Investigate the Role of Gut Microbiota in the Development of Type 1 Diabetes Using TEDDY Study

Title: Investigate the Role of Gut Microbiota in the Development of Type 1 Diabetes Using TEDDY Study Project Abstract: Gut dysbiosis in early childhood might cause or contribute to early-onset type 1 diabetes (T1D). The Environmental Determinants of Diabetes in the Young (TEDDY) study has established a nested case–control (NCC) microbiome study for islet autoimmunity (IA) and T1D, which provides an opportunity to study microbial factors involved in T1D development. However, only limited, subtle microbial associations with IA or T1D have been detected in TEDDY so far, possibly because the longitudinal microbiome data have been analyzed in cross- sectional fashion, neglecting the heterogeneity of the disease. We hypothesize that temporal changes in gut microbiota in various microbiome maturation phases are associated with the development of T1D as delineated by four distinct IA phenotypes and overt T1D. We propose to develop two novel joint modeling tools that integrate longitudinal microbiome measurements and times to onset of IA phenotypes and T1D and to implement these methods in a secondary analysis of TEDDY microbiome data. Our new tools will embrace unique challenges presented by TEDDY’s NCC longitudinal microbiome study. We have three aims. 1) Identify microbial biomarkers for specific IA phenotypes. We propose a novel joint modeling framework under the NCC study design to characterize the association between time-varying microbial abundances and the onset of specific IA phenotypes. We will apply the proposed statistical method to TEDDY data to pinpoint which microbial biomarkers, either taxonomically or functionally, are associated with the occurrence of specific IA phenotypes. 2) Identify microbial biomarkers that predict the risk of progression from IA to T1D. We will extend the statistical method to allow for the modeling of two-stage T1D progression (from birth to the onset of IA, and from onset of IA to overt T1D) and the discovery of microbial biomarkers that predict T1D progression using TEDDY data. 3) Evaluate and refine these statistical methods and disseminate companion software to the community. The proposed new methods will allow us to discover novel microbial biomarkers for each IA phenotype and T1D in the TEDDY study, broadening our understanding of the cause of T1D and ultimately promoting the development of new strategies to prevent or delay the disease.