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The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis

Polycystic ovary syndrome (PCOS) is the most common gynecological endocrine disorder. The genetic background is believed to play a crucial role in the pathogenesis of PCOS. In recent years, the role of insulin receptor (INSR) polymorphisms in PCOS predisposition has attracted much attention. We perf...

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Autores principales: Feng, Chun, Lv, Ping-Ping, Yu, Tian-Tian, Jin, Min, Shen, Jin-Ming, Wang, Xue, Zhou, Feng, Jiang, Shi-Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4346843/
https://www.ncbi.nlm.nih.gov/pubmed/25622255
http://dx.doi.org/10.3390/ijms16022403
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author Feng, Chun
Lv, Ping-Ping
Yu, Tian-Tian
Jin, Min
Shen, Jin-Ming
Wang, Xue
Zhou, Feng
Jiang, Shi-Wen
author_facet Feng, Chun
Lv, Ping-Ping
Yu, Tian-Tian
Jin, Min
Shen, Jin-Ming
Wang, Xue
Zhou, Feng
Jiang, Shi-Wen
author_sort Feng, Chun
collection PubMed
description Polycystic ovary syndrome (PCOS) is the most common gynecological endocrine disorder. The genetic background is believed to play a crucial role in the pathogenesis of PCOS. In recent years, the role of insulin receptor (INSR) polymorphisms in PCOS predisposition has attracted much attention. We performed a meta-analysis to investigate the association between the single nucleotide polymorphisms (SNPs) of INSR and PCOS. Published literature from Pubmed, Embase, and Cochrane CENTRAL was retrieved up until 7 August 2014. A total of 20 case-control studies including 23,845 controls and 17,460 PCOS cases with an average Newcastle-Ottawa quality assessment scale (NOS) score of 6.75 were analyzed. Ninety-eight SNPs distributed in 23 exons and the flanking regions of INSR were investigated, among which 17 SNPs were found to be associated with PCOS. Three SNPs detected in more than three studies were selected for further analyses. Twelve studies including 1158 controls and 1264 PCOS cases entered the analysis of rs1799817, but no significant association was found for every genotype (p > 0.05). Further subgroup stratification by ethnicity and weight did not lead to discovery of significant correlation (p > 0.05). For rs2059806, four studies including 442 controls and 524 PCOS cases were qualified for meta-analysis, and no significant association with PCOS was found for any genotype (p > 0.05). Four studies including 12,830 controls and 11,683 PCOS cases investigated the correlation between rs2059807 and PCOS, and five of the six cohorts indicated a significant impact. Our current meta-analysis suggests no significant correlation between rs1799817/rs2059806 SNPs and susceptibility of PCOS, while rs2059807 could be a promising candidate SNP that might be involved in the susceptibility of PCOS.
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spelling pubmed-43468432015-04-03 The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis Feng, Chun Lv, Ping-Ping Yu, Tian-Tian Jin, Min Shen, Jin-Ming Wang, Xue Zhou, Feng Jiang, Shi-Wen Int J Mol Sci Article Polycystic ovary syndrome (PCOS) is the most common gynecological endocrine disorder. The genetic background is believed to play a crucial role in the pathogenesis of PCOS. In recent years, the role of insulin receptor (INSR) polymorphisms in PCOS predisposition has attracted much attention. We performed a meta-analysis to investigate the association between the single nucleotide polymorphisms (SNPs) of INSR and PCOS. Published literature from Pubmed, Embase, and Cochrane CENTRAL was retrieved up until 7 August 2014. A total of 20 case-control studies including 23,845 controls and 17,460 PCOS cases with an average Newcastle-Ottawa quality assessment scale (NOS) score of 6.75 were analyzed. Ninety-eight SNPs distributed in 23 exons and the flanking regions of INSR were investigated, among which 17 SNPs were found to be associated with PCOS. Three SNPs detected in more than three studies were selected for further analyses. Twelve studies including 1158 controls and 1264 PCOS cases entered the analysis of rs1799817, but no significant association was found for every genotype (p > 0.05). Further subgroup stratification by ethnicity and weight did not lead to discovery of significant correlation (p > 0.05). For rs2059806, four studies including 442 controls and 524 PCOS cases were qualified for meta-analysis, and no significant association with PCOS was found for any genotype (p > 0.05). Four studies including 12,830 controls and 11,683 PCOS cases investigated the correlation between rs2059807 and PCOS, and five of the six cohorts indicated a significant impact. Our current meta-analysis suggests no significant correlation between rs1799817/rs2059806 SNPs and susceptibility of PCOS, while rs2059807 could be a promising candidate SNP that might be involved in the susceptibility of PCOS. MDPI 2015-01-22 /pmc/articles/PMC4346843/ /pubmed/25622255 http://dx.doi.org/10.3390/ijms16022403 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Feng, Chun
Lv, Ping-Ping
Yu, Tian-Tian
Jin, Min
Shen, Jin-Ming
Wang, Xue
Zhou, Feng
Jiang, Shi-Wen
The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis
title The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis
title_full The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis
title_fullStr The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis
title_full_unstemmed The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis
title_short The Association between Polymorphism of INSR and Polycystic Ovary Syndrome: A Meta-Analysis
title_sort association between polymorphism of insr and polycystic ovary syndrome: a meta-analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4346843/
https://www.ncbi.nlm.nih.gov/pubmed/25622255
http://dx.doi.org/10.3390/ijms16022403
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