In a recent study published in Cell Reports Medicine, researchers performed multi-organ single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) of collagen-induced arthritis (CIA) murine model to evaluate immune-mediated inflammatory disease (IMIDs) alterations by characterizing the genome, organizing the organome, and prioritizing pathways in the multi-organ data.
Many IMID patients do not show adequate response to therapy. Molecular mechanisms, therapeutic targets, and biomarkers of IMIDs must be analyzed in-depth for successful treatment; however, the interplay of several genes complicates analysis. Managing varied organome-wide clinical manifestations warrants further research on the organs affected to dissect the complexity and heterogeneity of the underlying molecular processes.
Studies must investigate whether the immunological changes could be organized into overriding structures, enabling systematic and detailed analyses, and whether the hierarchy could be exploited for prioritizing molecular targets for diagnosis and therapy.
About the study
In the present study, researchers performed single-cell RNA sequencing analysis using a CIA model for developing system-level strategies defining IMID-related structures that could be verified for human IMIDs.
DBA1/J murine animals (n=6.0) with collagen-induced arthritis and control murine animals (n=4.0) were used for the analyses. The team organized the immunological changes into a multi-organ and multi-cellular disease model (MO-MCDM), showing estimated molecular interactions within and between organs. Meta-analyses of human IMIDs were performed, followed by integrated analyses of the multi-organ information from the collagen-induced arthritis murine model and 10.0 human immune-mediated inflammatory diseases.
The team analyzed ten organs, namely, joints, lymph nodes, blood, skin, thymus, lungs, limb muscles, liver, kidney, and spleen, from ≥1.0 severely arthritic mice and healthy control mice. Following quality control, 3,320, 814, 2,230, 4,565, and 1,167 cells were recovered from the spleen, lungs, joints, muscles, and skin, respectively. To assess organ inflammation, a histological analysis of the organs was performed. Molecular interactions were inferred bioinformatically by linking the differentially-expressed genes (DEGs) in the different cell types with their estimated upstream regulators (URs).
DEGs linked to their estimated URs were the downstream molecular targets. URs estimated to be released in blood were referred to from the human protein atlas. Further, genome-wide association studies (GWAS) enrichment and connective pathway analyses were performed. The effects of anti-tumor necrosis factor (TNF) in treating ulcerative colitis and Crohn’s disease were evaluated.
The scRNA-seq findings of mouse arthritis showed complicated and diverse organome-, genome-, and cellulome-wide changes. However, only the joints exhibited inflammatory signs, including significant leukocytic infiltration in the synovium and cartilage, with synovial hyperplasia and bone destruction. DEGs in joints increased inflammation, whereas DEGs in other organs reduced inflammation. The changes could be switched on and off by pro- or anti-inflammatory URs. A similar, albeit graded, immunological switch was observed for human immunological diseases, and the URs could be exploited for personalized therapies.
The switch system showed the potential to prioritize, diagnose, and treat optimal UR combinations on the IMID, subgroup, and individual levels. The findings were underpinned by UR analysis findings in >600.0 serum samples of systemic lupus erythematosus patients and IMID patients unresponsive to anti-TNF treatment. The immunological changes could be organized into a MO-MCDM in which all organs interacted without evident hierarchy, with 1,966.0 inter-organ interactions identified and regulated by 48 URs.
DEG analysis findings showed 64.0% of genes involved in 428.0 pathways were shared across multiple pathways, with overlap between the Kyoto encyclopedia of genes and genomes (KEGG) and the ingenuity pathway analysis (IPA) pathways. IL-1β levels were elevated in muscles, whereas TNF levels were reduced, and the anti-inflammatory UR tumor-growth factor-beta (TGF-β) was elevated.
Contrastingly, TNF and IL-1β levels were elevated in the joints, but not TGF-β levers. Therefore, the altered UR balance could be considered an off/on switch for inflammation, explaining inflammation occurring exclusively in the joints.
The findings indicated a graded switch system wherein the non-inflamed state was intermediate between the extremes of healthy and inflammatory states. GWAS enrichment was observed in 72.0% of the IMID datasets, with the median odds ratio (OR) for the significant ones being 5.3. The analysis = showed pro-inflammatory pathways such as IL-6, B cell receptor (BCR), and acute phase response pathways, activated in joints and inhibited in muscles and contrasting patterns for the anti-inflammatory pathways such as the peroxisome proliferator-activated receptor (PPAR) pathway.
In muscles, pro-inflammatory URs such as apolipoprotein (Apoe) and TNF were downregulated, whereas anti-inflammatory URs such as TGF-β1 were upregulated. In the non-inflamed sites, pro-inflammatory pathways such as those involved in leukocyte extravasation and natural killer signaling were activated, which could contribute to chronic inflammation, turning the switch on.
For all IMIDs combined, 389 estimated URs were found, with 79.0 URs (median) for each disease, of which eight URs were shared by all IMIDs (except Sjogren’s syndrome), namely, interferon-gamma (IFN-γ), toll-like receptor 3 (TLR-3), androgen receptor (AR), estrogen receptor-beta (ER-β), IL-1α, IL-1β, TNF and Fas.
Overall, the study findings showed that genetic interactions complicate immunological disease management. Integrated analyses of arthritic mice and human IMIDs showed organome-, genome-, and cellulome-wide alterations that could be switched off or on by anti- or pro-inflammatory upstream regulators. Therefore, URs may be targeted to develop personalized therapies for IMIDs.