Inflammatory pathways and predictive biomarkers in sarcoidosis

Abstract

Despite decades of both basic and clinical research, our understanding of sarcoidosis is only beginning. At present, treatment options for sarcoidosis are both limited as well as hampered by a high prevalence of bothersome side effects. Consequently, there is need for more research to unravel the molecular basis of the disease, its various phenotypes/endotypes and identify associated biomarkers. This pursuit is not only important for improving patient care but also to provide the patient with better prediction of the long-term outcome. This thesis aimed to pave the way for precision medicine for sarcoidosis care by identifying novel predictive and therapeutic biomarkers in form of proteins or signaling pathways. Chapter 2 will provide an overview of current knowledge on biomarkers and disease pathology in sarcoidosis. In addition to existing biomarkers, this overview will also explore new biomarkers for diagnosis and prognosis as well as predictive for response to treatment of sarcoidosis. In the search for potential new biomarkers, there has been an increased interest in extracellular vesicles (EVs). Chapter 3 will focus on the use of EVs as a new medium for predictive biomarkers. In this pilot study, the predictive potential of four proteins is studied, comparing their concentration in serum to that in EVs. In Chapter 4 targeted proteomics by OLINK will be used to identify potential biomarkers predictive for treatment response. Of the 92 proteins studied in patient cohorts treated with either prednisone or methotrexate, twenty-five proteins are identified. A replication cohort will be used to confirm the predictability of the identified proteins and to study their related pathways with the aim of finding mechanisms of action of prednisone or methotrexate. In Chapter 5 we will continue our search for potential biomarkers in EV proteins by performing a proteomics approach using LC-MS/MS. Proteins that are significantly different between patients with sarcoidosis and healthy controls will be studied further to see what pathways are involved in the disease. In addition, proteins that are differently expressed between responders and non-responders to treatment with either prednisone or methotrexate are also identified. The top 10 differently expressed proteins will be validated by measuring them in a larger second cohort. Moreover, protein concentrations are measured over time in an additional prospective cohort to see how they behave during treatment. Data on successful treatment of sarcoidosis patients with JAK/STAT and mTORC1 inhibitors suggest that these immunological pathway could also be explored as predictive biomarkers or therapeutic targets. In Chapter 6 the activation of the mTORC1 signaling pathway will be studied with the use of immunohistochemistry in granulomas of Dutch patients with sarcoidosis, GPA, EGPA and HP. Results of the staining will be studied in relation to disease course. Chapter 7 will continue the exploration of immunological pathways as predictive biomarkers and will demonstrate the activation of the JAK-STAT and the NLRP3 inflammasome signaling pathways in Dutch patients with sarcoidosis. In this chapter specific ‘signaling endotypes’ will be evaluated in relation to disease course.