Discovery and Analysis Project

Discovery and Analysis Project Project Summary Diabetes is traditionally classified in two broad categories: autoimmune Type 1 and obesity-related Type 2. Numerous phenotypically and etiologically distinct forms exist and are emerging, collectively termed “atypical diabetes”, that do not fit into either category. We hypothesize that atypical diabetes comprises a spectrum that includes numerous forms, both known (e.g., MODY/monogenic, Ketosis-Prone Diabetes) and unknown. During the current U54 funding cycle we established the Rare and Atypical Diabetes Network (RADIANT), with a well-functioning infrastructure to identify and enroll participants with atypical diabetes; a pipeline for harmonized screening and adjudication of enrolled participants; full genomic characterization of participants via whole genome sequencing; transcriptomic characterization via RNA sequencing; quantitative plasma metabolomics; patient-specific, inducible pluripotent stem cell-based molecular physiology; enrollment of informative family members; and both standard and specialized phenotyping for each participant. In the next cycle of RADIANT, we propose to continue to recruit persons with atypical forms of diabetes to fulfill the original goals, together with discovery and analysis of the mechanisms and pathways that define these new forms of diabetes, by achieving the following Aims: 1) Continue the identification, genome sequencing, transcriptomic and metabolomic interrogation, and deep phenotyping of individuals and families with atypical forms of diabetes; 2) Discover and describe new forms of monogenic diabetes; 3) Expand and enrich the growing database to characterize atypical diabetes and recognize different genotypic and phenotypic clusters; and 4) Determine the pathophysiological mechanisms of atypical diabetes genomic variants. Thus, in the next cycle of RADIANT, our collaborative, multidisciplinary and diverse group of accomplished diabetes investigators will expand our repository of atypical diabetes cases, identify new disease mechanisms, target pathogenic pathways, advance our understanding of diabetes pathophysiology and develop an improved, etiologically based classification of diabetes.