Literature DB >> 26074154

Non-HLA gene effects on the disease process of type 1 diabetes: From HLA susceptibility to overt disease.

Johanna Lempainen1, Antti-Pekka Laine2, Anna Hammais2, Jorma Toppari3, Olli Simell3, Riitta Veijola4, Mikael Knip5, Jorma Ilonen6.   

Abstract

In addition to the HLA region numerous other gene loci have shown association with type 1 diabetes. How these polymorphisms exert their function has not been comprehensively described, however. We assessed the effect of 39 single nucleotide polymorphisms (SNP) on the development of autoantibody positivity, on progression from autoantibody positivity to clinical disease and on the specificity of the antibody initiating the autoimmune process in 521 autoantibody-positive and 989 control children from a follow-up study starting from birth. Interestingly, PTPN2 rs45450798 gene polymorphism was observed to strongly affect the progression rate of beta-cell destruction after the appearance of humoral beta-cell autoimmunity. Moreover, primary autoantigen dependent associations were also observed as effect of the IKZF4-ERBB3 region on the progression rate of β-cell destruction was restricted to children with GAD antibodies as their first autoantibody whereas the effect of the INS rs 689 polymorphism was observed among subjects with insulin as the primary autoantigen. In the whole study cohort, INS rs689, PTPN22 rs2476601 and IFIH1 rs1990760 polymorphisms were associated with the appearance of beta-cell autoantibodies. These findings provide new insights into the role of genetic factors implicated in the pathogenesis of type 1 diabetes. The effect of some of the gene variants is restricted to control the initiation of β-cell autoimmunity whereas others modify the destruction rate of the β-cells. Furthermore, signs of primary autoantigen-related pathways were detected.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Beta-cell autoimmunity; Genetics; Progression; Type 1 diabetes

Mesh:

Substances:

Year:  2015        PMID: 26074154     DOI: 10.1016/j.jaut.2015.05.005

Source DB:  PubMed          Journal:  J Autoimmun        ISSN: 0896-8411            Impact factor:   7.094


  20 in total

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2.  A novel approach for the analysis of longitudinal profiles reveals delayed progression to type 1 diabetes in a subgroup of multiple-islet-autoantibody-positive children.

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3.  Prediction of type 1 diabetes using a genetic risk model in the Diabetes Autoimmunity Study in the Young.

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4.  Genome-Wide Identification of N6-Methyladenosine Associated SNPs as Potential Functional Variants for Type 1 Diabetes.

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5.  Influence of Insulin Receptor Single Nucleotide Polymorphisms on Glycaemic Control and Formation of Anti-Insulin Antibodies in Diabetes Mellitus.

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Review 6.  Viral infections in type 1 diabetes mellitus--why the β cells?

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Journal:  Nat Rev Endocrinol       Date:  2016-03-29       Impact factor: 43.330

7.  Identification of non-HLA genes associated with development of islet autoimmunity and type 1 diabetes in the prospective TEDDY cohort.

Authors:  Ashok Sharma; Xiang Liu; David Hadley; William Hagopian; Wei-Min Chen; Suna Onengut-Gumuscu; Carina Törn; Andrea K Steck; Brigitte I Frohnert; Marian Rewers; Anette-G Ziegler; Åke Lernmark; Jorma Toppari; Jeffrey P Krischer; Beena Akolkar; Stephen S Rich; Jin-Xiong She
Journal:  J Autoimmun       Date:  2018-01-05       Impact factor: 14.511

Review 8.  The β Cell in Diabetes: Integrating Biomarkers With Functional Measures.

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9.  CRISPR-Cas9-Mediated Modification of the NOD Mouse Genome With Ptpn22R619W Mutation Increases Autoimmune Diabetes.

Authors:  Xiaotian Lin; Stephane Pelletier; Sebastien Gingras; Stephanie Rigaud; Christian J Maine; Kristi Marquardt; Yang D Dai; Karsten Sauer; Alberto R Rodriguez; Greg Martin; Sergey Kupriyanov; Ling Jiang; Liping Yu; Douglas R Green; Linda A Sherman
Journal:  Diabetes       Date:  2016-04-26       Impact factor: 9.461

Review 10.  T Cell Receptor Profiling in Type 1 Diabetes.

Authors:  Laura M Jacobsen; Amanda Posgai; Howard R Seay; Michael J Haller; Todd M Brusko
Journal:  Curr Diab Rep       Date:  2017-10-11       Impact factor: 4.810

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