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Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis

OBJECTIVES: To integrate published single-cell RNA sequencing (scRNA-seq) data and assess the contribution of synovial fibroblast (SF) subsets to synovial pathotypes and respective clinical characteristics in treatment-naïve early arthritis. METHODS: In this in silico study, we integrated scRNA-seq...

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Autores principales: Micheroli, Raphael, Elhai, Muriel, Edalat, Sam, Frank-Bertoncelj, Mojca, Bürki, Kristina, Ciurea, Adrian, MacDonald, Lucy, Kurowska-Stolarska, Mariola, Lewis, Myles J, Goldmann, Katriona, Cubuk, Cankut, Kuret, Tadeja, Distler, Oliver, Pitzalis, Costantino, Ospelt, Caroline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734041/
https://www.ncbi.nlm.nih.gov/pubmed/34987094
http://dx.doi.org/10.1136/rmdopen-2021-001949
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author Micheroli, Raphael
Elhai, Muriel
Edalat, Sam
Frank-Bertoncelj, Mojca
Bürki, Kristina
Ciurea, Adrian
MacDonald, Lucy
Kurowska-Stolarska, Mariola
Lewis, Myles J
Goldmann, Katriona
Cubuk, Cankut
Kuret, Tadeja
Distler, Oliver
Pitzalis, Costantino
Ospelt, Caroline
author_facet Micheroli, Raphael
Elhai, Muriel
Edalat, Sam
Frank-Bertoncelj, Mojca
Bürki, Kristina
Ciurea, Adrian
MacDonald, Lucy
Kurowska-Stolarska, Mariola
Lewis, Myles J
Goldmann, Katriona
Cubuk, Cankut
Kuret, Tadeja
Distler, Oliver
Pitzalis, Costantino
Ospelt, Caroline
author_sort Micheroli, Raphael
collection PubMed
description OBJECTIVES: To integrate published single-cell RNA sequencing (scRNA-seq) data and assess the contribution of synovial fibroblast (SF) subsets to synovial pathotypes and respective clinical characteristics in treatment-naïve early arthritis. METHODS: In this in silico study, we integrated scRNA-seq data from published studies with additional unpublished in-house data. Standard Seurat, Harmony and Liger workflow was performed for integration and differential gene expression analysis. We estimated single cell type proportions in bulk RNA-seq data (deconvolution) from synovial tissue from 87 treatment-naïve early arthritis patients in the Pathobiology of Early Arthritis Cohort using MuSiC. SF proportions across synovial pathotypes (fibroid, lymphoid and myeloid) and relationship of disease activity measurements across different synovial pathotypes were assessed. RESULTS: We identified four SF clusters with respective marker genes: PRG4(+) SF (CD55, MMP3, PRG4, THY1(neg)); CXCL12(+) SF (CXCL12, CCL2, ADAMTS1, THY1(low)); POSTN(+) SF (POSTN, collagen genes, THY1); CXCL14(+) SF (CXCL14, C3, CD34, ASPN, THY1) that correspond to lining (PRG4(+) SF) and sublining (CXCL12(+) SF, POSTN(+) + and CXCL14(+) SF) SF subsets. CXCL12(+) SF and POSTN(+) + were most prominent in the fibroid while PRG4(+) SF appeared highest in the myeloid pathotype. Corresponding, lining assessed by histology (assessed by Krenn-Score) was thicker in the myeloid, but also in the lymphoid pathotype + the fibroid pathotype. PRG4(+) SF correlated positively with disease severity parameters in the fibroid, POSTN(+) SF in the lymphoid pathotype whereas CXCL14(+) SF showed negative association with disease severity in all pathotypes. CONCLUSION: This study shows a so far unexplored association between distinct synovial pathologies and SF subtypes defined by scRNA-seq. The knowledge of the diverse interplay of SF with immune cells will advance opportunities for tailored targeted treatments.
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spelling pubmed-87340412022-01-20 Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis Micheroli, Raphael Elhai, Muriel Edalat, Sam Frank-Bertoncelj, Mojca Bürki, Kristina Ciurea, Adrian MacDonald, Lucy Kurowska-Stolarska, Mariola Lewis, Myles J Goldmann, Katriona Cubuk, Cankut Kuret, Tadeja Distler, Oliver Pitzalis, Costantino Ospelt, Caroline RMD Open Rheumatoid Arthritis OBJECTIVES: To integrate published single-cell RNA sequencing (scRNA-seq) data and assess the contribution of synovial fibroblast (SF) subsets to synovial pathotypes and respective clinical characteristics in treatment-naïve early arthritis. METHODS: In this in silico study, we integrated scRNA-seq data from published studies with additional unpublished in-house data. Standard Seurat, Harmony and Liger workflow was performed for integration and differential gene expression analysis. We estimated single cell type proportions in bulk RNA-seq data (deconvolution) from synovial tissue from 87 treatment-naïve early arthritis patients in the Pathobiology of Early Arthritis Cohort using MuSiC. SF proportions across synovial pathotypes (fibroid, lymphoid and myeloid) and relationship of disease activity measurements across different synovial pathotypes were assessed. RESULTS: We identified four SF clusters with respective marker genes: PRG4(+) SF (CD55, MMP3, PRG4, THY1(neg)); CXCL12(+) SF (CXCL12, CCL2, ADAMTS1, THY1(low)); POSTN(+) SF (POSTN, collagen genes, THY1); CXCL14(+) SF (CXCL14, C3, CD34, ASPN, THY1) that correspond to lining (PRG4(+) SF) and sublining (CXCL12(+) SF, POSTN(+) + and CXCL14(+) SF) SF subsets. CXCL12(+) SF and POSTN(+) + were most prominent in the fibroid while PRG4(+) SF appeared highest in the myeloid pathotype. Corresponding, lining assessed by histology (assessed by Krenn-Score) was thicker in the myeloid, but also in the lymphoid pathotype + the fibroid pathotype. PRG4(+) SF correlated positively with disease severity parameters in the fibroid, POSTN(+) SF in the lymphoid pathotype whereas CXCL14(+) SF showed negative association with disease severity in all pathotypes. CONCLUSION: This study shows a so far unexplored association between distinct synovial pathologies and SF subtypes defined by scRNA-seq. The knowledge of the diverse interplay of SF with immune cells will advance opportunities for tailored targeted treatments. BMJ Publishing Group 2022-01-05 /pmc/articles/PMC8734041/ /pubmed/34987094 http://dx.doi.org/10.1136/rmdopen-2021-001949 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Rheumatoid Arthritis
Micheroli, Raphael
Elhai, Muriel
Edalat, Sam
Frank-Bertoncelj, Mojca
Bürki, Kristina
Ciurea, Adrian
MacDonald, Lucy
Kurowska-Stolarska, Mariola
Lewis, Myles J
Goldmann, Katriona
Cubuk, Cankut
Kuret, Tadeja
Distler, Oliver
Pitzalis, Costantino
Ospelt, Caroline
Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
title Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
title_full Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
title_fullStr Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
title_full_unstemmed Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
title_short Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
title_sort role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis
topic Rheumatoid Arthritis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734041/
https://www.ncbi.nlm.nih.gov/pubmed/34987094
http://dx.doi.org/10.1136/rmdopen-2021-001949
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