Deciphering systemic lupus erythematosus-associated serum biomarkers reflecting apoptosis and disease activity

Deficiency of two-pore segment channel 2 contributes to systemic lupus erythematosus via regulation of apoptosis and cell cycle

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Proteomic Data Analysis for Differential Profiling of the Autoimmune Diseases SLE, RA, SS, and ANCA-Associated Vasculitis

Early and correct diagnosis of inflammatory rheumatic diseases (IRD) poses a clinical challenge due to the multifaceted nature of symptoms, which also may change over time. The aim of this study was to perform protein expression profiling of four systemic IRDs, systemic lupus erythematosus (SLE), ANCA-associated systemic vasculitis (SV), rheumatoid arthritis (RA), and Sjögren’s syndrome (SS), and healthy controls to identify candidate biomarker signatures for differential classification. A total of 316 serum samples collected from patients with SLE, RA, SS, or SV and from healthy controls were analyzed using 394-plex recombinant antibody microarrays. Differential protein expression profiling was examined using Wilcoxon signed rank test, and condensed biomarker panels were identified using advanced bioinformatics and state-of-the art classification algorithms to pinpoint signatures reflecting each disease (raw data set available at https://figshare.com/s/3bd3848a28ef6e7ae9a9.). In this study, we were able to classify the included individual IRDs with high accuracy, as demonstrated by the ROC area under the curve (ROC AUC) values ranging between 0.96 and 0.80. In addition, the groups of IRDs could be separated from healthy controls at an ROC AUC value of 0.94. Disease-specific candidate biomarker signatures and general autoimmune signature were identified, including several deregulated analytes. This study supports the rationale of using multiplexed affinity-based technologies to reflect the biological complexity of autoimmune diseases. A multiplexed approach for decoding multifactorial complex diseases, such as autoimmune diseases, will play a significant role for future diagnostic purposes, essential to prevent severe organ- and tissue-related damage.

Autoantibodies in SLE: prediction and the p value matrix

Autoantibodies (AA) and antinuclear antibodies (ANA) serve as key diagnostic and classification criteria for systemic lupus erythematosus (SLE). More than 200 different AA have been reported in SLE, although only a handful (<20) are considered "mainstream" because they are widely and routinely used in diagnostic, research and clinical medicine. Although the vast majority of AA have been relegated to the diminished status of "orphan" AA, some serve as predictors of SLE because they first appear in very early or subclinical SLE. Some AA are pathogenic, whereas others are thought to protect against or ameliorate disease progression and, hence, taken together can be used as predictive biomarkers of prognosis. Although studies have shown that specific AA are detected in the preclinical phase of SLE and are biomarkers of increased risk of developing the disease, AA are currently not widely used to predict very early SLE in individuals who have low pretest probability of disease. With the advent of multianalyte arrays with analytic algorithms, emerging evidence indicates that when certain combinations of biomarkers, such as the interferon signature and stem cell factor accompany AA and ANA, the predictive power for SLE is markedly increased.