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CD4+CD25+CD127hi cell frequency predicts disease progression in type 1 diabetes

Authors :
Aditi Narsale
Breanna Lam
Rosa Moya
TingTing Lu
Alessandra Mandelli
Irene Gotuzzo
Benedetta Pessina
Gianmaria Giamporcaro
Rhonda Geoffrey
Kerry Buchanan
Mark Harris
Anne-Sophie Bergot
Ranjeny Thomas
Martin J. Hessner
Manuela Battaglia
Elisavet Serti
Joanna D. Davies
Source :
JCI Insight, Vol 6, Iss 2 (2021)
Publication Year :
2021
Publisher :
American Society for Clinical investigation, 2021.

Abstract

Transient partial remission, a period of low insulin requirement experienced by most patients soon after diagnosis, has been associated with mechanisms of immune regulation. A better understanding of such natural mechanisms of immune regulation might identify new targets for immunotherapies that reverse type 1 diabetes (T1D). In this study, using Cox model multivariate analysis, we validated our previous findings that patients with the highest frequency of CD4+CD25+CD127hi (127-hi) cells at diagnosis experience the longest partial remission, and we showed that the 127-hi cell population is a mix of Th1- and Th2-type cells, with a significant bias toward antiinflammatory Th2-type cells. In addition, we extended these findings to show that patients with the highest frequency of 127-hi cells at diagnosis were significantly more likely to maintain β cell function. Moreover, in patients treated with alefacept in the T1DAL clinical trial, the probability of responding favorably to the antiinflammatory drug was significantly higher in those with a higher frequency of 127-hi cells at diagnosis than those with a lower 127-hi cell frequency. These data are consistent with the hypothesis that 127-hi cells maintain an antiinflammatory environment that is permissive for partial remission, β cell survival, and response to antiinflammatory immunotherapy.

Subjects

Subjects :
Autoimmunity
Immunology
Medicine

Details

Language :
English
ISSN :
23793708
Volume :
6
Issue :
2
Database :
Directory of Open Access Journals
Journal :
JCI Insight
Publication Type :
Academic Journal
Accession number :
edsdoj.20ba8c4ce6b4454ea7c69dca229e3557
Document Type :
article
Full Text :
https://doi.org/10.1172/jci.insight.136114