AUTHOR=Shen Zheng , Zhu Weifen , Du Lizhong TITLE=Analysis of Gene Expression Profiles in the Liver of Rats With Intrauterine Growth Retardation JOURNAL=Frontiers in Pediatrics VOLUME=Volume 10 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2022.801544 DOI=10.3389/fped.2022.801544 ISSN=2296-2360 ABSTRACT=Background

Intrauterine growth restriction (IUGR) is highly associated with fetal as well as neonatal morbidity, mortality, and an increased risk metabolic disease development later in life. The mechanism involved in the increased risk has not been established. We compared differentially expressed genes between the liver of appropriate for gestational age (AGA) and IUGR rat models and identified their effects on molecular pathways involved in the metabolic syndrome.

Methods

We extracted RNA from the liver of IUGR and AGA rats and profiled gene expression by microarray analysis. GO function and KEGG pathway enrichment analyses were conducted using the Search Tool for the Retrieval of Interacting Genes database. Then, the Cytoscape software was used to visualize regulatory interaction networks of IUGR-related genes. The results were further verified via quantitative reverse transcriptase PCR analysis.

Results

In this study, 815 genes were found to be markedly differentially expressed (fold-change >1.5, p < 0.05) between IUGR and AGA, with 347 genes elevated and 468 suppressed in IUGR, relative to AGA. Enrichment and protein–protein interaction network analyses of target genes revealed that core genes including Ppargc1a, Prkaa2, Slc2a1, Rxrg, and Gcgr, and pathways, including the PPAR signaling pathway and FoxO signaling pathway, had a potential association with metabolic syndrome development in IUGR. We also confirmed that at the mRNA level, five genes involved in glycometabolism were differentially expressed between IUGR and AGA.

Conclusion

Our findings elucidate on differential gene expression profiles in IUGR and AGA. Moreover, they elucidate on the pathogenesis of IUGR-associated metabolic syndromes. The suggested candidates are potential biomarkers and eventually intended to treat them appropriately.