A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort.
Oscar AlcazarSung-Ting ChuangGang RenMitsunori OgiharaBobbie-Jo M Webb-RobertsonErnesto S NakayasuPeter BuchwaldMidhat H AbdulredaPublished in: bioRxiv : the preprint server for biology (2024)
Results further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.