Treg gene signatures predict and measure type 1 diabetes trajectory

Area of Science:

• Immunology
• Endocrinology
• Genetics

Background:

• Type 1 diabetes (T1D) therapeutics aim to restore immune regulation and slow disease progression.
• Identifying reliable biomarkers is crucial for predicting patient response to immunotherapy and monitoring treatment efficacy.
• Previous research indicated altered Treg gene signatures (TGS) in children with new-onset T1D compared to healthy controls.

Purpose of the Study:

• To investigate the potential of TGS as an immunoregulatory biomarker in T1D.
• To develop and apply biomarker discovery pipelines for TGS analysis in various patient cohorts.
• To assess TGS's ability to predict disease progression and stratify patients for clinical trials.

Main Methods:

• nanoString technology was employed to measure TGS in sorted Tregs and peripheral blood mononuclear cells (PBMCs).
• Analysis included individuals with T1D, type 2 diabetes, healthy controls, and T1D patients undergoing immunotherapy.
• Biomarker discovery pipelines were utilized for comparative analysis across different sample groups.

Main Results:

• Altered TGS was observed in T1D cohorts (adult new-onset and cross-sectional) compared to controls, with improved biomarker sensitivity/specificity when incorporating T1D-associated SNPs.
• The TGS demonstrated distinct patterns in T1D versus type 2 diabetes, highlighting disease specificity.
• An algorithm based on TGS at T1D onset accurately predicted rapid versus slow C-peptide decline and stratified patients in a clinical trial for ustekinumab efficacy.

Conclusions:

• TGS-based biomarkers offer a promising new strategy for patient stratification in T1D.
• Measuring TGS can serve as a method to monitor autoimmune activity in individuals with T1D.
• These findings support the development of personalized immunotherapies for T1D based on individual biomarker profiles.