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Association between hOGG1 polymorphism rs1052133 and gastric cancer
PURPOSE: To conduct a comprehensive evaluation of the association of the human8-oxoguanine glycosylase 1 (hOGG1) gene polymorphism rs1052133 with gastric cancer (GC) through a systematic review and meta-analysis of genetic association study. RESULTS: A total of 15 articles from published papers were...
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/PMC5470970/ https://www.ncbi.nlm.nih.gov/pubmed/28415729 http://dx.doi.org/10.18632/oncotarget.16124 |
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author | Zhang, Dingding Guo, Xiaoxin Hu, Jinliang Zeng, Guangqun Huang, Maomin Qi, Dandan Gong, Bo |
author_facet | Zhang, Dingding Guo, Xiaoxin Hu, Jinliang Zeng, Guangqun Huang, Maomin Qi, Dandan Gong, Bo |
author_sort | Zhang, Dingding |
collection | PubMed |
description | PURPOSE: To conduct a comprehensive evaluation of the association of the human8-oxoguanine glycosylase 1 (hOGG1) gene polymorphism rs1052133 with gastric cancer (GC) through a systematic review and meta-analysis of genetic association study. RESULTS: A total of 15 articles from published papers were included in our analysis. The meta-analyses for hOGG1 rs1052133, composed of 4024GC patients and 6022controls, showed low heterogeneity for the included populations in all the genetic models, except for the Caucasian population under allelic genetic model, the Asian population under addictive model and Caucasian population under dominant model. The analyses of all the genetic models in overall pooled populations did not identify any significant association between GC and hOGG1 rs1052133 (Allelic model: C vs. G, p = 0.746; Addictive model: CC vs. GG, p = 0.888; Recessive model: CC +GC vs. GG, p = 0.628; Dominant model: CC vs. GG+GC, p = 0.147), even though stratified analyses were conducted in different ethnicities under each genetic model. MATERIALS AND METHODS: All case-control association studies on hOGG1 and GC reported up to December 15, 2016 in PubMed, Embase, Web of Science, and the Chinese Biomedical Database were retrieved. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for single-nucleotide polymorphism (SNP) using fixed- and random- effects models according to between-study heterogeneity. Publication bias analyses were conducted using Begg test. CONCLUSIONS: This meta-analysis showed there was no association between hOGG1 rs1052133 and GC. Given the limited sample size, further investigations including more ethnic groups are required to validate the association. |
format | Online Article Text |
id | pubmed-5470970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-54709702017-06-27 Association between hOGG1 polymorphism rs1052133 and gastric cancer Zhang, Dingding Guo, Xiaoxin Hu, Jinliang Zeng, Guangqun Huang, Maomin Qi, Dandan Gong, Bo Oncotarget Research Paper PURPOSE: To conduct a comprehensive evaluation of the association of the human8-oxoguanine glycosylase 1 (hOGG1) gene polymorphism rs1052133 with gastric cancer (GC) through a systematic review and meta-analysis of genetic association study. RESULTS: A total of 15 articles from published papers were included in our analysis. The meta-analyses for hOGG1 rs1052133, composed of 4024GC patients and 6022controls, showed low heterogeneity for the included populations in all the genetic models, except for the Caucasian population under allelic genetic model, the Asian population under addictive model and Caucasian population under dominant model. The analyses of all the genetic models in overall pooled populations did not identify any significant association between GC and hOGG1 rs1052133 (Allelic model: C vs. G, p = 0.746; Addictive model: CC vs. GG, p = 0.888; Recessive model: CC +GC vs. GG, p = 0.628; Dominant model: CC vs. GG+GC, p = 0.147), even though stratified analyses were conducted in different ethnicities under each genetic model. MATERIALS AND METHODS: All case-control association studies on hOGG1 and GC reported up to December 15, 2016 in PubMed, Embase, Web of Science, and the Chinese Biomedical Database were retrieved. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for single-nucleotide polymorphism (SNP) using fixed- and random- effects models according to between-study heterogeneity. Publication bias analyses were conducted using Begg test. CONCLUSIONS: This meta-analysis showed there was no association between hOGG1 rs1052133 and GC. Given the limited sample size, further investigations including more ethnic groups are required to validate the association. Impact Journals LLC 2017-03-11 /pmc/articles/PMC5470970/ /pubmed/28415729 http://dx.doi.org/10.18632/oncotarget.16124 Text en Copyright: © 2017 Zhang et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhang, Dingding Guo, Xiaoxin Hu, Jinliang Zeng, Guangqun Huang, Maomin Qi, Dandan Gong, Bo Association between hOGG1 polymorphism rs1052133 and gastric cancer |
title | Association between hOGG1 polymorphism rs1052133 and gastric cancer |
title_full | Association between hOGG1 polymorphism rs1052133 and gastric cancer |
title_fullStr | Association between hOGG1 polymorphism rs1052133 and gastric cancer |
title_full_unstemmed | Association between hOGG1 polymorphism rs1052133 and gastric cancer |
title_short | Association between hOGG1 polymorphism rs1052133 and gastric cancer |
title_sort | association between hogg1 polymorphism rs1052133 and gastric cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470970/ https://www.ncbi.nlm.nih.gov/pubmed/28415729 http://dx.doi.org/10.18632/oncotarget.16124 |
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