Immune cells infiltration in synovium
We first analyzed the composition of 22 immune cells in RA and normal synovial tissues. T cells CD4 memory resting, macrophage M2, mast cell resting are the main infiltrating immune cells (Figure 1A). Compared with normal samples, RA synovial samples contain more B cells memory, T cells CD4 memory activated, macrophage M1 and neutrophils, while T cells CD4 memory resting, T cells regulatory (Tregs), NK cells, mast cell resting are relatively less, p values < 0.01 (Figure 1B). The correlation heatmap showed that the increased expression of B cells memory was positively correlated with the T cells CD4 memory activated, macrophage M1 was negatively correlated with NK cell activated and mast cell resting, neutrophils were positively correlated with T cells CD4 naive, and were negatively correlated with macrophage M2, correlation coefficient > 0.4 (Figure 1C).
Screening of DE-IRGs and enrichment analysis in synovium
In synovial tissue, 8007 up-regulated DEGs and 1741 down-regulated DEGs were found in normal control group and RA patients (Figure 2A). The heat map shows 20 up-regulated genes and 20 down-regulated genes with the most obvious differences (Figure 2B). Through the intersection of DEGs and immune related genes, a total of 467 DE-IRGs were obtained (Figure 2C).
GO enrichment analysis showed that the changes of biological process (BP) of synovial DE-IRGs were mainly concentrated in the cellular response to stimulus and cytokine related immune response (Figure 3A). Cellular components (CC) were concentrated in plasma membranes, and molecular functions (MF) were concentrated in receptor activity and cytokine activity (Figure 3B-C). KEGG pathway analysis showed that NK cell mediated cytotoxicity, T cell receptor signaling pathway, Th17 cell differentiation, B cell receptor signaling pathway and rheumatoid arthritis were the main enrichment pathways (Figure 3D). These results prove the effectiveness of immune enrichment analysis and the importance of immune cells in RA.
Identification of RA molecular subtypes in whole blood
RA is a systemic immune disease, often associated with extra-articular organ involvement, so we used immune enrichment scores based on whole blood gene expression profiles for unsupervised clustering. According to the area under the cumulative distribution function curve and the average consistency evaluation within the cluster group, the consistency is better when the specific cluster number k=3 (Figure 4A-B). 232 RA tissue samples were divided into three subtypes: Cluster 1 (n=81), Cluster 2 (n=80), Cluster 3 (n=71) (Figure 4C). Umap analysis showed that there were differences among the three subtypes, which again proved the reliability of clustering (Figure 4D).
Enrichment analysis and clinical characteristics of different subtypes
GSEA analyzed the differences of gene expression profiles among different subtypes, and the results showed that the function of C1 subtype was enriched in neutrophil related regulatory processes (Figure 5A-B). C2 subtype is closely related to T cells and participates in T cell receptor signaling pathways (Figure 5C-D). C3 subtype is related to dendritic cell activated and participates in a variety of immune signaling pathways such as systemic lupus erythematosus, autoimmune thyroid disease, intestinal immune network (Figure 5E-F).
According to the clinical characteristic data of different samples, we further compared the differences between different subtypes. Rheumatoid factor, anti-cyclic citrullinated peptide antibody and antinuclear antibody of C3 subtype were increased, among which rheumatoid factor was statistically significant (Figure 6A-B). The C-reactive protein (CRP), erythrocyte sedimentation rates (ESR) and matrix metalloproteinase 3 (MMP3) of C1 subtype were the highest, followed by C3, and C2 subtype was the lowest. The differences were statistically significant (Figure 6C). The visual analog score (VAS) of C1 subtype was significantly higher than that of C2 subtype (Figure 6D). There was no significant difference in the number of 28 tenderness and swelling joints (TJC28, SJC28), drug use between subtypes (Figure 6E-F).
Immune cell infiltration of different subtypes in whole blood
We further analyzed the infiltration of different subtypes of immune cells in the whole blood. T cells CD8, T cells CD4 naive and NK cells resting are the main immune cells in whole blood, especially neutrophils (Figure 7A). We found that the expression of T cells CD8 and T cells CD4 naive of C2 subtype was significantly increased. The expression of T cells CD4 memory activated, T cells gamma delta was significantly higher than that of C1 subtype. The neutrophil expression of C1 subtype was significantly higher than that of the other two subtypes (Figure 7B). The correlation heat map showed that CRP, ESR and MMP3 were positively correlated with neutrophils and negatively correlated with NK cells resting (Figure 7C).
Screening and validation of immunodiagnostic markers
In order to screen hub genes of different subtypes, a scale-free network was constructed, and the soft threshold was set to 30 (Figure 8A-B). Based on the weighted gene co-expression correlation, 10 modules were obtained after hierarchical cluster analysis (Figure 8C-D). Among all modules, brown module was significantly positively correlated with C1 subtype, red and grey module was significantly positively correlated with C2 subtype, lightcyan module was significantly positively correlated with C3 subtype, r >0.5 (Figure 8E).
The diagnostic markers of different subtypes were obtained by overlapping hub genes of different subtype related modules in whole blood with DE-IRGs in synovium. There are five immune hub genes in C1 subtype, four in C2 subtype and two in C3 subtype (Figure 9A). Among them, IFNGR1, NAMPT, PPP3CA are most related to neutrophils, IL21R, LCK, PRKCQ, TRAC are most related to T cells, and IFITM1, TAP1 are most related to dendritic cells activated (Figure 9C-H). In all 11 immune hub genes, the AUC value of 6 genes is greater than 0.75 (Figure 9C-H).
Based on the correlation between immune cells and AUC values, we determined that IFNGR1 was immunodiagnostic markers of C1 subtype, TRAC was diagnostic marker of C2 subtype, and IFITM1 was diagnostic marker of C3 subtype. These three immune diagnostic markers showed good efficacy in synovium, with significant differences, p<0.0001 (Figure 10A-C). They also have diagnostic value in serum, but the difference is not as significant as that in synovium (Figure 10D-F).