Browsing by Author "Kaplan, Jennifer M."

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    Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort
    (Research Square, 2023-12-06) 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; Sweeney, Timothy E.; Khatri, Purvesh; Sanchez-Pinto, L. Nelson; Kamaleswaran, Rishikesan; Pediatrics, School of Medicine
    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.
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    Identification and transcriptomic assessment of latent profile pediatric septic shock phenotypes
    (Springer Nature, 2024-07-17) 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; Pediatrics, School of Medicine
    Background: 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. Methods: 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. Results: 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. Conclusions: 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 different facets of the host response, holds promise to inform targeted intervention among those critically ill.