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Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles

Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out...

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Autores principales: Lu, Chenqi, Liu, Xiaoqin, Wang, Lin, Jiang, Ning, Yu, Jun, Zhao, Xiaobo, Hu, Hairong, Zheng, Saihua, Li, Xuelian, Wang, Guiying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356873/
https://www.ncbi.nlm.nih.gov/pubmed/27965459
http://dx.doi.org/10.18632/oncotarget.13881
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author Lu, Chenqi
Liu, Xiaoqin
Wang, Lin
Jiang, Ning
Yu, Jun
Zhao, Xiaobo
Hu, Hairong
Zheng, Saihua
Li, Xuelian
Wang, Guiying
author_facet Lu, Chenqi
Liu, Xiaoqin
Wang, Lin
Jiang, Ning
Yu, Jun
Zhao, Xiaobo
Hu, Hairong
Zheng, Saihua
Li, Xuelian
Wang, Guiying
author_sort Lu, Chenqi
collection PubMed
description Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.
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spelling pubmed-53568732017-04-20 Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles Lu, Chenqi Liu, Xiaoqin Wang, Lin Jiang, Ning Yu, Jun Zhao, Xiaobo Hu, Hairong Zheng, Saihua Li, Xuelian Wang, Guiying Oncotarget Research Paper Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome. Impact Journals LLC 2016-12-10 /pmc/articles/PMC5356873/ /pubmed/27965459 http://dx.doi.org/10.18632/oncotarget.13881 Text en Copyright: © 2017 Lu 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Lu, Chenqi
Liu, Xiaoqin
Wang, Lin
Jiang, Ning
Yu, Jun
Zhao, Xiaobo
Hu, Hairong
Zheng, Saihua
Li, Xuelian
Wang, Guiying
Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
title Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
title_full Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
title_fullStr Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
title_full_unstemmed Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
title_short Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
title_sort integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356873/
https://www.ncbi.nlm.nih.gov/pubmed/27965459
http://dx.doi.org/10.18632/oncotarget.13881
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