BACKGROUND: This study aimed to integrate DNA methylation, miRNA, and mRNA microarray data to construct a gene co-expression network for polycystic ovarian syndrome (PCOS). METHODS: The weighted gene co-expression network analysis (WGCNA) was conducted to construct a PCOS-related co-expression network by using the GEO public datasets. We performed Gene Ontology and KEGG pathway enrichment analyses for a further exploration of gene function in networks. Finally, the dysfunction module consisting of a co-expression network was mapped to the PCOS patients and tried to provide guidance to the PCOS phenotyping. RESULTS: Three modules (Midnightbule, Pink, and Red) were identified to be PCOS-related by WGCNA analysis. These module-related genes were enriched in cell response to stimulus, PI3K-Akt signaling pathway, insulin biological process, signaling pathway, and cytokine-cytokine receptor interaction biological processes. The multiple-factor network, including miRNA-lncRNA and DNA methylation-mRNA interaction, was closely associated with PCOS dysfunction. CONCLUSION: Our study render a novel insight into the mechanisms and might provide candidate biomarkers and therapeutic targets for the classification of PCOS dysfunction. AJTR
BACKGROUND: This study aimed to integrate DNA methylation, miRNA, and mRNA microarray data to construct a gene co-expression network for polycystic ovarian syndrome (PCOS). METHODS: The weighted gene co-expression network analysis (WGCNA) was conducted to construct a PCOS-related co-expression network by using the GEO public datasets. We performed Gene Ontology and KEGG pathway enrichment analyses for a further exploration of gene function in networks. Finally, the dysfunction module consisting of a co-expression network was mapped to the PCOS patients and tried to provide guidance to the PCOS phenotyping. RESULTS: Three modules (Midnightbule, Pink, and Red) were identified to be PCOS-related by WGCNA analysis. These module-related genes were enriched in cell response to stimulus, PI3K-Akt signaling pathway, insulin biological process, signaling pathway, and cytokine-cytokine receptor interaction biological processes. The multiple-factor network, including miRNA-lncRNA and DNA methylation-mRNA interaction, was closely associated with PCOS dysfunction. CONCLUSION: Our study render a novel insight into the mechanisms and might provide candidate biomarkers and therapeutic targets for the classification of PCOS dysfunction. AJTR
Authors: Felix R Day; David A Hinds; Joyce Y Tung; Lisette Stolk; Unnur Styrkarsdottir; Richa Saxena; Andrew Bjonnes; Linda Broer; David B Dunger; Bjarni V Halldorsson; Debbie A Lawlor; Guillaume Laval; Iain Mathieson; Wendy L McCardle; Yvonne Louwers; Cindy Meun; Susan Ring; Robert A Scott; Patrick Sulem; André G Uitterlinden; Nicholas J Wareham; Unnur Thorsteinsdottir; Corrine Welt; Kari Stefansson; Joop S E Laven; Ken K Ong; John R B Perry Journal: Nat Commun Date: 2015-09-29 Impact factor: 14.919
Authors: M Geoffrey Hayes; Margrit Urbanek; David A Ehrmann; Loren L Armstrong; Ji Young Lee; Ryan Sisk; Tugce Karaderi; Thomas M Barber; Mark I McCarthy; Stephen Franks; Cecilia M Lindgren; Corrine K Welt; Evanthia Diamanti-Kandarakis; Dimitrios Panidis; Mark O Goodarzi; Ricardo Azziz; Yi Zhang; Roland G James; Michael Olivier; Ahmed H Kissebah; Elisabet Stener-Victorin; Richard S Legro; Andrea Dunaif Journal: Nat Commun Date: 2015-08-18 Impact factor: 14.919