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Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis

OBJECTIVES: Early diagnosis of rheumatoid arthritis (RA) is an unmet medical need in the field of rheumatology. Previously, we performed high-density transcriptomic studies on synovial biopsies from patients with arthritis, and found that synovial gene expression profiles were significantly differen...

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Autores principales: Lauwerys, Bernard R., Hernández-Lobato, Daniel, Gramme, Pierre, Ducreux, Julie, Dessy, Adrien, Focant, Isabelle, Ambroise, Jérôme, Bearzatto, Bertrand, Nzeusseu Toukap, Adrien, Van den Eynde, Benoît J., Elewaut, Dirk, Gala, Jean-Luc, Durez, Patrick, Houssiau, Frédéric A., Helleputte, Thibault, Dupont, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415786/
https://www.ncbi.nlm.nih.gov/pubmed/25927832
http://dx.doi.org/10.1371/journal.pone.0122104
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author Lauwerys, Bernard R.
Hernández-Lobato, Daniel
Gramme, Pierre
Ducreux, Julie
Dessy, Adrien
Focant, Isabelle
Ambroise, Jérôme
Bearzatto, Bertrand
Nzeusseu Toukap, Adrien
Van den Eynde, Benoît J.
Elewaut, Dirk
Gala, Jean-Luc
Durez, Patrick
Houssiau, Frédéric A.
Helleputte, Thibault
Dupont, Pierre
author_facet Lauwerys, Bernard R.
Hernández-Lobato, Daniel
Gramme, Pierre
Ducreux, Julie
Dessy, Adrien
Focant, Isabelle
Ambroise, Jérôme
Bearzatto, Bertrand
Nzeusseu Toukap, Adrien
Van den Eynde, Benoît J.
Elewaut, Dirk
Gala, Jean-Luc
Durez, Patrick
Houssiau, Frédéric A.
Helleputte, Thibault
Dupont, Pierre
author_sort Lauwerys, Bernard R.
collection PubMed
description OBJECTIVES: Early diagnosis of rheumatoid arthritis (RA) is an unmet medical need in the field of rheumatology. Previously, we performed high-density transcriptomic studies on synovial biopsies from patients with arthritis, and found that synovial gene expression profiles were significantly different according to the underlying disorder. Here, we wanted to further explore the consistency of the gene expression signals in synovial biopsies of patients with arthritis, using low-density platforms. METHODS: Low-density assays (cDNA microarray and microfluidics qPCR) were designed, based on the results of the high-density microarray data. Knee synovial biopsies were obtained from patients with RA, spondyloarthropathies (SA) or osteoarthritis (OA) (n = 39), and also from patients with initial undifferentiated arthritis (UA) (n = 49). RESULTS: According to high-density microarray data, several molecular pathways are differentially expressed in patients with RA, SA and OA: T and B cell activation, chromatin remodelling, RAS GTPase activation and extracellular matrix regulation. Strikingly, disease activity (DAS28-CRP) has a significant influence on gene expression patterns in RA samples. Using the low-density assays, samples from patients with OA are easily discriminated from RA and SA samples. However, overlapping molecular patterns are found, in particular between RA and SA biopsies. Therefore, prediction of the clinical diagnosis based on gene expression data results in a diagnostic accuracy of 56.8%, which is increased up to 98.6% by the addition of specific clinical symptoms in the prediction algorithm. Similar observations are made in initial UA samples, in which overlapping molecular patterns also impact the accuracy of the diagnostic algorithm. When clinical symptoms are added, the diagnostic accuracy is strongly improved. CONCLUSIONS: Gene expression signatures are overall different in patients with OA, RA and SA, but overlapping molecular signatures are found in patients with these conditions. Therefore, an accurate diagnosis in patients with UA requires a combination of gene expression and clinical data.
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spelling pubmed-44157862015-05-07 Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis Lauwerys, Bernard R. Hernández-Lobato, Daniel Gramme, Pierre Ducreux, Julie Dessy, Adrien Focant, Isabelle Ambroise, Jérôme Bearzatto, Bertrand Nzeusseu Toukap, Adrien Van den Eynde, Benoît J. Elewaut, Dirk Gala, Jean-Luc Durez, Patrick Houssiau, Frédéric A. Helleputte, Thibault Dupont, Pierre PLoS One Research Article OBJECTIVES: Early diagnosis of rheumatoid arthritis (RA) is an unmet medical need in the field of rheumatology. Previously, we performed high-density transcriptomic studies on synovial biopsies from patients with arthritis, and found that synovial gene expression profiles were significantly different according to the underlying disorder. Here, we wanted to further explore the consistency of the gene expression signals in synovial biopsies of patients with arthritis, using low-density platforms. METHODS: Low-density assays (cDNA microarray and microfluidics qPCR) were designed, based on the results of the high-density microarray data. Knee synovial biopsies were obtained from patients with RA, spondyloarthropathies (SA) or osteoarthritis (OA) (n = 39), and also from patients with initial undifferentiated arthritis (UA) (n = 49). RESULTS: According to high-density microarray data, several molecular pathways are differentially expressed in patients with RA, SA and OA: T and B cell activation, chromatin remodelling, RAS GTPase activation and extracellular matrix regulation. Strikingly, disease activity (DAS28-CRP) has a significant influence on gene expression patterns in RA samples. Using the low-density assays, samples from patients with OA are easily discriminated from RA and SA samples. However, overlapping molecular patterns are found, in particular between RA and SA biopsies. Therefore, prediction of the clinical diagnosis based on gene expression data results in a diagnostic accuracy of 56.8%, which is increased up to 98.6% by the addition of specific clinical symptoms in the prediction algorithm. Similar observations are made in initial UA samples, in which overlapping molecular patterns also impact the accuracy of the diagnostic algorithm. When clinical symptoms are added, the diagnostic accuracy is strongly improved. CONCLUSIONS: Gene expression signatures are overall different in patients with OA, RA and SA, but overlapping molecular signatures are found in patients with these conditions. Therefore, an accurate diagnosis in patients with UA requires a combination of gene expression and clinical data. Public Library of Science 2015-04-30 /pmc/articles/PMC4415786/ /pubmed/25927832 http://dx.doi.org/10.1371/journal.pone.0122104 Text en © 2015 Lauwerys et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lauwerys, Bernard R.
Hernández-Lobato, Daniel
Gramme, Pierre
Ducreux, Julie
Dessy, Adrien
Focant, Isabelle
Ambroise, Jérôme
Bearzatto, Bertrand
Nzeusseu Toukap, Adrien
Van den Eynde, Benoît J.
Elewaut, Dirk
Gala, Jean-Luc
Durez, Patrick
Houssiau, Frédéric A.
Helleputte, Thibault
Dupont, Pierre
Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
title Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
title_full Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
title_fullStr Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
title_full_unstemmed Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
title_short Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
title_sort heterogeneity of synovial molecular patterns in patients with arthritis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415786/
https://www.ncbi.nlm.nih.gov/pubmed/25927832
http://dx.doi.org/10.1371/journal.pone.0122104
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