Antibodies against insulin measured by electrochemiluminescence predicts insulitis severity and disease onset in non-obese diabetic mice and can distinguish human type 1 diabetes statusReportar como inadecuado




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Journal of Translational Medicine

, 9:203

First Online: 28 November 2011Received: 23 November 2011Accepted: 28 November 2011DOI: 10.1186-1479-5876-9-203

Cite this article as: Lo, B., Swafford, A.D., Shafer-Weaver, K.A. et al. J Transl Med 2011 9: 203. doi:10.1186-1479-5876-9-203

Abstract

BackgroundThe detection of insulin autoantibodies IAA aids in the prediction of autoimmune diabetes development. However, the long-standing, gold standard I-insulin radiobinding assay RBA has low reproducibility between laboratories, long sample processing times and requires the use of newly synthesized radiolabeled insulin for each set of assays. Therefore, a rapid, non-radioactive, and reproducible assay is highly desirable.

MethodsWe have developed electrochemiluminescence ECL-based assays that fulfill these criteria in the measurement of IAA and anti-insulin antibodies IA in non-obese diabetic NOD mice and in type 1 diabetic individuals, respectively. Using the murine IAA ECL assay, we examined the correlation between IAA, histopathological insulitis, and blood glucose in a cohort of female NOD mice from 4 up to 36 weeks of age. We developed a human IA ECL assay that we compared to conventional RBA and validated using samples from 34 diabetic and 59 non-diabetic individuals in three independent laboratories.

ResultsOur ECL assays were rapid and sensitive with a broad dynamic range and low background. In the NOD mouse model, IAA levels measured by ECL were positively correlated with insulitis severity, and the values measured at 8-10 weeks of age were predictive of diabetes onset. Using human serum and plasma samples, our IA ECL assay yielded reproducible and accurate results with an average sensitivity of 84% at 95% specificity with no statistically significant difference between laboratories.

ConclusionsThese novel, non-radioactive ECL-based assays should facilitate reliable and fast detection of antibodies to insulin and its precursors sera and plasma in a standardized manner between laboratories in both research and clinical settings. Our next step is to evaluate the human IA assay in the detection of IAA in prediabetic subjects or those at risk of type 1 diabetes and to develop similar assays for other autoantibodies that together are predictive for the diagnosis of this common disorder, in order to improve prediction and facilitate future therapeutic trials.

KeywordsNOD mice diabetes human autoantibodies insulin electrochemiluminescence IAA IA ECL List of abbreviationsIAAinsulin autoantibodies

IAanti-insulin antibodies

RBAradiobinding assay

ECLelectrochemiluminescence

NODnon-obese diabetic

T1Dtype 1 diabetes

GADAglutamic acid decarboxylase autoantibodies

I-A2Aislet-antigen 2 autoantibodies

ZnT8Azinc transporter-8 autoantibodies

ELISAenzyme-linked immunosorbent assay

BSAbovine serum albumin

NIAIDNational Institute of Allergy and Infectious Diseases

NIDDKNational Institute of Diabetes and Digestive and Kidney Diseases

HandEhematoxylin and eosin

ROCReceiver operating characteristic

HSDHuman Sample Diluent

HADHuman Assay Diluent

ARDAssay Run Diluent

RuRuthenium

TAGTrisbipyridinerutheniumII cation Rubipy3

TPAtripropylamine

rsSpearman-s correlation coefficient

SAstreptavidin

AUCarea-under-the curve

JDRFJuvenile Diabetes Research Foundation

WTThe Wellcome Trust

NIHRNational Institute for Health Research

CBRCCambridge Biomedical Research Centre

MRCMedical Research Council

CIMRCambridge Institute for Medical Research

CBRCambridge BioResource

NHLBINational Heart Lung and Blood Institute

AS95Sensitivity at 95% specificity

CI9595% confidence interval

avgaverage.

Electronic supplementary materialThe online version of this article doi:10.1186-1479-5876-9-203 contains supplementary material, which is available to authorized users.

Bernice Lo, Austin DE Swafford contributed equally to this work.

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Autor: Bernice Lo - Austin DE Swafford - Kimberly A Shafer-Weaver - Lawrence F Jerome - Luba Rakhlin - Douglas R Mathern - Cono

Fuente: https://link.springer.com/







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