Gene expression profiling at birth characterizing the preterm infant with early onset infection

Hilgendorff, Anne; Windhorst, Anita; Klein, Manuel; Tchatalbachev, Svetlin; Windemuth-Kieselbach, Christine; Kreuder, Joachim; Heckmann, Matthias; Gkatzoflia, Anna; Ehrhardt, Harald; Mysliwietz, Josef; Maier, Michael; Izar, Benjamin; Billion, Andre; Gortner, Ludwig; Chakraborty, Trinad und Hossain, Hamid (2017): Gene expression profiling at birth characterizing the preterm infant with early onset infection. In: Journal of Molecular Medicine-Jmm, Bd. 95, Nr. 2: S. 169-180

Abstract

Early onset infection (EOI) in preterm infants < 32 weeks gestational age (GA) is associated with a high mortality rate and the development of severe acute and long-term complications. The pathophysiology of EOI is not fully understood and clinical and laboratory signs of early onset infections in this patient cohort are often not conclusive. Thus, the aim of this study was to identify signatures characterizing preterm infants with EOI by using genome-wide gene expression (GWGE) analyses from umbilical arterial blood of preterm infants. This prospective cohort study was conducted in preterm infants < 32 weeks GA. GWGE analyses using CodeLink human microarrays were performed from umbilical arterial blood of preterm infants with and without EOI. GWGE analyses revealed differential expression of 292 genes in preterm infants with EOI as compared to infants without EOI. Infants with EOI could be further differentiated into two subclasses and were distinguished by the magnitude of the expression of genes involved in both neutrophil and T cell activation. A hallmark activity for both subclasses of EOI was a common suppression of genes involved in natural killer (NK) cell function, which was independent from NK cell numbers. Significant results were recapitulated in an independent validation cohort. Gene expression profiling may enable early and more precise diagnosis of EOI in preterm infants.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 0946-2716
• Sprache: Englisch