The Neuropeptide-Related HERC5/TAC1 Interactions May Be Associated with the Dysregulation of lncRNA GAS5 Expression in Gestational Diabetes Mellitus Exosomes

Value of Non-Coding RNA Expression in Biofluids to Identify Patients at Low Risk of Pathologies Associated with Pregnancy

Pregnancy-related complications (PRC) impact maternal and fetal morbidity and mortality and place a huge burden on healthcare systems. Thus, effective diagnostic screening strategies are crucial. Currently, national and international guidelines define patients at low risk of PRC exclusively based on their history, thus excluding the possibility of identifying patients with de novo risk (patients without a history of disease), which represents most women. In this setting, previous studies have underlined the potential contribution of non-coding RNAs (ncRNAs) to detect patients at risk of PRC. However, placenta biopsies or cord blood samples are required, which are not simple procedures. Our review explores the potential of ncRNAs in biofluids (fluids that are excreted, secreted, or developed because of a physiological or pathological process) as biomarkers for identifying patients with low-risk pregnancies. Beyond the regulatory roles of ncRNAs in placental development and vascular remodeling, we investigated their specific expressions in biofluids to determine favorable pregnancy outcomes as well as the most frequent pathologies of pregnant women. We report distinct ncRNA panels associated with PRC based on omics technologies and subsequently define patients at low risk. We present a comprehensive analysis of ncRNA expression in biofluids, including those using next-generation sequencing, shedding light on their predictive value in clinical practice. In conclusion, this paper underscores the emerging significance of ncRNAs in biofluids as promising biomarkers for risk stratification in PRC. The investigation of ncRNA expression patterns and their potential clinical applications is of diagnostic, prognostic, and theragnostic value and paves the way for innovative approaches to improve prenatal care and maternal and fetal outcomes.

GAS5: A pivotal lncRNA in diabetes mellitus pathogenesis and management

The long non-coding RNA (lncRNA), GAS5, has garnered significant attention recently for its multifaceted involvement in cellular processes, particularly within the context of diabetes. This comprehensive review delves into the intricate molecular interactions associated with GAS5 and their profound implications for understanding, diagnosing, and effectively managing diabetes mellitus. The article begins by highlighting the global prevalence of diabetes and the urgent need for innovative insights into its underlying mechanisms and therapeutic approaches. It introduces GAS5 as a crucial regulator of gene expression, with emerging significance in the context of diabetes-related processes. The core of this review unravels the regulatory network of GAS5 in diabetes, elucidating its impact on various aspects of the disease. It explores how GAS5 influences insulin signaling pathways, glucose metabolism, and the function of β-cells, shedding light on its role in hyperglycemia and insulin resistance. Moreover, the article underscores the clinical relevance of GAS5's interactions by discussing their associations with different diabetes subtypes, predictive value, and potential applications as both diagnostic tools and therapeutic targets. It provides insights into ongoing research endeavours aimed at harnessing the potential of GAS5 for innovative disease management strategies, including the development of RNA-based therapeutics. Concluding with a forward-looking perspective, the abstract highlights the broader implications of GAS5 in the field of diabetes, such as its connection to diabetic complications and its potential for personalized approaches in disease management.

High-fiber-diet-related metabolites improve neurodegenerative symptoms in patients with obesity with diabetes mellitus by modulating the hippocampal-hypothalamic endocrine axis

Objective

Through transcriptomic and metabolomic analyses, this study examined the role of high-fiber diet in obesity complicated by diabetes and neurodegenerative symptoms.

Method

The expression matrix of high-fiber-diet-related metabolites, blood methylation profile associated with pre-symptomatic dementia in elderly patients with type 2 diabetes mellitus (T2DM), and high-throughput single-cell sequencing data of hippocampal samples from patients with Alzheimer's disease (AD) were retrieved from the Gene Expression Omnibus (GEO) database and through a literature search. Data were analyzed using principal component analysis (PCA) after quality control and data filtering to identify different cell clusters and candidate markers. A protein-protein interaction network was mapped using the STRING database. To further investigate the interaction among high-fiber-diet-related metabolites, methylation-related DEGs related to T2DM, and single-cell marker genes related to AD, AutoDock was used for semi-flexible molecular docking.

Result

Based on GEO database data and previous studies, 24 marker genes associated with high-fiber diet, T2DM, and AD were identified. Top 10 core genes include SYNE1, ANK2, SPEG, PDZD2, KALRN, PTPRM, PTPRK, BIN1, DOCK9, and NPNT, and their functions are primarily related to autophagy. According to molecular docking analysis, acetamidobenzoic acid, the most substantially altered metabolic marker associated with a high-fiber diet, had the strongest binding affinity for SPEG.

Conclusion

By targeting the SPEG protein in the hippocampus, acetamidobenzoic acid, a metabolite associated with high-fiber diet, may improve diabetic and neurodegenerative diseases in obese people.

Analysis of co-expression gene network associated with intracranial aneurysm and type 2 diabetes mellitus

To screen for common target genes in intracranial aneurysms (IA) and type 2 diabetes mellitus (T2DM), construct a common transcriptional regulatory network to predict clusters of candidate genes involved in the pathogenesis of T2DM and IA, and identify the common neurovascular markers and pathways in T2DM causing IA. Microarray datasets (GSE55650, GSE25462, GSE26969, GSE75436, and GSE13353) from the GEO database were analyzed in this research. Screening of the IA and the T2DM datasets yielded a total of 126 DEGs, among which 78 were upregulated and 138 were downregulated. Functional enrichment analysis revealed that these DEGs were enriched for a total of 68 GO pathways, including extracellular matrix composition, coagulation regulation, hemostasis regulation, and collagen fiber composition pathways. We also constructed transcriptional regulatory networks, and identified key transcription factors involved in both the conditions. Univariate logistic regression analysis showed that ARNTL2 and STAT1 were significantly associated with the development of T2DM and IA, acting as the common neurovascular markers for both the diseases. In cellular experiments, hyperglycemic microenvironments exhibited upregulated STAT1 expression. STAT1 may be involved in the pathogenesis of IA in T2DM patients. Being the common neurovascular markers, STAT1 may acts as novel therapeutic targets for the treatment of IA and T2DM.

Quercetin targets VCAM1 to prevent diabetic cerebrovascular endothelial cell injury

Introduction

Endothelial cells play important roles in neurodegenerative diseases caused by diabetes, therefore, we aimed at investigating the mechanisms through which endothelial cells are involved in diabetes development.

Methods

Single cell analysis was performed to identify the major endothelial cell subtypes in cardiovascular tissues that are involved in diabetes development. A cell-cell communication approach was then used to identify ligand-receptor interaction pairs between these cell types. Differential expression analysis between the two experimental groups [standard chow diet group and diabetogenic diet with cholesterol (DDC) group] was used to identify diabetes-related differentially expressed genes (DEGs). The upregulated genes were used to identify candidate ligands or receptors, as well as the corresponding cell types. Cell trajectory inference was performed to identify the stage of cell development and changes in expression of candidate ligands or receptors during cell development. Gene set enrichment analysis (GSEA) was conducted to investigate the biological functions of genes of purpose. Finally, molecular dynamics simulations (MDSs) were used to predict potential drugs with the ability to target the proteins of purpose.

Results

Seven cell types, including five endothelial cell subtypes (EC_1, EC_2, EC_3, EC_4, and EC_EndMT), were identified from endothelial cell-enriched single cell samples from the heart and aorta of mice. Cell-cell communication analysis revealed the potential ligand-receptor interactions between these cell types while five important ligand-receptor-associated genes, including Fn1, Vcam1, Fbn1, Col4a1, and Col4a2, were established by differential expression analysis. Among them, Vcam1 is mainly expressed in EC_EndMT and is involved in interactions between EC_EndMT and other cells. Cell trajectory extrapolation analysis revealed a shift from EC_2/EC_4 to EC_EndMT and a shift from EC_EndMT to EC_3/EC_1 during the progression of diabetes. GSEA analysis revealed that upregulation of VCAM1 may have inhibitory effects on cell growth and energy metabolism.

Conclusion

EC_EndMT subtypes have a complex role in neurodegenerative diseases caused by diabetes. Through mechanisms involved in cell-cell communication, Vcam1 may play an important role in dysregulation of biological functions of EC_ EndMT. Molecular docking results of the quercetin-VCAM1 complex suggest that quercetin may be an effective drug for targeting this protein.

Current perspectives on clinical use of exosomes as novel biomarkers for cancer diagnosis

Exosomes are a heterogeneous subset of extracellular vesicles (EVs) that biogenesis from endosomes. Besides, exosomes contain a variety of molecular cargoes including proteins, lipids and nucleic acids, which play a key role in the mechanism of exosome formation. Meanwhile, exosomes are involved with physiological and pathological conditions. The molecular profile of exosomes reflects the type and pathophysiological status of the originating cells so could potentially be exploited for diagnostic of cancer. This review aims to describe important molecular cargoes involved in exosome biogenesis. In addition, we highlight exogenous factors, especially autophagy, hypoxia and pharmacology, that regulate the release of exosomes and their corresponding cargoes. Particularly, we also emphasize exosome molecular cargoes as potential biomarkers in liquid biopsy for diagnosis of cancer.

Susceptibility Loci for Type 2 Diabetes in the Ethnically Endogamous Indian Sindhi Population: A Pooled Blood Genome-Wide Association Study

Type 2 diabetes (T2D) is a complex metabolic derangement that has a strong genetic basis. There is substantial population-specificity in the association of genetic variants with T2D. The Indian urban Sindhi population is at a high risk of T2D. The genetic basis of T2D in this population is unknown. We interrogated 28 pooled whole blood genomes of 1402 participants from the Diabetes In Sindhi Families In Nagpur (DISFIN) study using Illumina’s Global Screening Array. From a total of 608,550 biallelic variants, 140 were significantly associated with T2D after adjusting for comorbidities, batch effects, pooling error, kinship status and pooling variation in a random effects multivariable logistic regression framework. Of the 102 well-characterized genes that these variants mapped onto, 70 genes have been previously reported to be associated with T2D to varying degrees with known functional relevance. Excluding open reading frames, intergenic non-coding elements and pseudogenes, our study identified 22 novel candidate genes in the Sindhi population studied. Our study thus points to the potential, interesting candidate genes associated with T2D in an ethnically endogamous population. These candidate genes need to be fully investigated in future studies.

Cervical Cancer Imaging Features Associated With ADRB1 as a Risk Factor for Cerebral Neurovascular Metastases

Bioinformatics tools are used to create a clinical prediction model for cervical cancer metastasis and to investigate the neurovascular-related genes that are involved in brain metastasis of cervical cancer. One hundred eighteen patients with cervical cancer were divided into two groups based on the presence or absence of metastases, and the clinical data and imaging findings of the two groups were compared retrospectively. The nomogram-based model was successfully constructed by taking into account four clinical characteristics (age, stage, N, and T) as well as one imaging characteristic (original_glszm_GrayLevelVariance Rad-score). In patients with cervical cancer, headaches and vomiting were more often reported in the brain metastasis group than in the other metastasis groups. According to the TCGA data, mRNA differential gene expression analysis of patients with cervical cancer revealed an increase in the expression of neurovascular-related gene Adrenoceptor Beta 1 (ADRB1) in the brain metastasis group. An analysis of the correlation between imaging features and ADRB1 expression revealed that ADRB1 expression was significantly higher in the low Rad-score group compared with the high Rad-score group (P = 0.025). Therefore, ADRB1 expression in cervical cancer was correlated with imaging features and was associated as a risk factor for cerebral neurovascular metastases. This study developed a nomogram prediction model for cervical cancer metastasis using age, stage, N, T and original_glszm_GrayLevelVariance. As a risk factor associated with the development of cerebral neurovascular metastases of cervical cancer, ADRB1 expression was significantly higher in brain metastases from cervical cancer.