Maternal smoking-induced lung injuries in dams and offspring via inflammatory cytokines

Xiaotong Ji; Huifeng Yue; Guangke Li; Nan Sang

doi:10.1016/j.envint.2021.106618

Maternal smoking-induced lung injuries in dams and offspring via inflammatory cytokines

Environ Int. 2021 Nov:156:106618. doi: 10.1016/j.envint.2021.106618. Epub 2021 May 11.

Authors

Xiaotong Ji¹, Huifeng Yue², Guangke Li³, Nan Sang³

Affiliations

¹ Department of Environmental Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China.
² College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China. Electronic address: yuehuifeng@sxu.edu.cn.
³ College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China.

PMID: 33989842
DOI: 10.1016/j.envint.2021.106618

Abstract

Maternal smoking during pregnancy can induce permanent changes in neonatal inflammation, which will result in lifelong implications. An original study of data from GSE96978, composed of 2 subseries (GSE96976 and GSE96977), investigated genome-wide changes in ELT cells, the lungs of mouse dams and their juvenile offspring and focused on finding an in vitro alternative as a human tissue-based replacement for the use of animals. Therefore, the study only analyzed the similarities of GO terms between ELT cells and dams. However, the relationship between differentially expressed genes (DEGs) in dams and offspring was not investigated. The present study aimed to identify the key molecules involved in maternal smoking-induced dam and offspring lung injuries. Data from GSE96977 were downloaded from Gene Expression Omnibus (GEO) data sets. In our study, differentially expressed genes (DEGs) in dams and offspring were reanalyzed using the limma package. The results of Gene Set Enrichment Analysis (GSEA) showed that the DEGs in the lungs of dams were significantly enriched in immune-related functions and those in the lungs of offspring were enriched in cell growth. Furthermore, a total of 90 DEGs shared in the dam and offspring datasets were screened out. In addition, most of these DEGs were enriched in cytokine and cytokine receptor interaction KEGG pathways. Furthermore, protein-protein interaction (PPI) network analysis screened out 4 core genes in cluster 1. In addition, the miRNAs related to these core genes were predicted, and mmu-miR-1903 was screened out. Taken together, our data indicate that inflammatory responses may play an important role in maternal smoking induced lung injuries in dams and offspring. Furthermore, mmu-miR-1903 is a potential epigenetic biomarker of lung inflammation in the offspring of dams who smoked during pregnancy. In conclusion, by screening shared differential genes, we only need to detect maternal genes to predict maternal smoking-induced lung injuries in offspring.

Keywords: Bioinformatic analysis; Biomarkers; Lung injuries; Maternal smoking; Offspring.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Cytokines / genetics
Female
Lung Injury* / chemically induced
Mice
MicroRNAs* / metabolism
Pregnancy
Protein Interaction Maps
Smoking / adverse effects

Substances

Cytokines
MicroRNAs