Evidence map›Paper›PMID 41729832›Full record

ArticleDiabetes2026

Memory Regulatory T Cells as a Biomarker of Early Type 1 Diabetes.

Davide Raineri, Silvia Savastio, Simonetta Bellone, Lorenza Scotti, Camilla Barbero-Mazzucca, Giuseppe Cappellano, Flavia Prodam, Erica Pozzi, Ivana Rabbone, Annalisa Chiocchetti

Abstract read
In one paragraph

Article in Diabetes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Davide RaineriDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.ORCID 0000-0003-3327-6305
Silvia SavastioDivision of Paediatrics, Department of Health Sciences, University of Eastern Piedmont, Novara, Italy.
Simonetta BelloneDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.
Lorenza ScottiDepartment of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
Camilla Barbero-MazzuccaDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.
Giuseppe CappellanoDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.
Flavia ProdamDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.ORCID 0000-0001-9660-5335
Erica PozziDivision of Paediatrics, Department of Health Sciences, University of Eastern Piedmont, Novara, Italy.
Ivana RabboneDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.ORCID 0000-0003-4173-146X
Annalisa ChiocchettiDepartment of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy.ORCID 0000-0002-4349-1087

Funding

Italian Ministry of Education, University and Research program Departments of Excellence 2018-2022
6 · The paper itself

Abstract

Type 1 diabetes (T1D) is the most common chronic autoimmune disease in children, driven by a breakdown in self-tolerance and T cell-mediated immune attack of pancreatic β-cells. There are no biomarkers to effectively diagnose autoimmunity before disease onset and clinical symptom development. Here, we applied deep multiparametric immunophenotyping to compare immune landscapes in 38 patients with new-onset T1D, 24 siblings, and 18 healthy control participants (HCs). Patients with T1D underwent clinical and metabolic evaluations. Immune populations in fresh whole-blood samples were analyzed using a panel of 26 antibodies, detecting 39 different cell populations. Memory regulatory T cells (memory Tregs) were significantly increased in patients with T1D (P < 0.05) and their siblings (P < 0.01) compared with HCs but not between patients with T1D and siblings. Memory Tregs were associated with disease status and age in multivariable analysis. There was a positive correlation between age and memory Tregs in the HC and sibling groups but not in patients with T1D. Baseline memory Treg levels in siblings resembled those of patients with T1D. These findings highlight the existence of an age-independent, disease-specific immune fingerprint that could serve as a minimally invasive biomarker for early diagnosis and personalized immunotherapy. Further studies using functional and single-cells analysis are needed to confirm memory Tregs as a pathogenic trait. ARTICLE HIGHLIGHTS: There are more memory regulatory T cells (Tregs) in individuals with type 1 diabetes (T1D) and siblings than in healthy control (HC) individuals. Individuals with T1D and their siblings share an immunological profile, with siblings displaying an intermediate phenotype that overlaps with both T1D and HC individuals. Memory Tregs increased with age in HC individuals and siblings but not in individuals with T1D. Diabetic ketoacidosis status had no impact on immune cell populations in patients with T1D.

Indexed as

Diabetes Mellitus, Type 1Immunologic MemoryMemory T CellsT-Lymphocytes, RegulatoryAdolescentBiomarkersChildChild, PreschoolFemaleHumansImmunophenotypingMaleSiblingsBiomarkers

Identifiers

PMID41729832
PMCPMC13007206

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.