Biomarkers in Scleroderma: Progressing from Association to Clinical Utility
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  • 作者：Colin Ligon ; Laura K. Hummers
  • 关键词：Biomarker ; Scleroderma ; Systemic sclerosis ; Gene microarray ; Latent subtype model
  • 刊名：Current Rheumatology Reports
  • 出版年：2016
  • 出版时间：March 2016
  • 年：2016
  • 卷：18
  • 期：3
  • 全文大小：487 KB
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  • 作者单位：Colin Ligon (1)
    Laura K. Hummers (1)

    1. Division of Rheumatology, Department of Medicine, Johns Hopkins University School of Medicine, 5200 Eastern Avenue, Mason F. Lord Building, Center Tower, Suite 4100, Baltimore, MD, 21224, USA
  • 刊物主题：Rheumatology;
  • 出版者：Springer US
  • ISSN：1534-6307
    • 文摘
    Scleroderma is a heterogenous disease characterized by autoimmunity, a characteristic vasculopathy, and often widely varying extents of deep organ fibrosis. Recent advances in the understanding of scleroderma’s evolution have improved the ability to identify subgroups of patients with similar prognosis in order to improve risk stratification, enrich clinical trials for patients likely to benefit from specific therapies, and identify promising therapeutic targets for intervention. High-throughput technologies have recently identified fibrotic and inflammatory effectors in scleroderma that exhibit strong prognostic ability and may be tied to disease evolution. Increasingly, the use of collections of assayed circulating proteins and patterns of gene expression in tissue has replaced single-marker investigations in understanding the evolution of scleroderma and in objectively characterizing disease extent. Lastly, identification of shared patterns of disease evolution has allowed classification of patients into latent disease subtypes, which may allow rapid clinical prognostication and targeted management in both clinical and research settings. The concept of biomarkers in scleroderma is expanding to include nontraditional measures of aggregate protein signatures and disease evolution. This review examines the recent advances in biomarkers with a focus on those approaches poised to guide prospective management or themselves serve as quantitative surrogate disease outcomes.

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