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Next steps in the identification of gene targets for type 1 diabetes
The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527360/ https://www.ncbi.nlm.nih.gov/pubmed/32797243 http://dx.doi.org/10.1007/s00125-020-05248-8 |
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author | Grant, Struan F. A. Wells, Andrew D. Rich, Stephen S. |
author_facet | Grant, Struan F. A. Wells, Andrew D. Rich, Stephen S. |
author_sort | Grant, Struan F. A. |
collection | PubMed |
description | The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-020-05248-8) contains a slide of the figure for download, which is available to authorised users. |
format | Online Article Text |
id | pubmed-7527360 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-75273602020-10-19 Next steps in the identification of gene targets for type 1 diabetes Grant, Struan F. A. Wells, Andrew D. Rich, Stephen S. Diabetologia Review The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-020-05248-8) contains a slide of the figure for download, which is available to authorised users. Springer Berlin Heidelberg 2020-08-14 2020 /pmc/articles/PMC7527360/ /pubmed/32797243 http://dx.doi.org/10.1007/s00125-020-05248-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Review Grant, Struan F. A. Wells, Andrew D. Rich, Stephen S. Next steps in the identification of gene targets for type 1 diabetes |
title | Next steps in the identification of gene targets for type 1 diabetes |
title_full | Next steps in the identification of gene targets for type 1 diabetes |
title_fullStr | Next steps in the identification of gene targets for type 1 diabetes |
title_full_unstemmed | Next steps in the identification of gene targets for type 1 diabetes |
title_short | Next steps in the identification of gene targets for type 1 diabetes |
title_sort | next steps in the identification of gene targets for type 1 diabetes |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527360/ https://www.ncbi.nlm.nih.gov/pubmed/32797243 http://dx.doi.org/10.1007/s00125-020-05248-8 |
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