Identification and transcriptomic assessment of latent profile pediatric septic shock phenotypes

• Published in: Critical care (London, England) England), 2024-07, Vol.28 (1), p.246, Article 246
• Main Authors: Atreya, Mihir R, Huang, Min, Moore, Andrew R, Zheng, Hong, Hasin-Brumshtein, Yehudit, Fitzgerald, Julie C, Weiss, Scott L, Cvijanovich, Natalie Z, Bigham, Michael T, Jain, Parag N, Schwarz, Adam J, Lutfi, Riad, Nowak, Jeffrey, Thomas, Neal J, Quasney, Michael, Dahmer, Mary K, Baines, Torrey, Haileselassie, Bereketeab, Lautz, Andrew J, Stanski, Natalja L, Standage, Stephen W, Kaplan, Jennifer M, Zingarelli, Basilia, Sahay, Rashmi, Zhang, Bin, Sweeney, Timothy E, Khatri, Purvesh, Sanchez-Pinto, L Nelson, Kamaleswaran, Rishikesan
• Format: Article
• Language: English
• Subjects: Adolescent; Biomarkers; Biomarkers - analysis; Care and treatment; Child; Child, Preschool; Clinical outcomes; Cohort Studies; Comorbidity; Datasets; Female; Gene Expression Profiling - methods; Genes; Genotype & phenotype; Humans; Infant; Infection; Interleukins; Male; Medical research; Medicine, Experimental; Mortality; Patients; Pediatrics; Phenotype; Precision medicine; Prospective Studies; Sepsis; Septic shock; Shock, Septic - classification; Shock, Septic - genetics; Shock, Septic - physiopathology; Steroids; Transcriptome - genetics
• ISSN: 1364-8535; 1466-609X; 1466-609X; 1364-8535; 1366-609X
• DOI: 10.1186/s13054-024-05020-z

Sepsis 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. We 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. Among 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. Our 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 diffe