Antibodies to oxidised insulin as biomarker for type 1 diabetes prediction and diagnosis

This abstract has open access
Abstract Summary

We have shown that in type 1 diabetes (T1D) oxidative post-translational modification (oxPTM) generates neoepitopes and that antibodies to oxPTM insulin (oxPTM-INS-Ab) can potentially become robust biomarkers for T1D prediction and early diagnosis. Sensitivity, specificity, accuracy of oxPTM-INS-Ab was compared to the standard islet-AAB that include insulin (IAA), GAD (GADA), and tyrosine-phosphatase 2 (IA-2A). In the Immunotherapy Diabetes (IMDIAB) cohort that include young individuals newly diagnosed with T1D before treatment with insulin, we observed significantly higher binding to oxPTM-INS vs native insulin with 84% sensitivity compared to 61% sensitivity for radio-binding assay (RBA). To validate the prediction potential of oxPTM-INS-Ab we used serum samples collected longitudinally from the ‘All Babies in Southeast Sweden’ (ABIS) cohort. ABIS is a large prospective birth cohort study in the general population that contains two groups of children who were islet-AAB positive (AAB+): one group progressed to T1D and one that did not progress to T1D (median follow-up 10.8 years). Antibodies to at least one oxPTM-INS were present in 90% of progressing AAB+ children versus 19% in children that did not progress to T1D. Risk for developing diabetes was higher (p=0.03) among multiple AAB+ who were also oxPTM-INS-Ab+ compared with those who were oxPTM-INS-Ab–. Importantly, when replacing IAA with oxPTM-INS-Ab diabetes risk increased to 100% in children with oxPTM-INS-Ab+ in combination with GADA+, and IA-2A+, compared to 84.37% in those with IAA+, GADA+, and IA-2A+ (p=0.04). Our data implies that oxPTM-INS-Ab improves T1D diagnosis and prediction accuracy of T1D. Using mass-spectrometry we have mapped the hotspots for insulin oxidations and our goal is to identify the exact neoepitope(s) for future state-of-the-art diagnosis and therapies.

Submission ID :
IDS1226
Submission Type
Abstract Topics
Queen Mary University
Linköping university
University of Exeter
Linköping University
Linköping University
Universitá Campus Bio-Medico di Roma
Universitá Campus Bio-Medico di Roma
Queen Mary University
Queen Mary University
Universitá Campus Bio-Medico di Roma
Universitá Campus Bio-Medico di Roma

Abstracts With Same Type

Submission ID
Submission Title
Submission Topic
Submission Type
Primary Author
7 visits

KEY DATES

Event dates:
Thursday 25 October - Monday 29 October 2018

Abstract submission deadline:
Monday 14 May 2018

Abstract notification:
July 2018

Early registration deadline:
Monday 3 September 2018

Registration deadline:
Monday 15 October 2018

Contact
British Society for Immunology
+44 (0)20 3019 5901
congress@immunology.org