome, features a systemic inflammatory response to tissue injury or infection, followed by a state of reduced immune responsiveness. Measurable alterations occur in both the innate and adaptive immune systems. Immunoparalysis, an immunosuppressed state, associates with worsened outcomes, including multiple organ dysfunction syndrome, secondary infections, and increased mortality. Multiple immune markers to identify sepsis immunoparalysis have been proposed, and some might offer clinical utility. Sepsis immunoparalysis is characterized by reduced lymphocyte numbers and downregulation of class II human leukocyte antigens (HLA) on innate immune monocytes. Class II HLA proteins present peptide antigens for recognition by and activation of antigen-specific T lymphocytes. One monocyte class II protein, mHLA-DR, can be measured by flow cytometry. Downregulated mHLA-DR indicates reduced monocyte responsiveness, as measured by ex-vivo cytokine production in response to endotoxin stimulation. Our literature survey reveals low mHLA-DR expression on peripheral blood monocytes correlates with increased risks for infection and death. For mHLA-DR, 15,000 antibodies/cell appears clinically acceptable as the lower limit of immunocompetence. Values less than 15,000 antibodies/cell are correlated with sepsis severity; and values at or less than 8000 antibodies/cell are identified as severe immunoparalysis. Several experimental immunotherapies have been evaluated for reversal of sepsis immunoparalysis. In particular, sargramostim, a recombinant human granulocyte-macrophage colony-stimulating factor (rhu GM-CSF), has demonstrated clinical benefit by reducing hospitalization duration and lowering secondary infection risk. Lowered infection risk correlates with increased mHLA-DR expression on peripheral blood monocytes in these patients. Although mHLA-DR has shown promising utility for identifying sepsis immunoparalysis, absence of a standardized, analytically validated method has thus far prevented widespread adoption. A clinically useful approach for patient inclusion and identification of clinically correlated output parameters could address the persistent high unmet medical need for effective targeted therapies in sepsis.