Skip to main content
Home
Latest news
Browse topics
Lupus Rheumatoid arthritis Spondyloarthropathies COVID-19 Browse all topics
In focus
Bimekizumab: Dual IL-17A/IL-17F inhibition in SpA Anifrolumab for the treatment of SLE JAK inhibitor safety: Weighing up the data and understanding the risks Rituximab and rheumatology practice in the COVID-19 era Safety snapshot: Upadacitinib in patients with PsA Repurposing rheumatology drugs for COVID-19 Telemedicine in rheumatology: COVID-19 and beyond Managing PsA in resource-limited settings
Conferences
ACR Convergence 2022 EULAR 2022 Congress
About us
Medicine Matters Rheumatology
EXTENDED SEARCH
Top

22-05-2018 | Systemic sclerosis | Review | Article

Existing and novel biomarkers for precision medicine in systemic sclerosis

Journal: Nature Reviews Rheumatology

Authors: Peter J. Wermuth, Sonsoles Piera-Velazquez, Joel Rosenbloom, Sergio A. Jimenez

Publisher: Nature Publishing Group UK

Login to get access

Abstract

The discovery and validation of biomarkers resulting from technological advances in the analysis of genomic, transcriptomic, lipidomic and metabolomic pathways involved in the pathogenesis of complex human diseases have led to the development of personalized and rationally designed approaches for the clinical management of such disorders. Although some of these approaches have been applied to systemic sclerosis (SSc), an unmet need remains for validated, non-invasive biomarkers to aid in the diagnosis of SSc, as well as in the assessment of disease progression and response to therapeutic interventions. Advances in global transcriptomic technology over the past 15 years have enabled the assessment of microRNAs that circulate in the blood of patients and the analysis of the macromolecular content of a diverse group of lipid bilayer membrane-enclosed extracellular vesicles, such as exosomes and other microvesicles, which are released by all cells into the extracellular space and circulation. Such advances have provided new opportunities for the discovery of biomarkers in SSc that could potentially be used to improve the design and evaluation of clinical trials and that will undoubtedly enable the development of personalized and individualized medicine for patients with SSc.

Glossary
Cutaneous induration
Thickening of the dermal and hypodermal layers of the skin as a result of oedema, inflammation or infiltration of immune cells.
Selected reaction monitoring
An emerging targeted mass spectrometry technique for peptide biomarker discovery and validation that is able to quantify the hundreds to several thousands of peptides that are present in complex biofluids in a single experiment.
Aptamers
Short single-stranded modified oligonucleotides that are able to bind to proteins, peptides and small molecules with extremely high specificity.
Biomarker sensitivity
The ability of a biomarker to be measured with adequate precision and with a magnitude of change capable of detection.
Biomarker specificity
The ability of a biomarker to distinguish between patients with different disease subtypes or between patients who do and do not respond to therapy.
Literature
1.
Snyder, M., Du, J. & Gerstein, M. Personal genome sequencing: current approaches and challenges. Genes Dev. 24, 423–431 (2010).PubMedPubMedCentralCrossRef
2.
Snyder, M., Weissman, S. & Gerstein, M. Personal phenotypes to go with personal genomes. Mol. Syst. Biol. 5, 273 (2009).PubMedPubMedCentralCrossRef
3.
Laufer, V. A., Chen, J. Y., Langefeld, C. D. & Bridges, S. L. Jr. Integrative approaches to understanding the pathogenic role of genetic variation in rheumatic diseases. Rheum. Dis. Clin. North Am. 43, 449–466 (2017).PubMedCrossRef
4.
Streeter, O. E. Jr, Beron, P. J. & Iyer, P. N. Precision medicine: genomic profiles to individualize therapy. Otolaryngol. Clin. North Am. 50, 765–773 (2017).PubMedCrossRef
5.
Collins, D. C., Sundar, R., Lim, J. S. & Yap, T. A. Towards precision medicine in the clinic: from biomarker discovery to novel therapeutics. Trends Pharmacol. Sci. 38, 25–40 (2017).PubMedCrossRef
6.
Hood, L. & Flores, M. A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized, and participatory. Nat. Biotechnol. 29, 613–624 (2012).
7.
Gabrielli, A., Avvedimento, E. V. & Krieg, T. Scleroderma. N. Engl. J. Med. 360, 1989–2003 (2009).PubMedCrossRef
8.
Allanore, Y. et al. Systemic sclerosis. Nat. Rev. Dis. Primers 1, 15002 (2015).PubMedCrossRef
9.
McCray, C. J. & Mayes, M. D. Update on systemic sclerosis. Curr. Allergy Asthma Rep. 15, 25 (2015).PubMedCrossRef
10.
Denton, C. P. & Khanna, D. Systemic sclerosis. Lancet 390, 1685–1699 (2017).PubMedCrossRef
11.
Jimenez, S. A. & Derk, C. T. Following the molecular pathways toward an understanding of the pathogenesis of systemic sclerosis. Ann. Intern. Med. 140, 37–50 (2004).PubMedCrossRef
12.
Varga, J. & Abraham, D. Systemic sclerosis: A prototypic multisystem fibrotic disorder. J. Clin. Invest. 117, 557–567 (2007).PubMedPubMedCentralCrossRef
13.
Katsumoto, T. R., Whitfield, M. L. & Connolly, M. K. The pathogenesis of systemic sclerosis. Annu. Rev. Pathol. 6, 509–537 (2011).PubMedCrossRef
14.
Ciechomska, M., van Laar, J. & O’Reilly, S. Current frontiers in systemic sclerosis pathogenesis. Exp. Dermatol. 24, 401–406 (2015).PubMedCrossRef
15.
Stern, E. P. & Denton, C. P. The pathogenesis of systemic sclerosis. Rheum. Dis. Clin. North Am. 41, 367–382 (2015).PubMedCrossRef
16.
Pattanaik, D. et al. Pathogenesis of systemic sclerosis. Front. Immunol. 6, 272 (2015).PubMedPubMedCentralCrossRef
17.
Young, A. & Khanna, D. Systemic sclerosis: a systemic review on therapeutic management from 2011 to 2014. Curr. Opin. Rheumatol. 27, 241–248 (2015).PubMedPubMedCentralCrossRef
18.
Nagaraja, V., Denton, C. P. & Khanna, D. Old medications and new targeted therapies in systemic sclerosis. Rheumatology 54, 1944–1953 (2015).PubMedCrossRef
19.
Mendoza, F. A., Mansoor, M. & Jimenez, S. A. Treatment of rapidly progressive systemic sclerosis: current and future perspectives. Expert Opin. Orphan Drugs 4, 31–47 (2016).PubMedCrossRef
20.
Mayes, M. D. et al. Prevalence, incidence, survival, and disease characteristics of systemic sclerosis in a large US population. Arthritis Rheum. 48, 2246–2255 (2003).PubMedCrossRef
21.
Steen, V. D. & Medsger, T. A. Changes in causes of death in systemic sclerosis, 1972–2002. Ann. Rheum. Dis. 66, 940–944 (2007).PubMedPubMedCentralCrossRef
22.
Barnes, J. & Mayes, M. D. Epidemiology of systemic sclerosis: incidence, prevalence, survival, risk factors, malignancy, and environmental triggers. Curr. Opin. Rheumatol. 24, 165–170 (2012).PubMedCrossRef
23.
Hummers, L. K. The current state of biomarkers in systemic sclerosis. Curr. Rheumatol. Rep. 12, 34–39 (2010).PubMedPubMedCentralCrossRef
24.
Castro, S. V. & Jimenez, S. A. Biomarkers in systemic sclerosis. Biomark. Med. 4, 133–147 (2010).PubMedCrossRef
25.
Abignano, G., Buch, M., Emery, P. & Del Galdo, F. Biomarkers in the management of scleroderma: an update. Curr. Rheumatol. Rep. 13, 4–12 (2011).PubMedCrossRef
26.
Castelino, F. V. & Varga, J. Current status of systemic sclerosis biomarkers: applications for diagnosis, management and drug development. Expert Rev. Clin. Immunol. 9, 1077–1090 (2013).PubMedCrossRef
27.
Affandi, A. J., Radstake, T. R. & Marut, W. Update on biomarkers in systemic sclerosis: tools for diagnosis and treatment. Semin. Immunopathol. 37, 475–487 (2015).PubMedPubMedCentralCrossRef
28.
Hasegawa, M. Biomarkers in systemic sclerosis: their potential to predict clinical courses. J. Dermatol. 43, 29–38 (2016).PubMedCrossRef
29.
Ligon, C. & Hummers, L. K. Biomarkers in scleroderma: progressing from association to clinical utility. Curr. Rheumatol. Rep. 18, 17 (2016).PubMedCrossRef
30.
Manetti, M. Emerging biomarkers in systemic sclerosis. Curr. Opin. Rheumatol. 28, 606–612 (2016).PubMedCrossRef
31.
NIH Definitions Working Group in Biomarkers and Surrogate Endpoints: Clinical Research and Applications: Proceedings of the NIH-FDA Conference, Bethesda, MD, 15–16 April 1999, in ICS 1205, 1e (International Congress) Ch. 1 (ed. Downing, G.) 1–9 (Elsevier, Amsterdam, 2000).
32.
Lesko, L. J. & Atkinson, A. J. Jr. Use of biomarkers and surrogate endpoints in drug development and regulatory decision making: criteria, validation, strategies. Annu. Rev. Toxicol. 41, 347–366 (2001).CrossRef
33.
Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69, 89–95 (2001).CrossRef
34.
Anderson, J. E. et al. Methods and biomarkers for the diagnosis and prognosis of cancer and other diseases: towards personalized medicine. Drug. Resist. Updat. 9, 198–210 (2006).PubMedCrossRef
35.
Collins, C. D. et al. The application of genomic and proteomic technologies in predictive, preventive and personalized medicine. Vascul. Pharmacol. 45, 258–267 (2006).PubMedCrossRef
36.
Isserlin, R. & Emili, A. Nine steps to proteomic wisdom: a practical guide to using protein-protein interaction networks and molecular pathways as a framework for interpreting disease proteomic profiles. Proteom. Clin. Appl. 1, 1156–1168 (2007).CrossRef
37.
Kostka, D. & Spang, R. Finding disease specific alterations in the co-expression of genes. Bioinformatics 20 (Suppl. 1), S32–S36 (2004).
38.
Xu, M. et al. An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer. BMC Genomics 9 (Suppl. 1), S12 (2008).PubMedPubMedCentralCrossRef
39.
Ross, J. S. Biomarkers and drug development 2009. Expert Opin. Med. Diagn. 3, 471–478 (2009).PubMedCrossRef
40.
Wagner, J. A. Overview of biomarkers and surrogate endpoints in drug development. Dis. Markers 18, 41–46 (2002).PubMedPubMedCentralCrossRef
41.
Colburn, W. A. & Lee, J. W. Biomarkers, validation and pharmacokinetic-pharmacodynamic modelling. Clin. Pharmacokinet. 42, 997–1022 (2003).PubMedCrossRef
42.
Venitz, J. Using exposure-response and biomarkers to streamline drug development. Ernst Schering Res. Found. Workshop 59, 47–63 (2007).CrossRef
43.
Sarker, D. & Workman, P. Pharmacodynamic biomarkers for molecular cancer therapeutics. Adv. Cancer Res. 96, 213–268 (2007).PubMedCrossRef
44.
Hollebecque, A., Massard, C. & Soria, J. C. Implementing precision medicine initiatives in the clinic: a new paradigm in drug development. Curr. Opin. Oncol. 26, 340–306 (2014).PubMedCrossRef
45.
Carrigan, P. & Krahn, T. Impact of biomarkers on personalized medicine. Handb. Exp. Pharmacol. 232, 285–311 (2016).PubMedCrossRef
46.
Fleming, T. R., DeGruttola, V., & DeMets, D. L. Surrogate endpoints. AIDS Clin. Rev. 1997–1998, 129–143 (1998).
47.
Lafyatis, R. & Jimenez, S. A. in Scleroderma: From Pathogenesis to Comprehensive Management Ch. 16 (eds Varga, J. et al.) 245–260 (Springer, New York, 2017).
48.
Hindorff, L. A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA 106, 9362–9367 (2009).PubMedPubMedCentralCrossRef
49.
Wray, N. R. et al. Pitfalls of predicting complex traits from SNPs. Nat. Rev. Genet. 14, 507–515 (2013).PubMedPubMedCentralCrossRef
50.
Peters, B. A. et al. Accurate whole-genome sequencing and haplotyping from 20 human cells. Nature 487, 190–195 (2012).PubMedPubMedCentralCrossRef
51.
Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10, 57–63 (2009).PubMedPubMedCentralCrossRef
52.
Kurkurba, K. R. & Montgomery, S. B. RNA sequencing and analysis. Cold Spring Harb. Protoc. 2015, 951–969 (2015).
53.
Favicchio, R. et al. Strategies in functional proteomics: Unveiling the pathways to precision oncology. Cancer Lett. 382, 86–94 (2016).PubMedCrossRef
54.
Zhou, L. et al. Clinical proteomics-driven precision medicine for targeted therapy: current overview and future perspectives. Expert Rev. Proteom. 13, 367–381 (2016).CrossRef
55.
Honda, K. et al. Proteomic approaches to the discovery of cancer biomarkers for early detection and personalized medicine. Jpn J. Clin. Oncol. 43, 103–109 (2013).PubMedCrossRef
56.
Huang, L., Michael, S. A., Chen, Y. & Wu, H. Current advances in highly multiplexed antibody-based single-cell proteomic measurements. Chem. Asian J. 12, 1680–1691 (2017).PubMedCrossRef
57.
Hathout, Y. Proteomic methods for biomarker discovery and validation. Are we there yet? Expert Rev. Proteom. 12, 329–331 (2015).CrossRef
58.
Richens, J. L., Lunt, E. A., Sanger, D., McKenzie, G. & O’Shea, P. Avoiding nonspecific interactions in studies of the plasma proteome: practical solutions to prevention of nonspecific interactions for label-free detection of low-abundance plasma proteins. J. Proteome Res. 8, 5103–5110 (2009).PubMedCrossRef
59.
Bruderer, R. et al. New targeted approaches for the quantification of data-independent acquisition mass spectrometry. Proteomics 17, 1700021 (2017).CrossRef
60.
Anderson, N. L. & Anderson, N. G. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell. Proteom. 1, 845–867 (2002).CrossRef
61.
Garabedian, A. et al. Towards discovery and targeted peptide biomarker detection using nanoESI-TIMS-TOF MS. J. Am. Soc. Mass Spectrom. https://​doi.​org/​10.​1007/​s13361-017-1787-8 (2017).PubMedCrossRefPubMedCentral
62.
Ishizaki, J. et al. Targeted proteomics reveals promising biomarkers of disease activity and organ involvement in antineutrophil cytoplasmic antibody-associated vasculitis. Arthritis Res. Ther. 19, 218 (2017).PubMedPubMedCentralCrossRef
63.
Nie, S. et al. Deep-dive targeted quantification for ultrasensitive analysis of proteins in nondepleted human blood plasma/serum and tissues. Anal. Chem. 89, 9139–9146 (2017).PubMedPubMedCentralCrossRef
64.
Kuster, B., Schirle, M., Mallick, P. & Aebersold, R. Scoring proteomes with proteotypic peptide probes. Nat. Rev. Mol. Cell Biol. 6, 577–583 (2005).PubMedCrossRef
65.
Mallick, P. et al. Computational prediction of proteotypic peptides for quantitative proteomics. Nat. Biotechnol. 25, 125–131 (2007).PubMedCrossRef
66.
Ellington, A. D. & Szostak, J. W. In vitro selection of RNA molecules that bind specific ligands. Nature 346, 818–822 (1990).PubMedCrossRef
67.
Tuerk, C. & Gold, L. Systematic evolution of ligands by exponential enrichment: RNA Ligands to bacteriophage T4 DNA polymerase. Science 249, 505–510 (1990).PubMedCrossRef
68.
Gramolini, A., Lau, E. & Lui, P. P. Identifying low-abundance biomarkers: aptamer-based proteomics potentially enables more sensitive detection in cardiovascular diseases. Circulation 134, 286–289 (2016).PubMedCrossRef
69.
Yoshida, Y., Waga, I. & Horii, K. Quantitative and sensitive protein detection strategies based on aptamers. Proteom. Clin. Appl. 6, 574–580 (2012).CrossRef
70.
Thiviyanathan, V. & Gorenstein, D. G. Aptamers and the next generation of diagnostic reagents. Proteom. Clin. Appl. 6, 563–573 (2012).CrossRef
71.
Fleming, T. R. & DeMets, D. L. Surrogate end points in clinical trials: are we being misled? Ann. Intern. Med. 125, 605–613 (1996).PubMedCrossRef
72.
Temple, R. Are surrogate markers adequate to assess cardiovascular disease drugs? JAMA 282, 790–795 (1999).PubMedCrossRef
73.
Perez-Gracia, J. L. Strategies to design clinical studies to identify predictive biomarkers in cancer research. Cancer Treat. Rev. 53, 79–97 (2017).PubMedCrossRef
74.
Wilhelm-Benartzi, C. S. et al. Challenges and methodology in the incorporation of biomarkers in cancer clinical trials. Crit. Rev. Oncol. Hematol. 110, 49–61 (2017).PubMedCrossRef
75.
Chau, C. H., Rixe, O., McLeod, H. & Figg, W. D. Validation of analytic methods for biomarkers used in drug development. Clin. Cancer Res. 14, 5967–5976 (2008).PubMedPubMedCentralCrossRef
76.
U.S. Food & Drug Administration. Guidance for industry — pharmacogenomics data submissions. U.S. Food & Drug Administration https://​www.​fda.​gov/​downloads/​drugs/​guidancecomplian​ceregulatoryinfo​rmation/​guidances/​ucm079849.​pdf (2005).
77.
Goodsaid, F. & Frueh, F. Biomarker qualification pilot process at the U.S. Food and Drug Administration. AAPS J. 9, E105–108 (2007).PubMedPubMedCentralCrossRef
78.
Lesko, L. J. & Atkinson Jr, A. J. Use of biomarkers and surrogate endpoints in drug development and regulatory decision making: criteria, validation, strategies. Pharmacol. Toxicol. 41, 347–366 (2001).
79.
Boers, M., Brooks, P., Strand, C. V. & Tugwell, P. The OMERACT filter for outcome measures in rheumatology. J. Rheumatol. 25, 198–199 (2004).
80.
Lassere, M. A users guide to measurement in medicine. Osteoarthritis Cartilage 14 (Suppl. 1), 10–14 (2006).CrossRef
81.
Prentice, R. L. Surrogate endpoints in clinical trials: definition and operational criteria. Stat. Med. 8, 431–440 (1989).PubMedCrossRef
82.
U.S. Food & Drug Administration. Guidance for industry and FDA staff — qualification process for drug development tools. U.S. Food & Drug Administration http://​www.​fda.​gov/​downloads/​drugs/​guidancecomplian​ceregulatoryinfo​rmation/​guidances/​ucm230597.​pdf (2014).
83.
Seibold, J. R. & McCloskey, D. A. Skin involvement as a relevant outcome measure in clinical trials of systemic sclerosis. Curr. Opin. Rheumatol. 9, 571–575 (1997).PubMedCrossRef
84.
Merkel, P. A. et al. OMERACT 6. Current status of outcome measure development for clinical trials in systemic sclerosis: report from OMERACT 6. J. Rheumatol. 30, 1630–1647 (2003).PubMed
85.
Furst, D. et al. Systemic sclerosis — continuing progress in developing clinical measures of response. J. Rheumatol. 34, 1194–1200 (2007).PubMed
86.
Khanna, D. & Merkel, P. A. Outcome measures in systemic sclerosis: an update on instruments and current research. Curr. Rheumatol. Rep. 9, 151–157 (2007).PubMedCrossRef
87.
Khanna, D. et al. The American College of Rheumatology provisional composite response index for clinical trials in early diffuse cutaneous systemic sclerosis. Arthritis Rheumatol. 68, 299–311 (2016).PubMedPubMedCentralCrossRef
88.
Kahaleh, M. B. et al. A modified scleroderma skin scoring method. Clin. Exp. Rheumatol. 4, 367–369 (1986).PubMed
89.
Furst, D. E. et al. The modified Rodnan skin score is an accurate reflection of skin biopsy thickness in systemic sclerosis. J. Rheumatol. 25, 84–88 (1998).PubMed
90.
Steen, V. D. & Medsger, T. A. Jr. Improvement in skin thickening in systemic sclerosis associated with improved survival. Arthritis Rheum. 44, 2828–2835 (2001).PubMedCrossRef
91.
Kaldas, M. et al. Sensitivity to change of the modified Rodnan skin score in diffuse systemic sclerosis — assessment of individual body sites in two large randomized controlled trials. Rheumatology 48, 1143–1146 (2009).PubMedPubMedCentralCrossRef
92.
Ziemek, J. et al. The relationship between skin symptoms and the scleroderma modification of the health assessment questionnaire, the modified Rodnan skin score, and skin pathology in patients with systemic sclerosis. Rheumatology 55, 911–917 (2016).PubMedPubMedCentralCrossRef
93.
Khanna, D. et al. Standardization of the modified Rodnan skin score for use in clinical trials of systemic sclerosis. J. Scleroderma Relat. Disord. 2, 11–18 (2017).PubMedCrossRef
94.
Kissin, E. Y. et al. Durometry for the assessment of skin disease in systemic sclerosis. Arthritis Rheum. 55, 603–609 (2006).PubMedCrossRef
95.
Merkel, P. A. et al. Validity, reliability, and feasibility of durometers measurements of scleroderma skin disease in a multicenter treatment trail. Arthritis Rheum. 59, 699–705 (2008).PubMedCrossRef
96.
Moore, T. L., Lunt, M., McManus, B., Anderson, M. E. & Herrick, A. L. Seventeen-point dermal ultrasound scoring system — a reliable measure of skin thickness in patients with systemic sclerosis. Rheumatology 42, 1559–1563 (2003).PubMedCrossRef
97.
Abignano, G. & Del Galdo, F. Quantitating skin fibrosis: innovative strategies and their clinical implications. Curr. Rheumatol. Rep. 16, 404 (2014).PubMedCrossRef
98.
Santiago, T. et al. A preliminary study using virtual touch imaging and quantification of the assessment of skin stiffness in systemic sclerosis. Clin. Exp. Rheumatol. 34 (Suppl. 100), S137–S141 (2016).
99.
Merkel, P. A. et al. Patterns and predictors of change in outcome measures in clinical trials in scleroderma: an individual patient meta-analysis of 629 subjects with diffuse cutaneous systemic sclerosis. Arthritis Rheum. 64, 3420–3429 (2012).PubMedPubMedCentralCrossRef
100.
Moore, O. A. et al. Quantifying change in pulmonary function as a prognostic marker in systemic sclerosis-related interstitial lung disease. Clin. Exp. Rheumatol. 33 (Suppl. 91), S111–S116 (2015).PubMed
101.
Goh, N. S. et al. Short term pulmonary function trends are predictive of mortality in interstitial lung disease associated with systemic sclerosis. Arthritis Rheumatol. 69, 1670–1678 (2017).PubMedCrossRef
102.
Campbell, R. M. & LeRoy, E. C. Pathogenesis of systemic sclerosis: a vascular hypotheses. Semin. Arthritis Rheum. 4, 351–368 (1975).PubMedCrossRef
103.
LeRoy, E. C. Systemic sclerosis. A vascular perspective. Rheum. Dis. Clin. North Am. 22, 675–694 (1996).PubMedCrossRef
104.
Fleming, J. N. & Schwartz, S. M. The pathology of scleroderma vascular disease. Rheum. Dis. Clin. North Am. 34, 41–55 (2008).PubMedCrossRef
105.
Kahaleh, B. Vascular disease in scleroderma: mechanisms of vascular injury. Rheum. Dis. Clin. North Am. 34, 57–71 (2008).PubMedCrossRef
106.
Trojanowska, M. Cellular and molecular aspects of vascular dysfunction in systemic sclerosis. Nat. Rev. Rheumatol. 6, 453–460 (2010).PubMedCrossRef
107.
Matucci-Cerinic, M., Kahaleh, B. & Wigley, F. M. Review: evidence that systemic sclerosis is a vascular disease. Arthritis Rheum. 65, 1953–1962 (2013).PubMedCrossRef
108.
Altorok, N., Wang, Y. & Kahaleh, B. Endothelial dysfunction in systemic sclerosis. Curr. Opin. Rheumatol. 26, 615–620 (2014).PubMedCrossRef
109.
Pattanaik, D., Brown, M. & Postlethwaite, A. E. Vascular involvement in systemic sclerosis (scleroderma). J. Inflamm. Res. 4, 105–125 (2011).PubMedPubMedCentral
110.
Herrick, A. L. Pathogenesis of Raynaud’s phenomenon. Rheumatology 44, 587–596 (2005).PubMedCrossRef
111.
Grassi, W. & De Angelis, R. Capillaroscopy: questions and answers. Clin. Rheumatol. 26, 2009–2016 (2007).PubMedCrossRef
112.
Maricq, H. R. & LeRoy, E. C. Patterns of finger capillary abnormalities in connective tissue disease by “wide-field” microscopy. Arthritis Rheum. 16, 619–628 (1973).PubMedCrossRef
113.
Herrick, A. L. & Cutolo, M. Clinical implications from capillaroscopic analysis in patients with Raynaud’s phenomenon and systemic sclerosis. Arthritis Rheum. 62, 2595–2604 (2010).PubMedCrossRef
114.
Maricq, H. R. et al. Diagnostic potential of in vivo microscopy in scleroderma and related disorders. Arthritis Rheum. 23, 183–189 (1980).PubMedCrossRef
115.
Maricq, H. R., Weinberger, A. B. & LeRoy, E. C. Early detection of scleroderma-spectrum disorders by in vivo capillary microscopy: a prospective study of patients with Raynaud’s phenomenon. J. Rheumatol. 9, 289–291 (1983).
116.
Cutolo, M. et al. Assessing microvascular changes in systemic sclerosis diagnosis and management. Nat. Rev. Rheumatol. 6, 578–587 (2010).PubMedCrossRef
117.
Chen, Z. Y. et al. Association between fluorescent antinuclear antibodies, capillary patterns, and clinical features in scleroderma spectrum disorders. Am. J. Med. 77, 812–822 (1984).PubMedCrossRef
118.
Caramaschi, P. et al. Scleroderma patients nailfold videocapillaroscopic patterns are associated with disease subset and disease severity. Rheumtology 46, 1566–1569 (2007).CrossRef
119.
Cutolo, M. et al. Nailfold videocapillaroscopic patterns and serum autoantibodies in systemic sclerosis. Rheumatology 43, 719–726 (2004).PubMedCrossRef
120.
Smith, V. et al. Do worsening scleroderma capillaroscopic patterns predict future severe organ involvement? A pilot study. Ann. Rheum. Dis. 71, 1636–1639 (2012).PubMedCrossRef
121.
Sulli, A. et al. Timing of transition between capillaroscopic patterns in systemic sclerosis. Arthritis Rheum. 64, 821–825 (2012).PubMedCrossRef
122.
Bredemeier, M. et al. Nailfold capillary microscopy can suggest pulmonary disease activity in systemic sclerosis. J. Rheumatol. 31, 286–294 (2004).PubMed
123.
Hofstee, H. M. et al. Nailfold capillary density is associated with the presence and severity of pulmonary arterial hypertension in systemic sclerosis. Ann. Rheum. Dis. 68, 191–195 (2009).PubMedCrossRef
124.
Sebastiani, M. et al. Predictive role of capillaroscopic skin ulcer risk index in systemic sclerosis: a multicenter validation study. Ann. Rheum. Dis. 71, 67–70 (2012).PubMedCrossRef
125.
Lambova, S. & Muller-Ladner, U. Capillaroscopic findings in systemic sclerosis — are they associated with disease duration and presence of digital ulcers. Discov. Med. 12, 413–418 (2011).PubMed
126.
Cutolo, M., Pizzorni, C., Sulli, A. & Smith, V. Early diagnostic and predictive value of capillaroscopy in systemic sclerosis. Curr. Rheumatol. Rev. 9, 249–253 (2013).PubMedCrossRef
127.
Cutolo, M. et al. Nailfold videocapillaroscopic features and other clinical risk factors for digital ulcers in systemic sclerosis: A multicenter prospective cohort study. Arthritis Rheumatol. 68, 2527–2539 (2016).PubMedPubMedCentralCrossRef
128.
van den Hoogen, F. et al. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 65, 2737–2747 (2013).
129.
Nihtyanova, S. I. & Denton, C. P. Autoantibodies as predictive tools in systemic sclerosis. Nat. Rev. Rheumatol. 6, 112–116 (2010).PubMedCrossRef
130.
Villalta, D. et al. Diagnostic accuracy and predictive value of extended autoantibody profile in systemic sclerosis. Autoimmun. Rev. 12, 114–120 (2012).PubMedCrossRef
131.
Domsic, R. T. Scleroderma: the role of serum autoantibodies in defining specific clinical phenotypes and organ system involvement. Curr. Opin. Rheumatol. 26, 646–652 (2014).PubMedPubMedCentralCrossRef
132.
Sirotti, S. et al. Personalized medicine in rheumatology: the paradigm of serum autoantibodies. Auto. Immun. Highlights 8, 10 (2017).PubMedPubMedCentralCrossRef
133.
Mueller, M. et al. Relation of nailfold capillaries and autoantibodies to mortality in patients with Raynaud phenomenon. Circulation 133, 509–517 (2016).PubMedCrossRef
134.
Sulli, A. et al. Progression of nailfold microvascular damage and antinuclear antibody pattern in systemic sclerosis. J. Rheumatol. 40, 634–639 (2013).PubMedCrossRef
135.
Xu, G. J. et al. Systemic autoantigen analysis identifies a distinct subset of scleroderma with coincident cancer. Proc. Natl Acad. Sci. USA 113, 57526–57534 (2016).
136.
Milano, A. et al. Molecular subsets in the gene expression signatures of scleroderma skin. PLoS ONE 3, e2696 (2008).PubMedPubMedCentralCrossRef
137.
Sargent, J. L. & Whitfield, M. L. Capturing the heterogeneity in systemic sclerosis with genome-wide expression profiling. Expert Rev. Clin. Immunol. 7, 463–473 (2011).PubMedPubMedCentralCrossRef
138.
Sargent, J. L. et al. A TGFβ-responsive gene signature is associated with a subset of diffuse scleroderma with increased disease severity. J. Invest. Dermatol. 130, 694–705 (2010).PubMedCrossRef
139.
Pendergrass, S. A. et al. Limited systemic sclerosis patients with pulmonary arterial hypertension show biomarkers of inflammation and vascular injury. PLoS ONE 5, e12106 (2010).PubMedPubMedCentralCrossRef
140.
Lenna, S. et al. Increased expression of endoplasmic reticulum stress and unfolded protein response genes in peripheral blood mononuclear cells from patients with limited cutaneous systemic sclerosis and pulmonary arterial hypertension. Arthritis Rheum. 65, 1357–1366 (2013).PubMedPubMedCentralCrossRef
141.
Derrett-Smith, E. C. et al. Limited cutaneous systemic sclerosis skin demonstrates distinct molecular subsets separated by a cardiovascular development gene expression signature. Arthritis Res. Ther. 19, 156 (2017).PubMedPubMedCentralCrossRef
142.
Mahoney, J. M. et al. Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms. PLoS Comput. Biol. 11, e1004005 (2015).PubMedPubMedCentralCrossRef
143.
Farina, G., Lafyatis, D., Lemaire, R. & Lafyatis, R. A four-gene biomarker predicts skin disease in patients with diffuse cutaneous systemic sclerosis. Arthritis Rheum. 62, 580–588 (2010).PubMedPubMedCentralCrossRef
144.
Rice, L. M. et al. A longitudinal biomarker for the extent of skin disease in patients with diffuse cutaneous systemic sclerosis. Arthritis Rheumatol. 67, 3004–3015 (2015).PubMedPubMedCentralCrossRef
145.
Lofgren, S. et al. Integrated multicohort analysis of systemic sclerosis identifies robust transcriptional signature of disease severity. JCI Insight 1, e89073 (2016).PubMedPubMedCentralCrossRef
146.
Taroni, J. N. et al. Molecular characterization of systemic sclerosis esophageal pathology identifies inflammatory and proliferative signatures. Arthritis Res. Ther. 17, 194 (2015).PubMedPubMedCentralCrossRef
147.
Taroni, J. N. et al. A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis. Genome Med. 9, 27 (2017).PubMedPubMedCentralCrossRef
148.
Hinchcliff, M. et al. Molecular signatures in skin associated with clinical improvement during mycophenolate treatment in systemic sclerosis. J. Invest. Dermatol. 133, 1979–1989 (2013).PubMedPubMedCentralCrossRef
149.
Chakravarty, E. F. et al. Gene expression changes reflect clinical response in placebo-controlled randomized trial of abatacept in patients with diffuse cutaneous systemic sclerosis. Arthritis Res. Ther. 17, 159 (2015).PubMedPubMedCentralCrossRef
150.
Rice, L. M. et al. Fresolimumab treatment decreases biomarkers and improves clinical symptoms in systemic sclerosis patients. J. Clin. Invest. 125, 2795–2807 (2015).PubMedPubMedCentralCrossRef
151.
Taroni, J. N., Martyanov, V., Mahoney, J. M. & Whitfield, M. L. A functional genomic meta-analysis of clinical trials in systemic sclerosis: toward precision medicine and combination therapy. J. Clin. Invest. Dermatol. 137, 1033–1041 (2017).CrossRef
152.
Etheridge, A. et al. The complexity, function and application of RNA in circulation. Front. Genet. 4, 115 (2013).PubMedPubMedCentralCrossRef
153.
Etheridge, A. et al. Extracellular microRNA: a new source of biomarkers. Mutat. Res. 717, 85–90 (2011).PubMedPubMedCentralCrossRef
154.
Witwer, K. W. Circulating microRNA biomarker studies: pitfalls and potential solution. Clin. Chem. 61, 56–63 (2015).PubMedCrossRef
155.
Bartel, D. P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297 (2004).PubMedCrossRef
156.
Eulalio, A., Huntzinger, E. & Izaurralde, E. Getting to the root of miRNA-mediated gene silencing. Cell 132, 9–14 (2008).PubMedCrossRef
157.
Treiber, T., Treiner, N. & Meister, G. Regulation of microRNA biogenesis and function. Thromb. Haemost. 107, 605–610 (2012).PubMedCrossRef
158.
Olive, V., Minella, A. C. & He, L. Outside the coding genome, mammalian microRNAs confer structural and functional complexity. Sci. Signal. 8, re2 (2015).PubMedPubMedCentralCrossRef
159.
Tanaka, S. et al. Alteration of circulating miRNAs in SSc: miR-30b regulates the expression of PDGF receptor β. Rheumatology 52, 1963–1972 (2013).PubMedCrossRef
160.
Makino, K. et al. Circulating miR-142-3p levels in patients with systemic sclerosis. Clin. Exp. Dermatol. 37, 34–39 (2012).PubMedCrossRef
161.
Honda, N. et al. miR-150 down-regulation contributes to the constitutive type I collagen overexpression in scleroderma dermal fibroblasts via the induction of integrin β3. Am. J. Pathol. 182, 206–216 (2013).PubMedCrossRef
162.
Honda, N. et al. TGF-β-mediated downregulation of microRNA-196a contributes to the constitutive upregulated type I collagen expression in scleroderma dermal fibroblast. J. Immunol. 18, 3323–3331 (2012).CrossRef
163.
Makino, K. et al. The downregulation of microRNA let-7a contributes to the excessive expression of type I collagen in systemic and localized scleroderma. J. Immunol. 190, 3905–3915 (2013).PubMedCrossRef
164.
Sing, T. et al. microRNA-92a expression in the sera and dermal fibroblast increases in patients with scleroderma. Rheumatology 51, 1550–1556 (2012).PubMedCrossRef
165.
Wuttge, D. M. et al. Specific autoantibody profiles and disease subgroups correlate with circulating micro-RNA in systemic sclerosis. Rheumatology 54, 2100–2107 (2015).PubMedCrossRef
166.
Théry, C., Ostrowsky, M. & Segura, E. Membrane vesicles as conveyors of immune responses. Nat. Rev. Immunol. 9, 581–593 (2009).PubMedCrossRef
167.
Gyorgy, B. et al. Membrane vesicles, current state-of-the-art: emerging role of extracellular vesicles. Cell. Mol. Life Sci. 68, 2667–2688 (2011).PubMedPubMedCentralCrossRef
168.
Raposo, G. & Stoorvogel, W. Extracellular vesicles: exosomes, microvesicles, and friends. J. Cell Biol. 200, 373–383 (2013).PubMedPubMedCentralCrossRef
169.
Colombo, M., Raposo, G. & Thery, C. Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles. Annu. Rev. Cell Dev. Biol. 30, 255–289 (2014).PubMedCrossRef
170.
Théry, C., Zitvogel, L. & Amigorena, S. Exosomes: composition, biogenesis and function. Nat. Rev. Immunol. 2, 569–579 (2002).PubMedCrossRef
171.
Vlassov, A. V., Magdaleno, S., Setterquist, R. & Conrad, R. Exosomes: current knowledge of their composition, biological functions, and diagnostic and therapeutic potentials. Biochim. Biophys. Acta 1820, 940–948 (2012).PubMedCrossRef
172.
Pant, S., Hilton, H. & Burczynski, M. E. The multifaceted exosome: biogenesis, role in normal and aberrant cellular function, and frontiers for pharmacological and biomarker opportunities. Biochem. Pharmacol. 83, 1484–1494 (2012).PubMedCrossRef
173.
Lotvall, J. et al. Minimal experimental requirements for definition of extracellular vesicles and their functions: a position statement from the International Society for Extracellular Vesicles. J. Extracell. Vesicles 3, 26913 (2014).PubMedCrossRef
174.
Hsu, V. W. & Prekeris, R. Transport at the recycling endosome. Curr. Opin. Cell Biol. 22, 528–534 (2010).PubMedPubMedCentralCrossRef
175.
Hessvik, N. P. & Llorente, A. Current knowledge on exosome biogenesis and release. Cell. Mol. Life Sci. 75, 193–208 (2018).PubMedCrossRef
176.
Ratajczak, J. et al. Embryonic stem cell-derived microvesicles reprogram hematopoietic progenitors: evidence for horizontal transfer of mRNA and protein delivery. Leukemia 20, 847–856 (2006).PubMedCrossRef
177.
Skog, J. et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat. Cell Biol. 10, 1470–1476 (2008).PubMedPubMedCentralCrossRef
178.
Valadi, H. et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol. 9, 654–659 (2007).PubMedCrossRef
179.
Gusachenko, O. N., Zenkova, M. A. & Vlassov, V. V. Nucleic acids in exosomes: disease markers and intercellular communication molecules. Biochemistry 78, 1 (2013).PubMed
180.
Shurtleff, M. J. et al. Broad role for YBX1 in defining the small noncoding RNA composition of exosomes. Proc. Natl Acad. Sci. USA 114, E8987–E8995 (2017).PubMedPubMedCentralCrossRef
181.
Shelke, G. V., Jang, S. D., Yin, Y., Lasser, C. & Lotvall, J. Human mast cells release extracellular vesicle-associated DNA. Matters https://​doi.​org/​10.​19185/​matters.​201602000034 (2016).CrossRef
182.
Nemeth, A. et al. Antibiotic-induced release of small extracellular vesicles (exosomes) with surface-associated DNA. Sci. Rep. 7, 8202 (2017).PubMedPubMedCentralCrossRef
183.
Simpson, R. J., Lim, J. W., Moritz, R. L. & Mathivanan, S. Exosomes: proteomic insights and diagnostic potential. Expert Rev. Proteom. 6, 267–283 (2009).CrossRef
184.
Simpson, R. J., Jensen, S. S. & Lim, J. W. Proteomic profiling of exosomes: current perspectives. Proteomics 8, 4083–4099 (2008).PubMedCrossRef
185.
Thery, C., Amigorena, S., Raposo, G. & Clayton, A. Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Curr. Protoc. Cell Biol. 30, 3.22.1–3.22.29 (2006).CrossRef
186.
Zeringer, E., Barta, T., Li, M. & Vlassov, A. V. Strategies for isolation of exosomes. Cold Spring Harb. Protoc. 2015, 319–323 (2015).PubMed
187.
Michalska-Jakubus, M., Kowal-Bielecka, O., Smith, V., Cutolo, M. & Krasowska, D. Plasma endothelial microparticles reflect the extent of capillaroscopic alterations and correlate with the severity of involvement in systemic sclerosis. Microvasc. Res. 110, 24–31 (2017).PubMedCrossRef
188.
Zhu, H., Luo, H. & Zuo, X. MicroRNAs: their involvement in fibrosis pathogenesis and use as diagnostic biomarkers in scleroderma. Exp. Mol. Med. 45, e41 (2013).PubMedPubMedCentralCrossRef
189.
Steen, S. O. et al. The circulating cell-free microRNA profile in systemic sclerosis is distinct from both healthy controls and systemic lupus erythematosus. J. Rheumatol. 42, 214–221 (2015).PubMedCrossRef
190.
Wermuth, P. J., Piera-Velazquez, S. & Jimenez, S. A. Exosomes isolated from serum of systemic sclerosis patients display alterations in their content of profibrotic and antifibrotic microRNA and induce a profibrotic phenotype in cultured normal dermal fibroblast. Clin. Exp. Rheumatol. 35 (Suppl. 106), 21–30 (2017).PubMedPubMedCentral
191.
Simpson, R. J., Kalra, H. & Mathivanan, S. ExoCarta as a resource for exosomal research. J. Extracell. Vesicles. 1, 18374 (2012).CrossRef
192.
Keerthikumar, S. et al. ExoCarta: A web-based compendium of exosomal cargo. J. Mol. Biol. 248, 688–692 (2016).CrossRef
193.
Kalra, H. et al. Vesiclepedia: A compendium for extracellular vesicles with continuous community annotation. PLoS Biol. 10, e1001450 (2012).PubMedPubMedCentralCrossRef
194.
Kim, D. K., Lee, J., Simpson, R. J., Lotvall, J. & Gho, Y. S. EVpedia: A community web resource for prokaryotic and eukaryotic extracellular vesicles research. Semin. Cell Dev. Biol. 40, 4–7 (2015).PubMedCrossRef
195.
Choi, D. S., Kim, D. K., Kim, Y. K. & Gho, Y. S. Proteomics of extracellular vesicles: exosomes and ectosomes. Mass Spectrom. Rev. 34, 474–490 (2015).PubMedCrossRef
196.
Schey, K. L., Luther, J. M. & Rose, K. L. Proteomics characterization of exosome cargo. Methods 87, 75–82 (2015).PubMedPubMedCentralCrossRef
197.
Abramowicz, A., Widlak, P. & Pietrowska, M. Proteomic analysis of exosomal cargo: the challenge of high purity vesicle isolation. Mol. Biosyst. 12, 1407–1419 (2016).PubMedCrossRef
198.
Wermuth, P. J., Piera-Velazquez, S. & Jimenez, S. A. Identification of novel systemic sclerosis biomarkers employing aptamer proteomic analysis. Rheumatology https://​doi.​org/​10.​1093/​rheumatology/​kex404 (2017).CrossRef
199.
Burmester, G. R., Bijlsma, J. W. J., Cutolo, M. & McInnes, I. B. Managing rheumatic and musculoskeletal diseases — past, present and future. Nat. Rev. Rheumatol. 13, 443–448 (2017).PubMedCrossRef
Image Credits