Cargando…

Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)

OBJECTIVE: To establish whether synovial pathobiology improves current clinical classification and prognostic algorithms in early inflammatory arthritis and identify predictors of subsequent biological therapy requirement. METHODS: 200 treatment-naïve patients with early arthritis were classified as...

Descripción completa

Detalles Bibliográficos
Autores principales: Lliso-Ribera, Gloria, Humby, Frances, Lewis, Myles, Nerviani, Alessandra, Mauro, Daniele, Rivellese, Felice, Kelly, Stephen, Hands, Rebecca, Bene, Fabiola, Ramamoorthi, Nandhini, Hackney, Jason A, Cauli, Alberto, Choy, Ernest H, Filer, Andrew, Taylor, Peter C, McInnes, Iain, Townsend, Michael J, Pitzalis, Costantino
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6900253/
https://www.ncbi.nlm.nih.gov/pubmed/31582377
http://dx.doi.org/10.1136/annrheumdis-2019-215751
_version_ 1783477314979364864
author Lliso-Ribera, Gloria
Humby, Frances
Lewis, Myles
Nerviani, Alessandra
Mauro, Daniele
Rivellese, Felice
Kelly, Stephen
Hands, Rebecca
Bene, Fabiola
Ramamoorthi, Nandhini
Hackney, Jason A
Cauli, Alberto
Choy, Ernest H
Filer, Andrew
Taylor, Peter C
McInnes, Iain
Townsend, Michael J
Pitzalis, Costantino
author_facet Lliso-Ribera, Gloria
Humby, Frances
Lewis, Myles
Nerviani, Alessandra
Mauro, Daniele
Rivellese, Felice
Kelly, Stephen
Hands, Rebecca
Bene, Fabiola
Ramamoorthi, Nandhini
Hackney, Jason A
Cauli, Alberto
Choy, Ernest H
Filer, Andrew
Taylor, Peter C
McInnes, Iain
Townsend, Michael J
Pitzalis, Costantino
author_sort Lliso-Ribera, Gloria
collection PubMed
description OBJECTIVE: To establish whether synovial pathobiology improves current clinical classification and prognostic algorithms in early inflammatory arthritis and identify predictors of subsequent biological therapy requirement. METHODS: 200 treatment-naïve patients with early arthritis were classified as fulfilling RA1987 American College of Rheumatology (ACR) criteria (RA1987) or as undifferentiated arthritis (UA) and patients with UA further classified into those fulfilling RA2010 ACR/European League Against Rheumatism (EULAR) criteria. Treatment requirements at 12 months (Conventional Synthetic Disease Modifying Antirheumatic Drugs (csDMARDs) vs biologics vs no-csDMARDs treatment) were determined. Synovial tissue was retrieved by minimally invasive, ultrasound-guided biopsy and underwent processing for immunohistochemical (IHC) and molecular characterisation. Samples were analysed for macrophage, plasma-cell and B-cells and T-cells markers, pathotype classification (lympho-myeloid, diffuse-myeloid or pauci-immune) by IHC and gene expression profiling by Nanostring. RESULTS: 128/200 patients were classified as RA1987, 25 as RA2010 and 47 as UA. Patients classified as RA1987 criteria had significantly higher levels of disease activity, histological synovitis, degree of immune cell infiltration and differential upregulation of genes involved in B and T cell activation/function compared with RA2010 or UA, which shared similar clinical and pathobiological features. At 12-month follow-up, a significantly higher proportion of patients classified as lympho-myeloid pathotype required biological therapy. Performance of a clinical prediction model for biological therapy requirement was improved by the integration of synovial pathobiological markers from 78.8% to 89%–90%. CONCLUSION: The capacity to refine early clinical classification criteria through synovial pathobiological markers offers the potential to predict disease outcome and stratify therapeutic intervention to patients most in need.
format Online
Article
Text
id pubmed-6900253
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-69002532019-12-23 Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC) Lliso-Ribera, Gloria Humby, Frances Lewis, Myles Nerviani, Alessandra Mauro, Daniele Rivellese, Felice Kelly, Stephen Hands, Rebecca Bene, Fabiola Ramamoorthi, Nandhini Hackney, Jason A Cauli, Alberto Choy, Ernest H Filer, Andrew Taylor, Peter C McInnes, Iain Townsend, Michael J Pitzalis, Costantino Ann Rheum Dis Early Arthritis OBJECTIVE: To establish whether synovial pathobiology improves current clinical classification and prognostic algorithms in early inflammatory arthritis and identify predictors of subsequent biological therapy requirement. METHODS: 200 treatment-naïve patients with early arthritis were classified as fulfilling RA1987 American College of Rheumatology (ACR) criteria (RA1987) or as undifferentiated arthritis (UA) and patients with UA further classified into those fulfilling RA2010 ACR/European League Against Rheumatism (EULAR) criteria. Treatment requirements at 12 months (Conventional Synthetic Disease Modifying Antirheumatic Drugs (csDMARDs) vs biologics vs no-csDMARDs treatment) were determined. Synovial tissue was retrieved by minimally invasive, ultrasound-guided biopsy and underwent processing for immunohistochemical (IHC) and molecular characterisation. Samples were analysed for macrophage, plasma-cell and B-cells and T-cells markers, pathotype classification (lympho-myeloid, diffuse-myeloid or pauci-immune) by IHC and gene expression profiling by Nanostring. RESULTS: 128/200 patients were classified as RA1987, 25 as RA2010 and 47 as UA. Patients classified as RA1987 criteria had significantly higher levels of disease activity, histological synovitis, degree of immune cell infiltration and differential upregulation of genes involved in B and T cell activation/function compared with RA2010 or UA, which shared similar clinical and pathobiological features. At 12-month follow-up, a significantly higher proportion of patients classified as lympho-myeloid pathotype required biological therapy. Performance of a clinical prediction model for biological therapy requirement was improved by the integration of synovial pathobiological markers from 78.8% to 89%–90%. CONCLUSION: The capacity to refine early clinical classification criteria through synovial pathobiological markers offers the potential to predict disease outcome and stratify therapeutic intervention to patients most in need. BMJ Publishing Group 2019-12 2019-10-02 /pmc/articles/PMC6900253/ /pubmed/31582377 http://dx.doi.org/10.1136/annrheumdis-2019-215751 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 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/.
spellingShingle Early Arthritis
Lliso-Ribera, Gloria
Humby, Frances
Lewis, Myles
Nerviani, Alessandra
Mauro, Daniele
Rivellese, Felice
Kelly, Stephen
Hands, Rebecca
Bene, Fabiola
Ramamoorthi, Nandhini
Hackney, Jason A
Cauli, Alberto
Choy, Ernest H
Filer, Andrew
Taylor, Peter C
McInnes, Iain
Townsend, Michael J
Pitzalis, Costantino
Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
title Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
title_full Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
title_fullStr Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
title_full_unstemmed Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
title_short Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)
title_sort synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (peac)
topic Early Arthritis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6900253/
https://www.ncbi.nlm.nih.gov/pubmed/31582377
http://dx.doi.org/10.1136/annrheumdis-2019-215751
work_keys_str_mv AT llisoriberagloria synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT humbyfrances synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT lewismyles synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT nervianialessandra synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT maurodaniele synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT rivellesefelice synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT kellystephen synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT handsrebecca synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT benefabiola synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT ramamoorthinandhini synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT hackneyjasona synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT caulialberto synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT choyernesth synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT filerandrew synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT taylorpeterc synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT mcinnesiain synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT townsendmichaelj synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac
AT pitzaliscostantino synovialtissuesignaturesenhanceclinicalclassificationandprognostictreatmentresponsealgorithmsinearlyinflammatoryarthritisandpredictrequirementforsubsequentbiologicaltherapyresultsfromthepathobiologyofearlyarthritiscohortpeac