Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort-Reference-Cited by-同舟云学术

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

Published:2023-12-06 Issue: Volume: Page:
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Author:

Atreya ¹,Huang BS Min²,Moore Andrew R.³,Zheng Hong⁴,Hasin-Brumshtein Yehudit⁵,Fitzgerald ⁶,Weiss Scott L.⁷,Cvijanovich Natalie Z.⁸,Bigham Michael T.⁹,Jain Parag N.¹⁰,Schwarz Adam J.¹¹,Lutfi Riad¹²,Nowak Jeffrey¹³,Thomas Neal J.¹⁴,Quasney Michael¹⁵,Dahmer Mary K.¹⁵,Baines Torrey¹⁶,Haileselassie Bereketeab¹⁷,Lautz Andrew J.¹,Stanski Natalja L.¹,Standage Stephen W.¹,Kaplan MD Jennifer M.¹,Zingarelli ¹,Sweeney ¹⁸,Khatri Purvesh⁴,Sanchez-Pinto ¹⁹,Kamaleswaran Rishikesan²⁰

Affiliation:

1. Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA

2. Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA.

3. Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA,

4. Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA. Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, 94305, CA.

5. Inflammatix, Sunnyvale, CA, 94085, USA.

6. Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA.

7. Nemours Children’s Health, Wilmington, DE, 19803, USA

8. UCSF Benioff Children’s Hospital Oakland, Oakland, CA, 94609, USA.

9. Akron Children’s Hospital, Akron, OH, 44308, USA.

10. Texas Children’s Hospital, Baylor College of Medicine, Houston, TX, 77030, USA.

11. Children’s Hospital of Orange County, Orange, CA, 92868, USA.

12. Riley Hospital for Children, Indianapolis, IN, 46202, USA.

13. Children’s Hospital and Clinics of Minnesota, Minneapolis, MN, 55404, USA.

14. Penn State Hershey Children’s Hospital, Hershey, PA, 17033, USA.

15. C.S Mott Children’s Hospital, University of Michigan, Ann Arbor, MI, 48109, USA.

16. University of Florida Health Shands Children’s Hospital, Gainesville, FL, 32610, USA.

17. Lucile Packard Children’s Hospital Stanford, Palo Alto, CA, 94304, USA.

18. Inflammatix, Sunnyvale, CA, 94085, USA

19. Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA. Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA.

20. Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, 30322, GA, USA. Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, 30322, GA, USA.

Abstract

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.

Funder

National Institute of General Medical Sciences

Publisher

Research Square Platform LLC

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