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Project description:BackgroundPro-inflammatory fibroblasts are critical for pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren's syndrome and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited our understanding of which pathways are shared by multiple diseases.MethodsWe profiled fibroblasts derived from inflamed and non-inflamed synovium, intestine, lungs, and salivary glands from affected individuals with single-cell RNA sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes.FindingsTwo shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts, were expanded in all inflamed tissues and mapped to dermal analogs in a public atopic dermatitis atlas. We confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation.ConclusionsThis work represents a thorough investigation into fibroblasts across organ systems, individual donors, and disease states that reveals shared pathogenic activation states across four chronic inflammatory diseases.FundingGrant from F. Hoffmann-La Roche (Roche) AG.
| S-EPMC9271637 | biostudies-literature
Project description:Pro-inflammatory fibroblasts are critical to pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren’s syndrome, and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited the understanding of which pathways are shared by multiple diseases. To investigate, we profiled patient-derived fibroblasts from inflamed and non-inflamed synovium, intestine, lung, and salivary glands with single-cell RNA-sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes. Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts were expanded in all inflamed tissues and additionally mapped to dermal analogues in a public atopic dermatitis atlas. We further confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation. This work represents the first cross-tissue, single-cell fibroblast atlas revealing shared pathogenic activation states across four chronic inflammatory diseases.
2022-06-01 | GSE185710 | GEO
Project description:Pro-inflammatory fibroblasts are critical to pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren’s syndrome, and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited the understanding of which pathways are shared by multiple diseases. To investigate, we profiled patient-derived fibroblasts from inflamed and non-inflamed synovium, intestine, lung, and salivary glands with single-cell RNA-sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes. Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts were expanded in all inflamed tissues and additionally mapped to dermal analogues in a public atopic dermatitis atlas. We further confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation. This work represents the first cross-tissue, single-cell fibroblast atlas revealing shared pathogenic activation states across four chronic inflammatory diseases.
2022-06-01 | GSE185696 | GEO
Project description:Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases
| PRJNA770543 | ENA
Project description:Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases [scRNA-Seq]
| PRJNA770522 | ENA
Project description:Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases [RNA-Seq]
| PRJNA770554 | ENA
Project description:BackgroundWhile genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.ResultsHere, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.ConclusionsThus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .
| S-EPMC8127495 | biostudies-literature
Project description:While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.
| S-EPMC7781346 | biostudies-literature
Project description:Interaction between genetic and epigenetic mechanisms may lead to autoimmune diseases. The features of these diseases show familial aggregation. The generality and specificity are keys to studying pathogenesis and etiology of them. This research integrated data of genetics and epigenetics, to find disease-related genes based on the levels of expression and regulation, and explored then to the shared and specific mechanism of them by analyzing shared and specific pathways of common four autoimmune diseases, including Type 1 Diabetes Mellitus (T1D), Multiple Sclerosis (MS), Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE). The results showed that Lysosome and Fc gamma R-mediated phagocytosis are shared pathways of the four diseases. It means that the occurrence and development of them may associate with lysosomes and phagocytosis. And there were 2 pathways are shared pathways of three diseases, ribosome pathway associated with susceptibility to MS, RA and SLE, and Pathogenic Escherichia coli infection associated with susceptibility to T1D, MS and RA; 9 pathways are shared pathways of two diseases. The corporate underlying causes of these diseases may be these shared pathways activated. Furthermore, we found that T1D-related specific pathways (Insulin signaling,etc.) were 9, MS (Proteasome,etc.) is also 9, RA and SLE is 10 and 6 respectively. These pathways could help us to reveal shared and specific mechanisms of the four diseases.
| S-EPMC5752449 | biostudies-literature
Project description:Stroma is a broad term referring to the connective tissue matrix in which other cells reside. It is composed of diverse cell types with functions such as extracellular matrix maintenance, blood and lymph vessel development, and effector cell recruitment. The tissue microenvironment is determined by the molecular characteristics and relative abundances of different stromal cells such as fibroblasts, endothelial cells, pericytes, and mesenchymal precursor cells. Stromal cell heterogeneity is explained by embryonic developmental lineage, stages of differentiation to other cell types, and activation states. Interaction between immune and stromal cell types is critical to wound healing, cancer, and a wide range of inflammatory diseases. Here, we review recent studies of inflammatory diseases that use functional genomics and single-cell technologies to identify and characterize stromal cell types associated with pathogenesis.High dimensional strategies using mRNA sequencing, mass cytometry, and fluorescence activated cell-sorting with fresh primary tissue samples are producing detailed views of what is happening in diseased tissue in rheumatoid arthritis, inflammatory bowel disease, and cancer. Fibroblasts positive for CD90 (Thy-1) are enriched in the synovium of rheumatoid arthritis patients. Single-cell RNA-seq studies will lead to more discoveries about the stroma in the near future.Stromal cells form the microenvironment of inflamed and diseased tissues. Functional genomics is producing an increasingly detailed view of subsets of stromal cells with pathogenic functions in rheumatic diseases and cancer. Future genomics studies will discover disease mechanisms by perturbing molecular pathways with chemokines and therapies known to affect patient outcomes. Functional genomics studies with large sample sizes of patient tissues will identify patient subsets with different disease phenotypes or treatment responses.
| S-EPMC5890939 | biostudies-other