Peripheral Blood Gene Expression Profile of Infants with Atopic Dermatitis

Abstract

To enhance the understanding of molecular mechanisms and mine previously unidentified biomarkers of pediatric atopic dermatitis, PBMC gene expression profiles were generated by RNA sequencing in infants with atopic dermatitis and age-matched controls. A total of 178 significantly differentially expressed genes (DEGs) (115 upregulations and 63 downregulations) were seen, compared with those in healthy controls. The DEGs identified included IL1β, TNF, TREM1, IL18R1, and IL18RAP. DEGs were validated by real-time RT- qPCR in a larger number of samples from PBMCs of infants with atopic dermatitis aged <12 months. Using the DAVID (Database for Annotation, Visualization and Integrated Discovery) database, functional and pathway enrichment analyses of DEGs were performed. Gene ontology enrichment analysis showed that DEGs were associated with immune responses, inflammatory responses, regulation of immune responses, and platelet activation. Pathway analysis indicated that DEGs were enriched in cytokine‒cytokine receptor interaction, immunoregulatory interactions between lymphoid and nonlymphoid cells, hematopoietic cell lineage, phosphoinositide 3-kinase‒protein kinase B signaling pathway, NK cell‒mediated cytotoxicity, and platelet activation. Furthermore, the protein‒protein interaction network was predicted using the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database and visualized with Cytoscape software. Finally, on the basis of the protein‒protein interaction network, 18 hub genes were selected, and two significant modules were obtained. In conclusion, this study sheds light on the molecular mechanisms of pediatric atopic dermatitis and may provide diagnostic biomarkers and therapeutic targets.

Keywords: AD, atopic dermatitis; BP, biological process; CC, cellular component; DEG, differentially expressed gene; GO, gene ontology; MF, molecular function; PIP, protein‒protein interaction; RNA-seq, RNA sequencing.

Figure 1

The overall framework of study design. AD, atopic dermatitis; QC, quality control.

Figure 2

Validation of RNA-sequencing data by RT-qPCR. RT-qPCR analyses for five genes from the top 10 differentially expressed genes identified by high-throughput RNA sequencing: (a) IL18RAP, (b) IL1β, (c) TNF, (d) TREM1, and (e) EGR3 in children with AD (n = 27) and healthy controls (n = 17). Fold change was calculated by 2-ΔΔCT method. The normalized expression data were log₂ transformed and shown as the means ± SD. Significant difference among groups was calculated by unpaired t test with Welch’s correction for normal distribution or with Mann‒Whitney rank-sum test for non-normal distribution data. ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001

Figure 3

Effect of infant’s age on the expression of differentially expressed genes in infants with AD. RT-qPCR analyses for five genes from the top 10 differentially expressed genes identified by high-throughput RNA sequencing: (a) IL18RAP, (b) IL1β, (c) TNF, (d) TREM1, and (e) EGR3 in children with AD (n = 27) and healthy controls (n = 17) after stratifying the dataset by age (0‒6 months and 7‒12 months). Fold change was calculated by 2-ΔΔCT method. The normalized expression data were log₂ transformed and shown as the means ± SD. Significant difference among groups was calculated by unpaired t test with Welch’s correction for normal distribution or with Mann‒Whitney rank-sum test for non-normal distribution data. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001. AD, atopic dermatitis; HC, healthy control.

Figure 4

GO enrichment and pathway analysis of differentially expressed genes. (a) The top 20 enriched GO terms; the x-axis represents gene counts, and the y-axis represents GO terms. (b) Selected KEGG pathways; the x-axis represents gene counts, and the y-axis represents KEGG pathway names. Akt, protein kinase B; ECM, extracellular matrix; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PI3K, phosphoinositide 3-kinase.

Figure 5

PPI networks. (a) PPI network with 82 nodes. In the network, nodes represent proteins, and lines (edges) represent the interactions between proteins. Red nodes represent the hub nodes with a large number of neighbors (≥8). (b) A first significant module with 12 nodes identified by MCODE. (c) A second significant module with 12 nodes identified by MCODE. MCODE, Molecular Complex Detection; PPI, protein‒protein interaction.