Literature DB >> 27173271

Exploration of association between EPHX1 and chronic obstructive pulmonary disease on the basis of combined data mining.

L An1, H Xia2,3, P Zhou2,3, L Hua2,3.   

Abstract

Chronic obstructive pulmonary disease (COPD) is an important respiratory disease with high mortality. Although smoking is the major environmental risk factor for the development of COPD, only 10% of heavy smokers develop symptomatic disease, suggesting association between genetic susceptibilities and environmental influences. In recent years, as one of the most widely studied genes including tests for associations between a genetic variant and COPD, epoxide hydrolase 1 (EPHX1) was found to be involved in the metabolism of tobacco smoke, an important risk factor of COPD. However, genetic associations with COPD identified in studies on EPHX1 are controversial. To address this issue, except for performing the meta-analysis, which specially added our current study on two polymorphisms (T337C and A416G) of EPHX1, we performed combined data mining based on functional prediction algorithms of nonsynonymous single-nucleotide polymorphisms and gene-based variable threshold testing. Genetic variations in EPHX1 did not affect COPD in Caucasian and Eastern Asian population, which is supported by recent evidence. We found no association between EPHX1 and COPD; however, a minor effect of EPHX1 on COPD risk was not completely excluded; further replication studies with large samples are needed to confirm our findings.

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Year:  2016        PMID: 27173271     DOI: 10.4238/gmr.15028639

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  3 in total

Review 1.  Genetic Variants Associated with Chronic Obstructive Pulmonary Disease Risk: Cumulative Epidemiological Evidence from Meta-Analyses and Genome-Wide Association Studies.

Authors:  Caiyang Liu; Ran Ran; Xiaoliang Li; Gaohua Liu; Xiaoyang Xie; Ji Li
Journal:  Can Respir J       Date:  2022-06-09       Impact factor: 2.130

Review 2.  Genetic polymorphism and chronic obstructive pulmonary disease.

Authors:  Cunhua Yuan; Guangming Lu; Xiaowei Deng
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2017-05-10

3.  Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population.

Authors:  Xia Ma; Yanping Wu; Ling Zhang; Weilan Yuan; Li Yan; Sha Fan; Yunzhi Lian; Xia Zhu; Junhui Gao; Jiangman Zhao; Ping Zhang; Hui Tang; Weihua Jia
Journal:  J Transl Med       Date:  2020-03-31       Impact factor: 5.531

  3 in total

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