Advantages of Multiplex Proteomics in Clinical Immunology The Case of Rheumatoid Arthritis: Novel IgXPLEX™ Planar Microarray Diagnosis

Clinical multiplex diagnostic proteomics is the application of proteomic technologies to improve a patient’s clinical outcomes. The future holds impact potential for testing prognosis, diagnosis, and drug therapy, while monitoring efficacious treatment with qualitative and quantitative data. Multiplex clinical diagnostic use of novel biomarkers in body fluids to confirm presence and severity of clinical disease states, holds great promise for clinical use. Challenges for diagnostic clinics include awareness of proteome complexity in clinical samples, the effects of high-abundance proteins, such as albumin, that could mask detection of other and low abundance disease proteins or biomarkers. Standardized approaches to sample collection and preparation, new analytical techniques and novel algorithms for bio-statistical analysis will facilitate release of the great potential of clinical multiplex diagnostic proteomics. A sensitive RA assay has been developed for the simultaneous measurement of the three rheumatoid factors (RFs), RF-IgA, IgG, and IgM, with the option to simultaneously measure anti-cyclic citrullinated peptide (anti-CCP) IgG antibodies using IgXPLEX™ technology. Testing 10-ىL serum samples, SQI’s multiplex microarray rheumatoid arthritis assay provides both positive/ negative as well as qualitative/semi-quantitative results for anti-CCP IgG, RF-IgA, IgG, and IgM in each sample well on a 96-well microtiter-formatted microarray plate. Signal detection uses sensitive fluorescent-tagged markers captured onto planar microarray spots and read in a microarray scanner. Each result is verified with confidence confirmation technology and validating quality controls in every sample well. For an 80-RA positive patient cohort, the 4-PLEX profile sensitivity was determined at 82.5%. The specificity for the 44 RA healthy control cohort was determined at 97.7%. The multiplex data also demonstrated that a patients’ severity of disease profile, mild to severe, correlates the status of RA biomarkers to disease status