April 17, 2025
Journal Article

RNA Splicing Events in Circulation Distinguish Individuals With and Without New-Onset Type 1 Diabetes

Abstract

Context: Alterations in RNA splicing may influence protein isoform diversity that contributes to or reflects the pathophysiology of certain diseases. Whereas specific RNA splicing events in pancreatic islets have been investigated in models of inflammation in vitro, how RNA splicing in the circulation correlates with or is reflective of T1D disease pathophysiology in humans remains unexplored. Objective: To use machine learning to investigate if alternative RNA splicing events differ between healthy controls and individuals with new-onset type 1 diabetes (T1D) and to determine if these splicing events provide insight into T1D pathophysiology. Methods: RNA deep sequencing was performed on whole blood samples from two independent cohorts: a training cohort consisting of 12 new-onset T1D subjects and 12 age- and gender-matched healthy controls in addition to a validation cohort of the same size and demographics. Machine learning analysis was used to identify specific isoforms that could distinguish T1D subjects from controls. Results: Distinct patterns of RNA splicing differentiated T1D subjects from healthy controls. Notably, certain splicing events, particularly involving retained introns, showed significant association with T1D. Machine learning analysis using these splicing events as features from the training cohort demonstrated high accuracy in distinguishing between T1D subjects and controls in the validation cohort. Gene Ontology pathway analysis of retained intron species showed evidence for a systemic viral response in T1D subjects. Conclusions: Alternative RNA splicing events in whole blood are significantly associated with new-onset T1D and can effectively distinguish patients from healthy individuals. These findings suggest that RNA splicing profiles could serve as biomarkers for T1D, offering the potential for early diagnosis and a better understanding of disease pathogenesis.

Published: April 17, 2025

Citation

Webb-Robertson B.M., W. Wu, J.E. Flores, L.M. Bramer, F. Syed, S.A. Tersey, and S. May, et al. 2025. RNA Splicing Events in Circulation Distinguish Individuals With and Without New-Onset Type 1 Diabetes. Journal of Clinical Endocrinology and Metabolism 110, no. 4:1148–1157. PNNL-SA-208201. doi:10.1210/clinem/dgae622

Research topics