DEFINE-T2D Projects
The DEFINE-T2D has five projects that are currently underway. See a description of each of the five projects below. For more information on planned, ongoing, and completed projects, as well as the process to propose a project, visit the DEFINE-T2D Publications & Presentations site.
Project 1: Phenotypic clustering of individuals with type 2 diabetes
Description:
- This project assesses T2D subtypes and shows the utility and challenges of using established subtypes across clinical scenarios.
Aims:
- Aim 1: To apply established T2D clustering methods using clinical phenotypic data to subgroup individuals with T2D (i.e., subtypes) and assess clustering performance and describe T2D subtypes.
- Aim 2: Assess T2D subtypes with risk for clinical outcomes including progression in glycated hemoglobin (HbA1c) level and incidence of cardiovascular disease (and subtypes coronary heart disease, cerebrovascular disease, and heart failure), chronic kidney disease, retinopathy, atrial fib, and mortality, where available.
- Aim 3: Compare use of established T2D clustering methods with (3a) alternative clustering methods and (3b) use of simple clinical data to risk-stratify or predict clinical outcomes for individuals with T2D.
Project co-leads:
- Miriam Udler
- Mike Bancks
Project 2: Genetic subtyping of type 2 diabetes and prediabetes
Description:
- This project uses T2D and cardiometabolic disease polygenic scores to subtype and cluster individuals with prediabetes and T2D with the goal of developing genetic tools for early T2D identification.
Aims:
- Aim 1:To develop genetic clustering models in individuals with T2D and prediabetes using T2D partitioned polygenic risk score (pPS) derived from GWAS of T2D and related traits and characterize the clinical features and outcomes across clusters.
- Aim 2:To develop genetic clustering models in individuals with T2D and prediabetes using PRS derived from GWAS of cardiometabolic traits and characterize the clinical features and outcomes across clusters.
- Aim 3:To evaluate T2D pPS and multi-trait T2D PRS in phenotype-based T2D subtypes, and to integrate genetic and phenotypic clustering in individuals with T2D and prediabetes.
Project co-leads:
- Maggie Ng
- Josep Mercader
Project 3: Clustering of T2D patients prior to disease onset
Description:
- This project examines individuals prior to T2D onset and uses metabolomics and proteomics to determine when lifestyle prevention efforts to reduce T2D severity may be most effective.
Aims:
- Aim 1:To examine whether participants with prediabetes who go on to develop T2D during the course of longitudinal study can be distinguished from those participants with prediabetes who do not go on to develop T2D during the course of longitudinal study via the clustering of their ‘omic data.
- Aim 2: To examine whether patients with T2D can be clustered into discrete groups according to their ‘omic data, prior to meeting clinical criteria to T2D (i.e., prior to disease onset)
Project co-leads:
- Lekki Wood
- Jerry Rotter
Project 4: Optimal variables for type 2 diabetes subtyping: A comparison of diagnosis and classification algorithms
Description:
- This project compares diagnosis and classification algorithms across the DEFINE-T2D cohorts to assess the potential for contamination by other forms of diabetes and identify optimal variables for T2D subtyping.
Project co-leads:
- Alisa Manning
- Leslie Lange
Project 5: Consortium visibility project
Description:
- This projects goal is to raise awareness and highlight the clinical/translational impact of the DEFINE-T2D consortium.
Project co-leads: The BRC
- Katerina Kechris
- Leslie Lange
- Wei Perng
- Ivana Yang