Towards personalised medicine in psoriasis

Abstract

Psoriasis is a chronic inflammatory disease of the skin with a strong genetic basis. In the past decade, great leaps have been made in understanding the molecular basis of psoriasis, and with this new knowledge, better treatment options were introduced for those with recalcitrant psoriasis. However, despite the plethora of new treatment options and biologics to treat the most difficult cases of psoriasis, dermatologists are still confronted with the heterogeneity of treatment effects for psoriasis in the area of treatment response as well as adverse drug effects. The field of personalised medicine is still nascent but holds much promise for chronic debilitating diseases like psoriasis. The ultimate goal of personalised medicine in psoriasis is allowing clinicians to predict who will get the disease, whether it will be a short benign or long debilitating course and who will get complications from the disease. More importantly, it will allow clinicians to better tailor treatment options for patients, avoiding drug toxicities and achieving long-term remission for patients. Personalised medicine includes a broad interdisciplinary research area (including both basic and applied approaches) and consequently various approaches can be pursued to personalise medicine. The primary aim of this thesis was to explore several strategies that could ultimately lead to personalised care for psoriasis patients. Since RNAi is a promising tool to personalise treatments, we explored the potential of RNAi-mediated gene suppression as a new targeted, patient-friendly topical therapy for psoriasis patients. To this end, preclinical models systems (in vitro and in vivo) were developed, which are indispensable tools in the discovery and development process of new drugs. We show the potential of a formulation consisting of siRNA-containing liposomes to deliver a specific siRNA to the epidermis of a skin humanised-mouse model for psoriasis and to inhibit psoriasis-specific genes. Our proposed models will serve to validate other strategies in therapeutic development in the future. Another goal was to optimise the current use of biologics in psoriasis. Therefore, we explored the usefulness of measuring anti-drug antibodies and serum trough levels to guide a clinician’s decisions making when dealing with non-response or adverse reactions to biologics. We provide a treatment paradigm, which can serve as a tool to personalise treatment for psoriasis patients treated with certain biologics. Biomarkers are of increasing importance for personalised medicine, with applications including diagnosis, prognosis, and selection of targeted therapies. In this work, we describe the detection of a miRNA signature in whole blood of patients, which could serve as a molecular signature of the disease. It is our aim to check in the future whether this signature can be used to predict phenotype evolution, and/or response to certain treatment. In conclusion, with this work we provide a first step into possible ways to personalised care for psoriasis patients. Future research will be necessary to assess the usefulness and clinical utility of these different strategies