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Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor

In rheumatoid arthritis (RA), only a subset of patients develop irreversible bone destruction. Our aim was to identify a microRNA (miR)‐based osteoclast‐related signature predictive of erosiveness in RA. Seventy‐six adults with erosive (E) or nonerosive (NE) seropositive RA and 43 sex‐ and age‐match...

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Autores principales: Hoang Dong, Nguyen, Audrey, Lortie, Leopold, Mbous Nguimbus, Javier, Marrugo, Hugues, Allard‐Chamard, Luigi, Bouchard, Gilles, Boire, Scott, Michelle S, Sophie, Roux
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443079/
https://www.ncbi.nlm.nih.gov/pubmed/37614303
http://dx.doi.org/10.1002/jbm4.10776
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author Hoang Dong, Nguyen
Audrey, Lortie
Leopold, Mbous Nguimbus
Javier, Marrugo
Hugues, Allard‐Chamard
Luigi, Bouchard
Gilles, Boire
Scott, Michelle S
Sophie, Roux
author_facet Hoang Dong, Nguyen
Audrey, Lortie
Leopold, Mbous Nguimbus
Javier, Marrugo
Hugues, Allard‐Chamard
Luigi, Bouchard
Gilles, Boire
Scott, Michelle S
Sophie, Roux
author_sort Hoang Dong, Nguyen
collection PubMed
description In rheumatoid arthritis (RA), only a subset of patients develop irreversible bone destruction. Our aim was to identify a microRNA (miR)‐based osteoclast‐related signature predictive of erosiveness in RA. Seventy‐six adults with erosive (E) or nonerosive (NE) seropositive RA and 43 sex‐ and age‐matched healthy controls were recruited. Twenty‐five miRs from peripheral blood mononuclear cell (PBMC)‐derived osteoclasts selected from RNA‐Seq (discovery cohort) were assessed by qPCR (replication cohort), as were 33 target genes (direct targets or associated with regulated pathways). The top five miRs found differentially expressed in RA osteoclasts were either decreased (hsa‐miR‐34a‐3p, 365b‐3p, 374a‐3p, and 511‐3p [E versus NE]) or increased (hsa‐miR‐193b‐3p [E versus controls]). In vitro, inhibition of miR‐34a‐3p had an impact on osteoclast bone resorption. An integrative network analysis of miRs and their targets highlighted correlations between mRNA and miR expression, both negative (CD38, CD80, SIRT1) and positive (MITF), and differential gene expression between NE versus E (GXYLT1, MITF) or versus controls (CD38, KLF4). Machine‐learning models were used to evaluate the value of miRs and target genes, in combination with clinical data, to predict erosion. One model, including a set of miRs (predominantly 365b‐3p) combined with rheumatoid factor titer, provided 70% accuracy (area under the curve [AUC] 0.66). Adding genes directly targeted or belonging to related pathways improved the predictive power of the model for the erosive phenotype (78% accuracy, AUC 0.85). This proof‐of‐concept study indicates that identification of RA subjects at risk of erosions may be improved by studying miR expression in PBMC‐derived osteoclasts, suggesting novel approaches toward personalized treatment. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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spelling pubmed-104430792023-08-23 Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor Hoang Dong, Nguyen Audrey, Lortie Leopold, Mbous Nguimbus Javier, Marrugo Hugues, Allard‐Chamard Luigi, Bouchard Gilles, Boire Scott, Michelle S Sophie, Roux JBMR Plus Research Articles In rheumatoid arthritis (RA), only a subset of patients develop irreversible bone destruction. Our aim was to identify a microRNA (miR)‐based osteoclast‐related signature predictive of erosiveness in RA. Seventy‐six adults with erosive (E) or nonerosive (NE) seropositive RA and 43 sex‐ and age‐matched healthy controls were recruited. Twenty‐five miRs from peripheral blood mononuclear cell (PBMC)‐derived osteoclasts selected from RNA‐Seq (discovery cohort) were assessed by qPCR (replication cohort), as were 33 target genes (direct targets or associated with regulated pathways). The top five miRs found differentially expressed in RA osteoclasts were either decreased (hsa‐miR‐34a‐3p, 365b‐3p, 374a‐3p, and 511‐3p [E versus NE]) or increased (hsa‐miR‐193b‐3p [E versus controls]). In vitro, inhibition of miR‐34a‐3p had an impact on osteoclast bone resorption. An integrative network analysis of miRs and their targets highlighted correlations between mRNA and miR expression, both negative (CD38, CD80, SIRT1) and positive (MITF), and differential gene expression between NE versus E (GXYLT1, MITF) or versus controls (CD38, KLF4). Machine‐learning models were used to evaluate the value of miRs and target genes, in combination with clinical data, to predict erosion. One model, including a set of miRs (predominantly 365b‐3p) combined with rheumatoid factor titer, provided 70% accuracy (area under the curve [AUC] 0.66). Adding genes directly targeted or belonging to related pathways improved the predictive power of the model for the erosive phenotype (78% accuracy, AUC 0.85). This proof‐of‐concept study indicates that identification of RA subjects at risk of erosions may be improved by studying miR expression in PBMC‐derived osteoclasts, suggesting novel approaches toward personalized treatment. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. John Wiley & Sons, Inc. 2023-06-05 /pmc/articles/PMC10443079/ /pubmed/37614303 http://dx.doi.org/10.1002/jbm4.10776 Text en © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Hoang Dong, Nguyen
Audrey, Lortie
Leopold, Mbous Nguimbus
Javier, Marrugo
Hugues, Allard‐Chamard
Luigi, Bouchard
Gilles, Boire
Scott, Michelle S
Sophie, Roux
Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor
title Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor
title_full Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor
title_fullStr Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor
title_full_unstemmed Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor
title_short Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor
title_sort osteoclast microrna profiling in rheumatoid arthritis to capture the erosive factor
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443079/
https://www.ncbi.nlm.nih.gov/pubmed/37614303
http://dx.doi.org/10.1002/jbm4.10776
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