Dataset Information

Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort.

ABSTRACT:

Background

Sepsis poses a grave threat, especially among children, but treatments are limited due to clinical and biological heterogeneity among patients. Thus, there is an urgent need for precise subclassification of patients to guide therapeutic interventions.

Methods

We used clinical, laboratory, and biomarker data from a prospective multi-center pediatric septic shock cohort to derive phenotypes using latent profile analyses. Thereafter, we trained a support vector machine model to assign phenotypes in a hold-out validation set. We tested interactions between phenotypes and common sepsis therapies on clinical outcomes and conducted transcriptomic analyses to better understand the phenotype-specific biology. Finally, we compared whether newly identified phenotypes overlapped with established gene-expression endotypes and tested the utility of an integrated subclassification scheme.

Findings

Among 1,071 patients included, we identified two phenotypes which we named 'inflamed' (19.5%) and an 'uninflamed' phenotype (80.5%). The 'inflamed' phenotype had an over 4-fold risk of 28-day mortality relative to those 'uninflamed'. Transcriptomic analysis revealed overexpression of genes implicated in the innate immune response and suggested an overabundance of developing neutrophils, pro-T/NK cells, and NK cells among those 'inflamed'. There was no significant overlap between endotypes and phenotypes. However, an integrated subclassification scheme demonstrated varying survival probabilities when comparing endophenotypes.

Interpretation

Our research underscores the reproducibility of latent profile analyses to identify clinical and biologically informative pediatric septic shock phenotypes with high prognostic relevance. Pending validation, an integrated subclassification scheme, reflective of the different facets of the host response, holds promise to inform targeted intervention among those critically ill.

SUBMITTER: Atreya MR

PROVIDER: S-EPMC10723552 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort.

Atreya Mihir R MR Huang Min M Moore Andrew R AR Zheng Hong H Hasin-Brumshtein Yehudit Y Fitzgerald Julie C JC Weiss Scott L SL Cvijanovich Natalie Z NZ Bigham Michael T MT Jain Parag N PN Schwarz Adam J AJ Lutfi Riad R Nowak Jeffrey J Thomas Neal J NJ Quasney Michael M Dahmer Mary K MK Baines Torrey T Haileselassie Bereketeab B Lautz Andrew J AJ Stanski Natalja L NL Standage Stephen W SW Kaplan Jennifer M JM Zingarelli Basilia B Sweeney Timothy E TE Khatri Purvesh P Sanchez-Pinto L Nelson LN Kamaleswaran Rishikesan R

Research square 20231206

<h4>Background</h4>Sepsis poses a grave threat, especially among children, but treatments are limited due to clinical and biological heterogeneity among patients. Thus, there is an urgent need for precise subclassification of patients to guide therapeutic interventions.<h4>Methods</h4>We used clinical, laboratory, and biomarker data from a prospective multi-center pediatric septic shock cohort to derive phenotypes using latent profile analyses. Thereafter, we trained a support vector machine mod ...[more]

PMID: 38105983

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Project description:BackgroundSepsis poses a grave threat, especially among children, but treatments are limited owing to heterogeneity among patients. We sought to test the clinical and biological relevance of pediatric septic shock subclasses identified using reproducible approaches.MethodsWe performed latent profile analyses using clinical, laboratory, and biomarker data from a prospective multi-center pediatric septic shock observational cohort to derive phenotypes and trained a support vector machine model to assign phenotypes in an internal validation set. We established the clinical relevance of phenotypes and tested for their interaction with common sepsis treatments on patient outcomes. We conducted transcriptomic analyses to delineate phenotype-specific biology and inferred underlying cell subpopulations. Finally, we compared whether latent profile phenotypes overlapped with established gene-expression endotypes and compared survival among patients based on an integrated subclassification scheme.ResultsAmong 1071 pediatric septic shock patients requiring vasoactive support on day 1 included, we identified two phenotypes which we designated as Phenotype 1 (19.5%) and Phenotype 2 (80.5%). Membership in Phenotype 1 was associated with ~ fourfold adjusted odds of complicated course relative to Phenotype 2. Patients belonging to Phenotype 1 were characterized by relatively higher Angiopoietin-2/Tie-2 ratio, Angiopoietin-2, soluble thrombomodulin (sTM), interleukin 8 (IL-8), and intercellular adhesion molecule 1 (ICAM-1) and lower Tie-2 and Angiopoietin-1 concentrations compared to Phenotype 2. We did not identify significant interactions between phenotypes, common treatments, and clinical outcomes. Transcriptomic analysis revealed overexpression of genes implicated in the innate immune response and driven primarily by developing neutrophils among patients designated as Phenotype 1. There was no statistically significant overlap between established gene-expression endotypes, reflective of the host adaptive response, and the newly derived phenotypes, reflective of the host innate response including microvascular endothelial dysfunction. However, an integrated subclassification scheme demonstrated varying survival probabilities when comparing patient endophenotypes.ConclusionsOur research underscores the reproducibility of latent profile analyses to identify pediatric septic shock phenotypes with high prognostic relevance. Pending validation, an integrated subclassification scheme, reflective of the different facets of the host response, holds promise to inform targeted intervention among those critically ill.

Project description:Background: Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods: Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results: Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the 3 putative subclasses (ANOVA, Bonferonni correction, p < 0.05) identified 6,934 differentially regulated genes. K means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the 3 subclasses. Leave one out cross validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusions: Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes. Expression data from 98 children with septic shock and 32 normal controls were generated using whole blood-derived RNA samples representing the first 24 hours of admission to the pediatric intensive care unit. The controls were used for normalization. Subsequently, we used the expression data to derive expression-based subclasses of patients using discovery oriented expression and statistical filters, followed by unsupervised hierarchical clustering.

Project description:BackgroundSevere innate immune suppression, termed immunoparalysis, is associated with increased risks of nosocomial infection and mortality in children with septic shock. Currently, immunoparalysis cannot be clinically diagnosed in children, and mechanisms remain unclear. Transcriptomic studies identify subsets of septic children with downregulation of genes within adaptive immune pathways, but assays of immune function have not been performed as part of these studies, and little is known about transcriptomic profiles of children with immunoparalysis.MethodsWe performed a nested case-control study to identify differences in RNA expression patterns between children with septic shock with immunoparalysis (defined as lipopolysaccharide (LPS)-induced tumor necrosis factor (TNF)α response < 200 pg/ml) vs those with normal LPS-induced TNFα response. Children were enrolled within 48 hours of the onset of septic shock and divided into two groups based on LPS-induced TNFα response. RNA was extracted from whole blood for RNAseq, differential expression analyses using DESeq2 software, and pathway analyses using Ingenuity Pathway Analysis.Results32 children were included in analyses. Comparing those with immunoparalysis (n =19) to those with normal TNFα response (n = 13), 2,303 transcripts were differentially expressed with absolute value fold change ≥ 1.5 and false discovery rate ≤ 0.05. The majority of downregulated pathways in children with immunoparalysis were pathways that involved interactions between innate and adaptive immune cells necessary for cell-mediated immunity, crosstalk between dendritic cells and natural killer cells, and natural killer cell signaling pathways. Upregulated pathways included those involved in humoral immunity (T helper cell type 2), corticotropin signaling, platelet activation (GP6 signaling), and leukocyte migration and extravasation.ConclusionsOur study suggests that gene expression data might be useful to identify children with immunoparalysis and identifies several key differentially regulated pathways involved in both innate and adaptive immunity. Our ongoing work in this area aims to dissect interactions between innate and adaptive immunity in septic children and to more fully elucidate patient-specific immunologic pathophysiology to guide individualized immunotherapeutic targets.

Project description:Sepsis therapeutics have a poor history of success in clinical trials, due in part to the heterogeneity of enrolled patients. Pharmacometabolomics could differentiate drug response phenotypes and permit a precision medicine approach to sepsis.To use existing serum samples from the phase 1 clinical trial of l-carnitine treatment for severe sepsis to metabolically phenotype l-carnitine responders and nonresponders.Serum samples collected before (T0) and after completion of the infusion (T24, T48) from patients randomized to either l-carnitine (12 g) or placebo for the treatment of vasopressor-dependent septic shock were assayed by untargeted (1)H-nuclear magnetic resonance metabolomics. The normalized, quantified metabolite data sets of l-carnitine- and placebo-treated patients at each time point were compared by analysis of variance with post-hoc testing for multiple comparisons. Pathway analysis was performed to statistically rank metabolic networks.Thirty-eight metabolites were identified in all samples. Concentrations of 3-hydroxybutyrate, acetoacetate, and 3-hydroxyisovalerate were different at T0 and over time in l-carnitine-treated survivors versus nonsurvivors. Pathway analysis of pretreatment metabolites revealed that synthesis and degradation of ketone bodies had the greatest impact in differentiating l-carnitine treatment response. Analysis of all patients based on pretreatment 3-hydroxybutyrate concentration yielded distinct phenotypes. Using the T0 median 3-hydroxybutyrate level (153 ?M), patients were categorized as either high or low ketone. l-Carnitine-treated low-ketone patients had greater use of carnitine as evidenced by lower post-treatment l-carnitine levels. The l-carnitine responders also had faster resolution of vasopressor requirement and a trend toward a greater improvement in mortality at 1 year (P = 0.038) compared with patients with higher 3-hydroxybutyrate.The results of this preliminary study, which were not readily apparent from the parent clinical trial, show a unique metabolite profile of l-carnitine responders and introduce pharmacometabolomics as a viable strategy for informing l-carnitine responsiveness. The approach taken in this study represents a concrete example for the application of precision medicine to sepsis therapeutics that warrants further study.

Project description:OBJECTIVES:Sepsis care is becoming a more common target for hospital performance measurement, but few studies have evaluated the acceptability of sepsis or septic shock mortality as a potential performance measure. In the absence of a gold standard to identify septic shock in claims data, we assessed agreement and stability of hospital mortality performance under different case definitions. DESIGN:Retrospective cohort study. SETTING:U.S. acute care hospitals. PATIENTS:Hospitalized with septic shock at admission, identified by either implicit diagnosis criteria (charges for antibiotics, cultures, and vasopressors) or by explicit International Classification of Diseases, 9th revision, codes. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We used hierarchical logistic regression models to determine hospital risk-standardized mortality rates and hospital performance outliers. We assessed agreement in hospital mortality rankings when septic shock cases were identified by either explicit International Classification of Diseases, 9th revision, codes or implicit diagnosis criteria. Kappa statistics and intraclass correlation coefficients were used to assess agreement in hospital risk-standardized mortality and hospital outlier status, respectively. Fifty-six thousand six-hundred seventy-three patients in 308 hospitals fulfilled at least one case definition for septic shock, whereas 19,136 (33.8%) met both the explicit International Classification of Diseases, 9th revision, and implicit septic shock definition. Hospitals varied widely in risk-standardized septic shock mortality (interquartile range of implicit diagnosis mortality: 25.4-33.5%; International Classification of Diseases, 9th revision, diagnosis: 30.2-38.0%). The median absolute difference in hospital ranking between septic shock cohorts defined by International Classification of Diseases, 9th revision, versus implicit criteria was 37 places (interquartile range, 16-70), with an intraclass correlation coefficient of 0.72, p value of less than 0.001; agreement between case definitions for identification of outlier hospitals was moderate (kappa, 0.44 [95% CI, 0.30-0.58]). CONCLUSIONS:Risk-standardized septic shock mortality rates varied considerably between hospitals, suggesting that septic shock is an important performance target. However, efforts to profile hospital performance were sensitive to septic shock case definitions, suggesting that septic shock mortality is not currently ready for widespread use as a hospital quality measure.

Dataset Information

Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort.

Background

Methods

Findings

Interpretation

Publications

Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort.

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