Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes

早期类风湿性关节炎的分子特征揭示临床和治疗反应表型

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作者:Myles J Lewis ,Michael R Barnes ,Kevin Blighe ,Katriona Goldmann ,Sharmila Rana ,Jason A Hackney ,Nandhini Ramamoorthi ,Christopher R John ,David S Watson ,Sarah K Kummerfeld ,Rebecca Hands ,Sudeh Riahi ,Vidalba Rocher-Ros ,Felice Rivellese ,Frances Humby ,Stephen Kelly ,Michele Bombardieri ,Nora Ng ,Maria DiCicco ,Désirée van der Heijde ,Robert Landewé ,Annette van der Helm-van Mil ,Alberto Cauli ,Iain B McInnes ,Christopher D Buckley ,Ernest Choy ,Peter C Taylor ,Michael J Townsend ,Costantino Pitzalis

Abstract

There is a current imperative to unravel the hierarchy of molecular pathways that drive the transition of early to established disease in rheumatoid arthritis (RA). Herein, we report a comprehensive RNA sequencing analysis of the molecular pathways that drive early RA progression in the disease tissue (synovium), comparing matched peripheral blood RNA-seq in a large cohort of early treatment-naive patients, namely, the Pathobiology of Early Arthritis Cohort (PEAC). We developed a data exploration website (https://peac.hpc.qmul.ac.uk/) to dissect gene signatures across synovial and blood compartments, integrated with deep phenotypic profiling. We identified transcriptional subgroups in synovium linked to three distinct pathotypes: fibroblastic pauci-immune pathotype, macrophage-rich diffuse-myeloid pathotype, and a lympho-myeloid pathotype characterized by infiltration of lymphocytes and myeloid cells. This is suggestive of divergent pathogenic pathways or activation disease states. Pro-myeloid inflammatory synovial gene signatures correlated with clinical response to initial drug therapy, whereas plasma cell genes identified a poor prognosis subgroup with progressive structural damage. Keywords: PEAC; Pathobiology of Early Arthritis Cohort study; RNA sequencing; ectopic lymphoid structures; lymphoid neogenesis; personalized medicine; rheumatoid arthritis; synovial biopsy; transcriptomics.

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