Identification of novel candidate indicators for assessing zinc status during pregnancy in mice from microarray data

BACKGROUND: This study aimed to identify potential zinc status indicators and to clarify the mechanisms underlying zinc deficiency-induced organ damage and mortality in mice. METHODS: The dataset GSE97112, including placental tissues of mice fed diets containing normal and low concentrations of zinc, was downloaded and preprocessed. Differentially expressed genes (DEGs) were calculated and identified for zinc deficiency-related gene clusters by using the weighed gene co-expression network analysis (WGCNA) algorithm. The Gene Ontology (GO)-Biological Process (BP) and KEGG pathway of genes in the zinc deficiency-related WGCNA modules were analyzed, and the protein-protein interaction (PPI) network was constructed. In addition, modules of the PPI network were identified, and transcription factors (TFs) and miRNAs regulating DEGs were predicted. Finally, drug-gene interactions were selected. RESULTS: A total of 1055 DEGs containing 586 up- and 469 down-regulated genes were obtained. Three modules based on WGCNA had high correlation with degree of zinc deficiency. Annexin A1 (ANXA1), C-C motif chemokine receptor 3 (CCR3), C-X-C motif chemokine receptor 2 (CXCR2), and interleukin 2 (IL-2) were hub nodes in the PPI network. Three modules in the PPI network were identified, including module 1 associated with olfactory conduction and module 2 associated with inflammatory response. ANXA1, CCR3, and IL-2 were regulated by TFs. In addition, CXCR2, ANXA, and IL-2 were drug targets. CONCLUSION: CXCR2, ANXA1, and CCR3 as well as olfactory receptor-related genes (proteins) may be used as biomarkers to assess zinc status in mice.