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Clin Rheumatol. 2018 Aug 24. doi: 10.1007/s10067-018-4240-x. [Epub ahead of print]

Utility of serological biomarkers for giant cell arteritis in a large cohort of treatment-naïve patients.

Author information

1
Department of Rheumatology, University Medical Centre Ljubljana, Vodnikova cesta 62, SI-1000, Ljubljana, Slovenia.
2
Institute of Computational Biotechnology, Graz University of Technology, Petersgasse 14, 8010, Graz, Austria.
3
OMICS Center Graz, BioTechMed Graz, Stiftingtalstraße 24, 8010, Graz, Austria.
4
Faculty of Mathematics, Natural Science and Information Technologies, University of Primorska, Glagoljaška ulica 8, SI-6000, Koper, Slovenia.
5
Department of Rheumatology, University Medical Centre Ljubljana, Vodnikova cesta 62, SI-1000, Ljubljana, Slovenia. ssodin1@yahoo.com.
6
Faculty of Mathematics, Natural Science and Information Technologies, University of Primorska, Glagoljaška ulica 8, SI-6000, Koper, Slovenia. ssodin1@yahoo.com.
7
Faculty of Pharmacy, University of Ljubljana, Aškerčeva cesta 7, SI-1000, Ljubljana, Slovenia.
8
Blood Transfusion Center of Slovenia, Šlajmerjeva ulica 6, SI-1000, Ljubljana, Slovenia.
9
Faculty of Medicine, University of Ljubljana, Korytkova ulica 2, SI-1000, Ljubljana, Slovenia.

Abstract

Early diagnosis and treatment of giant cell arteritis (GCA) is crucial for preventing ischemic complications. Multiple serological markers have been identified; however, there is a distinct lack of predicting markers for GCA relapse and complications. Our main objective was to identify serological parameters in a large cohort of treatment-naïve GCA patients, which could support clinicians in evaluating the course of the disease. Clinical data was gathered, along with analyte detection using Luminex technology, ELISA, and nephelometry, among others. Unsupervised hierarchical clustering and principal component analysis of analyte profiles were performed to determine delineation of GCA patients and healthy blood donors (HBDs). Highest, significantly elevated analytes in GCA patients were SAA (83-fold > HBDs median values), IL-23 (58-fold), and IL-6 (11-fold). Importantly, we show for the first time significantly changed levels of MARCO, alpha-fetoprotein, protein C, resistin, TNC, TNF RI, M-CSF, IL-18, and IL-31 in GCA versus HBDs. Changes in levels of SAA, CRP, haptoglobin, ESR, MMP-1 and MMP-2, and TNF-alpha were found associated with relapse and visual disturbances. aCL IgG was associated with limb artery involvement, even following adjustment for multiple testing. Principal component analysis revealed clear delineation between HBDs and GCA patients. Our study reveals biomarker clusters in a large cohort of patients with GCA and emphasizes the importance of using groups of serological biomarkers, such as acute phase proteins, MMPs, and cytokines (e.g. TNF-alpha) that could provide crucial insight into GCA complications and progression, leading to a more personalized disease management.

KEYWORDS:

Biomarkers; Clustering; Complications; Giant cell arteritis; Prognosis; Relapse

PMID:
30143961
DOI:
10.1007/s10067-018-4240-x

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