UTP14A, DKC1, DDX10, PinX1, and ESF1 Modulate Cardiac Angiogenesis Leading to Obesity-Induced Cardiac Injury

1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit

The COVID-19 pandemic prompted rapid research on SARS-CoV-2 pathogenicity. Consequently, new data can be used to advance the molecular understanding of SARS-CoV-2 infection. The present bioinformatics study discusses the "spikeopathy" at the molecular level and focuses on the possible post-transcriptional regulation of the SARS-CoV-2 spike protein S1 subunit in the host cell/tissue. A theoretical protein-RNA recognition code was used to check the compatibility of the SARS-CoV-2 spike protein S1 subunit with mRNAs in the human transcriptome (1-L transcription). The principle for this method is elucidated on the defined RNA binding protein GEMIN5 (gem nuclear organelle-associated protein 5) and RNU2-1 (U2 spliceosomal RNA). Using the method described here, it was shown that 45% of the genes/proteins identified by 1-L transcription of the SARS-CoV-2 spike protein S1 subunit are directly linked to COVID-19, 39% are indirectly linked to COVID-19, and 16% cannot currently be associated with COVID-19. The identified genes/proteins are associated with stroke, diabetes, and cardiac injury.

Effect of Semaglutide and Empagliflozin on Pulmonary Structure and Proteomics in Obese Mice

Objective

This study utilized proteomics to investigate changes in protein expression associated with lung health in obese mice exposed to semaglutide and empagliflozin through a high-fat diet.

Methods

Twenty-eight male C57BL/6JC mice were randomly assigned to two groups: a control diet group (n = 7) and a high-fat diet group (n = 21). The HFD group was further divided into three groups: HFD group (n = 7), Sema group (n = 7), and Empa group (n = 7). Post-treatment, mice underwent assessments including glucose tolerance, lipids, oxidative stress markers, body weight, lung weight, and structure. Proteomics identified differentially expressed proteins (DEPs) in lung tissue, and bioinformatics analyzed the biological processes and functions of these proteins.

Results

Semaglutide and empagliflozin significantly attenuated obesity-induced hyperglycemia, abnormal lipid metabolism, oxidative stress response, and can decrease alveolar wall thickness, enlarge alveolar lumen, and reduce collagen content in lung tissue. Both medications also attenuated lung elastic fibre cracking and disintegration. In the HFD/NCD group, there were 66 DEPs, comprising 30 proteins that were increased and 36 that were decreased. Twenty-three DEPs overlapped between Sema/HFD and Empa/HFD, with 11 up-regulated and 12 down-regulated simultaneously. After analysing DEPs in different groups, four proteins - LYVE1, BRAF, RGCC, and CHMP5 - were all downregulated in the HFD group and upregulated by semaglutide and empagliflozin treatment.

Conclusion

This study demonstrates that obesity induced by a high-fat diet causes a reduction in the expression of LYVE1, BRAF, RGCC, and CHMP5 proteins, potentially affecting lung function and structure in mice. Significantly, the administration of semaglutide and empagliflozin elevates the levels of these proteins, potentially offering therapeutic benefits against lung injury caused by obesity. Merging semaglutide with empagliflozin may exert a more pronounced impact.

Molecular mechanisms of diabetic heart disease: Insights from transcriptomic technologies

Over half a billion adults across the world have diabetes mellitus (DM). This has a wide-ranging impact on their health, including more than doubling their risk of major cardiovascular events, in comparison to age-sex matched individuals without DM. Notably, the risk of heart failure is particularly increased, even when coronary artery disease and hypertension are not present. Macro- and micro-vascular complications related to endothelial cell (EC) dysfunction are a systemic feature of DM and can affect the heart. However, it remains unclear to what extent these and other factors underpin myocardial dysfunction and heart failure linked with DM. Use of unbiased 'omics approaches to profile the molecular environment of the heart offers an opportunity to identify novel drivers of cardiac dysfunction in DM. Multiple transcriptomics studies have characterised the whole myocardium or isolated cardiac ECs. We present a systematic summary of relevant studies, which identifies common themes including alterations in both myocardial fatty acid metabolism and inflammation. These findings prompt further research focussed on these processes to validate potentially causal factors for prioritisation into therapeutic development pipelines.

The discovery of promising candidate biomarkers in kidney renal clear cell carcinoma: evidence from the in-depth analysis of high-throughput data

Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of renal tumor. The underlying mechanisms governing KIRC initiation and progression are less known. The present study aimed to reveal novel hub genes associated with the initiation and progression of KIRC, which may be utilized as novel molecular biomarkers and therapeutic targets for the treatment of KIRC. The GSE6344 dataset from the Gene Expression Omnibus (GEO) database was integrated to identify differentially expressed genes (DEGs) using the limma package. Then, hub genes were identified and UALCAN, GEPIA, OncoDB, DriverDBv3, GENT2, and HPA databases were employed for the expression, survival, and methylation analyses. cBioPortal tool was used to investigate the genetic alterations, while CancerSEA, TIMER, DAVID, ENCORI, DrugBank, and GSCAlite were utilized to explore a few more hub gene-associated parameters. Finally, targeted bisulfite sequencing (bisulfite-seq), and RT-qPCR techniques were used to validate the expression and methylation level of the hub genes using Human RCC cell line 786-O, A-498, and normal renal tubular epithelial cell line HK-2. In total, 7299 DEGs were found between KIRC and normal samples in the GSE6344 dataset. Using STRING and Cytohubba analysis, four hub genes including VEGFA (vascular endothelial growth factor), ALB (Albumin), ENO2 (enolase 2), and CAVI1 (Caveolin 1) were selected as the hub genes. Further, it was validated through extensive analysis of TCGA datasets that these VEGA, ENO2, and CAV1 hub genes were significantly up-regulated, while ALB was significantly down-regulated in KIRC samples compared to controls. The dysregulation of these genes was found to be associated with the overall survival (OS) of the KIRC patients. Moreover, this study also revealed some novel links between VEGA, ALB, ENO2, and CAV1 expression and genetic alterations, promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. The present study revealed a panel of four hub genes, which contributed to improving our understanding of the underlying molecular mechanisms of KIRC development and can be utilized as promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.

Investigating novel biomarkers in uterine corpus endometrial carcinoma: in silico analysis and clinical specimens validation via RT-qPCR and immunohistochemistry

The rising incidence and mortality rate of Uterine Corpus Endometrial Carcinoma (UCEC) pose significant health concerns. CC and CXC chemokines have been linked to tumorigenesis and cancer progression. Recognizing the growing significance of CC and CXC chemokines' diagnostic and prognostic significance in diverse cancer types, our objective was to comprehensively analyze the diagnostic and prognostic values of hub genes from the CC and CXC chemokines in UCEC, utilizing both in silico and clinical samples and cell lines-based approaches. In silico analyses include STRING, Cytoscape, Cytohubba, The Cancer Genome Atlas (TCGA) datasets analysis via the UALCAN, GEPIA, OncoDB, and MuTarget, SurvivalGenie, MEXPRESS, cBioPoratal, TIMER, ENCORI, and DrugBank. Meanwhile, clinical samples and cell lines based analyses include Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), targeted bisulfite sequencing (bisulfite-seq) analysis, and immunohistochemistry (IHC). Through present study, we identified CCL25 (CC motif chemokine ligand 25), CXCL10 (C-X-C motif chemokine ligand 10), CXCL12 (C-X-C motif chemokine ligand 12), and CXCL16 (C-X-C motif chemokine ligand 16) as crucial hub genes among the CC and CXC chemokines. Analyzing the expression data from TCGA, we observed a significant up-regulation of CCL25, CXCL10, and CXCL16 in UCEC samples compared to controls. In contrast, we noted a significant down-regulation of CXCL12 expression in UCEC samples. On clinical UCEC samples and cell lines analysis, the significant higher expression of CCL25, CXCL10, and CXCL16 and significant lower expression of CXCL12 were also denoted in UCEC samples than the controls via RT-qPCR and IHC analyses. Moreover, in silico analysis also confirmed the abnormal promoter methylation levels of the hub genes in TCGA UCEC samples, which was later validated by the clinical samples using targeted based bisulfite-seq analysis. In addition, various additional aspects of the CCL25, CXCL10, CXCL12, and CXCL16 have also been uncovered in UCEC during the present study. Our findings offer novel insights that contribute to the clinical utility of CCL25, CXCL10, CXCL12, and CXCL16 chemokines as potential diagnostic and prognostic biomarkers in UCEC.

Epitranscriptional Regulation: From the Perspectives of Cardiovascular Bioengineering

The central dogma of gene expression involves DNA transcription to RNA and RNA translation into protein. As key intermediaries and modifiers, RNAs undergo various forms of modifications such as methylation, pseudouridylation, deamination, and hydroxylation. These modifications, termed epitranscriptional regulations, lead to functional changes in RNAs. Recent studies have demonstrated crucial roles for RNA modifications in gene translation, DNA damage response, and cell fate regulation. Epitranscriptional modifications play an essential role in development, mechanosensing, atherogenesis, and regeneration in the cardiovascular (CV) system, and their elucidation is critically important to understanding the molecular mechanisms underlying CV physiology and pathophysiology. This review aims at providing biomedical engineers with an overview of the epitranscriptome landscape, related key concepts, recent findings in epitranscriptional regulations, and tools for epitranscriptome analysis. The potential applications of this important field in biomedical engineering research are discussed.

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer

Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management.

Effects of Semaglutide on Cardiac Protein Expression and Cardiac Function of Obese Mice

Purpose

Using proteomics to study the effect of semaglutide on cardiac protein expression in obese mice. Assessment of the effect of semaglutide on cardiac function in obese mice.

Materials and Methods

The mice were randomly divided into three groups: the control group (WC), the high-fat group (WF), and the high-fat diet with semaglutide intervention group (WS). Serum samples were collected, and lipids, blood glucose, inflammatory and oxidative stress markers, and cardiac ultrasound, were examined. The cardiac weight of each group of mice was measured, and pathological alterations were examined. Inflammation and oxidative stress levels in heart tissue were evaluated. The labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform was used to find differentially expressed proteins (DEPs) and screen for related pathways and key proteins in a proteomics study.

Results

Semaglutide greatly alleviated obesity-induced lipid metabolism abnormalities, improved cardiac ventricular wall thickening, and significantly reduced myocardial collagen content in obese mice. Semaglutide significantly reduces obesity-induced inflammation and oxidative stress. There were 64 DEPs in the WF/WC group, with 39 upregulated proteins and 25 downregulated proteins. The WS/WC group, on the other hand, had 83 DEPs, including 57 upregulated and 26 downregulated proteins. Following functional analysis, DEPs were shown to be largely associated with lipid metabolism and peroxisomes. Apolipoprotein A-II, catalase, diazepam-binding inhibitor, paraoxonase-1, and hydroxysteroid 17-dehydrogenase-4 were all upregulated in the WF group but significantly downregulated in the WS group. A high-fat diet increases the expression of lipid synthesis and transport proteins while increasing inflammation and oxidative stress damage.

Conclusion

Semaglutide decreases lipid synthesis alleviates inflammation and oxidative stress and prevents lipid peroxidation and cardiac impairment.

Association of Triglyceride-Glucose Index and Liver Function Parameters Among Healthy Obese Civil Servants: A Center-Based Study

PURPOSE

To investigate the correlation between Triglyceride-glucose (TyG) index and liver function parameters in healthy obese civil servants in Shijiazhuang, China.

MATERIALS AND METHODS

This was an outpatient-based cross-sectional study in which 6452 participants were recruited. A total of 784 participants were analyzed according to inclusion and exclusion criteria. A TyG index was calculated based on fasting glucose and triglycerides. All patients were divided into a high TyG index group and a low TyG index group, using the median TyG index as a cut-off. Finally, patients were further divided into two subgroups: males and females.

RESULTS

While AST/ALT and direct bilirubin levels were lower in the high TyG index group compared to the low TyG index group, ALT, AST, total protein, and albumin levels were greater. Particularly in male participants, TyG index was inversely connected with AST/ALT and direct bilirubin levels and favorably correlated with ALT, AST, total protein, and albumin levels. These connections persisted in the multilinear regression study even after adjusting for confounding variables.

CONCLUSION

This study describes the correlation between TyG index and liver function parameters in obese populations without co-morbid diseases, providing a new idea for early interventional treatment in this group.