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New tools for classification and monitoring of autoimmune diseases

Nature Reviews Rheumatology volume 8, pages 317–328 (2012)Cite this article

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A Correction to this article was published on 01 October 2012

This article has been updated

Abstract

Rheumatologists see patients with a range of autoimmune diseases. Phenotyping these diseases for diagnosis, prognosis and selection of therapies is an ever increasing problem. Advances in multiplexed assay technology at the gene, protein, and cellular level have enabled the identification of 'actionable biomarkers'; that is, biological metrics that can inform clinical practice. Not only will such biomarkers yield insight into the development, remission, and exacerbation of a disease, they will undoubtedly improve diagnostic sensitivity and accuracy of classification, and ultimately guide treatment. This Review provides an introduction to these powerful technologies that could promote the identification of actionable biomarkers, including mass cytometry, protein arrays, and immunoglobulin and T-cell receptor high-throughput sequencing. In our opinion, these technologies should become part of routine clinical practice for the management of autoimmune diseases. The use of analytical tools to deconvolve the data obtained from use of these technologies is also presented here. These analyses are revealing a more comprehensive and interconnected view of the immune system than ever before and should have an important role in directing future treatment approaches for autoimmune diseases.

Key Points

  • Antigen arrays are valuable for profiling autoantibodies in diverse rheumatic autoimmune diseases and can be composed of most biomolecules including proteins, peptides, protein complexes, sugars, nucleic acids and lipids

  • High-throughput DNA sequencing enables the tracking of disease-associated clones of T cells and B cells in autoimmune diseases; changes in populations of these cells can be correlated with therapeutic response

  • The analysis of peripheral blood cells following cellular activation might be important in identifying clinically actionable biomarkers

  • New technologies enable analysis of gene and protein expression in whole blood samples; deconvolution of datasets reveals which immune-cell subset underlies a change without isolating or manipulating the cells

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Figure 1: Application of new immune-monitoring technologies to rheumatology.
Figure 2: Alternative analysis approaches for high-complexity flow cytometry data.
Figure 3: Example of a SPADE representation of CyTOF data from analysis of peripheral blood mononuclear cells from two healthy individuals.
Figure 4: The use of high-throughput DNA sequencing of immunoglobulin or T-cell receptor gene rearrangements to detect dynamic changes in lymphocyte repertoire and clonal expansions.
Figure 5: Statistical deconvolution enables detection of system-wide cell-type specific differences between groups without cell-type isolation.

Change history

  • 01 October 2012

    In the versions of this article initially published in print and online, the authors did not include acknowledgements of grant support as required by their funding policies. This omission has been corrected for the HTML and PDF versions of the article.

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Acknowledgements

The authors wish to thank Dr Hongwu Du for his advice on the systems immunology section of the article and for assistance with editing the manuscript. In addition, the authors thank members of the Boyd lab and Dr A. Fire (Stanford University, Stanford, USA) in collaboration with Dr A. Lucas and Dr L. Liu (Children's Hospital Oakland Research Institute, Oakland, USA) for providing the basis for Figure 4. Furthermore, the authors gratefully acknowledge sources of funding for their research activities: H. T. Maecker's work was supported by NIH grants 3 U19 AI057229, 4 U19 AI090019, and 1 RC4 AG039014; P. J. Utz was the recipient of a Donald E. and Delia B. Baxter Foundation Career Development Award and his work is supported by National Heart, Lung, and Blood Institute (NHLBI) Proteomics contract HHSN288201000034C, Proteomics of Inflammatory Immunity and Pulmonary Arterial Hypertension, NIH grants 5 U19-AI082719, 5 U19-AI050864, 5 U19-AI056363, 1 U19 AI090019 and 4 U19 AI090019, Canadian Institutes of Health Research grant 2 OR-92141, Alliance for Lupus Research grant number 21858, a gift from the Ben May Trust and a gift from the Floren Family Trust, and the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement number 261382; S. D. Boyd is the recipient of NIH grants U19AI090019, U19AI067854, U54-AI065359, UM1AI100663-01, Ellison Medical Foundation grant AG-NS-792-11, and the Lucille Packard Pediatric Research Fund; the work of S. S. Shen-Orr is supported by NIH grant 3 U19 AI057229.

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Authors and Affiliations

  1. Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, 94305, CA, USA

    Holden T. Maecker & Matthew Hale

  2. Department of Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA

    Tamsin M. Lindstrom, William H. Robinson, Paul J. Utz & C. Garrison Fathman

  3. Department of Pathology, Stanford University School of Medicine, Stanford, 94305, CA, USA

    Scott D. Boyd

  4. Department of Immunology, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, 32000, Haifa, Israel

    Shai S. Shen-Orr

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All authors researched data for the article, substantially contributed to the discussion of content and selection of references and reviewed/edited the manuscript before submission. H. T. Maecker, T. M. Lindstrom, W. H. Robinson, P. J. Utz, M. Hale, S. D. Boyd and S. S. Shen-Orr wrote the article.

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S. D. Boyd is a consultant for ImmuMetrix LLC, and has received consultancy fees and equity compensation. The remaining authors declare no competing interests.

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Maecker, H., Lindstrom, T., Robinson, W. et al. New tools for classification and monitoring of autoimmune diseases. Nat Rev Rheumatol 8, 317–328 (2012). https://doi.org/10.1038/nrrheum.2012.66

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