Pathway cross-talk network analysis identifies critical pathways in neonatal sepsis

Genetic Diseases and Invasive Infections in Infants 100 Days or Younger

BACKGROUND

Understanding the association of genetic diseases with invasive infections in neonates or infants is important, given the clinical and public health implications of genetic diseases.

METHODS

We conducted a retrospective case-control study over a 5-year period to investigate the association between genetic diseases and invasive infections in neonates or infants. The case group included 56 patients with laboratory-confirmed invasive infections and a genetic etiology identified by exome sequencing. Another 155 patients without a genetic etiology were selected as controls from the same pool of patients.

RESULTS

An overview of genetic diseases that predispose patients to develop invasive infections were outlined. We identified 7 independent predictors for genetic conditions, including prenatal findings [adjusted odds ratio (aOR), 38.44; 95% confidence interval (CI): 3.94-374.92], neonatal intensive care unit admission (aOR, 46.87; 95% CI: 6.30-348.93), invasive ventilation (aOR, 6.66; 95% CI: 3.07-14.46), bacterial infections (aOR, 0.21; 95% CI: 0.06-0.69), fever (aOR, 0.15; 95% CI: 0.08-0.30), anemia (aOR, 6.64; 95% CI: 3.02-14.59) and neutrophilia (aOR, 0.98; 95% CI: 0.96-0.99). The area under the curve for the predictive model was 0.921 (95% CI: 0.876-0.954). We also found that a genetic etiology [hazard ratio (HR), 7.25; 95% CI: 1.71-30.81], neurological manifestations (HR, 3.56; 95% CI: 1.29-9.88) and septic shock (HR, 13.83; 95% CI: 3.18-60.10) were associated with severe outcomes.

CONCLUSIONS

Our study established predictive variables and risk factors for an underlying genetic etiology and its mortality in neonates or infants with invasive infections. These findings could lead to risk-directed screening and treatment strategies, which may improve patient outcomes.

Identification of Potential Biomarkers in Neonatal Sepsis by Establishing a Competitive Endogenous RNA Network

BACKGROUND

Neonatal sepsis is a serious and difficult-to-diagnose systemic infectious disease occurring during the neonatal period.

OBJECTIVE

This study aimed to identify potential biomarkers of neonatal sepsis and explore its underlying mechanisms.

METHODS

We downloaded the neonatal sepsis-related gene profile GSE25504 from the NCBI Gene Expression Omnibus (GEO) database. The differentially expressed RNAs (DERs) were screened and identified using LIMMA. Then, the functions of the DERs were evaluated using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Finally, a competing endogenous RNA (ceRNA) network was constructed and functional analyses were performed.

RESULTS

The initial screening identified 444 differentially expressed (DE)-mRNAs and 45 DElncRNAs. GO analysis showed that these DE-mRNAs were involved in immune response, defense response, and positive regulation of immune system process. KEGG analysis showed that these DE-mRNAs were enriched in 30 activated pathways and 6 suppressed pathways, and those with the highest scores were the IL-17 signaling pathway and ribosome. Next, 722 miRNAs associated with the identified lncRNAs were predicted using miRWalk. A ceRNA network was constructed that included 6 lncRNAs, 11 mRNAs, and 55 miRNAs. In this network, HCP5, LINC00638, XIST and TP53TG1 were hub nodes. Functional analysis of this network identified some essential immune functions, hematopoietic functions, osteoclast differentiation, and primary immunodeficiency as associated with neonatal sepsis.

CONCLUSION

HCP5, LINC00638, TP53TG1, ST20-AS1, and SERPINB9P1 may be potential biomarkers of neonatal sepsis and may be useful for rapid diagnosis; the biological process of the immune response was related to neonatal sepsis.