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A Systems Immunology Approach Identifies Cytokine-Induced STAT Signaling Pathways Critical to Rheumatoid Arthritis Disease Activity and Treatment Response

Authors :
Chander Raman
Marc C. Levesque
Houman Khalili
Dongmei Sun
Garry P. Nolan
S. Louis Bridges
Meggan Mackay
Brent Louie
Clifton O. Bingham
Peter K. Gregersen
Franak Batliwalla
Nancy A. Shadick
E. William St. Clair
Barbara B. Mittleman
Matthew Hale
Jeffrey R. Curtis
Rachael E. Hawtin
Stacey S. Cofield
Jason Ptacek
Maria I. Danila
Betty Diamond
Alessandra Cesano
Geoffrey M. Thiele
Erik Evensen
Peter A. Nigrovic
Guy Cavet
Mark C. Genovese
James R. O'Dell
Cynthia Aranow
Christopher C. Striebich
William H. Robinson
Larry W. Moreland
Richard Furie
Publication Year :
2019
Publisher :
Cold Spring Harbor Laboratory, 2019.

Abstract

Rheumatoid arthritis (RA), a chronic autoimmune disease characterized by circulating autoantibodies, involves many cytokine-mediated signaling pathways in multiple immune cell subsets. Most studies of immune cells in RA have limitations, such as analysis of a small number of cell subsets or pathways, and limited longitudinal data on patient phenotypes. In this study, we used an innovative systems immunology approach to simultaneously quantify up to 882 signaling nodes (Jak/STAT signaling readouts modulated by cytokines and other stimuli) in 21 immune cell subsets. We studied 194 RA patients and 41 controls, including 146 well-characterized RA patients prior to, and 6 months after, initiation of methotrexate or biologic agents from the Treatment Efficacy and Toxicity in RA Database and Repository (TETRAD). There was strikingly attenuated signaling capacity in RA patients in IFNα stimulation followed by measurement of phosphorylated STAT1 [IFNα→p-STAT1] in six immune cell subsets. Multiple nodes showed negative association with disease activity, including IFNα→STAT5 signaling in naive and memory B cells. In contrast, IL-6-induced STAT1 and STAT3 activation in central memory CD4-negative T cells showed a positive association with disease activity. Multiple nodes were associated with treatment response, including IFNα→STAT1 in monocytes and IL-6→STAT3 in CD4+ naive T cells. Decision tree analysis identified a model combining these two nodes as a high-performing classifier of treatment response to TNF inhibitors. Our study provides novel information on RA disease mechanisms and serves as a framework for the discovery and validation of biomarkers of treatment response in RA.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....f6c7cf0a5092248d584e2c490559beda
Full Text :
https://doi.org/10.1101/691865