Early-onset Neonatal Pneumococcal Sepsis: A Fatal Case Report and Brief Literature Review

Fulminant early-onset neonatal sepsis due to Streptococcus pneumoniae: Case report and review of the literature

Streptococcus pneumoniae is a rare cause of neonatal sepsis, and it is associated with significant morbidity and a very high fatality rate. The infection is usually acquired intrapartum, from the colonization of the maternal genital tract. Most affected neonates have an early-onset presentation of symptoms, usually within the first 48 hours after birth, which is similar to other causes of neonatal sepsis such as Streptococcus Agalactiae or Escherichia Coli. However, the virulence seems to be higher for Streptococcus pneumoniae, which has in addition a higher infant invasion/ maternal colonization ratio than Streptococcus Agalactiae. Pneumococcal vaccination has not resulted in a significant decline of neonatal cases. Many cases included ours, involved serotypes not present in the vaccine. Other strategies to protect these infants are necessary. We describe a late preterm infant with a fatal, early-onset sepsis caused by Streptococcus Pneumoniae serotype 28 A. Maternal vaginal culture grew the same bacteria.

Potential Genes and Pathways of Neonatal Sepsis Based on Functional Gene Set Enrichment Analyses

BACKGROUND

Neonatal sepsis (NS) is considered as the most common cause of neonatal deaths that newborns suffer from. Although numerous studies focus on gene biomarkers of NS, the predictive value of the gene biomarkers is low. NS pathogenesis is still needed to be investigated.

METHODS

After data preprocessing, we used KEGG enrichment method to identify the differentially expressed pathways between NS and normal controls. Then, functional principal component analysis (FPCA) was adopted to calculate gene values in NS. In order to further study the key signaling pathway of the NS, elastic-net regression model, Mann-Whitney U test, and coexpression network were used to estimate the weights of signaling pathway and hub genes.

RESULTS

A total of 115 different pathways between NS and controls were first identified. FPCA made full use of time-series gene expression information and estimated F values of genes in the different pathways. The top 1000 genes were considered as the different genes and were further analyzed by elastic-net regression and MWU test. There were 7 key signaling pathways between the NS and controls, according to different sources. Among those genes involved in key pathways, 7 hub genes, PIK3CA, TGFBR2, CDKN1B, KRAS, E2F3, TRAF6, and CHUK, were determined based on the coexpression network. Most of them were cancer-related genes. PIK3CA was considered as the common marker, which is highly expressed in the lymphocyte group. Little was known about the correlation of PIK3CA with NS, which gives us a new enlightenment for NS study.

CONCLUSION

This research might provide the perspective information to explore the potential novel genes and pathways as NS therapy targets.