Kyle J. Gaulton

Abstract Defining molecular pathways driving β-cell failure in type 2 diabetes (T2D) is challenging given donor heterogeneity. We developed an interpretable machine learning framework coupling sparse rule-based classification, pathway constrained modeling, and mitochondrial fitness stratification, applied to single-cell RNAseq from 52 human islet donors. A 50-gene classifier predicted T2D at single-cell resolution, outperforming ensemble models, with donor-level scores correlating with HbA1c.

Abstract Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can enhance biological and therapeutic discovery and improve risk prediction. Here we performed genome-wide genetic association and fine-mapping analyses in 20,355 T1D and 797,363 nondiabetic individuals of European ancestry and in 10,107 T1D and 19,639 nondiabetic individuals at the MHC locus, which identified 160 risk signals.

Abstract The SARS-CoV-2 mRNA vaccine provides effective protection against viral infection and severe disease by inducing efficient adaptive immunity. However, vaccine efficacy is decreased against emerging variants, and immune memory is relatively short-lived. Here, we added new T cell epitopes to the RBD (receptor-binding domain) mRNA vaccine and identified a SARS-CoV-2 membrane epitope that significantly improved vaccine-induced immunity and protection in vivo.