RARE and Atypical Diabetes Network(RADIANT)

There is considerable variability in the development and clinical presentation of diabetes. Atypical diabetes comprises both uncommon genetic syndromes as well as clusters of phenotypically distinct forms of diabetes within a spectrum between antibody-mediated type 1 diabetes (T1D) and metabolic syndrome-associated type 2 diabetes (T2D). A process to dissect the atypical forms away from the indistinct polar categories is essential to uncover their natural histories, novel mechanisms, and discover targeted therapies. The Rare and Atypical Diabetes Network is a consortium of 15 academic clinical sites led by Baylor College of Medicine (BCM) and University of Chicago. RADIANT performs whole genome sequencing (WGS), RNA sequencing, metabolomics, a standardized physical examination and a range of deeper phenotypic analyses. The University of South Florida is RADIANT’s Data Coordinating Center (DCC), and the Broad Institute, BCM and Duke University are the sequencing and metabolomics cores. In the last grant cycle, we have enrolled over 1000 participants with atypical forms of diabetes. Over 400 RADIANT participants thus far have undergone whole genome sequencing, leukocyte transcriptomics, plasma metabolomics, and a range of clinical measurements and biochemical tests, including quantification of insulin secretion and insulin sensitivity. Special interest groups within RADIANT (comprising geneticists, ‘omics experts and diabetologists) have identified 13 potential new monogenic forms and 9 phenotypically distinct clusters of atypical diabetes. The goal of the current cycle is to characterize endotypes of atypical forms of diabetes and uncover mechanistic pathways that may lead to the identification of actionable biomarkers. This proposal for an administrative supplement to RADIANT will enhance the development of Dr. Jordana Faruqi as a physician-scientist in the field of atypical diabetes. Working with an expert mentoring group, Dr. Faruqi will utilize multi-omics analyses to define the heterogeneity of autoantibody-negative, insulin deficient diabetes (ANIDD). We hypothesize that integrative multi-omics pathway analysis applied to subtypes of RADIANT’s ANIDD subgroup will reveal novel molecular pathways and identify unique molecular signatures. We will first subtype the ANIDD group using multi-omics integrative clustering (Aim 1). We will analyze phenotypic, genetic, transcriptomic and metabolomic data from the ANIDD group (N=65 currently, projected to grow to >100) by employing the integrative analysis framework iCluster. We will then elucidate molecular pathways of each ANIDD subtype through a multi-omics pathway approach and define endotypes within ANIDD (Aim 2). We will perform genomic, transcriptomic and metabolomic pathway analysis separately, then overlay these pathways to assess if there is a link between the identified genetic, transcriptomic and metabolic data. Pathway analysis may aid in identifying potential biomarkers. To accomplish these aims, we will collaborate with a team of experts within the field of computational biology who have successfully employed these techniques in cancer biology.