Transcriptomic mortality signature defines high-risk neonatal sepsis endotype.

ABSTRACT:

Introduction

Neonatal sepsis remains a leading cause of global childhood mortality, yet treatment options are limited. Clinical and biological heterogeneity hinders the development of targeted therapies. Gene-expression profiling offers a potential strategy to identify neonatal sepsis subtypes and guide targeted intervention.

Methods

We performed secondary analyses of publicly available gene-expression datasets. Differential gene expression analysis and T-distributed Stochastic Neighbor Embedding (t-SNE) identified biologically relevant patient clusters. Mortality and organ dysfunction were compared across clusters to determine clinical relevance.

Results

We identified three endotypes of neonatal sepsis based on the 100 gene expression mortality signature, distinguish

SUBMITTER: Al Gharaibeh FN 

PROVIDER: S-EPMC12245816 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature