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Construction and Application of Polygenic Risk Scores in Autoimmune Diseases
Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271862/ https://www.ncbi.nlm.nih.gov/pubmed/35833142 http://dx.doi.org/10.3389/fimmu.2022.889296 |
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author | Khunsriraksakul, Chachrit Markus, Havell Olsen, Nancy J. Carrel, Laura Jiang, Bibo Liu, Dajiang J. |
author_facet | Khunsriraksakul, Chachrit Markus, Havell Olsen, Nancy J. Carrel, Laura Jiang, Bibo Liu, Dajiang J. |
author_sort | Khunsriraksakul, Chachrit |
collection | PubMed |
description | Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited predictive power; however, when aggregated (e.g., via polygenic risk score method), they could provide meaningful risk predictions for a myriad of diseases. In this review, we describe the recent advances in GWAS for autoimmune diseases and the practical application of this knowledge to predict an individual’s susceptibility/severity for autoimmune diseases such as systemic lupus erythematosus (SLE) via the polygenic risk score method. We provide an overview of methods for deriving different polygenic risk scores and discuss the strategies to integrate additional information from correlated traits and diverse ancestries. We further advocate for the need to integrate clinical features (e.g., anti-nuclear antibody status) with genetic profiling to better identify patients at high risk of disease susceptibility/severity even before clinical signs or symptoms develop. We conclude by discussing future challenges and opportunities of applying polygenic risk score methods in clinical care. |
format | Online Article Text |
id | pubmed-9271862 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92718622022-07-12 Construction and Application of Polygenic Risk Scores in Autoimmune Diseases Khunsriraksakul, Chachrit Markus, Havell Olsen, Nancy J. Carrel, Laura Jiang, Bibo Liu, Dajiang J. Front Immunol Immunology Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited predictive power; however, when aggregated (e.g., via polygenic risk score method), they could provide meaningful risk predictions for a myriad of diseases. In this review, we describe the recent advances in GWAS for autoimmune diseases and the practical application of this knowledge to predict an individual’s susceptibility/severity for autoimmune diseases such as systemic lupus erythematosus (SLE) via the polygenic risk score method. We provide an overview of methods for deriving different polygenic risk scores and discuss the strategies to integrate additional information from correlated traits and diverse ancestries. We further advocate for the need to integrate clinical features (e.g., anti-nuclear antibody status) with genetic profiling to better identify patients at high risk of disease susceptibility/severity even before clinical signs or symptoms develop. We conclude by discussing future challenges and opportunities of applying polygenic risk score methods in clinical care. Frontiers Media S.A. 2022-06-27 /pmc/articles/PMC9271862/ /pubmed/35833142 http://dx.doi.org/10.3389/fimmu.2022.889296 Text en Copyright © 2022 Khunsriraksakul, Markus, Olsen, Carrel, Jiang and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Khunsriraksakul, Chachrit Markus, Havell Olsen, Nancy J. Carrel, Laura Jiang, Bibo Liu, Dajiang J. Construction and Application of Polygenic Risk Scores in Autoimmune Diseases |
title | Construction and Application of Polygenic Risk Scores in Autoimmune Diseases |
title_full | Construction and Application of Polygenic Risk Scores in Autoimmune Diseases |
title_fullStr | Construction and Application of Polygenic Risk Scores in Autoimmune Diseases |
title_full_unstemmed | Construction and Application of Polygenic Risk Scores in Autoimmune Diseases |
title_short | Construction and Application of Polygenic Risk Scores in Autoimmune Diseases |
title_sort | construction and application of polygenic risk scores in autoimmune diseases |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271862/ https://www.ncbi.nlm.nih.gov/pubmed/35833142 http://dx.doi.org/10.3389/fimmu.2022.889296 |
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