LAUSR

To date, Thyroid-Associated Orbitopathy (TAO), an autoimmune inflammatory disease affecting the eye, remains poorly characterised and its diagnosis challenging. The aim of this study was to investigate the tears of the TAO patients in order to identify potential biomarkers. Two independent quantitative Tandem Mass Tag™ 6-plex experiments were done. After in-solution digestion and isoelectric fractionation, the 12 fractions were analysed with a LTQ Orbitrap Velos coupled to a liquid chromatography. Raw files were searched against Swiss-Prot-AC database using Proteome Discoverer software, with a false discovery rate of 1% at peptide and protein levels. The differential proteins were then verified using orthogonal approaches in independent patients. Globally, 712 tear proteins were quantified with 2 unique peptides. Interestingly, cystatin c (TAO/controls ratio: 1.53), alpha-1 antichymotrypsin (ratio: 1.70) and retinal dehydrogenase (ratio: 0.68), displaying differential levels in the tears of TAO patients using proteomics experiments emerged as highly promising biomarkers after verification. In conclusion, this proteomics study supports the idea that tears reflect biological modifications occurring in a disease context and can therefore be a promising fluid for biomarker discovery. Moreover, our study identified three candidates that could in the future open new avenues in the diagnosis of TAO disease. SIGNIFICANCE Thyroid associated orbitopathy (TAO) is the most common disease affecting the orbit. Moreover, the later, severe stages of the disease can be sight threating [1]. On the other hand, the early sign and symptoms can be mistaken with other ocular pathologies [2]. Here we explore the modification of the tear content of the TAO patients using proteomics strategies and we proposed three new biomarker candidates, which could allow the early diagnosis of the disease and prompt action to prevent more severe stages. Moreover, our findings could also help to better understand the pathophysiology of the disease.