GSE193536
Network analyses of single cell-based digital twins for individualized treatment of antigen induced arthritis in mice.
Computational treatment of digital twins of individual patients has been proposed as a strategy to personalize treatment. Systematic solutions are though currently lacking for inflammatory diseases. Here, we propose a strategy (scDrugPrio) that creates scRNA-seq based multicellular disease models that incorporate the key biological and pharmacological properties such as gene interactions within and between cell types, varying gene expression levels between cells and individuals, and inhibitory or enhancing drug effects. scDrugPrio was constructed based on joint scRNA-seq data from a mouse model of antigen induced arthritis. It was and validated by improved precision/recall for known drug targets and in vitro studies of predicted but yet unknown drug targets. When applied to human multiple sclerosis and Crohn's disease, scDrugPrio was able to stratify predicted treatments based on interindividual variations. We hence propose scDrugPrio as a solution to personalize treatment by projecting network-based drug screening to digital twins of individual patients on cellulome-, genome-and drugome-wide scales. Overall design: After pre-sensitization to mBSA, antigen induced arthritis (AIA) was triggered in 8 weeks old, female 129/Sve mice (N = 5) by intra-articular injection of methylated bovine serum (mBSA) in the left knee joint. The left knee joint of the healthy control mice (N = 4) was injected with phosphate-buffered saline (PBS,20 µL). One week after triggering, the mice were sacrificed. Successful AIA was ensured among the sick mice by immunohistochemistry and the whole left joint was prepared for scRNA-seq.