Identification of Inflammatory Genes, Pathways, and Immune Cells in Necrotizing Enterocolitis of Preterm Infant by Bioinformatics Approaches

Bioinformatics in Neonatal/Pediatric Medicine-A Literature Review

Bioinformatics is a scientific field that uses computer technology to gather, store, analyze, and share biological data and information. DNA sequences of genes or entire genomes, protein amino acid sequences, nucleic acid, and protein-nucleic acid complex structures are examples of traditional bioinformatics data. Moreover, proteomics, the distribution of proteins in cells, interactomics, the patterns of interactions between proteins and nucleic acids, and metabolomics, the types and patterns of small-molecule transformations by the biochemical pathways in cells, are further data streams. Currently, the objectives of bioinformatics are integrative, focusing on how various data combinations might be utilized to comprehend organisms and diseases. Bioinformatic techniques have become popular as novel instruments for examining the fundamental mechanisms behind neonatal diseases. In the first few weeks of newborn life, these methods can be utilized in conjunction with clinical data to identify the most vulnerable neonates and to gain a better understanding of certain mortalities, including respiratory distress, bronchopulmonary dysplasia, sepsis, or inborn errors of metabolism. In the current study, we performed a literature review to summarize the current application of bioinformatics in neonatal medicine. Our aim was to provide evidence that could supply novel insights into the underlying mechanism of neonatal pathophysiology and could be used as an early diagnostic tool in neonatal care.

A potential pathogenic hypoxia-related gene HK2 in necrotizing enterocolitis (NEC) of newborns

Background

Necrotizing enterocolitis (NEC) is a disastrous gastrointestinal disease of newborns, and the mortality rate of infants with NEC is approximately 20%-30%. The exploration of pathogenic targets of NEC will be conducive to timely diagnosis of NEC.

Methods

The whole transcriptome RNA sequencing was performed on NEC samples to reveal the expression of lncRNAs, circRNAs, miRNAs and mRNAs. Using differential expression analysis, cross analysis, target prediction, enrichment analysis, the pathogenic ceRNA network and target was found.

Results

Preliminarily, 281 DEmRNAs, 21 DEmiRNAs, 253 DElncRNAs and 207 DEcircRNAs were identified in NEC samples compared with controls. After target prediction and cross analyses, a key ceRNA regulatory network was built including 2 lncRNAs, 4 circRNAs, 2 miRNAs and 20 mRNAs. These 20 mRNAs were significantly enriched in many carbohydrate metabolism related pathways. After cross analysis of hypoxia-, carbohydrate metabolism-related genes, and 20 core genes, one gene HK2 was finally obtained. Dendritic cells activated were significantly differentially infiltrated and negatively correlated with HK2 expression in NEC samples.

Conclusions

The promising pathogenic hypoxia-related gene HK2 has been firstly identified in NEC, which might also involve in the carbohydrate metabolism in NEC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03664-w.