IFN-γand TNF-αdrive aCXCL10+CCL2+ macrophage phenotype expanded in severe COVID-19 and other diseases with tissue inflammation

Abstract

Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Using an integrative strategy, we built a reference by meta-analyzing > 300,000 immune cells from COVID-19 and 5 inflammatory diseases including rheumatoid arthritis (RA), Crohn’s disease (CD), ulcerative colitis (UC), lupus, and interstitial lung disease. Our cross-disease analysis revealed that an FCN1+ inflammatory macrophage state is common to COVID-19 bronchoalveolar lavage samples, RA synovium, CD ileum, and UC colon. We also observed that a CXCL10+ CCL2+ inflammatory macrophage state is abundant in severe COVID-19, inflamed CD and RA, and expresses inflammatory genes such as GBP1, STAT1, and IL1B. We found that the CXCL10+ CCL2+ macrophages are transcriptionally similar to blood-derived macrophages stimulated with TNF-α and IFN-γ ex vivo. Our findings suggest that IFN-γ, alongside TNF-α, might be a key driver of this abundant inflammatory macrophage phenotype in severe COVID-19 and other inflammatory diseases, which may be targeted by existing immunomodulatory therapies.

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases

“…Here we use weighted PCA and weighted Harmony to account for imbalanced datasets and mixed effects Poisson regression to account for the effect of complex interactions between covariates on gene expression. Our analytical approach to decipher tissue-shared and tissue-specific gene expression serves as a template for well-powered and robust analysis of single-cell cluster markers, particularly relevant with the growing number of studies designed to identify shared etiology across tissues and diseases (Nieto et al, 2020; Szabo et al, 2019; Zhang et al, 2020).…”

“…Integrative clustering identifies similar cell states across a range of scRNAseq datasets, even when the datasets come from different donors, species, or tissues. For example, using integrative clustering, Zhang et al, 2020 identified shared macrophage activation states across five tissues, and Butler et al, 2018 identified shared pancreatic islet cells between mouse and human datasets. Reference mapping allows rapid comparison of data from a new study to a well annotated reference, even if the study represents a tissue, disease, or species not present in the reference atlas.…”

Circulatory Cytokines and Chemokines Profile in Human Coronaviruses: A systematic review and meta-analysis

“…Whereas CXCL10/IP10 and CCL2/MCP-1 were detected in the blood of patients infected with severe MERS. However, other studies that were not included in our systematic review reported elevated levels of IL-8 in the blood of patients infected with MERS and SARS (52, 62, 63) and CXCL10/IP10 and CCL2/MCP-1 in SARS (64) and COVID-19 (65, 66) infected patients.…”

Network pharmacology and RNA-sequencing reveal the molecular mechanism of Xuebijing injection on COVID-19-induced cardiac dysfunction

“…Meanwhile, the increased SERPINE1 could cause endothelial cell injury [ 32 ]. Another study stated that the CCL2+ inflammatory macrophage amount was abundant in peripheral blood of severe COVID-19 patients and inflammatory genes such as IL-1B were highly expressed in the CCL2+ inflammatory macrophages [ 33 ]. CXCL8, IL-1B, FOS and IFNB1 were identified to be up-regulated in COVID-19 patients and it was suggested that IFN-β might play a pivotal role in exacerbating inflammation in severe COVID-19 patients by enhancing TNF/IL-1B-driven inflammation [ 34 ].…”