Literature DB >> 25371395

Modular analysis of peripheral blood gene expression in rheumatoid arthritis captures reproducible gene expression changes in tumor necrosis factor responders.

Michaela Oswald1, Mark E Curran, Sarah L Lamberth, Robert M Townsend, Jennifer D Hamilton, David N Chernoff, John Carulli, Michael J Townsend, Michael E Weinblatt, Marlena Kern, Cassandra M Pond, Annette Lee, Peter K Gregersen.   

Abstract

OBJECTIVE: To establish whether the analysis of whole-blood gene expression is useful in predicting or monitoring response to anti-tumor necrosis factor (anti-TNF) therapy in patients with rheumatoid arthritis (RA).
METHODS: Whole-blood RNA (using a PAXgene system to stabilize whole-blood RNA in the collection tube) was obtained at baseline and at 14 weeks from 3 independent cohorts, consisting of a combined total of 240 RA patients who were beginning therapy with anti-TNF. We used an approach to gene expression analysis that is based on modular patterns of gene expression, or modules.
RESULTS: Good and moderate responders according to the European League Against Rheumatism criteria exhibited highly significant and consistent changes in multiple gene expression modules after 14 weeks of therapy, as demonstrated by hypergeometric analysis. Strikingly, nonresponders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all 3 cohorts, indicating that immunologic changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and nonresponders at baseline in the 3 study cohorts.
CONCLUSION: These data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors.
Copyright © 2015 by the American College of Rheumatology.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25371395      PMCID: PMC4476407          DOI: 10.1002/art.38947

Source DB:  PubMed          Journal:  Arthritis Rheumatol        ISSN: 2326-5191            Impact factor:   10.995


  21 in total

1.  Intravenous golimumab is effective in patients with active rheumatoid arthritis despite methotrexate therapy with responses as early as week 2: results of the phase 3, randomised, multicentre, double-blind, placebo-controlled GO-FURTHER trial.

Authors:  Michael E Weinblatt; Clifton O Bingham; Alan M Mendelsohn; Lilianne Kim; Michael Mack; Jiandong Lu; Daniel Baker; Rene Westhovens
Journal:  Ann Rheum Dis       Date:  2012-06-01       Impact factor: 19.103

Review 2.  Rheumatoid arthritis.

Authors:  David L Scott; Frederick Wolfe; Tom W J Huizinga
Journal:  Lancet       Date:  2010-09-25       Impact factor: 79.321

Review 3.  The potential use of expression profiling: implications for predicting treatment response in rheumatoid arthritis.

Authors:  Samantha Louise Smith; Darren Plant; Stephen Eyre; Anne Barton
Journal:  Ann Rheum Dis       Date:  2013-03-13       Impact factor: 19.103

Review 4.  Individualized medicine from prewomb to tomb.

Authors:  Eric J Topol
Journal:  Cell       Date:  2014-03-27       Impact factor: 41.582

5.  Editorial: the power of a modular approach to transcriptional analysis.

Authors:  Peter K Gregersen; Michaela Oswald
Journal:  Arthritis Rheumatol       Date:  2014-06       Impact factor: 10.995

6.  Differential gene expression profiles may differentiate responder and nonresponder patients with rheumatoid arthritis for methotrexate (MTX) monotherapy and MTX plus tumor necrosis factor inhibitor combined therapy.

Authors:  Renê Donizeti Ribeiro Oliveira; Vanessa Fontana; Cristina Moraes Junta; Márcia Maria Chiquitelli Marques; Cláudia Macedo; Diane Meyre Rassi; Geraldo Aleixo Passos; Eduardo Antonio Donadi; Paulo Louzada-Junior
Journal:  J Rheumatol       Date:  2012-07-01       Impact factor: 4.666

7.  Convergent Random Forest predictor: methodology for predicting drug response from genome-scale data applied to anti-TNF response.

Authors:  Jadwiga R Bienkowska; Gul S Dalgin; Franak Batliwalla; Normand Allaire; Ronenn Roubenoff; Peter K Gregersen; John P Carulli
Journal:  Genomics       Date:  2009-08-20       Impact factor: 5.736

8.  A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus.

Authors:  Damien Chaussabel; Charles Quinn; Jing Shen; Pinakeen Patel; Casey Glaser; Nicole Baldwin; Dorothee Stichweh; Derek Blankenship; Lei Li; Indira Munagala; Lynda Bennett; Florence Allantaz; Asuncion Mejias; Monica Ardura; Ellen Kaizer; Laurence Monnet; Windy Allman; Henry Randall; Diane Johnson; Aimee Lanier; Marilynn Punaro; Knut M Wittkowski; Perrin White; Joseph Fay; Goran Klintmalm; Octavio Ramilo; A Karolina Palucka; Jacques Banchereau; Virginia Pascual
Journal:  Immunity       Date:  2008-07-18       Impact factor: 31.745

9.  An eight-gene blood expression profile predicts the response to infliximab in rheumatoid arthritis.

Authors:  Antonio Julià; Alba Erra; Carles Palacio; Carlos Tomas; Xavier Sans; Pere Barceló; Sara Marsal
Journal:  PLoS One       Date:  2009-10-22       Impact factor: 3.240

10.  Molecular discrimination of responders and nonresponders to anti-TNF alpha therapy in rheumatoid arthritis by etanercept.

Authors:  Dirk Koczan; Susanne Drynda; Michael Hecker; Andreas Drynda; Reinhard Guthke; Joern Kekow; Hans-Juergen Thiesen
Journal:  Arthritis Res Ther       Date:  2008-05-02       Impact factor: 5.156

View more
  19 in total

Review 1.  Biomarkers to guide clinical therapeutics in rheumatology?

Authors:  William H Robinson; Rong Mao
Journal:  Curr Opin Rheumatol       Date:  2016-03       Impact factor: 5.006

2.  A vision and a prescription for big data-enabled medicine.

Authors:  Damien Chaussabel; Bali Pulendran
Journal:  Nat Immunol       Date:  2015-05       Impact factor: 25.606

3.  MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease.

Authors:  Jaclyn N Taroni; Peter C Grayson; Qiwen Hu; Sean Eddy; Matthias Kretzler; Peter A Merkel; Casey S Greene
Journal:  Cell Syst       Date:  2019-05-22       Impact factor: 10.304

4.  A compendium of monocyte transcriptome datasets to foster biomedical knowledge discovery.

Authors:  Darawan Rinchai; Sabri Boughorbel; Scott Presnell; Charlie Quinn; Damien Chaussabel
Journal:  F1000Res       Date:  2016-03-07

5.  The mechanistic implications of gene expression studies in SSc: Insights from Systems Biology.

Authors:  Jaclyn N Taroni; J Matthew Mahoney; Michael L Whitfield
Journal:  Curr Treatm Opt Rheumatol       Date:  2017-07-29

6.  Increased pretreatment serum IFN-β/α ratio predicts non-response to tumour necrosis factor α inhibition in rheumatoid arthritis.

Authors:  Theresa Wampler Muskardin; Priyanka Vashisht; Jessica M Dorschner; Mark A Jensen; Beverly S Chrabot; Marlena Kern; Jeffrey R Curtis; Maria I Danila; Stacey S Cofield; Nancy Shadick; Peter A Nigrovic; E William St Clair; Clifton O Bingham; Richard Furie; William Robinson; Mark Genovese; Christopher C Striebich; James R O'Dell; Geoffrey M Thiele; Larry W Moreland; Marc Levesque; S Louis Bridges; Peter K Gregersen; Timothy B Niewold
Journal:  Ann Rheum Dis       Date:  2015-11-06       Impact factor: 19.103

Review 7.  Potential clinical biomarkers in rheumatoid arthritis with an omic approach.

Authors:  Yolima Puentes-Osorio; Pedro Amariles; Miguel Ángel Calleja; Vicente Merino; Juan Camilo Díaz-Coronado; Daniel Taborda
Journal:  Auto Immun Highlights       Date:  2021-05-31

8.  Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.

Authors:  Matthew C Altman; Darawan Rinchai; Nicole Baldwin; Mohammed Toufiq; Elizabeth Whalen; Mathieu Garand; Basirudeen Syed Ahamed Kabeer; Mohamed Alfaki; Scott R Presnell; Prasong Khaenam; Aaron Ayllón-Benítez; Fleur Mougin; Patricia Thébault; Laurent Chiche; Noemie Jourde-Chiche; J Theodore Phillips; Goran Klintmalm; Anne O'Garra; Matthew Berry; Chloe Bloom; Robert J Wilkinson; Christine M Graham; Marc Lipman; Ganjana Lertmemongkolchai; Davide Bedognetti; Rodolphe Thiebaut; Farrah Kheradmand; Asuncion Mejias; Octavio Ramilo; Karolina Palucka; Virginia Pascual; Jacques Banchereau; Damien Chaussabel
Journal:  Nat Commun       Date:  2021-07-19       Impact factor: 14.919

9.  Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles.

Authors:  Arika Fukushima; Masahiro Sugimoto; Satoru Hiwa; Tomoyuki Hiroyasu
Journal:  BMC Bioinformatics       Date:  2021-03-18       Impact factor: 3.169

10.  Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE.

Authors:  Qinghua Fang; Tingyue Li; Peiya Chen; Yuzhe Wu; Tingting Wang; Lixia Mo; Jiaxin Ou; Kutty Selva Nandakumar
Journal:  Front Immunol       Date:  2021-05-17       Impact factor: 7.561

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.