Boolean analysis of the transcriptomic data to identify novel biomarkers of IVIG response

Intravenous immunoglobulin (IVIG) is used to treat several autoimmune and inflammatory diseases, but some patients are refractory IVIG require alternative treatments. Identifying a biomarker that could segregate responders from non-responders has been subject of intense research. Unfortunately, previous transcriptomic studies aimed at addressing resistance have failed predict identify IVIG-non-responders. Therefore, we novel data mining technique on the publicly available Kawasaki disease (KD) treated with potential biomarkers response. By studying boolean patterns hidden in expression profiles KD undergoing therapy, identified new metabolic pathways implicated KD. These be as prior infusion. Also, analysis further extended universal might response other diseases.