Functional Polymorphism Located in the microRNA Binding Site of the Insulin Receptor (INSR) Gene Confers Risk for Type 2 Diabetes Mellitus in the Bangladeshi Population

The miRNA variants MIR196A2 (rs11614913) and MIR423 (rs6505162) contribute to an increase in the risk of myocardial infarction

INTRODUCTION

MicroRNAs (miRNAs) are small, single-stranded RNA molecules that negatively regulate gene expression and play a key role in the pathogenesis of human diseases. Recent studies have suggested that miRNAs contribute to cardiovascular diseases (CVDs). However, the association between single-nucleotide polymorphisms (SNPs) in miRNAs and myocardial infarction (MI) remains in infancy.

AIM

The current study was designed to find out the association of SNPs in MIR196A2 and MIR423 (rs11614913 and rs6505162, respectively).

METHODS

Using Tetra-Primer Amplification Refractory Mutation System-Polymerase Chain Reaction (T-ARMS PCR) in 400 cases (MI patients) and 336 healthy controls. Using different inheritance models (co-dominant, homozygous dominant, homozygous recessive, and additive models), the association of these SNPs was genotyped with MI risk.

RESULTS

For variant rs11614913, significant distribution of the genotypes among the cases and controls was determined by co-dominant [χ2  = 29.19, 2; p value < 0.0001], dominant (C/C vs. C/T + T/T) [OR = 0.45 (0.34 to 0.61); p < 0.0001], recessive (T/T vs. C/T + C/C) [OR = 1.009 (0.63 to 1.63); p-value p value > 0.999], and additive models [OR = 0.65 (0.52 to 0.80); p value = 0.0001]. Similarly, a significant association of rs6505162 was determined by co-dominant [χ2  = 24.29, 2; p value < 0.0001], dominant (C/C vs. A/C+ A/A) [OR = 0.44 (0.32 to 0.61); p value < 0.0001], recessive (A/A vs. A/C + C/C) [OR = 1.29 (0.85 to 1.98); p value = 0.28], and additive models [OR = 0.65 (0.52 to 0.81); p value = 0.0001].

CONCLUSION

Therefore, the current study showed that both variants rs11614913 and rs6505162 are significantly associated with MI in the Pakistani population.

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.

MiR-3138 deteriorates the insulin resistance of HUVECs via KSR2/AMPK/GLUT4 signaling pathway

Insulin resistance (IR) is a complex pathological condition resulting from the dysregulation of cellular response to insulin hormone in insulin-dependent cells and is recognized as a pathogenic hallmark and strong risk factor for metabolic syndrome. The present study aims to elucidate the molecular mechanism of the pathogenesis of IR. Here, we used human umbilical vein endothelial cells (HUVECs) to establish the IR cell model induced by 1 × 10^-6 mmol/L insulin. After 48 h, reactive oxygen species (ROS) and glucose consumption were measured by DCFH-DA and GOD-POD methods, respectively. The results of Microarray analysis demonstrated that there were 10 differentially expressed miRNAs (DEMs) selected based on Fold change (FC) and P value in the IR cell model compared with HUVECs. The enriched gene ontology (GO) terms analysis showed that the target genes of these 10 DEMs were significantly enriched in biological process, cellular component and molecular function, and the significantly enriched Kyoto Encyclopedia of Genes or Genomes (KEGG) pathways mainly include AMPK signaling pathway and PI3K signaling pathway. Amongst all, the expression level of miR-3138 was highest in the IR cell model evaluated by qRT-PCR. Through Targetscan, KSR2 mRNA was predicted as a target of miR-3138. And mRNA and protein expression levels of miR-3138, KSR2, GLUT4, AMPK, PI3K, Akt were examined using qRT-PCR and Western blotting, respectively. The interaction between miR-3138 and KSR2 was evaluated by dual-luciferase reporter assay. Our results showed that miR-3138 significantly deteriorated the IR of HUVECs via KSR2/AMPK/GLUT4 signaling pathway.

Network pharmacology and metabolomics study on the intervention of traditional Chinese medicine Huanglian Decoction in rats with type 2 diabetes mellitus

ETHNOPHARMACOLOGICAL RELEVANCE

Type 2 diabetes mellitus (T2DM) is currently one of the most prominent and global chronic conditions. Huanglian Decoction (HLD) is a traditional Chinese medicine (TCM) preparation that has been used to treat T2DM for thousands of years in China. However, its mechanism of action at the metabolic level is still unclear. The purpose of this work is to study the mechanism of HLD in treating T2DM based on metabolomics and network pharmacology.

MATERIALS AND METHODS

In this study, metabolomics combined with network pharmacology was used to elucidate the therapeutic mechanism of HLD in T2DM. Serum samples were collected from rats with T2DM, induced by a high-sugar and high-fat diet combined with streptozotocin (STZ), to measure the levels of biochemical markers. Urinary metabolomics-based analysis using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) was conducted to evaluate the differential metabolites from multiple metabolic pathways.

RESULTS

After treatment with HLD for 4 weeks, biochemical indicators, including fasting blood glucose (FBG), blood lipid, fasting insulin (FINS), insulin sensitivity index (ISI), and homeostasis model assessment of insulin resistance (HOMA-IR), were significantly improved. Metabolomics results revealed that HLD regulated the biomarkers, such as cytosine, L-carnitine, betaine, phenylalanine, glucose, citrate, phenylpyruvate, and hippuric acid in glyoxylate and dicarboxylate metabolism, phenylalanine metabolism, and tricarboxylic acid (TCA) cycle. The combination of network pharmacology, metabolomics, western blot, and PCR showed that HLD can treat T2DM by enhancing the gene and protein expression levels of glucose transporter 4 (GLUT4), insulin receptor (INSR), and mitogen-activated protein kinase 1 (MAPK1) to interfere with glyoxylate and dicarboxylate metabolism.

CONCLUSIONS

The study based on metabolomics and network pharmacology indicated that HLD can improve T2DM through multiple targets and pathways, and it may be a useful alternative therapy for the treatment of T2DM.

Chronic heavy alcohol consumption influences the association between genetic variants of GCK or INSR and the development of diabetes in men: A 12-year follow-up study

Chronic heavy alcohol consumption is a risk factor for diabetes, which is characterized by impaired β-cell function and insulin resistance. We aimed to determine whether the longitudinal associations between genetic variants of glucokinase (GCK) and insulin receptor (INSR) and the risk of developing diabetes were influenced by chronic heavy alcohol consumption. Data were obtained from the Korean Genome and Epidemiology Study. To identify candidate variants, 1,520 subjects (726 non-drinkers and 794 heavy drinkers) were included in the baseline cross-sectional study. After excluding patients with diabetes at baseline and those with insufficient data on diabetes incidence, prospective analyses were conducted in 773 subjects (353 non-drinkers and 420 heavy drinkers). In the baseline cross-sectional study, one SNP (rs758989) in GCK and four SNPs (rs7245757, rs1035942, rs1035940, and rs2042901) in INSR were selected as candidate SNPs that interact with alcohol to affect prediabetes and diabetes. We identified that these GCK and INSR polymorphisms are affected by chronic heavy alcohol consumption and have an effect on the incidence of diabetes. The incidence of diabetes was increased in chronic heavy alcohol drinkers carrying the C allele of GCK compared with never-drinkers with the C allele (HR, 2.15; 95% CI 1.30-3.57), and was increased in chronic heavy alcohol drinkers who were not carrying the INSR haplotype (-/-) compared with never-drinkers carrying the AACT haplotype (HR, 1.98; 95% CI 1.24-3.18). Moreover, we observed that the aggravating effects on the late insulin secretion (I/G120 and I/G AUC 60-120) in individuals who were chronic heavy drinkers with C allele of GCK. In the INSR haplotype, chronic heavy drinkers not carrying AACT were associated with lower disposition index. These results potentially suggest that chronic heavy alcohol consumption induce β-cell dysfunction partially mediated by decreased GCK expression or decline of insulin sensitivity via inhibition of INSR, thereby contributing to the development of diabetes.

Potential Impact of MicroRNA Gene Polymorphisms in the Pathogenesis of Diabetes and Atherosclerotic Cardiovascular Disease

MicroRNAs (miRNAs) are endogenous, small (18–23 nucleotides), non-coding RNA molecules. They regulate the posttranscriptional expression of their target genes. MiRNAs control vital physiological processes such as metabolism, development, differentiation, cell cycle and apoptosis. The control of the gene expression by miRNAs requires efficient binding between the miRNA and their target mRNAs. Genome-wide association studies (GWASs) have suggested the association of single-nucleotide polymorphisms (SNPs) with certain diseases in various populations. Gene polymorphisms of miRNA target sites have been implicated in diseases such as cancers, diabetes, cardiovascular and Parkinson’s disease. Likewise, gene polymorphisms of miRNAs have been reported to be associated with diseases. In this review, we discuss the SNPs in miRNA genes that have been associated with diabetes and atherosclerotic cardiovascular disease in different populations. We also discuss briefly the potential underlining mechanisms through which these SNPs increase the risk of developing these diseases.