Hypomethylation of IL1RN and NFKB1 genes is linked to the dysbalance in IL1β/IL-1Ra axis in female patients with type 2 diabetes mellitus

Biochemical study of the effect of lead exposure in nonobese gasoline station workers and risk of hyperglycemia: A retrospective case-control study

Evaluate the relationship between blood lead (Pb) levels and other biomedical markers and the risk of diabetes in gasoline station workers. The participants were separated into 2 groups: group A consisted of 26 workers from gasoline filling stations, while group B comprised 26 healthy individuals. Serum levels of malondialdehyde, IL-1β, visfatin, insulin, fasting blood sugar, and vitamin D were assessed. Mean Pb level was significantly higher in group A compared to group B (almost 2.9 times higher levels) (14.43 ± 1.01 vs 5.01 ± 1.41, µg/dL). The levels of visfatin (23.19 ± 0.96 vs 3.88 ± 0.58, ng/mL), insulin (22.14 ± 1.31 vs 11.26 ± 0.75, mU/L), fasting blood sugar (118.4 ± 26.1 vs 82.7 ± 9.2, gm/dL), malondialdehyde (6.40 ± 0.27 vs 1.62 ± 0.21, nmol/mL), and IL-1β (330.25 ± 10.34 vs 12.35 ± 1.43, pg/mL) were significantly higher in group A, meanwhile; vitamin D (11.99 ± 1.55 vs 35.41 ± 3.16, ng/mL) were significantly lower in group A. A positive association exists between blood Pb levels and increased inflammatory markers. Lead exposure increases serum insulin and fasting blood sugar, which suggests that it is diabetogenic and that increased inflammation is a possible cause.

Cardiovascular benefits of SGLT2 inhibitors and GLP-1 receptor agonists through effects on mitochondrial function and oxidative stress

Overloaded glucose levels in several metabolic diseases such as type 2 diabetes (T2D) can lead to mitochondrial dysfunction and enhanced production of reactive oxygen species (ROS). Oxidative stress and altered mitochondrial homeostasis, particularly in the cardiovascular system, contribute to the development of chronic comorbidities of diabetes. Diabetes-associated hyperglycemia and dyslipidemia can directly damage vascular vessels and lead to coronary artery disease or stroke, and indirectly damage other organs and lead to kidney dysfunction, known as diabetic nephropathy. The new diabetes treatments include Na+-glucose cotransporter 2 inhibitors (iSGLT2) and glucagon-like 1 peptide receptor agonists (GLP-1RA), among others. The iSGLT2 are oral anti-diabetic drugs, whereas GLP-1RA are preferably administered through subcutaneous injection, even though GLP-1RA oral formulations have recently become available. Both therapies are known to improve both carbohydrate and lipid metabolism, as well as to improve cardiovascular and cardiorenal outcomes in diabetic patients. In this review, we present an overview of current knowledge on the relationship between oxidative stress, mitochondrial dysfunction, and cardiovascular therapeutic benefits of iSGLT2 and GLP-1RA. We explore the benefits, limits and common features of the treatments and remark how both are an interesting target in the prevention of obesity, T2D and cardiovascular diseases, and emphasize the lack of a complete understanding of the underlying mechanism of action.

A xonotlite nanofiber bioactive 3D-printed hydrogel scaffold based on osteo-/angiogenesis and osteoimmune microenvironment remodeling accelerates vascularized bone regeneration

BACKGROUND

Coordination between osteo-/angiogenesis and the osteoimmune microenvironment is essential for effective bone repair with biomaterials. As a highly personalized and precise biomaterial suitable for repairing complex bone defects in clinical practice, it is essential to endow 3D-printed scaffold the above key capabilities.

RESULTS

Herein, by introducing xonotlite nanofiber (Ca6(Si6O17) (OH)2, CS) into the 3D-printed silk fibroin/gelatin basal scaffold, a novel bone repair system named SGC was fabricated. It was noted that the incorporation of CS could greatly enhance the chemical and mechanical properties of the scaffold to match the needs of bone regeneration. Besides, benefiting from the addition of CS, SGC scaffolds could accelerate osteo-/angiogenic differentiation of bone mesenchymal stem cells (BMSCs) and meanwhile reprogram macrophages to establish a favorable osteoimmune microenvironment. In vivo experiments further demonstrated that SGC scaffolds could efficiently stimulate bone repair and create a regeneration-friendly osteoimmune microenvironment. Mechanistically, we discovered that SGC scaffolds may achieve immune reprogramming in macrophages through a decrease in the expression of Smad6 and Smad7, both of which participate in the transforming growth factor-β (TGF-β) signaling pathway.

CONCLUSION

Overall, this study demonstrated the clinical potential of the SGC scaffold due to its favorable pro-osteo-/angiogenic and osteoimmunomodulatory properties. In addition, it is a promising strategy to develop novel bone repair biomaterials by taking osteoinduction and osteoimmune microenvironment remodeling functions into account.

Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis

BACKGROUND

Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of macrophage phenotype transformation.

METHOD

Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define the cells involved and determine their transcriptomic characteristics. KEGG enrichment analysis, CIBERSORT, ESTIMATE, support vector machine (SVM), random forest (RF), and weighted correlation network analysis (WGCNA) were applied to bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO).

RESULT

Nine cell clusters were identified. M1 macrophages, M2 macrophages, and M2/M1 macrophages were identified as three clusters within the macrophages. According to pseudotime analysis, M2/M1 macrophages and M2 macrophages can be transformed into M1 macrophages. The ROC curve values of the six genes in the test group were statistically significant (AUC (IL1RN): 0.899, 95% CI: 0.764-0.990; AUC (NRP1): 0.817, 95% CI: 0.620-0.971; AUC (TAGLN): 0.846, 95% CI: 0.678-0.971; AUC (SPARCL1): 0.825, 95% CI: 0.620-0.988; AUC (EMP2): 0.808, 95% CI: 0.630-0.947; AUC (ACTA2): 0.784, 95% CI: 0.591-0.938). The atherosclerosis prediction model showed significant statistical significance in both the train group (AUC: 0.909, 95% CI: 0.842-0.967) and the test group (AUC: 0.812, 95% CI: 0.630-0.966).

CONCLUSIONS

IL1RNHigh M1, NRP1High M2, ACTA2High M2/M1, EMP2High M1/M1, SPACL1High M2/M1 and TAGLNHigh M2/M1 macrophages play key roles in the occurrence and development of arterial atherosclerosis. These marker genes of macrophage phenotypic transformation can also be used to establish a model to predict the occurrence of atherosclerosis.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

The role of interleukin-1β in type 2 diabetes mellitus: A systematic review and meta-analysis

Type 2 diabetes mellitus (T2DM) is a multifactorial non-communicable disease that is characterized by insulin resistance and chronic sub-clinical inflammation. Among the emerging inflammatory markers observed to be associated with β-cell damage is interleukin 1β (IL1β), a proinflammatory cytokine that modulates important metabolic processes including insulin secretion and β-cell apoptosis. The present systematic review and meta-analysis gathers available evidence on the emerging role of IL1β in T2DM. PubMed and Embase were searched for human studies that assessed 1L1β in T2DM individuals from 2016-2021. Thirteen studies (N=2680; T2DM=1182, controls=1498) out of 523 were included in the systematic review and only 3 studies in the meta-analysis. Assays were the most commonly used quantification method and lipopolysaccharides as the most common stimulator for IL1β upregulation. Random and fixed effects meta-analysis showed non-significant mean differences of IL1β concentrations between the T2DM and controls. Given the high heterogeneity and small subset of studies included, caution is advised in the interpretation of results. The present systematic review and meta-analysis highlights the limited evidence available that could implicate 1L1β as a potent biomarker for T2DM. Standardization of 1L1β assays with larger sample sizes are encouraged in future observational and prospective studies.

qPCR Analysis Reveals Association of Differential Expression of SRR, NFKB1, and PDE4B Genes With Type 2 Diabetes Mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a heterogeneous, metabolic, and chronic condition affecting vast numbers of the world's population. The related variables and T2DM associations have not been fully understood due to their diverse nature. However, functional genomics can facilitate understanding of the disease. This information will be useful in drug design, advanced diagnostic, and prognostic markers.

AIM

To understand the genetic causes of T2DM, this study was designed to identify the differentially expressed genes (DEGs) of the disease.

METHODS

We investigated 20 publicly available disease-specific cDNA datasets from Gene Expression Omnibus (GEO) containing several attributes including gene symbols and clone identifiers, GenBank accession numbers, and phenotypic feature coordinates. We analyzed an integrated system-level framework involving Gene Ontology (GO), protein motifs and co-expression analysis, pathway enrichment, and transcriptional factors to reveal the biological information of genes. A co-expression network was studied to highlight the genes that showed a coordinated expression pattern across a group of samples. The DEGs were validated by quantitative PCR (qPCR) to analyze the expression levels of case and control samples (50 each) using glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as the reference gene.

RESULTS

From the list of 50 DEGs, we ranked three T2DM-related genes (p < 0.05): SRR, NFKB1, and PDE4B. The enriched terms revealed a significant functional role in amino acid metabolism, signal transduction, transmembrane and intracellular transport, and other vital biological functions. DMBX1, TAL1, ZFP161, NFIC (66.7%), and NR1H4 (33.3%) are transcriptional factors associated with the regulatory mechanism. We found substantial enrichment of insulin signaling and other T2DM-related pathways, such as valine, leucine and isoleucine biosynthesis, serine and threonine metabolism, adipocytokine signaling pathway, P13K/Akt pathway, and Hedgehog signaling pathway. The expression profiles of these DEGs verified by qPCR showed a substantial level of twofold change (FC) expression (2-ΔΔCT) in the genes SRR (FC ≤ 0.12), NFKB1 (FC ≤ 1.09), and PDE4B (FC ≤ 0.9) compared to controls (FC ≥ 1.6). The downregulated expression of these genes is associated with pathophysiological development and metabolic disorders.

CONCLUSION

This study would help to modulate the therapeutic strategies for T2DM and could speed up drug discovery outcomes.