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- W2073131267 abstract "The presence of autoimmune disease-associated autoantibodies prior to the presentation of clinical symptoms has been well-documented, and can be exploited for the development of multiplex assays offering improved sensitivity, selectivity, and reproducibility over currently available immunodiagnostics. This study utilized high-content protein microarrays comprised of more than 5,000 human proteins, including 25 known autoantigens, to evaluate immunological profiles across panels of serum samples derived from healthy donors and Systemic Lupus Erythematosus (SLE) patients. Three statistical approaches were applied in parallel, utilizing M-statistics, volcano analysis, and fold change calculations applied to quantile normalized or unnormalized signal intensity data, to identify candidate biomarkers. Independent expression and purification of these putative autoantigens was carried out in order to develop both custom protein microarrays and Luminex bead sets for validation studies. A validation rate of approximately 70% was observed across both technology platforms when the same set of disease and normal serum samples were used as probes. Improved discrimination between the two populations was observed when Principle Component Analysis was applied to data derived from novel, protein microarray-defined proteins relative to autoantigens with annotated associated with SLE. Leave-one-out cross-validation analysis using support vector machine learning calculated a classification error rate of 3.3% for the arraydefined candidate biomarkers, relative to an error rate of 13.3% calculated for the annotated SLE biomarkers. Taken together, this study provides the experimental and statistical framework to support the adoption of protein microarray technology as a tool for immunological profiling for disease biomarker discovery." @default.
- W2073131267 created "2016-06-24" @default.
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- W2073131267 date "2008-01-01" @default.
- W2073131267 modified "2023-10-17" @default.
- W2073131267 title "Sa.27. Discovery of SLE Autoantibody Biomarkers Utilizing Protein Microarray Technology" @default.
- W2073131267 doi "https://doi.org/10.1016/j.clim.2008.03.248" @default.
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