A Gene Modular Approach to a Temporal Meningococcal Septic Shock Transcriptome, Enabling Clinical Phenotype Genotype Association

Abstract

Meningococcal Septic Shock (MSS) is a life-threatening condition, especially in Infants. Acutely, critical care support to physiologically impact disease progression is an imperative. Exploring the clinical relationship according to temporal microarray data could aid in tracking MSS pathogenesis during this critical period. For the first time, clinical-phenotype gene-expression association studies using Weighted Gene Co Expression Network analysis (WGCNA) was completed on 5 children admitted to the Paediatric Intensive Care Unit (PICU). Then using WGCNA, 18 gene modular clusters were identified. A gene list was generated for each module that was significantly associated with clinical traits. Each gene list underwent gene enrichment analysis. The modules associated with Pediatric Logistic Organ Dysfunction (PELOD) score at 0, 24, and 48 hours showed a changing pattern of enriched pathways related to nuclear (p < 2e-08), cytoplasmic (p < 4e-05) and then extracellular gene regulation (p < 7e-17) for PELOD 0, 24 and 48 hours, respectively. Though WGCNA has been applied to sepsis datasets by other researchers, this study demonstrates association of important temporal clinical characteristics, i.e. PELOD score, with changing cellular processes. This study is an important step in design a gene modular approach with pathophysiological insights, potentially aiding future clinical research design and therapeutic approaches.