Exploring the potential of microRNA as a diagnostic tool for gestational diabetes

Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus

Background

Intrauterine exposure to gestational diabetes mellitus (GDM) poses significant risks to fetal development and future metabolic health. Despite its clinical importance, the role of microRNAs (miRNAs) in fetoplacental vascular endothelial cell (VEC) programming in the context of GDM remains elusive. This study aims to identify signature miRNA genes involved in this process using bioinformatics analysis via multiple algorithms.

Methods

The dataset used in this study was acquired from Gene Expression Omnibus (GEO). Firstly, differentially expressed miRNA genes (DEMGs) were evaluated using limma package. Thereafter, an enrichment analysis of DEMGs was performed. Then, the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) were used as the other algorithms for screening candidate signature miRNA genes. Genes from the intersection of limma, LASSO, and SVM genes were used as the final signature miRNA genes. The receiver operator characteristic curve (ROC), the nomogram diagram, gene set enrichment analysis (GSEA), and signature miRNAs-target genes interaction network were implemented further to explore the features and functions of signature genes.

Results

A total of 32 DEMGs, with 21 upregulated and 11 downregulated miRNA genes, were obtained from limma analysis. LASSO and SVM analyses identified 15 and 12 candidate signature miRNA genes, respectively. After the intersection of genes from limma, LASSO, and SVM analyses, MIR34A and MIR186 were found as the final signature genes related to fetoplacental VEC programming. MIR34A and MIR186 were highly expressed and were associated with an increased risk of fetoplacental VEC programming in GDM mothers. The area under the curve (AUC) of ROC for MIR34A and MIR186 were 0.960 and 0.935, respectively. GSEA analysis revealed that these signature genes positively participate in cellular processes related to VEC migration, cell differentiation, angiogenesis, programmed cell death, and inflammatory response. Finally, miRNAs-target genes interaction network analysis provides the interaction of signature miRNAs and their critical target genes, which may help further studies for miR-34a and miR-186 in GDM.

Conclusions

MIR34A and MIR186 are novel signature miRNA genes related to fetoplacental VEC programming that may represent critical genes associated with placental function and fetal programming under GDM conditions.

Deciphering Depression: Epigenetic Mechanisms and Treatment Strategies

Depression, a significant mental health disorder, is under intense research scrutiny to uncover its molecular foundations. Epigenetics, which focuses on controlling gene expression without altering DNA sequences, offers promising avenues for innovative treatment. This review explores the pivotal role of epigenetics in depression, emphasizing two key aspects: (I) identifying epigenetic targets for new antidepressants and (II) using personalized medicine based on distinct epigenetic profiles, highlighting potential epigenetic focal points such as DNA methylation, histone structure alterations, and non-coding RNA molecules such as miRNAs. Variations in DNA methylation in individuals with depression provide opportunities to target genes that are associated with neuroplasticity and synaptic activity. Aberrant histone acetylation may indicate that antidepressant strategies involve enzyme modifications. Modulating miRNA levels can reshape depression-linked gene expression. The second section discusses personalized medicine based on epigenetic profiles. Analyzing these patterns could identify biomarkers associated with treatment response and susceptibility to depression, facilitating tailored treatments and proactive mental health care. Addressing ethical concerns regarding epigenetic information, such as privacy and stigmatization, is crucial in understanding the biological basis of depression. Therefore, researchers must consider these issues when examining the role of epigenetics in mental health disorders. The importance of epigenetics in depression is a critical aspect of modern medical research. These findings hold great potential for novel antidepressant medications and personalized treatments, which would significantly improve patient outcomes, and transform psychiatry. As research progresses, it is expected to uncover more complex aspects of epigenetic processes associated with depression, enhance our comprehension, and increase the effectiveness of therapies.

MicroRNA Associations with Preterm Labor-A Systematic Review

This systematic review delves into the connections between microRNAs and preterm labor, with a focus on identifying diagnostic and prognostic markers for this crucial pregnancy complication. Covering studies disseminated from 2018 to 2023, the review integrates discoveries from diverse pregnancy-related scenarios, encompassing gestational diabetes, hypertensive disorders and pregnancy loss. Through meticulous search strategies and rigorous quality assessments, 47 relevant studies were incorporated. The synthesis highlights the transformative potential of microRNAs as valuable diagnostic tools, offering promising avenues for early intervention. Notably, specific miRNAs demonstrate robust predictive capabilities. In conclusion, this comprehensive analysis lays the foundation for subsequent research, intervention strategies and improved outcomes in the realm of preterm labor.

Bioinformatics-based Identification of Ferroptosis-related Genes and their Diagnostic Value in Gestational Diabetes Mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) is considered a risk factor for heart metabolic disorder in future mothers and offspring. Ferroptosis is a new type of programmed cell death, which may participate in the occurrence and development of GDM.

OBJECTIVE

This study aims to identify ferroptosis-related genes in GDM by bioinformatics methods and to explore their clinical diagnostic value.

METHODS

The dataset GSE103552 was analyzed using the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs) in GDM. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and proteinprotein interaction (PPI) network were performed. Gene sets for ferroptosis were retrieved in MSigDB and GSVA gene set analysis was performed on the database. Finally, logistic regression was performed to differentiate between GDM patients and controls to screen for diagnostic markers.

RESULTS

A total of 179 DEGs were identified in the expression profile of GDM. GO and KEGG enrichment analysis revealed significant enrichment in the TGF-β, p53 signaling pathway, platelet activation, glutathione metabolism, sensory perception of taste, and leukocyte and vascular endothelial cell migration regulation. DEGs (n = 107) associated with the ferroptosis gene set were screened by GSVA analysis. The screened DEGs for disease and DEGs for ferroptosis scores were intersected and 35 intersected genes were identified. PPI identified two key genes associated with GDM as CCNB2 and CDK1. Wilcox-test showed low expression of CCNB2 and CDK1 in GDM. The area under the ROC curve (AUC) of the CCNB2 and CDK1 prognostic model was 0.822.

CONCLUSION

The genes associated with ferroptosis in GDM were CCNB2 and CDK1, which can be used as valid indicators for the diagnosis of GDM.

Treatment of type 2 diabetes mellitus with stem cells and antidiabetic drugs: a dualistic and future-focused approach

Type 2 Diabetes Mellitus (T2DM) accounts for more than 90% of total diabetes mellitus cases all over the world. Obesity and lack of balance between energy intake and energy expenditure are closely linked to T2DM. Initial pharmaceutical treatment and lifestyle interventions can at times lead to remission but usually help alleviate it to a certain extent and the condition remains, thus, recurrent with the patient being permanently pharmaco-dependent. Mesenchymal stromal cells (MSCs) are multipotent, self-renewing cells with the ability to secrete a variety of biological factors that can help restore and repair injured tissues. MSC-derived exosomes possess these properties of the original stem cells and are potentially able to confer superior effects due to advanced cell-to-cell signaling and the presence of stem cell-specific miRNAs. On the other hand, the repository of antidiabetic agents is constantly updated with novel T2DM disease-modifying drugs, with higher efficacy and increasingly convenient delivery protocols. Delving deeply, this review details the latest progress and ongoing studies related to the amalgamation of stem cells and antidiabetic drugs, establishing how this harmonized approach can exert superior effects in the management and potential reversal of T2DM.