Skip to main content

Single-cell immune transcriptomics reveals an inflammatory-inhibitory set-point spectrum in autoimmune diabetes.

JCI insight2025-12-01PubMed
Total: 87.0Innovation: 9Impact: 8Rigor: 9Citation: 8

Summary

Single-cell profiling of >400,000 PBMCs across new-onset T1D, LADA, and controls maps a spectrum from high NF-κB/EGFR-driven inflammation (T1D) to restrained effector activity via HLA-C–KIR checkpoints (LADA). The study proposes the NF-κB/EGFR–JAK/STAT gradient and HLA-C–KIR axis as tractable therapeutic targets to preserve β-cell function.

Key Findings

  • PBMC composition was similar across cohorts; qualitative signaling differences underlay disease heterogeneity.
  • T1D showed pan-lineage NF-κB/EGFR/MAPK/hypoxia activation with TNF-centered communication and enhanced MHC signaling.
  • LADA exhibited suppressed NF-κB/EGFR, moderate JAK/STAT tone, reinforced HLA-C–KIR inhibitory checkpoints, and stabilized CD8+ T cell synapses via HLA-C–CD8.
  • Single-cell V(D)J analysis revealed multiclonal, patient-unique repertoires, emphasizing signaling context over receptor convergence.

Clinical Implications

Suggests biomarker-guided stratification (e.g., NF-κB/EGFR activity, HLA-C–KIR interactions) to tailor immunotherapies aimed at preserving β-cell function, and cautions that peripheral immune qualitatives—not cell counts—may drive heterogeneity.

Why It Matters

This mechanistic atlas reframes autoimmune diabetes as an adjustable immune set point, highlighting druggable pathways/checkpoints with potential to stratify and tailor immunomodulation across T1D and LADA.

Limitations

  • Peripheral blood may not fully represent pancreatic islet immunity
  • Cross-sectional design; functional in vivo validation of targets not reported

Future Directions

Prospective studies integrating islet tissue, longitudinal immune profiling, and interventional testing of the NF-κB/EGFR and HLA-C–KIR axes.

Study Information

Study Type
Case-control
Research Domain
Pathophysiology
Evidence Level
III - Cross-sectional case-control comparison using single-cell multi-omics across disease groups
Study Design
OTHER