This study leverages clinical data, baseline bulk RNA-seq data from whole blood, cell type enrichment analysis to profile the response of Euro-Lupus (EL) treatment regimen, among 94 Lupus Nephritis (LN) patients and elucidate the role of adaptive and innate immune system in responders vs. non-responders. Machine learning (ML) feature selection and model generation is used in tandem with statistical tests to achieve a Receiver Operating Characteristic Curve (ROC) area under the curve (AUC) score of 0.81 for predicting response to CYC in LN patients before treatment.

Authors:

Raghav Ganesh (Presenter)
Lynbrook High School

Dmitry Rychkov, University of California, San Francisco
Sharon Chung, University of California, San Francisco
Marina Sirota, University of California, San Francisco