Multiplex immune serum biomarker profiling in sarcoidosis and systemic sclerosis

¹ Dept of Respiratory Medicine, Royal Brompton & Harefield NHS Trust; and Interstitial Lung Disease Unit, Dept of Population Genetics and Gene Therapy, National Heart and Lung Institute, Imperial College School of Medicine, London, UK
² Division of Immunology, Imperial College NHS Trust, London, UK; and Kennedy Institute of Rheumatology, Imperial College
³ Dept of Respiratory Medicine, Royal Brompton & Harefield NHS Trust
⁴ Division of Medicine, Research Dept of Inflammation, Centre for Rheumatology and Connective Tissue Diseases, Royal Free and University College Medical School, University College London, London, UK
⁵ National Jewish Health, Denver Colorado, USA
⁶ Dept of Respiratory Medicine, Royal Brompton & Harefield NHS Trust; Division of Immunology, Imperial College NHS Trust, London, UK; and Dept of Immunology, Imperial College, Chelsea & Westminster Hospital Campus, London, UK

^* To whom correspondence should be addressed. E-mail: p.kelleher{at}imperial.ac.uk.

	Abstract

Multiplex protein technology has the potential to identify biomarkers for the differentiation, classification and improved understanding of the pathogenesis of interstitial lung disease. The aim of this study was to determine whether a thirty inflammatory biomarker panel could discriminate between healthy controls, sarcoidosis and systemic sclerosis (SSc) patients independently of other clinical indicators. We also evaluated whether a panel of biomarkers could differentiate between the presence/absence of lung fibrosis (PF) in SSc patients.

We measured 30 circulating biomarkers in 20 SSc patients, 21 sarcoidosis patients and 20 healthy controls using Luminex bead technology and used Fisher's discriminant function analysis to establish the groups of classification mediators.

There were significant differences in median concentration measurements between study groups for 20 of the mediators, but with considerable range overlap between the groups, limiting group differentiation by single analyte measurements. However, a 17 analyte biomarker model correctly classified 90% of study individuals to their respective group whilst another 14 biomarker panel correctly identified the presence of PF in SSc patients.

These findings, if they are corroborated by independent studies in other centres, have potential for clinical application and may generate novel insights into the modulation of immune profiles during disease evolution.