Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome

Identification of shared gene signatures and biological mechanisms between preeclampsia and polycystic ovary syndrome

Preeclampsia (PE) is one of the most common complications of pregnancy and polycystic ovary syndrome (PCOS) is a prevalent metabolic and endocrinopathy disorder in women of reproductive age. Identifying the shared genetic signatures and molecular mechanisms between PCOS and PE was the objective of this study. The intersections of WGCNA module genes, PPI module genes, and PPI hub genes revealed that 8 immunity-related genes might be shared causative genes of PE and PCOS. Further, qRT-PCR results showed that TSIX/miR-223-3p/DDX58 might play a crucial role in immune dysregulation in PE and PCOS and Spearman rank correlation analysis results illustrated the potential of DDX58 as a novel diagnostic and therapeutic target for PE and PCOS. Our study demonstrated a common disease pathway model TSIX/miR-223-3p/DDX58, illustrating that immune dysregulation may be a possible mechanism of PE and PCOS, and revealed that DDX58 might be a novel predictive target for PE and PCOS.

MiRNAs related in signaling pathways of women's reproductive diseases: an overview

BACKGROUND

One of the main health issues that can affect women's health is reproductive diseases, such as polycystic ovary syndrome (PCOS), endometriosis (EMs), uterine leiomyomas (ULs), and ovarian cancer (OC). Although these diseases are very common, we do not have a complete understanding of their underlying cellular and molecular mechanisms. It is important to mention that the majority of patients are diagnosed with these diseases at later stages because of the absence of early diagnostic techniques and dependable molecular indicators. Hence, it is crucial to discover novel and non-invasive biomarkers that have prognostic, diagnostic and therapeutic capabilities. MiRNAs, also known as microRNAs, are small non-coding RNAs that play a crucial role in regulating gene expression at the post-transcriptional level. They are short in length, typically consisting of around 22 nucleotides, and are highly conserved across species. Numerous studies have shown that miRNAs are expressed differently in various diseases and can act as either oncogenes or tumor suppressors.

METHODS

The author conducted a comprehensive review of all the pertinent papers available in web of science, PubMed, Google Scholar, and Scopus databases.

RESULTS

We achieved three goals: providing readers with better information, enhancing search results, and making peer review easier.

CONCLUSIONS

This review focuses on the investigation of miRNAs and their involvement in various reproductive disorders in women, including their molecular targets. Additionally, it explores the role of miRNAs in the development and progression of these disorders.

CXC chemokines influence immune surveillance in immunological disorders: Polycystic ovary syndrome and endometriosis

Reproductive health is a worldwide challenge, but it is of particular significance to women during their reproductive age. Several female reproductive problems, including polycystic ovary syndrome (PCOS) and endometriosis, affect about 10 % of women and have a negative impact on their health, fertility, and quality of life. Small, chemotactic, and secreted cytokines are CXC chemokines. Both PCOS and endometriosis demonstrate dysregulation of CXC chemokines, which are critical to the development and progression of both diseases. Recent research has shown that both in humans and animals, CXC chemokines tend to cause inflammation. It has also been found that CXC chemokines are necessary for promoting angiogenesis and inflammatory responses. CXC chemokine overexpression is frequently associated with poor survival and prognosis. CXC chemokine levels in PCOS and endometriosis patients impact their circumstances significantly. Hence, CXC chemokines have significant potential as diagnostic and prognostic biomarkers and therapeutic targets. The molecular mechanisms through which CXC chemokines promote inflammation and the development of PCOS and endometriosis are currently unknown. This article will discuss the functions of CXC chemokines in the promotion, development, and therapy of PCOS and endometriosis, as well as future research directions. The current state and future prospects of CXC chemokine -based therapeutic strategies in the management of PCOS and endometriosis are also highlighted.

Transcriptomic screening to identify hub genes and drug signatures for PCOS based on RNA-Seq data in granulosa cells

BACKGROUND

Polycystic ovary syndrome (PCOS) is one of the most incident reproductive diseases, and remains the main cause of female infertility. Granulosa cells play a critical role in normal follicle development and steroid hormones synthesis. In spite of extensive research, no sole medication has been approved by FDA to treat PCOS. This study aimed to investigate the novel therapeutics targets in PCOS, focusing on granulosa cells transcriptome functional analysis with a drug repositioning approach.

METHODS

PCOS microarray and RNA-Seq datasets in granulosa cells were screened and reanalyzed. KEGG pathway enrichment and interaction network analyses were performed and followed by a set of drug signature screening and Poly-pharmacology survey.

RESULTS

545 deregulated genes were identified via filters including p_adj < 0.05 and |log2FC| > 1. Amongst the top 15 KEGG pathways significantly enriched, metabolism of xenobiotics by cytochrome P450, steroid hormone biosynthesis and ovarian steroidogenesis were observed. The Protein-Protein Interaction network identified 18 hub genes amongst this set. Interestingly, most candidate drug signatures have been introduced by databases are either FDA approved or entered into clinical trials, including melatonin, resveratrol and raloxifene. Investigational or experimental introduced drugs obey rules of drug-likeness with almost safe and acceptable ADMET properties. Notably, 21 top target genes of the final drug set were also included in the granulosa significant differentially expressed genes.

CONCLUSION

Results of the current study represent approved, investigational and experimental drug signatures according to the differentially expressed genes in granulosa cells with supported literature reviews. This data might be useful for researchers and clinicians to pave the way for better management of PCOS.

Unveiling Key Biomarkers and Therapeutic Drugs in Polycystic Ovary Syndrome (PCOS) Through Pathway Enrichment Analysis and Hub Gene-miRNA Networks

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.

Multiomics Analysis-Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome

Polycystic ovarian syndrome is an utmost communal endocrine, psychological, reproductive, and metabolic disorder that occurs in women of reproductive age with extensive range of clinical manifestations. This may even lead to long-term multiple morbidities including obesity, diabetes mellitus, insulin resistance, cardiovascular disease, infertility, cerebrovascular diseases, and ovarian and endometrial cancer. Women affliction from PCOS in midst assemblage of manifestations allied with menstrual dysfunction and androgen exorbitance, which considerably affects eminence of life. PCOS is recognized as a multifactorial disorder and systemic syndrome in first-degree family members; therefore, the etiology of PCOS syndrome has not been copiously interpreted. The disorder of PCOS comprehends numerous allied health conditions and has influenced various metabolic processes. Due to multifaceted pathophysiology engaging several pathways and proteins, single genetic diagnostic tests cannot be supportive to determine in straight way. Clarification of cellular and biochemical pathways and various genetic players underlying PCOS could upsurge our consideration of pathophysiology of this syndrome. It is requisite to know pathophysiological relationship between biomarker and their reflection towards PCOS disease. Biomarkers deliver vibrantly and potent ways to apprehend the spectrum of PCOS with applications in screening, diagnosis, characterization, and monitoring. This paper relies on the endeavor to point out many candidates as potential biomarkers based on omics technologies, thus highlighting correlation between PCOS disease with innovative technologies. Therefore, the objective of existing review is to encapsulate more findings towards cutting-edge advances in prospective use of biomarkers for PCOS disease. Discussed biomarkers may be fruitful in guiding therapies, addressing disease risk, and predicting clinical outcomes in future.

Systems biology and in silico-based analysis of PCOS revealed the risk of metabolic disorders

Background

Polycystic ovarian syndrome (PCOS) is a common condition of hyperandrogenism, chronic ovulation, and polycystic ovaries in females during the reproduction and maturation of the ovum. Although PCOS has been associated with metabolic disorders, including type 2 diabetes (T2D), obesity (OBE), and cardiovascular disease (CVD), Causal connection and molecular features are still unknown.

Purpose

Therefore, we investigated the shared common differentially expressed genes (DEGs), pathways, and networks of associated proteins in PCOS and metabolic diseases with therapeutic intervention.

Methods

We have used a bioinformatics pipeline to analyze transcriptome data for the polycystic ovarian syndrome (PCOS), type 2 diabetes (T2D), obesity (OBE), and cardiovascular diseases (CVD) in female patients. Then we employed gene-disease association network, gene ontology (GO) and signaling pathway analysis, selection of hub genes from protein-protein interaction (PPI) network, molecular docking, and gold benchmarking approach to screen potential hub proteins.

Result

We discovered 2225 DEGs in PCOS patients relative to healthy controls and 34, 91, and 205 significant DEGs with T2D, Obesity, and CVD, respectively. Gene Ontology analysis revealed several significant shared and metabolic pathways from signaling pathway analysis. Furthermore, we identified ten potential hub proteins from PPI analysis that may serve as a therapeutic intervention in the future. Finally, we targeted one significant hub protein, IGF2R (PDB ID: 2V5O), out of ten hub proteins based on the Maximal clique centrality (MCC) algorithm and literature review for molecular docking study. Enzastaurin (-12.5), Kaempferol (-9.1), Quercetin (-9.0), and Coumestrol (-8.9) kcal/mol showed higher binding affinity in the molecular docking approach than 19 drug compounds. We have also found that the selected four compounds displayed favorable ADMET properties compared to the native ligand.

Conclusion

Our in-silico research findings identified a shared molecular etiology between PCOS and metabolic diseases that may suggest new therapeutic targets and warrants future experimental validation of the key targets.

Exploration of hub genes involved in PCOS using biological informatics methods

BACKGROUND

The aim of this study was to find underlying genes and their interaction mechanism crucial to the polycystic ovarian syndrome (PCOS) by analyzing differentially expressed genes (DEGs) between PCOS and non-PCOS subjects.

METHODS

Gene expression data of PCOS and non-PCOS subjects were collected from gene expression omnibus (GEO) database. GEO2R were used to calculating P value and logFC. The screening threshold of DEGs was P < .05 and | FC | ≥ 1.2. GO annotation and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway enrichment analysis was performed by using DAVID (2021 Update). The protein-protein interaction (PPI) network of DEGs was constructed by using the STRING database, and the hub genes were recognized through Hubba plugin of Cytoscape software.

RESULTS

PCOS and non-PCOS subjects shared a total of 174 DGEs, including 14 upregulated and 160 downregulated genes. The GO biological processes enriched by DEGs mainly involved actin cytoskeleton organization, positive regulation of NF-κB signaling pathway, and positive regulation of canonical Wnt signaling pathway. The DEGs were significantly enriched in cytoplasm, nucleus and cytosol. Their molecular functions mainly focused on protein binding, calmodulin binding and glycerol-3-phosphate dehydrogenase activity. The PI3K/Akt signaling pathway and glycosaminoglycan biosynthesis were highlighted as critical pathways enriched by DEGs. 10 hub genes were screened from the constructed PPI network, of which EGF, FN1 and TLR4 were mainly enriched in the PI3K/Akt signaling pathway.

CONCLUSION

In this study, a total of 174 DEGs and 10 hub genes were identified as new candidate targets for insulin resistance (IR) in PCOS individuals, which may provide a new direction for developing novel treatment strategies for PCOS.

The interactions of CAP and LYN with the insulin signaling transducer CBL play an important role in polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is a hormonal disorder characterized by hyperandrogenism, ovulatory dysfunction, and insulin resistance. Evidence suggests that aberrations in insulin signaling-associated pathways may underlie PCOS pathogenesis. Our aim was to investigate the molecular mechanisms underlying PCOS and associated insulin resistance using in silico analyses, in vitro cell models, and in vivo murine models.

METHODS

R-based bioinformatics analysis was performed on granulosa cell microarray data from three human cohorts: healthy control, PCOS patients without insulin resistance, and PCOS patients with insulin resistance. Transgenic human granulosa cell models were utilized for in vitro studies. Transgenic murine models of dehydroepiandrosterone (DHEA)-induced PCOS were utilized for in vivo studies.

RESULTS

Sorbin and SH3 Domain Containing 1 (SORBS1), the parent gene of the insulin receptor-associated Casitas B-lineage lymphoma protein (CBL)-associated protein (CAP), is a key downregulated gene in PCOS patients with insulin resistance. CAP binding to CBL reduced CBL^Y731 phosphorylation, CBL-phosphoinositide 3-kinase (PI3K) p85α interactivity, protein kinase B (Akt)^S473 phosphorylation, and NFκB-induced inflammatory marker expression but enhanced CRKII-mediated membrane GLUT4 translocation in granulosa cells. In contrast, the tyrosine kinase Lck/Yes-Related Novel Protein (LYN) is upregulated in PCOS patients with insulin resistance. LYN binding to CBL enhanced CBL^Y731 phosphorylation, CBL-PI3K p85α interactivity, Akt^S473 phosphorylation, and NFκB-induced inflammatory marker expression but did not impact membrane GLUT4 translocation. In PCOS mice, Cap overexpression, Cap transactivation by metformin, or enhancing Cbl-CrkII binding improved insulin sensitivity and ovarian dysfunction (i.e., estrous cycle disruption, cyst-like follicle formation, and sex hormone dysregulation). In contrast, Lyn knockdown, Lyn inhibition by PP2, or CBL-PI3K p85α blockade improved only ovarian dysfunction. Cbl^3YF phosphomutant overexpression (which enhances Cbl-CrkII binding but blocks Cbl-PI3K p85α binding) ameliorated both ovarian dysfunction and insulin resistance.

CONCLUSIONS

The interactions of CAP and LYN with CBL, and the resulting effects on CBL phosphorylation and activity, may play an important role in PCOS pathogenesis. Targeting these players may be a viable therapeutic strategy for PCOS.

Transcriptome Profiling of Oocytes at the Germinal Vesicle Stage from Women from Mongolia with Polycystic Ovary Syndrome

Background

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders. Evidence indicates that genetic and environmental factors contribute to the pathogenesis of PCOS. The molecular basis of PCOS is not well understood.

Methods

Whole-genome RNA sequencing was performed on single oocyte at the germinal vesicle (GV) stage from females with normal ovulation and females with PCOS. All subjects were women from Mongolia undergoing intracytoplasmic sperm injection in vitro fertilization (ICSI-IVF) who met the Rotterdam criteria for PCOS. Women with normal ovulation who were undergoing ICSI-IVF owing to male factor infertility were recruited as control subjects.

Results

A total of 1313 differentially expressed genes were found by bio-informatics software in the GV oocytes of PCOS patients and compared with the control group. There were 367 upregulated and 946 downregulated genes (fold change > 2, false discovery rate < 0.01). When compared with the healthy controls, it was shown that the DEGs like VEGF, IGF, FADS1 et al were investigated as potential causes of PCOS oocytes. The DEGs were related to kinase activity, cell proliferation, gene regulation, and the signaling pathways of phosphatidylinositol 3-kinase, Hippo, and ECM-receptor pathway in patients with PCOS. In addition, the interconnected gene co-expression network was constructed by gene bionetwork analysis, indicating that ITGB5, ITGB3, and CAV2 were the core genes in regulating the module expression of DEGs in PCOS.

Conclusion

RNA sequencing analysis demonstrated DEGs were linked to inflammation, cardiovascular disease, and lipid metabolism in the GV oocytes of women with PCOS. We hypothesize that ITGB5, ITGB3, and CAV2 may be involved in metabolic disorders associated with the different phenotypes of PCOS.

Rho GTPase Activating Protein 9 (ARHGAP9) in Human Cancers

BACKGROUND

In recent years, targeted therapy combined with traditional chemoradiotherapy and surgery has brought new opportunities for cancer treatment. However, the complex characteristics of cancer, such as heterogeneity and diversity, limit the clinical success of targeted drugs. The discovery of new cancer targets and deepening the understanding of their functional mechanisms will bring additional promising application prospects for the research and development of personalized cancer-targeted drugs.

OBJECTIVE

This study aimed to summarize the role of the Rho GTPase activating protein 9 (ARHGAP9) gene in tumorigenesis and development to discover therapeutic targets for cancer in the future.

METHODS

For this review, we collected patents from the databases of Espacenet and WIPO and articles from PubMed that were related to the ARHGAP9 gene.

RESULTS

Genetic/epigenetic variations and abnormal expression of the ARHGAP9 gene are closely associated with a variety of diseases, including cancer. ARHGAP9 can inactivate Rho GTPases by hydrolyzing GTP into GDP and regulate cancer cellular events, including proliferation, differentiation, apoptosis, migration and invasion, by inhibiting JNK/ERK/p38 and PI3K/AKT signaling pathways. In addition to reviewing these mechanisms, we assessed various patents on ARHGAP9 to determine whether ARHGAP9 might be used as a predictive biomarker for diagnosis/prognosis evaluation and a druggable target for cancer treatment.

CONCLUSION

In this review, the current knowledge of ARHGAP9 in cancer is summarized with an emphasis on its molecular function, regulatory mechanism and disease implications. Its characterization is crucial to understanding its important roles during different stages of cancer progression and therapy as a predictive biomarker and/or target.

Association between melatonin receptor gene polymorphisms and polycystic ovarian syndrome: a systematic review and meta-analysis

BACKGROUND

Polycystic ovarian syndrome (PCOS) is a kind of common gynecological endocrine disorder. And the mutations of melatonin receptor (MTNR) genes are related to the occurrence of PCOS. But previous researches have shown opposite results. So, the object of our systematic review and meta-analysis is to investigate the relationship between MTNR 1A/B polymorphisms and PCOS.

METHODS

PubMed, Embase, Ovid, the Cochrane Library, Web of Science and three Chinese databases (VIP, CNKI and Wanfang) were used to retrieve eligible articles published between January 1980 and February 2020. And we used the odds ratio (OR) and its 95% confidence interval (CI) to investigate the strength of the association by six genetic models, allelic, codominant (homozygous and heterozygous), dominant, recessive and superdominant models. Review Manager 5.3, IBM SPSS statistics 25 and Stata MP 16.0 software were used to do this meta-analysis.

RESULTS

Our meta-analysis involved 2553 PCOS patients and 3152 controls, for two single nucleotide polymorphisms (rs10830963 C> G in MTNR1B and rs2119882 T> C in MTNR1A) and significant associations were found in some genetic models of these single nucleotide polymorphisms (SNPs). For rs10830963, strongly significant was found in the heterozygote model (GC vs. CC, P=0.02). Additionally, a slight trend was detected in the allelic (G vs. C), homozygote (GG vs. CC) and dominant (GG+GC vs. CC) model of rs10830963 (P=0.05). And after further sensitivity analysis, a study with high heterogeneity was removed. In the allelic (P=0.000), homozygote (P=0.001), dominant (P=0.000) and recessive (GG vs. GC+CC, P=0.001) model, strong associations between rs10830963 and PCOS were found. Moreover, for rs2119882, five genetic models, allelic (C vs. T, P=0.000), codominant (the homozygote (CC vs. TT, P=0.000) and heterozygote model (CT vs. TT, P=0.02), dominant (CC + CT vs. TT, P=0.03) and recessive model (CC vs. CT + TT, P=0.000) showed significant statistical associations with PCOS.

CONCLUSION

MTNR1B rs10830963 and MTNR1B rs2119882 polymorphisms are associated with PCOS risk. However, the above conclusions still require being confirmed by much larger multi-ethnic studies.

Different transcriptome profiles between human retinoblastoma Y79 cells and an etoposide-resistant subline reveal a chemoresistance mechanism

Background

Retinoblastoma (RB) is the most frequent pediatric retinal tumor. In the present study, to elucidate chemoresistance mechanisms and identify potential biomarkers in RB, we utilized RNA sequencing (RNAseq) technological platforms to reveal transcriptome profiles and identify any differentially expressed genes (DEGs) between an etoposide drug-resistant subline (Y79/EDR) and parental Y79 cells.

Methods

To test whether Y79/EDR cells showed resistance to antineoplastic agents for RB, we treated the cells with etoposide, carboplatin and vincristine and analyzed them with a Cell Counting Kit-8 (CCK-8). Y79/EDR and parental Y79 cells were used for RNAseq and bioinformatics analysis to enable a genome-wide review of DEGs between the two lines using the DESeq R package (1.10.1). Then, DEG enrichment in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was analyzed with KOBAS software. Next, real-time quantitative reverse transcription polymerase chain reaction (real time QRT-PCR) and cytotoxicity assays were performed to experimentally and functionally validate the identified candidate biomarkers.

Results

Y79/EDR cells showed resistance to etoposide, carboplatin and vincristine at different concentrations. In total, 524 transcripts were differentially expressed in Y79/EDR cells based on analysis of fragments per kilobase of transcript per million fragments mapped (FPKM); among these, 57 genes were downregulated and 467 genes were upregulated in Y79/EDR cells compared to parental Y79 cells. We selected candidate DEGs, including ARHGAP9, HIST1H4H, RELN, DDIT4, HK2, STC1 and PFKFB4, for mRNA expression validation with real time QRT-PCR assays and found that the expression levels determined by real time QRT-PCR were consistent with the RNAseq data. Further studies involving downregulation of ARHGAP9 with a specific siRNA showed that ARHGAP9 altered the cellular sensitivity of Y79 cells to etoposide and carboplatin.

Conclusion

Our initial findings provided a genomic view of the transcription profiles of etoposide-induced acquired resistance in RB. Follow-up studies indicated that ARHGAP9 might be a chemoresistance biomarker in RB, providing insight into potential therapeutic targets for overcoming acquired chemoresistance in RB. These findings can aid in understanding and overcoming chemoresistance during treatment of RB in the clinic.

Topologically inferring active miRNA-mediated subpathways toward precise cancer classification by directed random walk

Accurate predictions of classification biomarkers and disease status are indispensable for clinical cancer diagnosis and research. However, the robustness of conventional gene biomarkers is limited by issues with reproducibility across different measurement platforms and cohorts of patients. In this study, we collected 4775 samples from 12 different cancer datasets, which contained 4636 TCGA samples and 139 GEO samples. A new method was developed to detect miRNA‐mediated subpathway activities by using directed random walk (miDRW). To calculate the activity of each miRNA‐mediated subpathway, we constructed a global directed pathway network (GDPN) with genes as nodes. We then identified miRNAs with expression levels which were strongly inversely correlated with differentially expressed target genes in the GDPN. Finally, each miRNA‐mediated subpathway activity was integrated with the topological information, differential levels of miRNAs and genes, expression levels of genes, and target relationships between miRNAs and genes. The results showed that the proposed method yielded a more robust and accurate overall performance compared with other existing pathway‐based, miRNA‐based, and gene‐based classification methods. The high‐frequency miRNA‐mediated subpathways are more reliable in classifying samples and for selecting therapeutic strategies.

Epigenetic association analysis of clinical sub-phenotypes in patients with polycystic ovary syndrome (PCOS)

Polycystic ovarian syndrome (PCOS) is a complex disorder affecting up to 15-20% of reproductive women. PCOS has recently been investigated using genome-wide association studies revealing important mutations and DNA methylation sites associated with the syndrome. As a clinically highly heterogenous condition, studying the molecular basis of the differential manifestation of PCOS is both meaningful concerning individualized management and important for understanding the biology of PCOS. Using genome-wide DNA methylation data collected from PCOS patients, we performed a powerful region-based analysis to detect differentially methylated regions (DMR) by correlating DNA methylation pattern in a genomic region with the level of each PCOS clinical sub-phenotype. We identified seven significant DMRs on chromosome 19 (12877188-12876846 bp) and chromosome 6 (MHC region) associated with prolactin level, as well as chromosomes 11 and 2 associated with metabolic attributes. Functional annotation linked significant DNA methylation patterns to functional genes (HOOK2, BDNFl, HLA-G, HLA-H, HLA-J, RNF39, etc) of metabolic disorders and immunity or novel associations to serve as targets for validation and replication.