Exploration of Common Genomic Signatures of Systemic Juvenile Rheumatoid Arthritis and Type 1 Diabetes - Scientific Reports

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Characteristic of differentially expressed genes in sJRA and T1D

As shown in Fig. 1, there were 175 up-regulated SDEGs and 245 down-regulated SDEGs in sJRA and T1D. Most of the DEGs are related to extracellular proteins (Fig. 2), and the vast majority of the SDEGs, except 6 of the up-regulated sDEGs and 9 of the down-regulated sDEGs, were extracellular protein-related genes (Supplementary Table S3).

Figure 1

Shared differentially expressed genes in sJRA and T1D.

Figure 2

Relationship of genes of extracellular proteins and differentially expressed genes. *The percentage refers to ratios of genes in the circle to all genes listed.

The shared transcription factors-SDEGs network construction

By comparing the data of HumanTFDB, 13 TFs in the up-regulated SDEGs (ARID3A, LTF, HLX, NFE2, E2F2, ZNF341, ZNF213, CEBPE, E2F8, MTF1, KLF17, THAP3, CREB5), and 40 TFs in the down-regulated SDEGs (ZNF8, ZSCAN25, MAF, ZNF256, PRDM4, ZIK1, AKNA, LYAR, NFATC2, ZBTB44, ZNF621, ZNF571, STAT4, ZNF329, L3MBTL4, ZXDB, RORA, ATMIN, SMARCE1, SMAD7, TRERF1, MYBL1, FOXK2, ZNF600, ZNF26, TSHZ1, BNC2, HOPX, ZNF568, ZFP36L2, RLF, ZNF28, ZNF684, ZBTB16, ZBTB25, NR1D2, ZNF254, ZXDA, RUNX3, PRDM1) were screened. As shown in Fig. 3, among those TFs, RUNX3 has the maximum potential target genes in the SDEGs (TFs-target SDEGs), ARID3A and NFE2 have the second and third most number of TFs-target SDEGs. As shown in the figure, the expression of RUNX3 is downregulated, while ARID3A and NEF2 are upregulated. Among these TFs, ARID3A and NFE2 are mutually target genes, besides, ARID3A is also regulated by RUNX3.

Figure 3

Shared transcription factors-SDEGs network. Triangle transcription factors, Red up-regulated SDEGs, Blue down-regulated shared SDEGs.

The functional analyses of interested gene sets

Functional enrichment analysis of the up- and down-regulated SDEGs is shown in Supplementary Table S4. Up-regulated SDEGs were enriched in 238 GO terms, 62 REAC pathways, and 17 KEGG pathways. They are mainly involved in the cell cycle process, regulation of innate immune response, neutrophil degranulation, as well as several signaling pathways such as JAK-STAT, and PI3K signaling pathways.

The down-regulated SDEGs were only enriched in 154 GO terms, 36 REAC pathways, and 17 KEGG pathways. They are mostly related with adaptive immune system such as T cell activation, T/B cell receptor, Th1, Th2 and Th17 cell differentiation, and function of cytokines such as TGF-beta, interferon type I(IFN- I), interleukin(IL)23, IL12, IL11, IL2, IL3, IL5, etc. Besides, they were also enriched in innate immune system related terms such as natural killer cell function and signalings by M-CSF and GM-CSF.

The terms that up-regulated TFs targeted SDEGs enriched in are mostly included in the terms that up-regulated SDEGs were enriched in. The same in the enrichment results of down-regulated TFs targeted SDEGs. Figure 4a shows the shared terms enriched between up-regulated SDEGs and TFs targeted SDEGs. Still, neutrophil degranulation is closely related, together with cell cycle process. As is shown in Fig. 4b, the shared terms enriched between down-regulated SDEGs and TFs targeted SDEGs also involve CD4 positive T cell activation, Th1, and Th2 cell differentiation, cytokines functions as well as natural killer cell functions. Hormones feature like growth factor beta and steroid hormone stimulus were also involved.

Figure 4

(a) The shared terms enriched between up-regulated SDEGs and TFs targeted SDEGs. (b) The shared terms enriched between down-regulated SDEGs and TFs targeted SDEGs. A: Reactome Gene Sets; B: KEGG Pathway; C: WikiPathways; D: Canonical Pathways; ALPHA: adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains; BETA: immune response-regulating cell surface receptor signaling pathway; THETA: immune response-activating cell surface receptor signaling pathway; DELTA: immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell.

Immune cell infiltration in sJRA and T1D

We performed CIBERSORT analysis to assess infiltrating levels of 22 immune cells in sJRA and T1D samples by R software. Our results showed that both diseases have higher levels of neutrophils, and CD4 naive T cells, while a lower level of CD4 memory resting T cells. Infiltrating levels of monocytes were also significantly different in both diseases compared to control samples. However, sJRA showed a higher level of monocytes (p < 0.05, Figs. 5, 6).

Figure 5

Comparison of 22 immune cells between sJRA samples and control samples.

Figure 6

Comparison of 22 immune cells between T1D samples and control samples.

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