Cytokine production from stimulated whole blood cultures in rheumatoid arthritis patients treated with various TNF blocking agents

2009 ◽  
Vol 20 (2) ◽  
pp. 88-93 ◽  
Author(s):  
Calin Popa ◽  
Pilar Barrera ◽  
Leo A.B. Joosten ◽  
Piet L.C.M. van Riel ◽  
Bart-Jan Kullberg ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Whole Blood ◽  
Cytokine Production ◽  
Blood Cultures ◽  
Blocking Agents

Cytokine production of stimulated whole blood cultures in rheumatoid arthritis patients receiving short-term infliximab therapy

Cytokine ◽  
2005 ◽  
Vol 30 (2) ◽  
pp. 72-77 ◽  
Author(s):  
Calin Popa ◽  
Mihai G. Netea ◽  
Pilar Barrera ◽  
Timothy R.D.S. Radstake ◽  
Piet L. van Riel ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Whole Blood ◽  
Cytokine Production ◽  
Blood Cultures ◽  
Infliximab Therapy ◽  
Short Term

Cytokine production by leukocytes of Papillon–Lefèvre syndrome patients in whole blood cultures

2011 ◽  
Vol 16 (2) ◽  
pp. 591-597 ◽  
Author(s):  
Christian D. Sadik ◽  
Barbara Noack ◽  
Beate Schacher ◽  
Josef Pfeilschifter ◽  
Heiko Mühl ◽  
...  
Keyword(s):  
Whole Blood ◽  
Cytokine Production ◽  
Blood Cultures

scholarly journals Cytokine production in whole-blood cultures following immunization with an influenza vaccine

2018 ◽  
Vol 14 (12) ◽  
pp. 2990-2998 ◽  
Author(s):  
Tetsuo Nakayama ◽  
Takuji Kumagai ◽  
Yasuyo Kashiwagi ◽  
Hironori Yoshii ◽  
Kenta Honjo ◽  
...  
Keyword(s):  
Influenza Vaccine ◽  
Whole Blood ◽  
Cytokine Production ◽  
Blood Cultures

scholarly journals Interleukin-1  measurement in stimulated whole blood cultures is useful to predict response to anti-TNF therapies in rheumatoid arthritis

Rheumatology ◽  
2012 ◽  
Vol 51 (9) ◽  
pp. 1639-1643 ◽  
Author(s):  
K. Kayakabe ◽  
T. Kuroiwa ◽  
N. Sakurai ◽  
H. Ikeuchi ◽  
A. T. Kadiombo ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Whole Blood ◽  
Interleukin 1 ◽  
Blood Cultures

Investigations of cytokine production in whole blood cultures of paranoid and residual schizophrenic patients

1996 ◽  
Vol 246 (5) ◽  
pp. 279-284 ◽  
Author(s):  
I. Wilke ◽  
V. Arolt ◽  
M. Rothermundt ◽  
Ch. Weitzsch ◽  
M. Hornberg ◽  
...  
Keyword(s):  
Whole Blood ◽  
Cytokine Production ◽  
Blood Cultures ◽  
Schizophrenic Patients

scholarly journals AB0108 USING RNA SEQUENCING TO IDENTIFY GENE EXPRESSION SIGNATURES ASSOCIATED WITH RESPONSE TO ABATACEPT IN PATIENTS WITH RHEUMATOID ARTHRITIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1082-1083
Author(s):  
H. H. Chen ◽  
W. C. Chao ◽  
J. R. Wang ◽  
T. M. Ko
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Mhc Class Ii ◽  
Whole Blood ◽  
Antigen Processing ◽  
Cytokine Production ◽  
Rna Seq ◽  
Eular Response ◽  
Gene Expression Signatures ◽  
Identify Gene Expression

Background:Rheumatoid arthritis (RA) is a common chronic autoimmune disease. Abatacept (CTLA4-immunoglobulin) is one of the biological disease-modifying antirheumatic drug (bDMARD) for RA patients with indequate response to methotrexate. Recently, Yokoyama-Kokuryo et al. compared gene expression levels between abatacept responders and non-responders in RA patients using a microarray and found that type I IFN score and expression levels of nine genes may be used as a biomarker to predict response to abatacept. However, little study used RNA sequencing (RNA-seq) to identify whole blood gene expression signatures to predict therapeutic response to abatacept.Objectives:The aim of this study is to identify gene expression signatures to predict therapeutic responses to abatacept in RA patients using RNA-seq.Methods:This study is a single-center, prospective study. We used a PAX gene Blood RNA kit to collect whole blood at baseline and 4 weeks after abatacept treatment from RA patients. We also measured DAS28, physician global assessment, HAQ, ESR, CRP at baseline and 12 week to calculate EULAR response at 12 week. Patients with good EULAR response were defined as responders and those with moderate or no EULAR response were defined as non-responders.Results:We finally conducted RNA-seq for whole blood from 7 RA patients initiating abatacept therapy. Of the 7 RA patients, one was non-responder and 6 were responders. We first use DESeq2 to analyze the differentially expressed genes of non-responder and responder before taking the drug. We used hierarchical clustering and PCA to evaluate the overall similarity of the samples, and group the patient data, and find that the nonresponder can be distinguished from responders. Subsequently, we analyzed the differentially expressed genes of the two groups of non-responder and responder patients before taking the drug. Before treatment, we found that 72 genes had a higher expression in the non-responder, and 23 genes had a higher expression level in responders. Figure 1 showed the top 20 DEG Heatmap between the non-responder and responders.Using these two sets of genes for GO analysis, we found that most of the pathways in the non-responder are related to immune response and cytokine production, and most of the pathways in the responders are related to antigen processing and MHC class II.Figure 1.Top 20 DEG Heatmap between non-responder and respondersConclusion:The study showed that most of the pathways in RA patients with no EULAR response to abatacept are related to immune response and cytokine production; while most of the pathways in RA patients with moderate/good response to abatacept are related to antigen processing and MHC class II.References:[1]Yokoyama-Kokuyo W, Yamazaki H, Takeuchi T, et al. Identification of molecules associated with response to abatacept in patients with rheumatoid arthritis. Arthritis Research & Therapy. 2020;22:46.Disclosure of Interests:Hsin-Hua Chen Grant/research support from: This is an investigator-sponsored trial with Bristol-Myers Squibb who provides funding support., Wen-Cheng Chao: None declared, Jing-Rong Wang: None declared, Tai-Ming Ko: None declared

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