TY - JOUR T1 - Dialogue: High-throughput studies in rheumatology: time for unsupervised clustering? JF - Lupus Science & Medicine JO - Lupus Sci Med DO - 10.1136/lupus-2021-000643 VL - 8 IS - 1 SP - e000643 AU - George Bertsias Y1 - 2021/12/01 UR - http://lupus.bmj.com/content/8/1/e000643.abstract N2 - In complex autoimmune rheumatic diseases, high-throughput technologies simultaneously analysing dozens, hundreds or thousands of biological cues (genes, metabolites, serum proteins etc) have long been considered valuable in obtaining unique pathogenic insights while facilitating the discovery of therapeutic targets and biomarkers for diagnosis, monitoring and prognosis.1In the current issue of Lupus Science and Medicine, Brunekreef et al2 used a custom chip-based microarray to probe serum samples for a total 57 known and new IgG autoantibodies and explore their diagnostic utility in SLE. By comparing the prevalence of each autoantibody in 483 patients with SLE and 1397 disease controls (including 361 healthy individuals), they found that anti-double stranded(ds)DNA antibodies and antibodies against Cytosine-phosphate-Guanine (anti-CpG) DNA motifs could best discriminate SLE versus control groups with corresponding area under the receiver operating curve (AUC) values of 0.800 and 0.756, respectively.2 Notably, 15.1% of patients with SLE negative for anti-dsDNA tested positive for anti-CpG DNA antibodies, therefore suggesting added diagnostic value. Although the exact specificity of CpG-targeting antibodies was not explored and some cross-reactivity with anti-dsDNA antibodies … ER -