W36 - Plasma Levels of the MiR-193b/365a Cluster in Combination with Clinical Parameters Predict Response to Lactococcus Lactis-based Antigen-specific Combination Therapy

Abstract Text: Combining systemic immunomodulation with disease-relevant antigens could provide longer-term solutions for preventing and even reversing autoimmune type 1 diabetes (T1D). Our team established that a combination therapy (CT), composed of a short-course low-dose anti-CD3 treatment with oral delivery of genetically-modified Lactococcus lactis (L. lactis) bacteria secreting full proinsulin plus the anti-inflammatory cytokine IL-10 (LL-PINS+IL-10), was effective in reversing T1D in the non-obese diabetic (NOD) mouse model. Overall disease remission was 45% by the CT (n=110) compared to 0% in untreated controls (n=13; P< 0.01) that remained hyperglycaemic. Here, we aimed to identify robust peripheral biomarkers for prediction of CT response using circulating cell-free microRNAs (miRNAs). Using a TaqMan™ miRNA array, we identified a miR-193b/365a cluster that was significantly overexpressed in plasma of non-responders compared to responders mice before CT initiation. Combining plasma expression of the miR-193b/365a cluster with clinical parameters (i.e., age and glycaemia at CT initiation) allowed prediction of CT outcome with 83% specificity and 89% sensitivity. Furthermore, we exploited CITE-sequencing (CITE-seq), a multimodal phenotyping method that simultaneously measures RNA and cell surface proteins at single cell level, to investigate the immune cell types regulated by the identified miRNA signature. We selected high-confidence miR-193b/365a target genes and scored their expression in CITE-seq profiled immune cells. Interestingly, increased levels of miR-365-3p and miR-193-3p in NR mice could influence several lymphoid and myeloid cell types. In conclusion, the miR-193b/365a cluster may serve as a novel circulating biomarker that provides additional support for individualized therapy with the L. lactis-based CT.