A comparison of gene expression profiles in patients with coronary artery disease, type 2 diabetes, and their coexisting conditions

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

Epigenome-Wide Histone Acetylation Changes in Peripheral Blood Mononuclear Cells in Patients with Type 2 Diabetes and Atherosclerotic Disease

There is emerging evidence of an association between epigenetic modifications, glycemic control and atherosclerosis risk. In this study, we mapped genome-wide epigenetic changes in patients with type 2 diabetes (T2D) and advanced atherosclerotic disease. We performed chromatin immunoprecipitation sequencing (ChIP-seq) using a histone 3 lysine 9 acetylation (H3K9ac) mark in peripheral blood mononuclear cells from patients with atherosclerosis with T2D (n = 8) or without T2D (ND, n = 10). We mapped epigenome changes and identified 23,394 and 13,133 peaks in ND and T2D individuals, respectively. Out of all the peaks, 753 domains near the transcription start site (TSS) were unique to T2D. We found that T2D in atherosclerosis leads to an H3K9ac increase in 118, and loss in 63 genomic regions. Furthermore, we discovered an association between the genomic locations of significant H3K9ac changes with genetic variants identified in previous T2D GWAS. The transcription factor 7-like 2 (TCF7L2) rs7903146, together with several human leukocyte antigen (HLA) variants, were among the domains with the most dramatic changes of H3K9ac enrichments. Pathway analysis revealed multiple activated pathways involved in immunity, including type 1 diabetes. Our results present novel evidence on the interaction between genetics and epigenetics, as well as epigenetic changes related to immunity in patients with T2D and advanced atherosclerotic disease.

In silico analysis of non-coding RNAs and putative target genes implicated in metabolic syndrome

Regulation of gene expression is vital to maintain normal cellular functions and its dysregulation leads to molecular pathogenesis of many diseases and disorders. Non-coding RNAs regulate the expression of approximately 60% of protein-coding genes and their malfunction contribute to the development of numerous diseases. The involvement of variant forms of circulating non-coding RNAs in diseases has been established. However, their function as biomarkers or therapeutic targets in metabolic disorders are underexploited. The aim of this study was to predict therapeutic targets and construction of biomarker panel for early detection of metabolic syndrome (MS). Non-coding RNAs including circular RNAs (circRNAs), long chain non-coding RNAs (lncRNA) and micro RNAs (miRNAs) were extracted from intensive literature search and experimentally supported databases. Raw data of gene expression profiles of MS were obtained from the GEO dataset and analyzed to get differentially expressed genes (DEGs). Functional enrichment analysis, network illustration of non-coding RNAs and predicted target DEGs were performed. Furthermore, a few numbers of miRNAs targeted DEGs were subjected to homology study. The strong association of hsa-miR-548c-3p, hsa-miR-579-3p, hsa-miR-17-5p and hsa-miR-320a was observed with the pathogenesis of MS. It includes the regulation of genes in glucose and lipid homeostasis, MAPKK activity, regulation of inflammatory responses and many signaling pathways such as insulin resistance, JAK/STAT and mTOR. Finally, interactions of hsa-miR-17-5p:STAT3, hsa-miR-320:JAK2, hsa-miR-320:S6K and hsa-let-7:DVL hybrids were predicted. Results of this study suggest the designing of a biomarker panel to detect early onset and molecular approach for the management of MS.

Effect of feeding type 2 diabetes mellitus rats with synbiotic yogurt sweetened with monk fruit extract on serum lipid levels and hepatic AMPK (5' adenosine monophosphate-activated protein kinase) signaling pathway

Monk fruit extract (MFE) is a natural sweetener that has been used as an ingredient of food and pharmaceutical products. The effects of feeding synbiotic yogurt fortified with MFE to rats with type 2 diabetes induced by high-fat diet and streptozotocin on serum lipid levels and hepatic AMPK signaling pathway were evaluated. Results showed that oral administration of the synbiotic yogurt fortified with MFE could improve serum lipid levels, respiratory exchange rate, and heat level in type 2 diabetic rats. Transcriptome analysis showed that synbiotic yogurt fortified with MFE may affect the expression of genes involved in binding, catalytic activity, and transporter activity. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that these differentially expressed genes were related to AMPK signaling pathway, linoleic acid metabolism, and α-linolenic acid metabolism. Western blotting confirmed that synbiotic yogurt fortified with MFE could activate AMPK signaling and improve the protein level of the hepatic gluconeogenic enzyme G6Pase in diabetic rats. The results indicated that MFE could be a novel sweetener for functional yogurt and related products.

A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort

The aggregation of Electronic Health Records (EHR) and personalized genetics leads to powerful discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant SNPs, BMI, and incidence of extreme obesity. The first GWAS examines associations with BMI in a cohort with no type 2 diabetics, focusing exclusively on BMI. The second GWAS examines associations with BMI in a cohort that includes type 2 diabetics. In the second GWAS, type 2 diabetes is a comorbidity, and thus becomes a covariate in the statistical model. The intersection of significant variants of these two studies is surprising. The third GWAS is a case vs. control study, with cases defined as extremely obese (Class 2 or 3 obesity), and controls defined as participants with BMI between 18.5 and 25. This last GWAS identifies strong associations with extreme obesity, including established variants in the FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR database to validate known associations and identify putative novel links with BMI and obesity.

Integration of Gene Expression Profile Data of Human Epicardial Adipose Tissue from Coronary Artery Disease to Verification of Hub Genes and Pathways

Background

This study aim to identify the core pathogenic genes and explore the potential molecular mechanisms of human coronary artery disease (CAD).

Methodology

Two gene profiles of epicardial adipose tissue from CAD patients including GSE 18612 and GSE 64554 were downloaded and integrated by R software packages. All the coexpression of deferentially expressed genes (DEGs) were picked out and analyzed by DAVID online bioinformatic tools. In addition, the DEGs were totally typed into protein-protein interaction (PPI) networks to get the interaction data among all coexpression genes. Pictures were drawn by cytoscape software with the PPI networks data. CytoHubba were used to predict the hub genes by degree analysis. Finally all the top 10 hub genes and prediction genes in Molecular complex detection were analyzed by Gene ontology and Kyoto encyclopedia of genes and genomes pathway analysis. qRT-PCR were used to identified all the 10 hub genes.

Results

The top 10 hub genes calculated by the degree method were AKT1, MYC, EGFR, ACTB, CDC42, IGF1, FGF2, CXCR4, MMP2 and LYN, which relevant with the focal adhesion pathway. Module analysis revealed that the focal adhesion was also acted an important role in CAD, which was consistence with cytoHubba. All the top 10 hub genes were verified by qRT-PCR which presented that AKT1, EGFR, CDC42, FGF2, and MMP2 were significantly decreased in epicardial adipose tissue of CAD samples (p < 0.05) and MYC, ACTB, IGF1, CXCR4, and LYN were significantly increased (p < 0.05).

Conclusions

These candidate genes could be used as potential diagnostic biomarkers and therapeutic targets of CAD.

Circular RNA profile in coronary artery disease

Circular RNAs (circRNAs) are potential biomarkers and therapeutic targets of coronary artery disease due to their high stability, covalently closed structure. And implied roles in gene regulation. The aim of this study was to identify and characterize circRNAs from human coronary arteries. Epicardial coronary arteries were removed during the autopsy of an 81-year-old man who died from heart attack. The natural history and histological classification of atherosclerotic lesions in coronary artery segments were analyzed by hematoxylin and eosin staining, and their circRNA expression profiles were characterized by RNA sequencing. RNA sequencing identified 1259 annotated and 381 novel circRNAs. Combined with the results of histologic examination, intersection analysis identified 54 upregulated and 12 downregulated circRNAs, representing 4.0% of the total number. Coronary artery segments with or without severe atherosclerosis showed distinctly different circRNA profiles on the basis of hierarchical clustering. Our results suggest that these 66 circRNAs contribute to the pathology underlying coronary artery atherosclerosis and may serve as diagnostic or therapeutic targets in coronary artery disease.

Identification of the molecular subgroups in coronary artery disease by gene expression profiles

Coronary artery disease (CAD) is the most common type of cardiovascular disease and becomes a leading cause of death worldwide. Aiming to uncover the underlying molecular features for different types of CAD, we classified 352 CAD cases into three subgroups based on gene expression profiles, which were retrieved from the Gene Expression Omnibus database. Also, these subgroups present different expression patterns and clinical characteristics. To uncover the transcriptomic differences between the subgroups, weighted gene co-expression analysis (WGCNA) was used and identified six subgroup-specific WGCNA modules. Characterization of the WCGNA modules revealed that lipid metabolism pathways, specifically upregulated in subgroup I, might be an indicator of increased severity. Moreover, subgroup II was considered as an early-stage of CAD because of normal-like gene expression patterns. In contrast, the mammalian target of rapamycin signaling pathway was significantly upregulated in subgroup III. Although subgroups II and III did not have a significant prognostic difference, their intrinsic biological characteristics were highly different, suggesting that the transcriptome classification may represent risk factors of both age and the intrinsic biological characteristics. In conclusion, the transcriptome classification of CAD cases revealed that cases from different subgroups may have their unique gene expression patterns, indicating that patients in each subgroup should receive more personalized treatment.

Genetic and epigenetic-sensitive regulatory network in immune response: a putative link between HLA-G and diabetes

INTRODUCTION

Human leukocyte antigen-G (HLA-G) gene encodes for a tolerogenic molecule constitutively expressed in human pancreas and upregulated upon inflammatory signals. The 14 bp INS/DEL polymorphism in the 3'UTR of HLA-G may influence the susceptibility for diabetes and coronary heart diseases (CHD), thus suggesting a novel candidate gene. DNA hypomethylation at HLA-G promoter may be a putative useful clinical biomarker for CHD onset. Upregulation of soluble HLA-G isoform (sHLA-G) was detected in prediabetic and diabetic subjects, suggesting a putative role in metabolic dysfunctions.

AREAS COVERED

We conducted a scoping literature review of genetic and epigenetic-sensitive mechanisms regulating HLA-G in diabetes. English-language manuscripts published between 1997 and 2019, were identified through PubMed, Google Scholar, and Web of Science database searches. After selecting 14 original articles representing case-control studies, we summarized and critically evaluated their main findings.

EXPERT COMMENTARY

Although epigenetic modifications are involved in the onset of hyperglycemic conditions evolving into diabetes and CHD, it is still difficult to obtain simple and useful clinical biomarkers. Inflammatory-induced KDM6A/INF-β/HLA-G axis might be a part of the epigenetic network leading to overexpression of HLA-G at pancreatic level. Network medicine may show whether HLA-G is involved in diabetes and CHD.

Narrowband UVB treatment induces expression of WNT7B, WNT10B and TCF7L2 in psoriasis skin

WNT/β-catenin signaling pathways play a pivotal role in the human immune defense against infections and in chronic inflammatory conditions as psoriasis. Wnt gene alterations are linked to known comorbidities of psoriasis as obesity, diabetes and Crohn’s disease. The objective of this study was to investigate WNT7B, WNT10B, WNT16 and TCF7L2 gene and protein expression in lesional and non-lesional skin and in the peripheral blood of patients with chronic plaque psoriasis compared with healthy individuals. To investigate the effect of narrowband UVB radiation, expression of these genes were analyzed before and after narrowband UVB treatment. Associations between single nucleotide polymorphisms for WNT7B, WNT10B, WNT16 and TCF7L2 genes and psoriasis were tested. Our results show significantly decreased WNT7B, WNT10B and TCF7L2 gene expression in lesional skin compared with non-lesional skin and healthy controls. Narrowband UVB treatment significantly increased expression of these genes in lesional skin. Immunohistochemistry shows increased WNT16 expression in lesional skin. No significant differences in allele or genotype frequencies for Wnt or TCF7L2 gene polymorphisms were found between patient and control group. This study shows for the first time significant UVB induced upregulation of WNT7B, WNT10B and TCF7L2 in patients with psoriasis and suggests a potential role of these genes in psoriasis pathogenesis.