Biomarker search in rheumatic diseases through conventional and emerging proteomic technologies

Abstract

There are more than 200 rheumatic diseases, which are the second leading cause of incapacitation worldwide and affect about 2 billion people, mainly women. This thesis focuses especially on two of the most common: osteoarthritis (OA) and rheumatoid arthritis (RA). Despite the differences between them, they all produce similar symptoms (joint pain, stiffness and even loss of functionality), although their current diagnosis and treatment are limited. The standard diagnosis includes the use of imaging techniques, which can be harmful to the patient, and the analysis of non-specific markers. OA treatment is aimed at alleviating pain and improving the functionality of the joints, although joint replacement may be even necessary at the last stages of the disease; while RA treatment includes various therapeutic strategies through trial-error. Due to these limitations in diagnosis and treatment, there is a great need to find biomarkers that facilitate the understanding of the pathological processes that take place, in order to better specify the diagnosis and effective treatment for the management of these diseases. Particularly, in this thesis, different proteomic studies based on mass spectrometry (MS) and immunoassays have been carried out, with the aim of finding proteins with potential biomarker value in RA and OA, which could facilitate classification, diagnosis and subsequent selection of effective therapies. In the first study, the search for a biomarker protein panel has been carried out for monitoring disease activity in RA patients, one of the major limitations for the corresponding selection of effective and specific therapies that could help to remit the characteristic acute episodes of this pathology. Initially, a panel of 11 candidate proteins has been identified by MS and relative quantification with iTRAQ labeling in depleted plasma pools of RA patients with extreme disease activities. In order to confirm the trend of these 11 proteins, 80 individual plasma samples of RA patients with different disease activities have been analyzed by targeted MS, with the aid of standard labeled peptides, of which 5 have been verified as potential biomarkers. Finally, 4 of them (SAA1, AACT, HPT and A1AG1) have been validated by ELISA in 420 plasma samples from patients with RA, healthy donors and controls of other analogous diseases. Hence, this validated panel could be useful for the diagnosis of autoimmune inflammatory rheumatic diseases such as RA and disease activity monitoring, crucial for proper follow-up and treatment. In the second and third studies, two different types of more emerging proteomic techniques have been carried out in order to find biomarkers in OA. On the one hand, two independent peptide studies have been carried out by means of MS in cartilage secretomes and synovial fluid and serum samples from OA patients and healthy donors. Peptidomics can be of great interest in OA, since the deterioration of cartilage is linked to various processes, among which, the action of proteases that produce neopeptides with possible biomarker role for OA diagnosis or monitoring stands out. Thus, 8 PRELP, CLUS, CILP1, COMP and MGP neopeptides were significantly altered in cartilage secretomes of OA patients, whose release seems to be also dependent on the affected joint. In addition, 6 neopeptides belonging to APOA4, ITIH4, CO3 and KNG1 have been altered in serum pools of OA patients and healthy donors, although no confirmatory statistical analysis has been performed yet. On the other hand, two hybrid immunoaffinity-based techniques coupled to mass spectrometry (IA-MS) have been developed for the detection of two specific cartilage proteins (CILP1 and PRG4) in serum samples. An immuno-MALDI (iMALDI) assay for the detection of PRG4 and another of SISCAPA-MRM for the analysis of CILP1 have been developed. Although the tendency of these proteins is to be increased in OA patients versus healthy controls, this alteration has not become significant yet in the analyzed small cohort of serum samples.