Related Experiment Video

Updated: Jun 3, 2025

Author Spotlight: Advancing Type 1 Diabetes Research Using Innovative Pancreatic Slice Platforms

Author Spotlight: Advancing Type 1 Diabetes Research Using Innovative Pancreatic Slice Platforms

Published on: March 15, 2024

Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium

Michael E McCullough¹, Lisa R Letourneau-Freiberg¹, Rochelle N Naylor^1,2

¹Department of Medicine, The University of Chicago, Chicago, IL, USA.

Journal of Diabetes Science and Technology

|January 9, 2025

Abstract:

Monogenic diabetes mellitus (MDM) is a group of relatively rare disorders caused by pathogenic variants in key genes that result in hyperglycemia. Lack of identified cases, along with absent data standards, and limited collaboration across institutions have hindered research progress. To address this, the UChicago Monogenic Diabetes Registry (UCMDMR) and UChicago Data for the Common Good (D4CG) created a national consortium of MDM research institutions called the PREcision DIabetes ConsorTium (PREDICT). Following the D4CG model, PREDICT has successfully established a multicenter MDM data commons. PREDICT has created a consensus data dictionary that will be utilized to address critical gaps in understanding of these rare types of diabetes. This approach may be useful for other rare conditions that would benefit from access to harmonized pooled data.

Insights

Researchers established the PREcision DIabetes ConsorTium (PREDICT) to pool data for monogenic diabetes mellitus (MDM). This national consortium created a data commons and dictionary to advance understanding of rare diabetes types.

Area of Science:

Endocrinology
Genetics
Data Science

Background:

Monogenic diabetes mellitus (MDM) comprises rare genetic disorders causing hyperglycemia.
Research is limited by scarce cases, lack of data standards, and poor institutional collaboration.

Purpose of the Study:

To establish a national consortium for monogenic diabetes mellitus research.
To create a multicenter data commons for harmonized data.

Main Methods:

Formation of the PREcision DIabetes ConsorTium (PREDICT) national consortium.
Development of a consensus data dictionary for MDM research.
Leveraging the UChicago Data for the Common Good (D4CG) model.

Main Results:

Successfully established a multicenter MDM data commons.
Created a consensus data dictionary to standardize MDM data.
Facilitated collaboration among MDM research institutions.

Conclusions:

The PREDICT consortium addresses critical gaps in understanding rare diabetes.
This data commons and dictionary approach can advance MDM research.
The model may be applicable to other rare diseases requiring pooled data.

Read full analysis

Keywords:

data commons data dictionary data governance data sharing data standards monogenic diabetes

More Related Videos

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19

Published on: July 5, 2022

High Resolution 3D Imaging of the Human Pancreas Neuro-insular Network

High Resolution 3D Imaging of the Human Pancreas Neuro-insular Network

Published on: January 29, 2018

Related Concept Videos

Diabetes: Management and Pharmacotherapy

Diabetes: Management and Pharmacotherapy

The therapy for diabetes aims to alleviate hyperglycemia-related symptoms, prevent acute metabolic decompensation, and reduce chronic end-organ complications. Glycemic control is evaluated through short-term (self-monitoring, continuous glucose monitoring) and long-term (A1c, fructosamine) metrics, enabling near real-time tracking of blood glucose levels and reflecting glycemic control over specific time frames.
Insulin remains the cornerstone of treatment for most patients with type 1 and many...

Diabetes: Symptoms, Diagnosis, and Complications

Diabetes: Symptoms, Diagnosis, and Complications

For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

Articles linked to this work by shared authors, journal, and citation graph.

β-Cell Dysfunction Identifies Individuals With Single Autoantibody Positivity at Increased Risk of Type 1 Diabetes Progression.

Diabetes care·2026

Efficacy and safety of mazdutide in adults with obesity or overweight: a US-based, multicentre, phase 2, randomised, placebo-controlled clinical trial.

The lancet. Diabetes & endocrinology·2026

Sustainable Community-Wide Model to Enhance Cancer Data Usage and Utility.

JCO clinical cancer informatics·2026

SARS-CoV-2 and diabetes: a post-pandemic reappraisal.

Diabetologia·2026

Extended Follow-up of Type 1 Diabetes Immunotherapy Trial Participants Suggests Benign Side Effect Profile.

Diabetes care·2026

Cagrilintide-semaglutide (CagriSema) as an add-on to basal insulin in adults with type 2 diabetes (REIMAGINE 3): a randomised, double-blind, placebo-controlled, multicentre, phase 3 study.

Lancet (London, England)·2026

See all related articles