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Heidarzadehpilehrood R, Pirhoushiaran M. Biomarker potential of competing endogenous RNA networks in Polycystic Ovary Syndrome (PCOS). Noncoding RNA Res 2024; 9:624-640. [PMID: 38571815 PMCID: PMC10988127 DOI: 10.1016/j.ncrna.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 12/21/2023] [Accepted: 01/08/2024] [Indexed: 04/05/2024] Open
Abstract
Polycystic ovary syndrome (PCOS) is the most common condition affecting women of reproductive age globally. PCOS continues to be the largest contributing factor to female infertility despite significant progress in our knowledge of the molecular underpinnings and treatment of the condition. The fact that PCOS is a very diverse condition makes it one of the key reasons why we haven't been able to overcome it. Non-coding RNAs (ncRNAs) are implicated in the development of PCOS, according to growing evidence. However, it is unclear how the complex regulatory relationships between the many ncRNA types contribute to the growth of this malignancy. Competing endogenous RNA (ceRNA), a recently identified mechanism in the RNA world, suggests regulatory interactions between various RNAs, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), transcribed pseudogenes, and circular RNAs (circRNAs). Recent studies on PCOS have shown that dysregulation of multiple ceRNA networks (ceRNETs) between these ncRNAs plays crucial roles in developing the defining characteristics of PCOS development. And it is believed that such a finding may open a new door for a deeper comprehension of PCOS's unexplored facets. In addition, it may be able to provide fresh biomarkers and effective therapy targets for PCOS. This review will go over the body of information that exists about the primary roles of ceRNETs before highlighting the developing involvement of several newly found ceRNETs in a number of PCOS characteristics.
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Affiliation(s)
- Roozbeh Heidarzadehpilehrood
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Maryam Pirhoushiaran
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, 1417613151, Iran
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Heidarzadehpilehrood R, Pirhoushiaran M, Binti Osman M, Abdul Hamid H, Ling KH. Weighted Gene Co-Expression Network Analysis (WGCNA) Discovered Novel Long Non-Coding RNAs for Polycystic Ovary Syndrome. Biomedicines 2023; 11:biomedicines11020518. [PMID: 36831054 PMCID: PMC9953234 DOI: 10.3390/biomedicines11020518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 02/15/2023] Open
Abstract
Polycystic ovary syndrome (PCOS) affects reproductive-age women. This condition causes infertility, insulin resistance, obesity, and heart difficulties. The molecular basis and mechanism of PCOS might potentially generate effective treatments. Long non-coding RNAs (lncRNAs) show control over multifactorial disorders' growth and incidence. Numerous studies have emphasized its significance and alterations in PCOS. We used bioinformatic methods to find novel dysregulated lncRNAs in PCOS. To achieve this objective, the gene expression profile of GSE48301, comprising PCOS patients and normal control tissue samples, was evaluated using the R limma package with the following cut-off criterion: p-value < 0.05. Firstly, weighted gene co-expression network analysis (WGCNA) was used to determine the co-expression genes of lncRNAs; subsequently, hub gene identification and pathway enrichment analysis were used. With the defined criteria, nine novel dysregulated lncRNAs were identified. In WGCNA, different colors represent different modules. In the current study, WGCNA resulted in turquoise, gray, blue, and black co-expression modules with dysregulated lncRNAs. The pathway enrichment analysis of these co-expressed modules revealed enrichment in PCOS-associated pathways, including gene expression, signal transduction, metabolism, and apoptosis. In addition, CCT7, EFTUD2, ESR1, JUN, NDUFAB1, CTTNB1, GRB2, and CTNNB1 were identified as hub genes, and some of them have been investigated in PCOS. This study uncovered nine novel PCOS-related lncRNAs. To confirm how these lncRNAs control translational modification in PCOS, functional studies are required.
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Affiliation(s)
- Roozbeh Heidarzadehpilehrood
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Maryam Pirhoushiaran
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran 1417613151, Iran
| | - Malina Binti Osman
- Department of Medical Microbiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Habibah Abdul Hamid
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Malaysia
- Correspondence: (H.A.H.); (K.-H.L.)
| | - King-Hwa Ling
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Malaysia
- Correspondence: (H.A.H.); (K.-H.L.)
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Heidarzadehpilehrood R, Pirhoushiaran M, Binti Osman M, Ling KH, Abdul Hamid H. Unveiling Key Biomarkers and Therapeutic Drugs in Polycystic Ovary Syndrome (PCOS) Through Pathway Enrichment Analysis and Hub Gene-miRNA Networks. Iran J Pharm Res 2023; 22:e139985. [PMID: 38444712 PMCID: PMC10912876 DOI: 10.5812/ijpr-139985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 10/07/2023] [Accepted: 10/16/2023] [Indexed: 03/07/2024]
Abstract
Background Polycystic ovary syndrome (PCOS) affects women of reproductive age globally with an incidence rate of 5% - 26%. Growing evidence reports important roles for microRNAs (miRNAs) in the pathophysiology of granulosa cells (GCs) in PCOS. Objectives The objectives of this study were to identify the top differentially expressed miRNAs (DE-miRNAs) and their corresponding targets in hub gene-miRNA networks, as well as identify novel DE-miRNAs by analyzing three distinct microarray datasets. Additionally, functional enrichment analysis was performed using bioinformatics approaches. Finally, interactions between the 5 top-ranked hub genes and drugs were investigated. Methods Using bioinformatics approaches, three GC profiles from the gene expression omnibus (GEO), namely gene expression omnibus series (GSE)-34526, GSE114419, and GSE137684, were analyzed. Targets of the top DE-miRNAs were predicted using the multiMiR R package, and only miRNAs with validated results were retrieved. Genes that were common between the "DE-miRNA prediction results" and the "existing tissue DE-mRNAs" were designated as differentially expressed genes (DEGs). Gene ontology (GO) and pathway enrichment analyses were implemented for DEGs. In order to identify hub genes and hub DE-miRNAs, the protein-protein interaction (PPI) network and miRNA-mRNA interaction network were constructed using Cytoscape software. The drug-gene interaction database (DGIdb) database was utilized to identify interactions between the top-ranked hub genes and drugs. Results Out of the top 20 DE-miRNAs that were retrieved from the GSE114419 and GSE34526 microarray datasets, only 13 of them had "validated results" through the multiMiR prediction method. Among the 13 DE-miRNAs investigated, only 5, namely hsa-miR-8085, hsa-miR-548w, hsa-miR-612, hsa-miR-1470, and hsa-miR-644a, demonstrated interactions with the 10 hub genes in the hub gene-miRNA networks in our study. Except for hsa-miR-612, the other 4 DE-miRNAs, including hsa-miR-8085, hsa-miR-548w, hsa-miR-1470, and hsa-miR-644a, are novel and had not been reported in PCOS pathogenesis before. Also, GO and pathway enrichment analyses identified "pathogenic E. coli infection" in the Kyoto encyclopedia of genes and genomes (KEGG) and "regulation of Rac1 activity" in FunRich as the top pathways. The drug-hub gene interaction network identified ACTB, JUN, PTEN, KRAS, and MAPK1 as potential targets to treat PCOS with therapeutic drugs. Conclusions The findings from this study might assist researchers in uncovering new biomarkers and potential therapeutic drug targets in PCOS treatment.
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Affiliation(s)
- Roozbeh Heidarzadehpilehrood
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Maryam Pirhoushiaran
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, 1417613151, Tehran, Iran
| | - Malina Binti Osman
- Department of Medical Microbiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - King-Hwa Ling
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
- Malaysian Research Institution on Ageing, (MyAgeing), Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Habibah Abdul Hamid
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
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Rahimpour A, Heidarzadehpilehrood R, Abdollahi S, Ranjbari H, Shams Z, Ghasemi SA, Najmaei S, Pirhoushiaran M. A comprehensive bioinformatic analysis revealed novel MicroRNA biomarkers of Parkinson's disease. Cell Biol Int 2022; 46:1841-1851. [PMID: 36098337 DOI: 10.1002/cbin.11869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/18/2022] [Accepted: 07/06/2022] [Indexed: 11/08/2022]
Abstract
Parkinson's disease (PD) is categorized as a neurodegenerative disorder. Different studies have focused on the role of microRNAs (miRNAs) on PD progression. Due to its complexity in initiation and progression, a considerable requirement has arisen to identify novel miRNA biomarkers in a noninvasive manner. In silico analysis has been used to select differentially expressed miRNAs (DE-miRNAs) and key pathways in this disease. In this manner, several data sets of different neurodegenerative diseases have been analyzed to purify the findings of the present study. Totally, 15 DE miRNAs showed significant changes compared to healthy controls and other neurodegenerative diseases. Then, the targets of the miRNAs were predicted through miRTarBase and TargetScan databases. Besides, enrichment analysis was implemented for predicted target genes. Most of the target genes were enriched in the TRAIL signaling pathway, Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism, protein serine/threonine kinase activity, and Cytoplasm. Moreover, a protein-protein interaction network was constructed to find the most key DE miRNAs and targets in this disease. The results of the present study may help researchers shed light on the discovery of novel biomarkers for PD.
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Affiliation(s)
- Alireza Rahimpour
- Islamic Azad University of science and research branch Tehran, Tehran, Iran
| | - Roozbeh Heidarzadehpilehrood
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Sepideh Abdollahi
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Haidar Ranjbari
- Student Research Committee, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Zinat Shams
- Department of Biological Sciences, Kharazmi University, Tehran, Iran
| | - Seyed Abbas Ghasemi
- Department of Medical Microbiology and Parasitology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor Darul Ehsan, Malaysia
| | - Shima Najmaei
- University of Rostock, Institute of Biological Sciences, Division of Microbiology, A.-Einstein-Str. 3, Rostock, Germany
| | - Maryam Pirhoushiaran
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Abdollahzadeh R, Shushizadeh MH, Barazandehrokh M, Choopani S, Azarnezhad A, Paknahad S, Pirhoushiaran M, Makani SZ, Yeganeh RZ, Al-Kateb A, Heidarzadehpilehrood R. Association of Vitamin D receptor gene polymorphisms and clinical/severe outcomes of COVID-19 patients. Infect Genet Evol 2021; 96:105098. [PMID: 34610433 PMCID: PMC8487094 DOI: 10.1016/j.meegid.2021.105098] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 09/11/2021] [Accepted: 09/27/2021] [Indexed: 12/23/2022]
Abstract
Introduction Growing evidence documented the critical impacts of vitamin D (VD) in the prognosis of COVID-19 patients. The functions of VD are dependent on the vitamin D receptor (VDR) in the VD/VDR signaling pathway. Therefore, we aimed to assess the association of VDR gene polymorphisms with COVID-19 outcomes. Methods In the present study, eight VDR single nucleotide polymorphisms (SNPs) were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in 500 COVID-19 patients in Iran, including 160 asymptomatic, 250 mild/moderate, and 90 severe/critical cases. The association of these polymorphisms with severity, clinical outcomes, and comorbidities were evaluated through the calculation of the Odds ratio (OR). Results Interestingly, significant associations were disclosed for some of the SNP-related alleles and/or genotypes in one or more genetic models with different clinical data in COVID-19 patients. Significant association of VDR-SNPs with signs, symptoms, and comorbidities was as follows: ApaI with shortness of breath (P ˂ 0.001) and asthma (P = 0.034) in severe/critical patients (group III); BsmI with chronic renal disease (P = 0.010) in mild/moderate patients (group II); Tru9I with vomiting (P = 0.031), shortness of breath (P = 0.04), and hypertension (P = 0.030); FokI with fever and hypertension (P = 0.027) in severe/critical patients (group III); CDX2 with shortness of breath (P = 0.022), hypertension (P = 0.036), and diabetes (P = 0.042) in severe/critical patients (group III); EcoRV with diabetes (P ˂ 0.001 and P = 0.045 in mild/moderate patients (group II) and severe/critical patients (group III), respectively). However, the association of VDR TaqI and BglI polymorphisms with clinical symptoms and comorbidities in COVID-19 patients was not significant. Conclusion VDR gene polymorphisms might play critical roles in the vulnerability to infection and severity of COVID-19, probably by altering the risk of comorbidities. However, these results require further validation in larger studies with different ethnicities and geographical regions.
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Affiliation(s)
- Rasoul Abdollahzadeh
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
| | | | - Mina Barazandehrokh
- Faculty of Advanced Sciences and Technology, Pharmaceutical Sciences Branch, Islamic Azad University (IAUPS), Tehran, Iran
| | | | - Asaad Azarnezhad
- Liver and Digestive Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
| | - Sahereh Paknahad
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Pirhoushiaran
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - S Zahra Makani
- Babol Razi Pathology and Genetic Laboratory, Babol, Iran
| | - Razieh Zarifian Yeganeh
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmed Al-Kateb
- Department of Medical Genetics, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
| | - Roozbeh Heidarzadehpilehrood
- Department of Obstetrics & Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Malaysia.
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