Literature DB >> 17299447

Technology insight: can autoantibody profiling improve clinical practice?

Veronika Sharp1, Paul J Utz.   

Abstract

A hallmark of autoimmune diseases is the production of high titers of highly specific autoantibodies, which are routinely measured to guide clinical decision-making. Multiplex antigen microarrays are powerful tools that can provide profiles of the autoantibodies found in blood and other biological fluids. This high-throughput technology allows for rapid identification of antibody and antigen biomarker sets, which is sorely needed in the clinic to improve diagnosis, predictions of prognosis, and selection of targeted therapies. In this article we will describe the antigen microarray technologies that are currently available, and those that are in development. We highlight recent applications for antibody profiling, as well as the challenges that need to be faced before such technologies enter the clinic.

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Year:  2007        PMID: 17299447     DOI: 10.1038/ncprheum0404

Source DB:  PubMed          Journal:  Nat Clin Pract Rheumatol        ISSN: 1745-8382


  10 in total

Review 1.  New tools for classification and monitoring of autoimmune diseases.

Authors:  Holden T Maecker; Tamsin M Lindstrom; William H Robinson; Paul J Utz; Matthew Hale; Scott D Boyd; Shai S Shen-Orr; C Garrison Fathman
Journal:  Nat Rev Rheumatol       Date:  2012-05-31       Impact factor: 20.543

Review 2.  Myositis-specific autoantibodies: detection and clinical associations.

Authors:  Sander H J van Dooren; Walther J van Venrooij; Ger J M Pruijn
Journal:  Auto Immun Highlights       Date:  2011-03-23

Review 3.  Overview: the maturing of proteomics in cardiovascular research.

Authors:  Jennifer E Van Eyk
Journal:  Circ Res       Date:  2011-02-18       Impact factor: 17.367

4.  Analytical validation of serum proteomic profiling for diagnosis of prostate cancer: sources of sample bias.

Authors:  Dale McLerran; William E Grizzle; Ziding Feng; William L Bigbee; Lionel L Banez; Lisa H Cazares; Daniel W Chan; Jose Diaz; Elzbieta Izbicka; Jacob Kagan; David E Malehorn; Gunjan Malik; Denise Oelschlager; Alan Partin; Timothy Randolph; Nicole Rosenzweig; Shiv Srivastava; Sudhir Srivastava; Ian M Thompson; Mark Thornquist; Dean Troyer; Yutaka Yasui; Zhen Zhang; Liu Zhu; O John Semmes
Journal:  Clin Chem       Date:  2007-11-02       Impact factor: 8.327

5.  Sensitive and robust luminescent profiling of anti-La and other autoantibodies in Sjogren's syndrome.

Authors:  Peter D Burbelo; Hannah P Leahy; Alexandra T Issa; Sandra Groot; James N Baraniuk; Nikolay P Nikolov; Gabor G Illei; Michael J Iadarola
Journal:  Autoimmunity       Date:  2009-09       Impact factor: 2.815

Review 6.  New autoantibody detection technologies yield novel insights into autoimmune disease.

Authors:  Peter D Burbelo; Terrance P O'Hanlon
Journal:  Curr Opin Rheumatol       Date:  2014-11       Impact factor: 5.006

7.  Quantifying antibody binding on protein microarrays using microarray nonlinear calibration.

Authors:  Xiaobo Yu; Garrick Wallstrom; Dewey Mitchell Magee; Ji Qiu; D Eliseo A Mendoza; Jie Wang; Xiaofang Bian; Morgan Graves; Joshua LaBaer
Journal:  Biotechniques       Date:  2013-05       Impact factor: 1.993

8.  High definition profiling of autoantibodies to glutamic acid decarboxylases GAD65/GAD67 in stiff-person syndrome.

Authors:  Peter D Burbelo; Sandra Groot; Marinos C Dalakas; Michael J Iadarola
Journal:  Biochem Biophys Res Commun       Date:  2007-11-29       Impact factor: 3.575

9.  Rapid serological detection of autoantibodies associated with Sjögren's syndrome.

Authors:  Peter D Burbelo; Kathryn H Ching; Alexandra T Issa; Caroline M Loftus; Yi Li; Minoru Satoh; Westley H Reeves; Michael J Iadarola
Journal:  J Transl Med       Date:  2009-09-24       Impact factor: 5.531

10.  Autoantibody profiling in multiple sclerosis using arrays of human protein fragments.

Authors:  Burcu Ayoglu; Anna Häggmark; Mohsen Khademi; Tomas Olsson; Mathias Uhlén; Jochen M Schwenk; Peter Nilsson
Journal:  Mol Cell Proteomics       Date:  2013-06-03       Impact factor: 5.911

  10 in total

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