Literature DB >> 11121550

Novel fusion proteins in the analysis of diabetes-associated autoantibodies to GAD65 and IA-2.

A Zavialov1, M Ankelo, A Westerlund-Karlsson, M Knip, J Ilonen, A Hinkkanen.   

Abstract

Assays to detect autoantibodies to glutamic acid decarboxylase (GAD65) and the protein tyrosine phosphatase-like molecule IA-2, which are both present in pancreatic islets, have been used in the diagnosis and prediction of type 1 diabetes. In this study a novel fusion protein combining the entire GAD65 molecule with the 40 kDa intracellular domain of IA-2 (GAD-IA-2) was constructed to detect autoantibodies to both antigens by one single assay. For the same purpose a truncated version of this fusion protein which contained the entire GAD65 linked to the 203 carboxy-terminal amino acids of IA-2 (GAD-dIA-2) was made. A panel of 34 diabetic sera which represented unequivocally positive or negative antibody responses to GAD65 and/or IA-2 as well as 20 serum samples from healthy controls were tested in a radioligand binding assay with the constructed fusion proteins as antigens. Nine of the samples from patients with type 1 diabetes reacted with GAD65 while being negative for IA-2. Six sera were positive for IA-2 only, 11 were double positive, and 8 negative for both antibodies using the standard in vitro transcription translation assay with single antigens. The full-length, as well as the truncated fusion protein detected all samples positive for antibodies either to GAD65 or IA-2 or both, except for one GAD65 antibody positive sample. All samples from healthy controls tested negative in all assays. We conclude that the principle of a combinatorial molecule where a fusion protein expresses both GAD65 and IA-2 epitopes is feasible, and such a fusion protein can be used instead of the single antigens to reduce time and costs of large-scale screening for clinical purposes.

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Year:  2000        PMID: 11121550     DOI: 10.1016/s0022-1759(00)00303-3

Source DB:  PubMed          Journal:  J Immunol Methods        ISSN: 0022-1759            Impact factor:   2.303


  2 in total

Review 1.  Serum biomarkers for diagnosis and prediction of type 1 diabetes.

Authors:  Lian Yi; Adam C Swensen; Wei-Jun Qian
Journal:  Transl Res       Date:  2018-08-01       Impact factor: 7.012

Review 2.  Prediction and prevention of type 1 diabetes.

Authors:  A E Morales; J X She; D A Schatz
Journal:  Curr Diab Rep       Date:  2001-08       Impact factor: 4.810

  2 in total

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