Genomic analysis, which is the study of the structure, function, and expression of genes in an organism, is one of the methodologies used to explain the molecular basis of PCOS and its consequences. We used published gene expression profile data and a bioinformatics analysis tool to investigate DEGs in PCOS skeletal muscle. Our systematic analysis would help to understand the molecular complications of PCOS associated with diabetes. This study is complemented by knowledge of PCOS-related disorders to the PCOS pathway network to establish the mechanistic interactions between PCOS and other diseases.
The etiopathology of PCOS has not been fully understood despite a vast amount of research being progressed and to date, no effective systemic or targeted therapy exists. A large amount of data from transcriptomic or genome-wide associated studies on PCOS patients are publicly available. These data profiles can be used to comprehensively understand the pathophysiology of PCOS and its accelerated risks in the patients. An integrated GEO analysis and systems biology approaches analyze gene expression data extracted from the microarray or RNA-seq methods. In the present study, the R software-based GEO2R is used to analyze differentially expressed genes. The GEO2R uses GEOquery and limma R package (from Bioconductor project) to compare original submitter-supplied processed data tables. Here, the gene expression profile of GSE8157 was analyzed by using a wide variety of bioinformatics methods. We explored the DEGs in the skeletal muscle of women with PCOS regulating a common metabolic abnormality and leading to increased risk of T2DM. We identified a total of 339 DEGs between the PCOS cases and control samples, in which 18 genes were up-regulated and 321 were down-regulated. A series of bioinformatics tools were used for this data analysis to predict the key genes and molecular pathways associated with the PCOS linking to the risk of T2DM.
The GO analysis has shown that the up-regulated genes mainly participate in the biological process like regulation of cell shape (GO:0008360; genes: FGD6, BRWD1, FMNL3, MYH9), cytoskeleton organization (GO:0007010; genes: FGD6, BRWD1, FMNL3) and actin cytoskeleton organization (GO:0030036; genes: FGD6, FMNL3). The cellular components (CC) enriched include ruffle membrane (GO:0001726; genes: FGD6, MYH9). The molecular functions (MF) enriched was poly(A) RNA binding (GO:0003723; genes: IMP3, PSIP1, MAGOHB, MYH9). However, the down-regulated DEGs were mainly found in the biological process, like glucose homeostasis, negative regulation of cell growth, intracellular receptor signaling pathway, and phospholipase C-activating G-protein coupled receptor signaling pathway. Recent studies have primarily focused on the expression, quantification, and genetic polymorphisms of PCOS and have built a considerable argument that abnormal PCOS is linked to diabetes and infertility; however, few studies have given direct proof. Anovulation, hyperandrogenism, and insulin resistance are all symptoms of PCOS. Hyperinsulinemia has been linked to an increased risk of cardiovascular disease and the progression of T2DM. T2DM is manifested by hyperglycaemia caused by insulin resistance, which results in impaired glucose uptake and utilization. Insulin resistance can be found in the liver, skeletal muscle, and adipose tissue. Skeletal muscle, in particular, loses its metabolic versatility, making it difficult to switch between glucose and fatty acid use [27]. Recent evidence suggests that broken-down fatty acid oxidation is a contributing factor in insulin resistance in muscles [28]. By 2025, a global agreement has been reached to halt the increase in diabetes and obesity. Diabetes affects approximately 422 million people worldwide, most of whom live in low- and middle-income countries, and diabetes is directly responsible for 1.6 million deaths per year. Over the last few decades, both the number of cases and the incidence of diabetes have gradually increased. (who.int).
The KEGG pathway analysis also indicated that the DEGs were mainly enriched in the AMPK signaling pathway; alanine, aspartate and glutamate metabolism; neuroactive ligand-receptor interaction; butanoate metabolism; and adipocytokine signaling pathway. While AMPK is commonly considered an energy sensor, recent research has established fructose 1,6-bisphosphate as an AMPK metabolite regulator [29]. For T2DM, AMPK activation in response to exercise has a huge advantage [30]. Therapeutic agents that resolve insulin resistance have gotten a lot of publicity for the same reason. The thiazolidinediones (TZDs) and metformin are two primary insulin-sensitizing agents that have been developed. Both drugs work by activating AMPK and thus bypassing insulin signaling [31]. AMPK regulates the downstream kinases glucose-6-phosphatase (G-6-Pase) and phosphoenolpyruvate carboxykinase (PEPCK), influencing gluconeogenesis and alleviating diabetes. AMPK can also enhance IR by regulating glucose transporter 4 and free fatty acids [32]. Understanding the entire signal transduction pathway involving AMPK in skeletal muscle may lead to major pharmacologic improvements in managing and treating T2DM. Further, an increase in adipocytokine is also found an essential role in PCOS pathophysiology [33].
The gene interaction network of DEGs is used to explore the underlying biochemical processes and interaction pathways related to insulin resistance in PCOS women, which may lead to a risk of T2DM. The background network was further constructed by the genes like AR, STK11, PDX1, MYCN, DYPK1A, FST, SFYA, RAD51, SIRT5, REST, THRA, NRF1, TWIST2, NR4A, TP73, SMARCA4, SIRT5, and RAD51. Further, the hub genes (top 10) in the network were identified based on the five ranking methods of Cytohubba. The overlap of results from all the five methods resulted from two central genes, such as AR and STK11. Several studies have been demonstrated that AR is a target to prevent androgen-related metabolic disorders like T2DM. AR is less important in females to maintain energy homeostasis, but elevated androgen concentrations increase pathological levels leading to metabolic dysfunction [34]. The main clinical hallmark of PCOS is hyperandrogenism [35] and clinical evidence has been reported that the ovary is the primary source of androgens in women with PCOS [36]. Gao et al. [37] reported that AR was differently expressed in PCOS, especially in actual PCOS subtypes. On the other side, it is also hypothesized that gene variants in SKT11 would be associated with the metabolic risk in PCOS women [38, 39]. Similarly, Single Nucleotide Polymorphism in the STK11 gene has been suggested to be associated with metformin efficacy in PCOS-treated patients [40]. Another study has demonstrated that a polymorphism in the STK11 gene is associated with low ovulatory response to treatment with metformin alone in a prospective, randomized trial [41].
However, the current analysis of the GEO dataset revealed major metabolic processes and pathways involved in PCOS women that may lead to the risk of T2DM. The DEGs identified are majorly found enriched in the down-regulation of various biological processes and pathways. Overall, our systematic analysis will gain insights into PCOS pathogenesis at molecular level and help to identify the potential candidate genes for development of metabolic disorders in PCOS individuals. Therefore, the hub genes and pathways may be potential therapeutic targets of PCOS treatment. Nevertheless, the potential limitations and other alternative explanations would be very insightful for future research, such as the limited control numbers in the database. Furthermore, we inferred the possible role of the hub genes identified, which need to be verified by further experimental biological studies and confirm the potential mechanisms of the hub proteins identified. The next stage of this study involves in vivo or clinical studies to verify in silico results.