Research Projects

Thyroid disorders rank among the most prevalent endocrine diseases globally, with India seeing a significant burden of such conditions. It is estimated that around 42 million people in India are affected by thyroid-related diseases. This may lead to development of Graves' orbitopathy (GO), a debilitating autoimmune condition caused by increased auto-antibodies against the thyroid receptor leading to an upregulation of orbital fibroblasts and consequent adipogenesis. This leads to orbital inflammation, proptosis, and, in severe cases, vision-threatening complications like dysthyroid optic neuropathy (DON), which occurs in approximately 5% of cases. Although relatively rare, it remains a significant concern due to its impact on quality of life caused by significant morbidity associated with this disease. Clinical assessment remains the cornerstone for GO diagnosis, guided by the Bartley and Gorman criteria and the Clinical Activity Score (CAS), which evaluates inflammatory activity and monitors treatment effectiveness. Radiological modalities like CT or MRI are invaluable in detecting subtle orbital changes. Given the limited treatment options and the significant morbidity associated with GO, identifying sensitive and specific biomarkers for early diagnosis and disease monitoring is crucial. This study aims to identify and validate tear and serum biomarkers in early detection, risk stratification and assessment of the course of treatment of patients with GO. Tear collection is non-invasive and rapid, making it ideal for routine clinical use. Previous studies have identified over 1,500 tear proteins, highlighting the potential for biomarker discovery. Conversely, the majority of research on this area has been done in Western countries and China, and data specific to the Indian sub continent population are lacking. This study will fill that lacuna by providing a comprehensive description of characterizing the clinic-demographic profile of GO amongst Indian patients and correlating the clinical features with the biochemical and radiological profiles of the patients. We hypothesize that specific proteins proteins in tears and serum, which could be identified through proteomics techniques and validated with the use of ddPCR would be associated with the activity and the severity of GO. These biomarkers may distinguish active from inactive disease, predict progression, and monitor therapeutic efficacy.