Giant cell arteritis is the most common form of vasculitis in adults. Early diagnosis and treatment plays a crucial role in preventing severe complications or even relapse. Therefore, in this project promising serological markers for diagnostic and prognostic use were identified, with the goal of enabling personalized disease management to benefit the patients.
Eingereicht von: Julia Feichtinger, PhD
Firma/Universität: Graz University of Technology; Omics Center Graz
Kooperationspartner: University Medical Centre Ljubljana, Biomedis M.B. d.o.o.
Giant cell arteritis (GCA) is the most common form of vasculitis in adults leading to inflammation of the blood vessels. Most patients who suffer from GCA are over the age of 50 and the disease is characterized by general symptoms, such as fever, fatigue and weight loss, as well as by ischemic symptoms, such as severe headaches, vision disturbances and jaw claudication. GCA etiology is unknown and even diagnosis remains difficult, as it relies on invasive temporal artery biopsies or imaging modalities (vascular ultrasound). However, early diagnosis and treatment of GCA is crucial for preventing ischemic complications.
The number of patients diagnosed with GCA by 2050 is projected to be over 3 million in Europe, North America and Oceania, representing a significant clinical and financial challenge and thereby outlining the importance of a cost-efficient method for diagnosis and prognosis. To date, there is a clear lack of serological markers for GCA diagnosis as well as for predicting GCA relapse and complications. Therefore, the Graz University of Technology is currently working on determining panels of suitable GCA biomarkers for clinical use with the goal of enabling personalized disease management.
They have identified promising GCA biomarkers including, among others, a number of acute phase parameters and interleukins (funded by Slovene Research Agency Program #P3-0314, Omics Center Graz and the company Biomedis). To screen a large number of biomarker candidates and eventually to identify promising biomarker panels, we have used a combination of methods, including literature review and meta-analysis (Burja et al., 2017 Autoimmunity Reviews) as well as statistical evaluation, clustering and principal component analysis of clinical data and analyte measurements (Luminex, ELISA and nephelometry data from the Ljubljana University Medical Centre) in the largest cohort of treatment-naïve patients (n=97) to date. The results show that a number of biomarkers are not only promising candidates for early diagnosis but also for predicting GCA complications, such as relapse and visual disturbances.