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  • Review Article
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Mechanistic biomarkers for clinical decision making in rheumatic diseases

Nature Reviews Rheumatology volume 9, pages 267–276 (2013)Cite this article

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Abstract

The use of biomarkers is becoming increasingly intrinsic to the practice of medicine and holds great promise for transforming the practice of rheumatology. Biomarkers have the potential to aid clinical diagnosis when symptoms are present or to provide a means of detecting early signs of disease when they are not. Some biomarkers can serve as early surrogates of eventual clinical outcomes or guide therapeutic decision making by enabling identification of individuals likely to respond to a specific therapy. Using biomarkers might reduce the costs of drug development by enabling individuals most likely to respond to be enrolled in clinical trials, thereby minimizing the number of participants required. In this Review, we discuss the current use and the potential of biomarkers in rheumatology and in select fields at the forefront of biomarker research. We emphasize the value of different types of biomarkers, addressing the concept of 'actionable' biomarkers, which can be used to guide clinical decision making, and 'mechanistic' biomarkers, a subtype of actionable biomarker that is embedded in disease pathogenesis and, therefore, represents a potentially superior biomarker. We provide examples of actionable and mechanistic biomarkers currently available, and discuss how development of such biomarkers could revolutionize clinical practice and drug development.

Key Points

  • Biomarkers can aid in the management of disease by facilitating diagnosis and stratification of disease, as well as assessment or prediction of disease severity or response to therapy

  • Drug development can be facilitated by biomarkers that enable selective recruitment of individuals likely to benefit from the intervention being tested or rapid assessment of response to a candidate therapeutic

  • Biomarkers rooted in the mechanism underlying the disease (mechanistic biomarkers) are likely to be more useful than those that are byproducts of the disease process (descriptive biomarkers)

  • Mechanistic biomarkers are more likely to perform better than descriptive biomarkers in differential diagnosis of disease, disease stratification and targeting of treatment, and as surrogate endpoints in clinical trials

  • Cytokines, chemokines, autoantibodies, microRNAs, gene-expression profiles and immune-cell types can all act as mechanistic biomarkers for rheumatic diseases

  • Mechanistic biomarkers might help to establish a molecular taxonomy of diseases

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Figure 1: Possible clinical uses of actionable biomarkers at different stages of the development of RA.
Figure 2: Mechanistic biomarkers of autoimmune diseases.
Figure 3: Types and uses of descriptive and mechanistic biomarkers for autoimmune rheumatic diseases.

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Acknowledgements

The work of W. H. Robinson is supported by N01-HV-00242/HV/ NHLBI NIH HSS/United States, RC1 AR058713/AR/NIAMS NIH HHS/United States, R01 AR-054822/AR/NIAMS NIH HHS/United States, and U01 U01AI101981/NIAID NIH HSS/United States grants, and Veterans Affairs Health Care System funding. J. Sokolove receives salary support from an American College of Rheumatology Research and Education Foundation Physician Scientist Development Award and a Veterans Affairs Career Development 2 Award.

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  1. VA Palo Alto Health Care System, 3801 Miranda Ave, Palo Alto, 94304, CA, USA

    William H. Robinson & Jeremy Sokolove

  2. Division of Immunology and Rheumatology, Stanford University School of Medicine, CCSR 4135, 269 Campus Drive, Stanford, 94305, CA, USA

    Tamsin M. Lindstrom & Regina K. Cheung

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W. H. Robinson is an inventor on patents owned by Stanford University that have been licensed to, or for which option agreements to license have been taken by, Bio-Rad Laboratories, Crescendo Biosciences and Roche Diagnostics, and has received research support from Genentech and Roche Diagnostics. All other authors declare no competing interests.

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Robinson, W., Lindstrom, T., Cheung, R. et al. Mechanistic biomarkers for clinical decision making in rheumatic diseases. Nat Rev Rheumatol 9, 267–276 (2013). https://doi.org/10.1038/nrrheum.2013.14

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