Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules

Abstract To enhance understanding of polycystic ovary syndrome (PCOS) at the molecular level; this investigation intends to examine the genes and pathways associated with PCOS by using an integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing data GSE8495...

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Main Authors: Praveenkumar Devarbhavi, Lata Telang, Basavaraj Vastrad, Anandkumar Tengli, Chanabasayya Vastrad, Iranna Kotturshetti
Format: Article
Language:English
Published: BMC 2021-02-01
Series:Reproductive Biology and Endocrinology
Subjects:
Online Access:https://doi.org/10.1186/s12958-021-00706-3
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spelling doaj-6dfb8d4cee354f809d3d960fb2b3d4df2021-02-23T09:28:14ZengBMCReproductive Biology and Endocrinology1477-78272021-02-0119113910.1186/s12958-021-00706-3Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic moleculesPraveenkumar Devarbhavi0Lata Telang1Basavaraj Vastrad2Anandkumar Tengli3Chanabasayya Vastrad4Iranna Kotturshetti5Department of Endocrinology and Metabolism, Subbaiah Institute of Medical Sciences and Research CentreDepartment of Gynaecology and Obstetrics, Subbaiah Institute of Medical Sciences and Research CentreDepartment of Biochemistry, Basaveshwar College of PharmacyDepartment of Pharmaceutical Chemistry, JSS College of Pharmacy, Mysuru and JSS Academy of Higher Education & ResearchBiostatistics and BioinformaticsDepartment of Ayurveda, Rajiv Gandhi Education Society’s Ayurvedic Medical CollegeAbstract To enhance understanding of polycystic ovary syndrome (PCOS) at the molecular level; this investigation intends to examine the genes and pathways associated with PCOS by using an integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing data GSE84958 derived from the Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) between PCOS samples and normal controls were identified. We performed a functional enrichment analysis. A protein-protein interaction (PPI) network, miRNA- target genes and TF - target gene networks, were constructed and visualized, with which the hub gene nodes were identified. Validation of hub genes was performed by using receiver operating characteristic (ROC) and RT-PCR. Small drug molecules were predicted by using molecular docking. A total of 739 DEGs were identified, of which 360 genes were up regulated and 379 genes were down regulated. GO enrichment analysis revealed that up regulated genes were mainly involved in peptide metabolic process, organelle envelope and RNA binding and the down regulated genes were significantly enriched in plasma membrane bounded cell projection organization, neuron projection and DNA-binding transcription factor activity, RNA polymerase II-specific. REACTOME pathway enrichment analysis revealed that the up regulated genes were mainly enriched in translation and respiratory electron transport and the down regulated genes were mainly enriched in generic transcription pathway and transmembrane transport of small molecules. The top 10 hub genes (SAA1, ADCY6, POLR2K, RPS15, RPS15A, CTNND1, ESR1, NEDD4L, KNTC1 and NGFR) were identified from PPI network, miRNA - target gene network and TF - target gene network. The modules analysis showed that genes in modules were mainly associated with the transport of respiratory electrons and signaling NGF, respectively. We find a series of crucial genes along with the pathways that were most closely related with PCOS initiation and advancement. Our investigations provide a more detailed molecular mechanism for the progression of PCOS, detail information on the potential biomarkers and therapeutic targets.https://doi.org/10.1186/s12958-021-00706-3polycystic ovary syndromeexpression profiling by high throughput sequencingbiomarkerspathway enrichment analysisdifferentially expressed gene
collection DOAJ
language English
format Article
sources DOAJ
author Praveenkumar Devarbhavi
Lata Telang
Basavaraj Vastrad
Anandkumar Tengli
Chanabasayya Vastrad
Iranna Kotturshetti
spellingShingle Praveenkumar Devarbhavi
Lata Telang
Basavaraj Vastrad
Anandkumar Tengli
Chanabasayya Vastrad
Iranna Kotturshetti
Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
Reproductive Biology and Endocrinology
polycystic ovary syndrome
expression profiling by high throughput sequencing
biomarkers
pathway enrichment analysis
differentially expressed gene
author_facet Praveenkumar Devarbhavi
Lata Telang
Basavaraj Vastrad
Anandkumar Tengli
Chanabasayya Vastrad
Iranna Kotturshetti
author_sort Praveenkumar Devarbhavi
title Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
title_short Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
title_full Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
title_fullStr Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
title_full_unstemmed Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
title_sort identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
publisher BMC
series Reproductive Biology and Endocrinology
issn 1477-7827
publishDate 2021-02-01
description Abstract To enhance understanding of polycystic ovary syndrome (PCOS) at the molecular level; this investigation intends to examine the genes and pathways associated with PCOS by using an integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing data GSE84958 derived from the Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) between PCOS samples and normal controls were identified. We performed a functional enrichment analysis. A protein-protein interaction (PPI) network, miRNA- target genes and TF - target gene networks, were constructed and visualized, with which the hub gene nodes were identified. Validation of hub genes was performed by using receiver operating characteristic (ROC) and RT-PCR. Small drug molecules were predicted by using molecular docking. A total of 739 DEGs were identified, of which 360 genes were up regulated and 379 genes were down regulated. GO enrichment analysis revealed that up regulated genes were mainly involved in peptide metabolic process, organelle envelope and RNA binding and the down regulated genes were significantly enriched in plasma membrane bounded cell projection organization, neuron projection and DNA-binding transcription factor activity, RNA polymerase II-specific. REACTOME pathway enrichment analysis revealed that the up regulated genes were mainly enriched in translation and respiratory electron transport and the down regulated genes were mainly enriched in generic transcription pathway and transmembrane transport of small molecules. The top 10 hub genes (SAA1, ADCY6, POLR2K, RPS15, RPS15A, CTNND1, ESR1, NEDD4L, KNTC1 and NGFR) were identified from PPI network, miRNA - target gene network and TF - target gene network. The modules analysis showed that genes in modules were mainly associated with the transport of respiratory electrons and signaling NGF, respectively. We find a series of crucial genes along with the pathways that were most closely related with PCOS initiation and advancement. Our investigations provide a more detailed molecular mechanism for the progression of PCOS, detail information on the potential biomarkers and therapeutic targets.
topic polycystic ovary syndrome
expression profiling by high throughput sequencing
biomarkers
pathway enrichment analysis
differentially expressed gene
url https://doi.org/10.1186/s12958-021-00706-3
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