Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes

Comparative Analysis of Transcriptome Profiles in Patients with Thromboangiitis Obliterans

BACKGROUND

Thromboangiitis obliterans (TAO) causes vascular insufficiency due to chronic inflammation and abrupt thrombosis of the medium and small arteries of the extremities. In our study, we aimed to determine biomarkers for the diagnosis of TAO by evaluating 15 male TAO patients with Shinoya diagnostic criteria and 5 healthy controls who did not have TAO-related symptoms in their family histories.

METHODS

The Clariom D Affymetrix platform was used to conduct microarray analysis on total RNA extracted from whole blood. A total of 477 genes (FC ≤ 5 or >5) common to the fifteen patient and five control samples were selected using comparative microarray analysis; among them, 79 genes were upregulated and 398 genes were downregulated.

RESULTS

According to FC ≤ 10 or >10, in the same TAO patient and control group, 13 genes out of 28 were upregulated, whereas 15 genes were downregulated. The 11 key genes identified according to their mean log2FC values were PLP2, RPL27A, CCL4, FMNL1, EGR1, EIF4A1, RPL9, LAMP2, RNF149, EIF4G2, and DGKZ. The genes were ranked according to their relative expression as follows: FMNL1 > RNF149 > RPL27A > EIF4G2 > EIF4A1 > LAMP2 > EGR1 > PLP2 > DGKZ > RPL9 > CCL4. Using protein-protein interaction network analysis, RPL9, RPL27A, and RPL32 were found to be closely related to EIF4G2 and EIF4A1. The Reactome pathway found pathways linked to 28 genes. These pathways included the immune system, cellular responses to stress, cytokine signaling in the immune system, and signaling by ROBO receptors.

CONCLUSIONS

By figuring out the protein expression levels of the genes that have been found to explain how TAO disease works at the molecular level, it will be possible to figure out how well these chosen transcripts can diagnose and predict the disease.

Genome-wide analysis of DNA methylation and its relationship with serum homocysteine levels in patients with hypertension

BACKGROUND

Homocysteine (Hcy) is an independent risk factor for cardiovascular diseases, and elevated plasma Hcy levels could aggravate vascular injury in hypertension. Hyperhomocysteinemia can change the methylation status of global DNA and specific genes. In the present study, we aim to examine the comprehensive influence of Hcy levels on DNA methylation status in patients with hypertension.

METHODS

Epigenome-wide methylation profiles of the peripheral leukocyte DNA of 218 patients with hypertension were analyzed using the Illumina Infinium Methylation EPIC BeadChip. Differentially methylated positions (DMPs) associated with serum Hcy levels were identified by mixed linear regression with the adjustment of potential confounders. Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to determine the potential functions of the identified DMPs. The association between the methylation level of DMPs and carotid-femoral pulse wave velocity (Cf-PWV) was also analyzed.

RESULTS

Five DMPs at cg13169662, cg03179312, cg21976560, cg25262698, and cg09433843 showed significant association with serum Hcy levels (false discovery rate-corrected P  < 0.05). An additional six CpG sites met the threshold for suggestive significance ( P  < 1 × 10 -6 ), among which three DMPs (cg25781123, cg26463106, and cg06679221) were annotated to THUMPD3 . Furthermore, the methylation levels of cg13169662 and cg25262698 (RPRD1A) were significantly associated with Cf-PWV.

CONCLUSION

Our results suggest that Hcy could induce DNA methylation alteration in patients with hypertension. Further functional research is warranted to elucidate the concrete role of DMPs in hypertension.

Identification of diagnostic biomarkers and therapeutic targets in peripheral immune landscape from coronary artery disease

Background

Peripheral biomarkers are increasingly vital non-invasive methods for monitoring coronary artery disease (CAD) progression. Their superiority in early detection, prognosis evaluation and classified diagnosis is becoming irreplaceable. Nevertheless, they are still less explored. This study aimed to determine and validate the diagnostic and therapeutic values of differentially expressed immune-related genes (DE-IRGs) in CAD.

Methods

We downloaded clinical information and RNA sequence data from the GEO database. We used R software, GO, KEGG and Cytoscape to analyze and visualize the data. A LASSO method was conducted to identify key genes for diagnostic model construction. The ssGSEA analysis was used to investigate the differential immune cell infiltration. Besides, we constructed CAD mouse model (low-density lipoprotein receptor deficient mice with high fat diet) to discover the correlation between the screened genes and severe CAD progress. We further uncovered the role of IL13RA1 might play in atherosclerosis.

Results

A total of 762 differential genes were identified between the peripheral blood of 218 controls and 199 CAD patients, which were significantly associated with infection, immune response and neural activity. 58 DE-IRGs were obtained by overlapping the differentially expressed genes(DEGs) and immune-related genes downloaded from ImmpDb database. Through LASSO regression, CCR9, CER1, CSF2, IL13RA1, INSL5, MBL2, MMP9, MSR1, NTS, TNFRSF19, CXCL2, HTR3C, IL1A, and NR4A2 were distinguished as peripheral biomarkers of CAD with eligible diagnostic capabilities in the training set (AUC = 0.968) and test set (AUC = 0.859). The ssGSEA analysis showed that the peripheral immune cells had characteristic distribution in CAD and also close relationship with specific DE-IRGs. RT-qPCR test showed that CCR9, CSF2, IL13RA1, and NTS had a significant correlation with LDLR^−/− mice. IL13RA1 knocked down in RAW264.7 cell lines decreased SCARB1 and ox-LDL-stimulated CD36 mRNA expression, TGF-β, VEGF-C and α-SMA protein levels and increased the production of IL-6, with downregulation of JAK1/STAT3 signal pathway.

Conclusions

We constructed a diagnostic model of advanced-stage CAD based on the screened 14 DE-IRGs. We verified 4 genes of them to have a strong correlation with CAD, and IL13RA1 might participate in the inflammation, fibrosis, and cholesterol efflux process of atherosclerosis by regulating JAK1/STAT3 pathway.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03614-1.

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.

Identification of differentially expressed genes and the role of PDK4 in CD14+ monocytes of coronary artery disease

Background. Coronary artery disease (CAD) is a chronic inflammatory disease caused by development of atherosclerosis (AS), which is the leading cause of mortality and disability. Our study aimed to identify the differentially expressed genes (DEGs) in CD14⁺ monocytes from CAD patients compared with those from non-CAD controls, which might pave the way to diagnosis and treatment for CAD. Methods. The RNA-sequencing (RNA-seq) was performed by BGISEQ-500, followed by analyzing with R package to screening DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by R package. In addition, we validated the results of RNA-seq using real-time quantitative polymerase chain reaction (RT-qPCR). Furthermore, we explored the function of selected ten genes in LDL-treated CD14⁺ monocytes by RT-qPCR. Results. a total of 2897 DEGs were identified, including 753 up- and 2144 down-regulated genes in CD14⁺ monocytes from CAD patients. These DEGs were mainly enriched in plasma membrane and cell periphery of cell component, immune system process of biological process, NF-κB signaling pathway, cell adhesion molecules signaling pathway and cytokine–cytokine receptor interaction signaling pathway. In LDL-treated CD14⁺ monocytes, the mRNA expression of pyruvate dehydrogenase kinase 4 (PDK4) was significantly up-regulated. Conclusion. In the present study, we suggested that PDK4 might play a role in progression of CAD. The study will provide some pieces of evidence to investigate the role and mechanism of key genes in the pathogenesis of CAD.

Integrated Network and Gene Ontology Analysis Identifies Key Genes and Pathways for Coronary Artery Diseases

BACKGROUND

The prevalence of Coronary Artery Disease (CAD) in developing countries is on the rise, owing to rapidly changing lifestyle. Therefore, it is imperative that the underlying genetic and molecular mechanisms be understood to develop specific treatment strategies. Comprehensive disease network and Gene Ontology (GO) studies aid in prioritizing potential candidate genes for CAD and also give insights into gene function by establishing gene and disease pathway relationships.

METHODS

In the present study, CAD-associated genes were collated from different data sources and protein-protein interaction network was constructed using STRING. Highly interconnected network clusters were inferred and GO analysis was performed.

RESULTS

Interrelation between genes and pathways were analyzed on ClueGO and 38 candidates were identified from 1475 CAD-associated genes, which were significantly enriched in CAD-related pathways such as metabolism and regulation of lipid molecules, platelet activation, macrophage derived foam cell differentiation, and blood coagulation and fibrin clot formation.

DISCUSSION

Integrated network and ontology analysis enables biomarker prioritization for common complex diseases such as CAD. Experimental validation and future studies on the prioritized genes may reveal valuable insights into CAD development mechanism and targeted treatment strategies.

A preliminary study of the effect of a high-salt diet on transcriptome dynamics in rat hypothalamic forebrain and brainstem cardiovascular control centers

BACKGROUND

High dietary salt intake is strongly correlated with cardiovascular (CV) diseases and it is regarded as a major risk factor associated with the pathogenesis of hypertension. The CV control centres in the brainstem (the nucleus tractus solitarii (NTS) and the rostral ventrolateral medulla (RVLM)) and hypothalamic forebrain (the subfornical organ, SFO; the supraoptic nucleus, SON and the paraventricular nucleus, PVN) have critical roles in regulating CV autonomic motor outflows, and thus maintaining blood pressure (BP). Growing evidence has implicated autonomic regulatory networks in salt-sensitive HPN (SSH), but the genetic basis remains to be delineated. We hypothesized that the development and/ or maintenance of SSH is reliant on the change in the expression of genes in brain regions controlling the CV system.

METHODOLOGY

We used RNA-Sequencing (RNA-Seq) to describe the differential expression of genes in SFO, SON, PVN, NTS and RVLM of rats being chronically fed with high-salt (HS) diet. Subsequently, a selection of putatively regulated genes was validated with quantitative reverse transcription polymerase chain reaction (qRT-PCR) in both Spontaneously Hypertensive rats (SHRs) and Wistar Kyoto (WKY) rats.

RESULTS

The findings enabled us to identify number of differentially expressed genes in SFO, SON, PVN, NTS and RVLM; that are either up-regulated in both strains of rats (SON- Caprin2, Sctr), down-regulated in both strains of rats (PVN- Orc, Gkap1), up-regulated only in SHRs (SFO- Apopt1, Lin52, AVP, OXT; SON- AVP, OXT; PVN- Caprin2, Sclt; RVLM- A4galt, Slc29a4, Cmc1) or down-regulated only in SHRs (SON- Ndufaf2, Kcnv1; PVN- Pi4k2a; NTS- Snrpd2l, Ankrd29, St6galnac6, Rnf157, Iglon5, Csrnp3, Rprd1a; RVLM- Ttr, Faim).

CONCLUSIONS

These findings demonstrated the adverse effects of HS diet on BP, which may be mediated via modulating the signaling systems in CV centers in the hypothalamic forebrain and brainstem.

Differential gene expression profiles in peripheral blood in Northeast Chinese Han people with acute myocardial infarction

This study aimed to use gene chips to investigate differential gene expression profiles in the occurrence and development of acute myocardial infarction (AMI). The study included 12 AMI patients and 12 healthy individuals. Total mRNA of peripheral bloodwas extracted and reversed-transcribed to cDNA for microarray analysis. After establishing two pools with three subjects each (3 AMI patients and 3 healthy individuals), the remaining samples were used for RT-qPCR to confirm the microarray data. From the microarray results, seven genes were randomly selected for RT-qPCR. RT-qPCR results were analyzed by the 2^-ΔΔCt method. Microarray analysis showed that 228 genes were up- regulated and 271 were down-regulated (p ≤ 0.05, |logFC| > 1). Gene ontology showed that these genes belong to 128 cellular components, 521 biological processes, and 151 molecular functions. KEGG pathway analysis showed that these genes are involved in 107 gene pathways. RT-qPCR results for the seven genes showed expression levels consistent with those obtained by microarray. Thus, microarray data could be used to select the pathogenic genes for AMI. Investigating the abnormal expression of these differentially expressed genes might suggest efficient strategies for the prevention, diagnosis, and treatment of AMI.

The role of lnc-DC long non-coding RNA and SOCS1 in the regulation of STAT3 in coronary artery disease and type 2 diabetes mellitus

AIMS

Coronary artery disease (CAD) can be classified as an inflammatory disease, which affected by type 2 diabetes mellitus (T2DM). Elevated levels of many inflammatory molecules were found in the serum of patients with CAD. STAT3 molecule as a transcription factor plays an important role in the cytokines expression. Here, we examined the expression levels of STAT3 and its important regulatory genes lnc-DC and SOCS1, in patients with CAD and T2DM.

METHODS

Blood samples were obtained from 37 CAD+ and 36 CAD- patients. These patients were enrolled in this study based on angiography findings and categorized based on T2DM status. The expression levels of STAT3, lnc-DC and SOCS1 genes were examined with Real time PCR method.

RESULTS

A significant increase was observed in expression of STAT3 and lnc-DC genes but not SOCS1 in CAD+ versus CAD- patients. These results replicated partially in some groups categorized based on T2DM and CAD status. However, severity of CAD had no effect on expressions of these genes. Moreover, we found some significant correlations between expressions of lnc-DC with SOCS1 and STAT3, which confirmed by in silico analysis.

CONCLUSION

Our results shed further light to the inflammatory aspects of CAD and T2DM with emphasis to JAK/STAT pathway and the regulatory role of long non-coding RNAs in the physiopathology of these diseases.

Integrative gene ontology and network analysis of coronary artery disease associated genes suggests potential role of ErbB pathway gene EGFR

Coronary artery disease (CAD) is a major cause of mortality in India, more importantly the young Indians. Combinatorial and integrative approaches to evaluate pathways and genes to gain an improved understanding and potential biomarkers for risk assessment are required. Therefore, 608 genes from the CADgene database version 2.0, classified into 12 functional classes representing the atherosclerotic disease process, were analyzed. Homology analysis of the unique list of gene ontologies (GO) from each functional class gave 8 GO terms represented in 11 and 10 functional classes. Using disease ontology analysis 80 genes belonging to 8 GO terms, using FunDO suggested that 29 of them were identified to be associated with CAD. Extended network analysis of these genes using STRING version 9.1 gave 328 nodes and 4,525 interactions of which the top 5% had a node degree of ≥75 associated with pathways including the ErbB signaling pathway with epidermal growth factor receptor (EGFR) gene as the central hub. Evaluation of EFGR protein levels in age and gender-matched 342 CAD patients vs. 342 control subjects demonstrated significant differences [controls=149.76±2.47 pg/ml and CAD patients stratified into stable angina (SA)=161.65±3.40 pg/ml and myocardial infarction (MI)=171.51±4.26 pg/ml]. Logistic regression analysis suggested that increased EGFR levels exhibit 3-fold higher risk of CAD [odds ratio (OR) 3.51, 95% confidence interval [CI] 1.96–6.28, P≤0.001], upon adjustment for hypertension, diabetes and smoking. A unit increase in EGFR levels increased the risk by 2-fold for SA (OR 2.58, 95% CI 1.25–5.33, P=0.01) and 3.8-fold for MI (OR 3.82, 95% CI 1.94–7.52, P≤0.001) following adjustment. Thus, the use of ontology mapping and network analysis in an integrative manner aids in the prioritization of biomarkers of complex disease.

Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits

Identifying causal genetic variants and understanding their mechanisms of effect on traits remains a challenge in genome-wide association studies (GWASs). In particular, how genetic variants (i.e., trans-eQTLs) affect expression of remote genes (i.e., trans-eGenes) remains unknown. We hypothesized that some trans-eQTLs regulate expression of distant genes by altering the expression of nearby genes (cis-eGenes). Using published GWAS datasets with 39,165 single-nucleotide polymorphisms (SNPs) associated with 1,960 traits, we explored whole blood gene expression associations of trait-associated SNPs in 5,257 individuals from the Framingham Heart Study. We identified 2,350 trans-eQTLs (at p < 10^-7); more than 80% of them were found to have cis-associated eGenes. Mediation testing suggested that for 35% of trans-eQTL-trans-eGene pairs in different chromosomes and 90% pairs in the same chromosome, the disease-associated SNP may alter expression of the trans-eGene via cis-eGene expression. In addition, we identified 13 trans-eQTL hotspots, affecting from ten to hundreds of genes, suggesting the existence of master genetic regulators. Using causal inference testing, we searched causal variants across eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, and fasting blood glucose) and identified several cis-eGenes (ALDH2 for systolic and diastolic blood pressure, MCM6 and DARS for total cholesterol, and TRIB1 for triglycerides) that were causal mediators for the corresponding traits, as well as examples of trans-mediators (TAGAP for LDL cholesterol). The finding of extensive evidence of genome-wide mediation effects suggests a critical role of cryptic gene regulation underlying many disease traits.

In-Cardiome: integrated knowledgebase for coronary artery disease enabling translational research

Coronary artery disease (CAD) is a leading cause of death worldwide. Prevention, diagnosis and clinical interventions are dependent on the conventional risk factors like hypertension, diabetes and obesity. However, these conventional risk factors do not completely identify high risk individuals. One major hurdle in the improvement of diagnosis and treatment for CAD is the lack of integration of knowledge from different areas of research like molecular, clinical and drug development. In order to provide comprehensive information from hitherto dispersed data, we developed an integrative knowledgebase called “In-Cardiome or Integrated Cardiome” for all the stake holders in healthcare such as scientists, clinicians and pharmaceutical companies. It is created by integrating 16 different data sources, 995 curated genes classified into 12 different functional categories associated with disease, 1204 completed clinical trials, 12 therapy or drug classifications with 62 approved drugs and drug target networks. This knowledgebase gives the most needed opportunity to understand the disease process and therapeutic impact along with gene expression data from both animal models and patients. The data is classified into three different search categories functional groups, risk factors and therapy/drug based classes. One more unique aspect of In-Cardiome is integration of clinical data of 10,217 subject data from our ongoing Indian Atherosclerosis Research Study (IARS) (6357 unaffected and 3860 CAD affected). IARS data showing demographics and associations of individual and combinations of risk factors in Indian population along with molecular information will enable better translational and drug development research.

Genomic translational research: Paving the way to individualized cardiac functional analyses and personalized cardiology

For most of Medicine's past, the best that physicians could do to cope with disease prevention and treatment was based on the expected response of an average patient. Currently, however, a more personalized/precise approach to cardiology and medicine in general is becoming possible, as the cost of sequencing a human genome has declined substantially. As a result, we are witnessing an era of precipitous advances in biomedicine and bourgeoning understanding of the genetic basis of cardiovascular and other diseases, reminiscent of the resurgence of innovations in physico-mathematical sciences and biology-anatomy-cardiology in the Renaissance, a parallel time of radical change and reformation of medical knowledge, education and practice. Now on the horizon is an individualized, diverse patient-centered, approach to medical practice that encompasses the development of new, gene-based diagnostics and preventive medicine tactics, and offers the broadest range of personalized therapies based on pharmacogenetics. Over time, translation of genomic and high-tech approaches unquestionably will transform clinical practice in cardiology and medicine as a whole, with the adoption of new personalized medicine approaches and procedures. Clearly, future prospects far outweigh present accomplishments, which are best viewed as a promising start. It is now essential for pluridisciplinary health care providers to examine the drivers and barriers to the clinical adoption of this emerging revolutionary paradigm, in order to expedite the realization of its potential. So, we are not there yet, but we are definitely on our way.