Identification of Novel Protein Biomarkers as Predictors of Type 1 Diabetes Development and Progression, and as Indicators of Treatment Efficacy

The aim was to identify novel protein biomarkers as predictors of Type 1 diabetes (T1D) development and progression in NOD mice, and as indicators of treatment efficacy. Heparin plasma was obtained from 6-weeks old NOD mice divided into Control, Prehyperglycemic, Diabetic, and IgM-treated groups. Plasma samples were analyzed using SomaScan Proteomic platform. 7288 somamers were evaluated. Cyclic Loess normalized Log2 signal was used to analyze the ADAT files (Boulder BioConsulting). Linear regression models were fit and ANOVA performed. Extracted pairwise contrasts, coefficients and predictions were used for downstream analysis in R. BH FDR correction was performed for p values. Differentially expressed (DE) somamer selection was based on p value or q value <0.05 and/or >2 absolute fold-change criteria. GSEA v4.2.2 and Cytoscape v3.9.1 EnrichmentMap pipeline v1.1.0 was used for Pathway analysis, and enrichment results mapped as a network of gene sets. Our studies identified four significant DE proteins in the prehyperglycemic stage and seven in diabetes, with an overlap of two. 17 enriched pathways were downregulated and two upregulated with diabetes. IgM group formed a distinct cluster in principal component analysis suggesting a global effect of the treatment. IgM-treated vs. Diabetic contrast found 418 DE proteins, many associated with the treatment itself. IgM-treated vs. Prehyperglycemic + Diabetic contrast identified 386 DE proteins in a second model. IgM-treated vs. healthy controls had 334 DE proteins. 33 DE proteins in the diabetic group were maintained at normal levels with IgM therapy. Venn diagrams comparing contrasts involving IgM-treated samples showed a significant overlap of unique DE proteins. IgM downregulated ~46 pathways. To conclude, novel proteins have been identified with significant clinical potential as predictors for T1D development and progression, and for monitoring treatment efficacy. Disclosure P.Chhabra: None. M.Ma: None. K.L.Brayman: None. Funding Manning Family Foundation (GF006791)