Multicomponent biomarkers: A novel method for accurate diagnosis of psoriasis

The accurate diagnosis of psoriasis has remained a challenge, as no disease-specific biomarkers have yet been identified. Currently, the diagnosis of chronic inflammatory diseases relies mainly on the assessment of visible symptoms or the histological features of the biopsy. This approach is heavily reliant on the experience of the clinician and, therefore, may lead to misdiagnosis as there are numerous different chronic inflammatory skin diseases that may present similar clinical features. Hence, the need for diagnostic biomarkers is clear. Although different investigations have reported the discovery of potential psoriasis biomarkers, still no accurate and reliable biomarker is available. Rather than searching for a single valid biomarker, we propose that applying a multicomponent bio-marker-based approach would result in a higher degree of success and translation into clinical practice. An extensive review of published studies to identify the most relevant psoriasis-specific biomarker candidates was conducted. This led us to conclude that the expression levels of specific genes in the skin hold the most promise as discriminatory biomarkers, resulting in the selection of five genes, the expression levels of which have been demonstrated to be exclusive for psoriasis vulgaris. We first conducted a preliminary validation study applying support vector machine-based classification and principle component analysis on the skin-derived expression data of 12 patients with psoriasis vulgaris and 12 healthy controls, previously produced in our departments. We then confirmed that the expression levels of the five genes in psoriatic lesions indeed present a unique pattern. Encouraged by these results, we continued to develop a quantitative polymerase chain reaction panel to allow the accurate measurement of expression levels for the five genes to be used in the studies to follow. Although we have yet to confirm these results in the context of other chronic inflammatory skin diseases, the results of previously published studies regarding these five genes are promising. Therefore, we are in the process of collecting additional skin samples from patients with chronic inflammatory disease (including different papulosquamous disorders and atopic dermatitis) to validate the discriminatory power of our panel. These results may further be translated to viable clinical diagnostic tests in the near future. This work was supported by the ERA Chair for Translational Genomics and Personalized Medicine at the University of Tartu