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Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population
Genome-wide association studies have identified that TERT gene was associated with telomere length and age-related diseases. However, little study directly focused on the association between TERT gene polymorphisms and risk of coronary heart disease (CHD). We conducted a case-control study to examin...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5620190/ https://www.ncbi.nlm.nih.gov/pubmed/28978050 http://dx.doi.org/10.18632/oncotarget.18727 |
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author | Han, Hongmei Zhang, Jianxia Hou, Jianghong Wang, Haibo Zheng, Jianpeng Wang, Huan Zhong, Zhong Wang, Yijin Wang, Xiaoni Yang, Bei Wang, Lei Quan, Dangjun Li, Junnong |
author_facet | Han, Hongmei Zhang, Jianxia Hou, Jianghong Wang, Haibo Zheng, Jianpeng Wang, Huan Zhong, Zhong Wang, Yijin Wang, Xiaoni Yang, Bei Wang, Lei Quan, Dangjun Li, Junnong |
author_sort | Han, Hongmei |
collection | PubMed |
description | Genome-wide association studies have identified that TERT gene was associated with telomere length and age-related diseases. However, little study directly focused on the association between TERT gene polymorphisms and risk of coronary heart disease (CHD). We conducted a case-control study to examine the effect of TERT polymorphisms on CHD risk among 596 CHD patients and 603 healthy controls from China. Five significant single nucleotide polymorphisms (SNP) in TERT were selected and genotyped using Sequenom Mass-ARRAY technology. Odds ratios (OR) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression adjusting for age and gender. Allelic model analysis revealed that for TERT rs10069690, allele frequency distributions differed between cases and controls (OR= 1.267, 95%CI = 1.018-1.576; p = 0.034). Genotypic model analysis revealed that genotype frequency distributions of rs10069690 differed between cases and controls after adjusted by age and sex (TC vs. CC: adjusted OR = 1.352, 95% CI = 1.007-1.815; p = 0.045). Genetic model analysis revealed that rs10069690 was associated with an increased risk of CHD under co-dominant, dominant, over-dominant and log-additive models. After adjustments, it remained significant under over-dominant model (adjusted OR = 1.35, 95% CI = 1.01-1.81; p = 0.044). Our results shed new light on the association between telomere-related gene TERT polymorphisms and CHD susceptibility in a Chinese Han population. |
format | Online Article Text |
id | pubmed-5620190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-56201902017-10-03 Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population Han, Hongmei Zhang, Jianxia Hou, Jianghong Wang, Haibo Zheng, Jianpeng Wang, Huan Zhong, Zhong Wang, Yijin Wang, Xiaoni Yang, Bei Wang, Lei Quan, Dangjun Li, Junnong Oncotarget Research Paper Genome-wide association studies have identified that TERT gene was associated with telomere length and age-related diseases. However, little study directly focused on the association between TERT gene polymorphisms and risk of coronary heart disease (CHD). We conducted a case-control study to examine the effect of TERT polymorphisms on CHD risk among 596 CHD patients and 603 healthy controls from China. Five significant single nucleotide polymorphisms (SNP) in TERT were selected and genotyped using Sequenom Mass-ARRAY technology. Odds ratios (OR) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression adjusting for age and gender. Allelic model analysis revealed that for TERT rs10069690, allele frequency distributions differed between cases and controls (OR= 1.267, 95%CI = 1.018-1.576; p = 0.034). Genotypic model analysis revealed that genotype frequency distributions of rs10069690 differed between cases and controls after adjusted by age and sex (TC vs. CC: adjusted OR = 1.352, 95% CI = 1.007-1.815; p = 0.045). Genetic model analysis revealed that rs10069690 was associated with an increased risk of CHD under co-dominant, dominant, over-dominant and log-additive models. After adjustments, it remained significant under over-dominant model (adjusted OR = 1.35, 95% CI = 1.01-1.81; p = 0.044). Our results shed new light on the association between telomere-related gene TERT polymorphisms and CHD susceptibility in a Chinese Han population. Impact Journals LLC 2017-06-28 /pmc/articles/PMC5620190/ /pubmed/28978050 http://dx.doi.org/10.18632/oncotarget.18727 Text en Copyright: © 2017 Han et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Paper Han, Hongmei Zhang, Jianxia Hou, Jianghong Wang, Haibo Zheng, Jianpeng Wang, Huan Zhong, Zhong Wang, Yijin Wang, Xiaoni Yang, Bei Wang, Lei Quan, Dangjun Li, Junnong Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population |
title | Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population |
title_full | Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population |
title_fullStr | Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population |
title_full_unstemmed | Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population |
title_short | Association of TERT polymorphisms and risk of coronary heart disease in a Chinese Han population |
title_sort | association of tert polymorphisms and risk of coronary heart disease in a chinese han population |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5620190/ https://www.ncbi.nlm.nih.gov/pubmed/28978050 http://dx.doi.org/10.18632/oncotarget.18727 |
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