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Utility of genetic risk scores in type 1 diabetes
Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combine...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390619/ https://www.ncbi.nlm.nih.gov/pubmed/37439792 http://dx.doi.org/10.1007/s00125-023-05955-y |
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author | Luckett, Amber M. Weedon, Michael N. Hawkes, Gareth Leslie, R. David Oram, Richard A. Grant, Struan F. A. |
author_facet | Luckett, Amber M. Weedon, Michael N. Hawkes, Gareth Leslie, R. David Oram, Richard A. Grant, Struan F. A. |
author_sort | Luckett, Amber M. |
collection | PubMed |
description | Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case–control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for ‘test and treat’ approaches to be used to tailor care for individuals with type 1 diabetes. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains a slideset of the figures for download available at 10.1007/s00125-023-05955-y. |
format | Online Article Text |
id | pubmed-10390619 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-103906192023-08-02 Utility of genetic risk scores in type 1 diabetes Luckett, Amber M. Weedon, Michael N. Hawkes, Gareth Leslie, R. David Oram, Richard A. Grant, Struan F. A. Diabetologia Review Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case–control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for ‘test and treat’ approaches to be used to tailor care for individuals with type 1 diabetes. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains a slideset of the figures for download available at 10.1007/s00125-023-05955-y. Springer Berlin Heidelberg 2023-07-13 2023 /pmc/articles/PMC10390619/ /pubmed/37439792 http://dx.doi.org/10.1007/s00125-023-05955-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Luckett, Amber M. Weedon, Michael N. Hawkes, Gareth Leslie, R. David Oram, Richard A. Grant, Struan F. A. Utility of genetic risk scores in type 1 diabetes |
title | Utility of genetic risk scores in type 1 diabetes |
title_full | Utility of genetic risk scores in type 1 diabetes |
title_fullStr | Utility of genetic risk scores in type 1 diabetes |
title_full_unstemmed | Utility of genetic risk scores in type 1 diabetes |
title_short | Utility of genetic risk scores in type 1 diabetes |
title_sort | utility of genetic risk scores in type 1 diabetes |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390619/ https://www.ncbi.nlm.nih.gov/pubmed/37439792 http://dx.doi.org/10.1007/s00125-023-05955-y |
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