Correlation between SEPS1 gene polymorphism and type 2 diabetes mellitus: A preliminary study

Current views on selenoprotein S in the pathophysiological processes of diabetes-induced atherosclerosis: potential therapeutics and underlying biomarkers

Atherosclerotic cardiovascular disease (ASCVD) consistently ranks as the primary mortality factor among diabetic people. A thorough comprehension of the pathophysiological routes and processes activated by atherosclerosis (AS) caused by diabetes mellitus (DM), together with the recognition of new contributing factors, could lead to the discovery of crucial biomarkers and the development of innovative drugs against atherosclerosis. Selenoprotein S (SELENOS) has been implicated in the pathology and progression of numerous conditions, including diabetes, dyslipidemia, obesity, and insulin resistance (IR)-all recognized contributors to endothelial dysfunction (ED), a precursor event to diabetes-induced AS. Hepatic-specific deletion of SELENOS accelerated the onset and progression of obesity, impaired glucose tolerance and insulin sensitivity, and increased hepatic triglycerides (TG) and diacylglycerol (DAG) accumulation; SELENOS expression in subcutaneous and omental adipose tissue was elevated in obese human subjects, and act as a positive regulator for adipogenesis in 3T3-L1 preadipocytes; knockdown of SELENOS in Min6 β-cells induced β-cell apoptosis and reduced cell proliferation. SELENOS also participates in the early stages of AS, notably by enhancing endothelial function, curbing the expression of adhesion molecules, and lessening leukocyte recruitment-actions that collectively reduce the formation of foam cells. Furthermore, SELENOS forestalls the apoptosis of vascular smooth muscle cells (VSMCs) and macrophages, mitigates vascular calcification, and alleviates inflammation in macrophages and CD4+ T cells. These actions help stifle the creation of unstable plaque characterized by thinner fibrous caps, larger necrotic cores, heightened inflammation, and more extensive vascular calcification-features seen in advanced atherosclerotic lesion development. Additionally, serum SELENOS could function as a potential biomarker, and SELENOS single nucleotide polymorphisms (SNPs) rs4965814, rs28628459, and rs9806366, might be effective gene markers for atherosclerosis-related diseases in diabetes. This review accentuates the pathophysiological processes of atherosclerosis in diabetes and amasses current evidence on SELENOS's potential therapeutic benefits or as predictive biomarkers in the various stages of diabetes-induced atherosclerosis.

The Regulation of Selenoproteins in Diabetes: A New Way to Treat Diabetes

Selenium is an essential micronutrient required for the synthesis and function of selenoproteins, most of which are enzymes involved in maintaining oxidative balance in the body. Diabetes is a group of metabolic disorders characterized by high blood glucose levels over a prolonged period of time. There are three main types of diabetes: type 1, type 2, and gestational diabetes. This review summarizes recent advances in the field of diabetes research with an emphasis on the roles of selenoproteins on metabolic disturbance in diabetes. We also discuss the interaction between selenoproteins and glucose and lipid metabolism to provide new insights into the prevention and treatment of diabetes.

Selenoprotein S Interacts with the Replication and Transcription Complex of SARS-CoV-2 by Binding nsp7

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replicates and evades detection using ER membranes and their associated protein machinery. Among these hijacked human proteins is selenoprotein S (selenos). This selenoprotein takes part in the protein quality control, signaling, and the regulation of cytokine secretion. While the role of selenos in the viral life cycle is not yet known, it has been reported to interact with SARS-CoV-2 nonstructural protein 7 (nsp7), a viral protein essential for the replication of the virus. We set to study whether selenos and nsp7 interact directly and if they can still bind when nsp7 is bound to the replication and transcription complex of the virus. Using biochemical assays, we show that selenos binds directly to nsp7. In addition, we found that selenos can bind to nsp7 when it is in a complex with the coronavirus's minimal replication and transcription complex, comprised of nsp7, nsp8, and the RNA-dependent RNA polymerase nsp12. In addition, through crosslinking experiments, we mapped the interaction sites of selenos and nsp7 in the replication complex and showed that the hydrophobic segment of selenos is essential for binding to nsp7. This arrangement leaves an extended helix and the intrinsically disordered segment of selenos-including the reactive selenocysteine-exposed and free to potentially recruit additional proteins to the replication and transcription complex.

Selenoprotein S: A versatile disordered protein

Selenoprotein S (selenos) is a small, intrinsically disordered membrane protein that is associated with various cellular functions, such as inflammatory processes, cellular stress response, protein quality control, and signaling pathways. It is primarily known for its contribution to the ER-associated degradation (ERAD) pathway, which governs the extraction of misfolded proteins or misassembled protein complexes from the ER to the cytosol for degradation by the proteasome. However, selenos's other cellular roles in signaling are equally vital, including the control of transcription factors and cytokine levels. Consequently, genetic polymorphisms of selenos are associated with increased risk for diabetes, dyslipidemia, and cardiovascular diseases, while high expression levels correlate with poor prognosis in several cancers. Its inhibitory role in cytokine secretion is also exploited by viruses. Since selenos binds multiple protein complexes, however, its specific contributions to various cellular pathways and diseases have been difficult to establish. Thus, the precise cellular functions of selenos and their interconnectivity have only recently begun to emerge. This review aims to summarize recent insights into the structure, interactome, and cellular roles of selenos.

Identification of Key Genes as Early Warning Signals of Acute Myocardial Infarction Based on Weighted Gene Correlation Network Analysis and Dynamic Network Biomarker Algorithm

Purpose

The specific mechanisms and biomarkersunderlying the progression of stable coronary artery disease (CAD) to acute myocardial infarction (AMI) remain unclear. The current study aims to explore novel gene biomarkers associated with CAD progression by analyzing the transcriptomic sequencing data of peripheral blood monocytes in different stages of CAD.

Material and Methods

A total of 24 age- and sex- matched patients at different CAD stages who received coronary angiography were enrolled, which included 8 patients with normal coronary angiography, 8 patients with angiographic intermediate lesion, and 8 patients with AMI. The RNA from peripheral blood monocytes was extracted and transcriptome sequenced to analyze the gene expression and the differentially expressed genes (DEG). A Gene Oncology (GO) enrichment analysis was performed to analyze the biological function of genes. Weighted gene correlation network analysis (WGCNA) was performed to classify genes into several gene modules with similar expression profiles, and correlation analysis was carried out to explore the association of each gene module with a clinical trait. The dynamic network biomarker (DNB) algorithm was used to calculate the key genes that promote disease progression. Finally, the overlapping genes between different analytic methods were explored.

Results

WGCNA analysis identified a total of nine gene modules, of which two modules have the highest positive association with CAD stages. GO enrichment analysis indicated that the biological function of genes in these two gene modules was closely related to inflammatory response, which included T-cell activation, cell response to inflammatory stimuli, lymphocyte activation, cytokine production, and the apoptotic signaling pathway. DNB analysis identified a total of 103 genes that may play key roles in the progression of atherosclerosis plaque. The overlapping genes between DEG/WGCAN and DNB analysis identified the following 13 genes that may play key roles in the progression of atherosclerosis disease: SGPP2, DAZAP2, INSIG1, CD82, OLR1, ARL6IP1, LIMS1, CCL5, CDK7, HBP1, PLAU, SELENOS, and DNAJB6.

Conclusions

The current study identified a total of 13 genes that may play key roles in the progression of atherosclerotic plaque and provides new insights for early warning biomarkers and underlying mechanisms underlying the progression of CAD.

Positive Selection and Enhancer Evolution Shaped Lifespan and Body Mass in Great Apes

Within primates, the great apes are outliers both in terms of body size and lifespan, since they include the largest and longest-lived species in the order. Yet, the molecular bases underlying such features are poorly understood. Here, we leveraged an integrated approach to investigate multiple sources of molecular variation across primates, focusing on over 10,000 genes, including approximately 1,500 previously associated with lifespan, and additional approximately 9,000 for which an association with longevity has never been suggested. We analyzed dN/dS rates, positive selection, gene expression (RNA-seq), and gene regulation (ChIP-seq). By analyzing the correlation between dN/dS, maximum lifespan, and body mass, we identified 276 genes whose rate of evolution positively correlates with maximum lifespan in primates. Further, we identified five genes, important for tumor suppression, adaptive immunity, metastasis, and inflammation, under positive selection exclusively in the great ape lineage. RNA-seq data, generated from the liver of six species representing all the primate lineages, revealed that 8% of approximately 1,500 genes previously associated with longevity are differentially expressed in apes relative to other primates. Importantly, by integrating RNA-seq with ChIP-seq for H3K27ac (which marks active enhancers), we show that the differentially expressed longevity genes are significantly more likely than expected to be located near a novel "ape-specific" enhancer. Moreover, these particular ape-specific enhancers are enriched for young transposable elements, and specifically SINE-Vntr-Alus. In summary, we demonstrate that multiple evolutionary forces have contributed to the evolution of lifespan and body size in primates.

Correlation between SEPS1 gene polymorphism and type 2 diabetes mellitus: A preliminary study

Background

The protein encoded by the selenoprotein S gene is considered to be an anti‐inflammatory and antioxidant protein and is involved in a variety of diseases. Therefore, we want to study the distribution characteristics of this gene in Chinese diabetic population.

Methods

A total of 170 patients with DM (including 100 patients with T2DM and 70 patients with diabetic nephropathy [DN]) and 100 healthy controls (HC) were selected from Haikou People's Hospital (China) between January 2017 and July 2017. The polymorphisms of three SEPS1 genes (SNP ID: rs4965814, rs28665122, and rs34713741) were measured by massARRAY method, while the polymorphisms of SEPS1 genes (SNP ID: rs4965373) were detected by Sanger sequencing.

Results

Comparing three groups, the results were the following: (a) There was a significant difference in the genotype and allele distribution of rs34713741 between DN group and HC group and between T2DM group and DN group; For this gene locus, the risk of diabetic nephropathy in healthy individuals with T allele was 0.6 times higher than that in individuals with GG genotype (OR = 0.60, 95% CI: 0.46 ~ 0.77). (b) There was a significant difference in the distribution of rs4975814 genotype between DN group and HC group; for this gene locus, the risk of diabetic nephropathy in healthy individuals with T allele was 2.71 times higher than that in individuals with GG genotype (OR = 2.71, 95% CI: 1.66 ~ 4.45).

Conclusion

We conclude that rs34713741 (GT + TT) may be a protective gene for DN and the rs4975814 (GT + TT) may be a susceptibility gene for DN.