Literature DB >> 25562486

Electrochemiluminescence assays for insulin and glutamic acid decarboxylase autoantibodies improve prediction of type 1 diabetes risk.

Dongmei Miao1, Andrea K Steck, Li Zhang, K Michelle Guyer, Ling Jiang, Taylor Armstrong, Sarah M Muller, Jeffrey Krischer, Marian Rewers, Liping Yu.   

Abstract

We recently developed new electrochemiluminescence (ECL) insulin autoantibody (IAA) and glutamic acid decarboxylase 65 autoantibody (GADA) assays that discriminate high-affinity, high-risk diabetes-specific autoantibodies from low-affinity, low-risk islet autoantibodies (iAbs) detected by radioassay (RAD). Here, we report a further validation of the ECL-IAA and -GADA assays in 3,484 TrialNet study participants. The ECL assay and RAD were congruent in those with prediabetes and in subjects with multiple autoantibodies, but only 24% (P<0.0001) of single RAD-IAA-positive and 46% (P<0.0001) of single RAD-GADA-positive were confirmed by the ECL-IAA and -GADA assays, respectively. During a follow-up (mean, 2.4 years), 51% of RAD-IAA-positive and 63% of RAD-GADA-positive subjects not confirmed by ECL became iAb negative, compared with only 17% of RAD-IAA-positive (P<0.0001) and 15% of RAD-GADA-positive (P<0.0001) subjects confirmed by ECL assays. Among subjects with multiple iAbs, diabetes-free survival was significantly shorter if IAA or GADA was positive by ECL and negative by RAD than if IAA or GADA was negative by ECL and positive by RAD (P<0.019 and P<0.0001, respectively). Both positive and negative predictive values in terms of progression to type 1 diabetes mellitus were superior for ECL-IAA and ECL-GADA, compared with RADs. The prevalence of the high-risk human leukocyte antigen-DR3/4, DQB1*0302 genotype was significantly higher in subjects with RAD-IAA or RAD-GADA confirmed by ECL. In conclusion, both ECL-IAA and -GADA are more disease-specific and better able to predict the risk of progression to type 1 diabetes mellitus than the current standard RADs.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25562486      PMCID: PMC4321773          DOI: 10.1089/dia.2014.0186

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  18 in total

1.  Early autoantibody responses in prediabetes are IgG1 dominated and suggest antigen-specific regulation.

Authors:  E Bonifacio; M Scirpoli; K Kredel; M Füchtenbusch; A G Ziegler
Journal:  J Immunol       Date:  1999-07-01       Impact factor: 5.422

2.  Prevalence of autoantibody-negative diabetes is not rare at all ages and increases with older age and obesity.

Authors:  Jian Wang; Dongmei Miao; Sunanda Babu; Jeesuk Yu; Jennifer Barker; Georgeanna Klingensmith; Marian Rewers; George S Eisenbarth; Liping Yu
Journal:  J Clin Endocrinol Metab       Date:  2006-10-24       Impact factor: 5.958

3.  Dual-parameter model for prediction of type I diabetes mellitus.

Authors:  G S Eisenbarth; R Gianani; L Yu; M Pietropaolo; C F Verge; H P Chase; M J Redondo; P Colman; L Harrison; R Jackson
Journal:  Proc Assoc Am Physicians       Date:  1998 Mar-Apr

4.  GAD autoantibody affinity and epitope specificity identify distinct immunization profiles in children at risk for type 1 diabetes.

Authors:  Anja Mayr; Michael Schlosser; Natalie Grober; Heidrun Kenk; Anette G Ziegler; Ezio Bonifacio; Peter Achenbach
Journal:  Diabetes       Date:  2007-02-26       Impact factor: 9.461

5.  IgG subclass antibodies to glutamic acid decarboxylase and risk for progression to clinical insulin-dependent diabetes.

Authors:  J J Couper; L C Harrison; J J Aldis; P G Colman; M C Honeyman; A Ferrante
Journal:  Hum Immunol       Date:  1998-08       Impact factor: 2.850

6.  Mature high-affinity immune responses to (pro)insulin anticipate the autoimmune cascade that leads to type 1 diabetes.

Authors:  Peter Achenbach; Kerstin Koczwara; Annette Knopff; Heike Naserke; Anette-G Ziegler; Ezio Bonifacio
Journal:  J Clin Invest       Date:  2004-08       Impact factor: 14.808

7.  The Environmental Determinants of Diabetes in the Young (TEDDY) study: study design.

Authors: 
Journal:  Pediatr Diabetes       Date:  2007-10       Impact factor: 4.866

8.  Role of insulin autoantibody affinity as a predictive marker for type 1 diabetes in young children with HLA-conferred disease susceptibility.

Authors:  Heli Siljander; Taina Härkönen; Robert Hermann; Satu Simell; Anne Hekkala; Riikka-Tiina Salonsaari; Tuula Simell; Olli Simell; Jorma Ilonen; Riitta Veijola; Mikael Knip
Journal:  Diabetes Metab Res Rev       Date:  2009-10       Impact factor: 4.876

9.  Stratification of type 1 diabetes risk on the basis of islet autoantibody characteristics.

Authors:  Peter Achenbach; Katharina Warncke; Jürgen Reiter; Heike E Naserke; Alistair J K Williams; Polly J Bingley; Ezio Bonifacio; Anette-G Ziegler
Journal:  Diabetes       Date:  2004-02       Impact factor: 9.461

10.  Pancreatic islet autoantibodies as predictors of type 1 diabetes in the Diabetes Prevention Trial-Type 1.

Authors:  Tihamer Orban; Jay M Sosenko; David Cuthbertson; Jeffrey P Krischer; Jay S Skyler; Richard Jackson; Liping Yu; Jerry P Palmer; Desmond Schatz; George Eisenbarth
Journal:  Diabetes Care       Date:  2009-09-09       Impact factor: 17.152

View more
  26 in total

1.  Alternate Ways to Quantify Antibodies.

Authors:  Kimber M Simmons; Aaron W Michels
Journal:  Diabetes Technol Ther       Date:  2015-11-06       Impact factor: 6.118

Review 2.  Immune Mechanisms and Pathways Targeted in Type 1 Diabetes.

Authors:  Laura M Jacobsen; Brittney N Newby; Daniel J Perry; Amanda L Posgai; Michael J Haller; Todd M Brusko
Journal:  Curr Diab Rep       Date:  2018-08-30       Impact factor: 4.810

Review 3.  T1D Autoantibodies: room for improvement?

Authors:  Liping Yu; Zhiyuan Zhao; Andrea K Steck
Journal:  Curr Opin Endocrinol Diabetes Obes       Date:  2017-08       Impact factor: 3.243

4.  ECL-IAA and ECL-GADA Can Identify High-Risk Single Autoantibody-Positive Relatives in the TrialNet Pathway to Prevention Study.

Authors:  Andrea K Steck; Alexandra Fouts; Dongmei Miao; Zhiyuan Zhao; Fran Dong; Jay Sosenko; Peter Gottlieb; Marian J Rewers; Liping Yu
Journal:  Diabetes Technol Ther       Date:  2016-03-18       Impact factor: 6.118

5.  Islet Autoantibody Detection by Electrochemiluminescence (ECL) Assay.

Authors:  Liping Yu
Journal:  Methods Mol Biol       Date:  2016

6.  The Use of Electrochemiluminescence Assays to Predict Autoantibody and Glycemic Progression Toward Type 1 Diabetes in Individuals with Single Autoantibodies.

Authors:  Jay M Sosenko; Liping Yu; Jay S Skyler; Jeffrey P Krischer; Peter A Gottlieb; David Boulware; Dongmei Miao; Jerry P Palmer; Andrea K Steck
Journal:  Diabetes Technol Ther       Date:  2017-02-08       Impact factor: 6.118

7.  Do Electrochemiluminescence Assays Improve Prediction of Time to Type 1 Diabetes in Autoantibody-Positive TrialNet Subjects?

Authors:  Alexandra Fouts; Laura Pyle; Liping Yu; Dongmei Miao; Aaron Michels; Jeffrey Krischer; Jay Sosenko; Peter Gottlieb; Andrea K Steck
Journal:  Diabetes Care       Date:  2016-07-25       Impact factor: 19.112

Review 8.  Staging the progression to type 1 diabetes with prediagnostic markers.

Authors:  Jay M Sosenko
Journal:  Curr Opin Endocrinol Diabetes Obes       Date:  2016-08       Impact factor: 3.243

9.  A multiplex assay combining insulin, GAD, IA-2 and transglutaminase autoantibodies to facilitate screening for pre-type 1 diabetes and celiac disease.

Authors:  Zhiyuan Zhao; Dongmei Miao; Aaron Michels; Andrea Steck; Fran Dong; Marian Rewers; Liping Yu
Journal:  J Immunol Methods       Date:  2016-01-22       Impact factor: 2.303

Review 10.  Islet autoantibodies in disease prediction and pathogenesis.

Authors:  Xiaofan Jia; Yong Gu; Hilary High; Liping Yu
Journal:  Diabetol Int       Date:  2019-10-16
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.