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Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan
The aim of this study is to explore the effect of genetic variation on diabetic retinopathy (DR) risk in a Taiwanese population. The logistic regression model was used to evaluate the relationship between DR status and risk factors, including the conventional parameters and genetic risk score (GRS)....
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6162301/ https://www.ncbi.nlm.nih.gov/pubmed/30266984 http://dx.doi.org/10.1038/s41598-018-32916-y |
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author | Liao, Wen-Ling Lin, Jang-Ming Chen, Wen-Lu Hsieh, Ming-Chia Wu, Chia-Ming Chang, Ya-Wen Huang, Yu-Chuen Tsai, Fuu-Jen |
author_facet | Liao, Wen-Ling Lin, Jang-Ming Chen, Wen-Lu Hsieh, Ming-Chia Wu, Chia-Ming Chang, Ya-Wen Huang, Yu-Chuen Tsai, Fuu-Jen |
author_sort | Liao, Wen-Ling |
collection | PubMed |
description | The aim of this study is to explore the effect of genetic variation on diabetic retinopathy (DR) risk in a Taiwanese population. The logistic regression model was used to evaluate the relationship between DR status and risk factors, including the conventional parameters and genetic risk score (GRS). Candidate single nucleotide polymorphisms (SNPs) in GRS were selected based on previous reports with a combined P < 10(−4) (genome-wide association) and P < 0.05 (meta-analysis). In total, 58 SNPs in 44 susceptibility loci were selected, and four were used to calculate GRS. After adjustment for age, systolic blood pressure, diabetes duration, and HbA1c, the DR risk was 4.95 times higher for patients in the top GRS third tile than for those in the bottom third tile (95% CI = 2.99–8.18; P < 0.001). The addition of genetic information improved DR prediction, increasing the area under the curve (AUC) from 0.72 to 0.77 (P = 0.0024) and improving the sensitivity of the model such that 40 more subjects were reclassified into DR status. The developed multivariate logistic regression model combining conventional risk factors and the multilocus GRS can predict DR, thus enabling timely treatment to reduce blindness in T2D patients. |
format | Online Article Text |
id | pubmed-6162301 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61623012018-10-02 Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan Liao, Wen-Ling Lin, Jang-Ming Chen, Wen-Lu Hsieh, Ming-Chia Wu, Chia-Ming Chang, Ya-Wen Huang, Yu-Chuen Tsai, Fuu-Jen Sci Rep Article The aim of this study is to explore the effect of genetic variation on diabetic retinopathy (DR) risk in a Taiwanese population. The logistic regression model was used to evaluate the relationship between DR status and risk factors, including the conventional parameters and genetic risk score (GRS). Candidate single nucleotide polymorphisms (SNPs) in GRS were selected based on previous reports with a combined P < 10(−4) (genome-wide association) and P < 0.05 (meta-analysis). In total, 58 SNPs in 44 susceptibility loci were selected, and four were used to calculate GRS. After adjustment for age, systolic blood pressure, diabetes duration, and HbA1c, the DR risk was 4.95 times higher for patients in the top GRS third tile than for those in the bottom third tile (95% CI = 2.99–8.18; P < 0.001). The addition of genetic information improved DR prediction, increasing the area under the curve (AUC) from 0.72 to 0.77 (P = 0.0024) and improving the sensitivity of the model such that 40 more subjects were reclassified into DR status. The developed multivariate logistic regression model combining conventional risk factors and the multilocus GRS can predict DR, thus enabling timely treatment to reduce blindness in T2D patients. Nature Publishing Group UK 2018-09-28 /pmc/articles/PMC6162301/ /pubmed/30266984 http://dx.doi.org/10.1038/s41598-018-32916-y Text en © The Author(s) 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liao, Wen-Ling Lin, Jang-Ming Chen, Wen-Lu Hsieh, Ming-Chia Wu, Chia-Ming Chang, Ya-Wen Huang, Yu-Chuen Tsai, Fuu-Jen Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan |
title | Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan |
title_full | Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan |
title_fullStr | Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan |
title_full_unstemmed | Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan |
title_short | Multilocus genetic risk score for diabetic retinopathy in the Han Chinese population of Taiwan |
title_sort | multilocus genetic risk score for diabetic retinopathy in the han chinese population of taiwan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6162301/ https://www.ncbi.nlm.nih.gov/pubmed/30266984 http://dx.doi.org/10.1038/s41598-018-32916-y |
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