Daily Endocrinology Research Analysis
Evidence from a large multicenter analysis shows that remission of prediabetes can be achieved without weight loss and protects against incident type 2 diabetes, accompanied by improved insulin sensitivity and adipose redistribution. A randomized trial demonstrates that a Bayesian decision support system safely lowers HbA1c in adults with type 1 diabetes using multiple daily injections. Translational work identifies a neutrophil-enriched blood gene signature predicting teplizumab resistance acro
Summary
Evidence from a large multicenter analysis shows that remission of prediabetes can be achieved without weight loss and protects against incident type 2 diabetes, accompanied by improved insulin sensitivity and adipose redistribution. A randomized trial demonstrates that a Bayesian decision support system safely lowers HbA1c in adults with type 1 diabetes using multiple daily injections. Translational work identifies a neutrophil-enriched blood gene signature predicting teplizumab resistance across stages of type 1 diabetes, supporting precision immunotherapy.
Research Themes
- Glycemic remission beyond weight loss for diabetes prevention
- AI-driven insulin dosing decision support in type 1 diabetes
- Precision immunotherapy biomarkers predicting teplizumab response
Selected Articles
1. Prevention of type 2 diabetes through prediabetes remission without weight loss.
Post hoc analyses of PLIS, replicated in the US DPP, show that prediabetes remission can occur without weight loss and confers protection against incident T2D. Mechanisms include improved insulin sensitivity, beta-cell function, and increased beta-cell GLP-1 sensitivity, alongside a shift toward subcutaneous rather than visceral fat.
Impact: This challenges the prevailing paradigm that weight loss is the primary driver of diabetes prevention, prioritizing glycemic remission as a target. It introduces mechanistic evidence that could shift guideline emphasis beyond weight loss alone.
Clinical Implications: Prevention programs should incorporate explicit glycemic remission targets and consider therapies that improve insulin sensitivity and beta-cell GLP-1 responsiveness, not solely weight-centric goals. Risk stratification may consider fat distribution changes.
Key Findings
- Prediabetes remission occurred without weight loss and was protective against incident T2D.
- Responders showed improved insulin sensitivity, beta-cell function, and beta-cell GLP-1 sensitivity.
- Adipose tissue redistributed toward subcutaneous depots in responders vs visceral gain in nonresponders.
- Findings were reproduced in the US Diabetes Prevention Program.
Methodological Strengths
- Large multicenter randomized trial dataset with rigorous phenotyping and mechanistic endpoints
- Independent replication in the US Diabetes Prevention Program
Limitations
- Post hoc analysis; not a primary randomized comparison targeting remission without weight loss
- Sample size and duration details not specified in the abstract limit assessment of effect heterogeneity
Future Directions: Prospective trials targeting glycemic remission independent of weight change; elucidation of molecular mediators of adipose redistribution and beta-cell GLP-1 sensitivity; integration into risk-based prevention guidelines.
2. A Bayesian decision support system for automated insulin doses in adults with type 1 diabetes on multiple daily injections: a randomized controlled trial.
In a 12-week randomized trial of 84 adults with type 1 diabetes on MDI, a Bayesian decision support system reduced HbA1c by 0.4% versus a non-adaptive bolus calculator without severe hypoglycemia or DKA. The system provides weekly basal and prandial dose recommendations using CGM data.
Impact: Demonstrates clinically meaningful HbA1c reduction with an algorithmic titration tool in real-world MDI users, bridging a key gap where closed-loop is unavailable or unacceptable.
Clinical Implications: Clinicians may consider DSS tools to support weekly insulin titration for adults on MDI, potentially improving control without increasing severe hypoglycemia risk. Integration with CGM workflows is feasible.
Key Findings
- Bayesian DSS reduced HbA1c by 0.40% vs control over 12 weeks (p=0.025).
- No severe hypoglycemia or diabetic ketoacidosis occurred in either arm.
- Weekly algorithm-driven basal and prandial dosing recommendations were feasible alongside CGM.
Methodological Strengths
- Randomized controlled design with predefined primary endpoint (HbA1c change)
- Safety monitored with clinically relevant adverse events and use of CGM for objective data
Limitations
- Open-label design may introduce performance bias
- Short duration (12 weeks) and modest sample size limit long-term generalizability
Future Directions: Longer multicenter trials assessing durability, scalability, and cost-effectiveness; head-to-head comparisons with other DSS and hybrid closed-loop; evaluation in diverse populations.
3. Neutrophil-enriched gene signature correlates with teplizumab therapy resistance in different stages of type 1 diabetes.
Single-cell transcriptomics in NOD mice and human cohorts (AbATE, TN10) revealed that neutrophil-enriched gene signatures mark teplizumab resistance, while T cell–enriched signatures associate with response. A 26-gene blood signature predicted teplizumab efficacy with an AUC of 0.97.
Impact: Provides a robust, biologically grounded predictor of response to the first disease-modifying therapy in T1D, enabling precision selection and potentially improving outcomes.
Clinical Implications: Baseline blood transcriptomic profiling could be used to identify likely responders and avoid unnecessary exposure in nonresponders, informing trial design and clinical decision-making for teplizumab.
Key Findings
- Neutrophil-enriched gene signatures associate with resistance to anti-CD3 therapy; T cell–enriched signatures associate with success.
- Findings are consistent across compartments (blood, pancreas) in NOD mice and validated in human AbATE (stage 3) and TN10 (stage 2) cohorts.
- A 26-gene blood signature predicts teplizumab response with AUC 0.97 using elastic net logistic regression.
Methodological Strengths
- Integrated single-cell and bulk transcriptomics across mouse and human with cross-compartment validation
- Independent validation in two human cohorts and high-performing predictive model (AUC 0.97)
Limitations
- Observational and translational design; prospective clinical utility testing is needed
- Potential cohort-specific biases and limited sample sizes in validation sets
Future Directions: Prospective stratified trials testing teplizumab guided by the 26-gene signature; mechanistic dissection of neutrophil-driven resistance; development of CLIA-grade assays.