The Discovery of Novel Genomic, Transcriptomic, and Proteomic Biomarkers in Cardiovascular and Peripheral Vascular Disease: The State of the Art

Omics Science and Social Aspects in Detecting Biomarkers for Diagnosis, Risk Prediction, and Outcomes of Carotid Stenosis

Carotid stenosis is characterized by the progressive narrowing of the carotid arteries due to the formation of atherosclerotic plaque, which can lead to stroke and death as major complications. Numerous biomarkers allow for its study and characterization, particularly those related to "omics" sciences. Through the most common research databases, we report representative studies about carotid stenosis biomarkers based on genomics, transcriptomics, proteomics, and metabolomics in a narrative review. To establish a priority among studies based on their internal validity, we used a quality assessment tool, the Scale for the Assessment of Narrative Review Articles (SANRA). Genes, transcriptomes, proteins, and metabolites can diagnose the disease, define plaque connotations, predict consequences after revascularization interventions, and associate carotid stenosis with other patient comorbidities. It also emerged that many aspects determining the patient's psychological and social sphere are implicated in carotid disease. In conclusion, when taking the multidisciplinary approach that combines human sciences with biological sciences, it is possible to comprehensively define a patient's health and thus improve their clinical management through precision medicine.

Chronic Venous Disease: Pathophysiological Aspects, Risk Factors, and Diagnosis

Chronic venous disease (CVD) is highly prevalent in the general population and encompasses a range of pathological and hemodynamic changes in the veins of the lower extremities. These alterations give rise to a variety of symptoms, with more severe forms resulting in venous ulceration, which causes morbidity and high socioeconomic burden. The origins and underlying mechanisms of CVD are intricate and multifaceted, involving environmental factors, genetics, hormonal factors, and immunological factors that bring about structural and functional alterations in the venous system. This review offers the latest insights into the epidemiology, pathophysiology, and risk factors of CVD, aiming to provide a comprehensive overview of the current state of knowledge. Furthermore, the diagnostic approach for CVD is highlighted and current diagnostic tools are described.

Identification of key proteins as potential biomarkers associated with post-infarction complications in diabetics

Background: The ability of transcriptome analysis to identify dysregulated pathways and outcome-related genes following myocardial infarction in diabetic patients remains unknown. The present study was designed to detect possible biomarkers associated with the incidence of post-infarction complications in diabetes to assist thedevelopment of novel treatments for this condition.Methods: Two gene expression datasets, GSE12639 and GSE6880, were downloaded from the Gene Expression Omnibus (GEO) database, and then differentially expressed genes (DEGs) were identified between post-infarction diabetics and healthy samples from the left ventricular wall of rats. These DEGs were then arranged into a protein-protein interaction (PPI) network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were performed to explore the functional roles of these genes.Results: In total, 30 DEGs (14 upregulated and 16 downregulated) were shared between these two datasets, as identified through Venn diagram analyses. GO analyses revealed these DEGs to be significantly enriched in ovarian steroidogenesis, fatty acid elongation, biosynthesis of unsaturated fatty acids, synthesis and degradation of ketone bodies, and butanoate metabolism. The PPI network of the DEGs had 14 genes and 70 edges. We identified two key proteins, 3-hydroxymethylglutaryl-CoA synthase 2 (Hmgcs2) and Δ3, Δ2-Enoyl-CoA Delta Isomerase 1 (ECI1), and the upregulated gene Hmgcs2 with the highest score in the MCC method. We generated a co-expression network for the hub genes and obtained the top ten medications suggested for infarction with diabetes.Conclusion: Taken together, the findings of these bioinformatics analyses identified key hub genes associated with the development of myocardial infarction in diabetics. These hub genes and potential drugs may become novel biomarkers for prognosis and precision treatment in the future.

MicroRNA and Hemostasis Profile of Carotid Atherosclerosis

Carotid atherosclerosis (CA) is an important risk factor for ischemic stroke. We described the miRNA and hemostasis profile of patients with moderate and advanced stages of carotid atherosclerosis and elucidated potential correlations with hemostatic activation. A prospective case-control study included 61 patients with evidence of carotid atherosclerosis (via ultrasound). The study population was divided into groups depending on the degree of carotid artery stenosis: 60% or more (advanced) and <60% (moderate). All patients underwent the following blood tests: general blood test, hemostatic parameters and microRNA. Extraction of microRNA was performed using Leukocyte RNA Purification Kit (NORGEN Biotec Corp., Thorold, ON, Canada); miRNA quantification was performed via RT-PCR. Statistical analysis was performed in R programming language (v. 4.1.0) using RSudio. MicroRNA expression profile was different depending on CA degree. MiR-33a-5p/3p levels were higher in patients with ≥60% carotid stenosis (42.70 and 42.45 versus 38.50 and 38.50, respectively, p < 0.05). Almost complete separation can be visualized with the levels of miR-126-5p: 9.50 in the moderate CA group versus 5.25 in the advanced CA (p < 0.001). MiR-29-5p was higher in the moderate CA group: 28.60 [25.50;33.05] than in advanced CA group: 25.75 [24.38;29.50] (p = 0.086); miR-29-3p was also higher in the moderate CA group: 10.36 [8.60;14.99] than in advanced CA group: 8.46 [7.47;10.3] (p = 0.001). By-group pairwise correlation analyses revealed at least three clusters with significant positive correlations in the moderate CA group: miR-29-3p with factors V and XII (r = 0.53 and r = 0.37, respectively, p < 0.05); miR-21-5p with ADAMTS13, erythrocyte sedimentation rate and D-dimer (r = 0.42, r = 0.36 and r = 0.44, respectively, p < 0.05); stenosis degree with miR-33a-5p/3p and factor VIII levels (r = 0.43 (both) and r = 0.62, respectively, p < 0.05). Hemostasis parameters did not reveal significant changes in CA patients: the only statistically significant differences concerned factor VIII, plasminogen and (marginally significant) ADAMTS-13 and protein C. Down-regulation of miR-126-5p expression has been identified as a promising biomarker of advanced carotid atherosclerosis with high specificity and sensitivity. Correlation cluster analysis showed potential interplay between miRNAs and hemostatic activation in the setting of carotid atherosclerosis.

N, Adigal S, Lukose J, Kartha VB, Chidangil S. Cardiovascular biomarkers in body fluids: progress and prospects in optical sensors

Cardiovascular diseases (CVD) are the major causative factors for high mortality and morbidity in developing and developed nations. The biomarker detection plays a crucial role in the early diagnosis of several non-infectious and life-threatening diseases like CVD and many cancers, which in turn will help in more successful therapy, reducing the mortality rate. Biomarkers have diagnostic, prognostic and therapeutic significances. The search for novel biomarkers using proteomics, bio-sensing, micro-fluidics, and spectroscopic techniques with good sensitivity and specificity for CVD is progressing rapidly at present, in addition to the use of gold standard biomarkers like troponin. This review is dealing with the current progress and prospects in biomarker research for the diagnosis of cardiovascular diseases. Expert opinion. Fast diagnosis of cardiovascular diseases (CVDs) can help to provide rapid medical intervention, which can affect the patient's short and long-term health. Identification and detection of proper biomarkers for early diagnosis are crucial for successful therapy and prognosis of CVDs. The present review discusses the analysis of clinical samples such as whole blood, blood serum, and other body fluids using techniques like high-performance liquid chromatography-LASER/LED-induced fluorescence, Raman spectroscopy, mainly, optical methods, combined with nanotechnology and micro-fluidic technologies, to probe patterns of multiple markers (marker signatures) as compared to conventional techniques.

Study on Proteomics-Based Aortic Dissection Molecular Markers Using iTRAQ Combined With Label Free Techniques

Background: Aortic dissection refers to the separation of aortic media and extension along the long axis to form the true and false chambers of the aortic wall. 65–70% of the patients died of cardiac tamponade, arrhythmia, dissection rupture, etc. At present, echocardiography, computed tomography angiography (CTA), etc. are the main diagnosis tools for aortic dissection. To date, there is no rapid serum molecular marker that can be used for differential diagnosis and risk assessment.

Objectives: To screen serum molecular markers systematically amid aortic dissection and acute coronary syndrome and to preliminarily identify the pathogenesis of acute aortic dissection.

Methods: Related disputes cases of all hospitals were statistically analyzed for the AAD medical disputes ratio, early death ratio and misdiagnosis ratio from the database of Guangdong Province Medical Disputes Coordination Committee from 2013 to 2017. Serum and Aortic tissues samples were respectively quantified by iTRAQ and label-free analysis, further validated by ELISA and protein verified by immunofluorescence and Western blot from AAD and control patients enrolled from the Zhujiang Hospital of Southern Medical University and Guangdong Province people's Hospital from 2016 to 2018.

Results: AAD cases ratio accounted for 15.29% in all 150 cardiovascular disputes, 59.26% in all cardiovascular death less than 24 h, and 88.89% in the patients who remained undiagnosed at the time of death, 84 proteins (66 and 18 upregulated and downregulated, respectively) were identified by iTRAQ and 16 proteins (9 and 7 upregulated and downregulated, respectively) by Label-free. Nine proteins (Lumican, FGL1, PI16, MMP9, FBN1, MMP2, VWF, MMRN1, and PF4) related to the pathogenesis of aortic dissection were identified by David /Ease and String techniques as candidate biomarkers for verification test. Four proteins (Lumican, FGL1, PI16, and MMP9) were found to be statistically different after ELISA verification. The expression of FGL1, PI16, and MMP9 proteins was pathologically significantly increased except for Lumican. Histologically, TGF-β1, α-SMA, and Collagen1 were also significantly higher in the aortic group.

Conclusion: Lumican, FGL1, PI16, and MMP9 may be potential biomarkers in AAD patients, and the Lumican-mediated TGF-β1 pathway is likely to be involved in the pathogenesis of aortic dissection.

Angiopoietin 2 as a Novel Potential Biomarker for Acute Aortic Dissection

Biomarker-assisted diagnosis of acute aortic dissection (AAD) is important for initiation of treatment and improved survival. However, identification of biomarkers for AAD in blood is a challenging task. The present study aims to find the potential AAD biomarkers using a transcriptomic strategy. Arrays based genome-wide gene expression profiling were performed using ascending aortic tissues which were collected from AAD patients and healthy donors. The differentially expressed genes were validated using quantitative reverse transcriptase PCR (qRT-PCR) and western blot. The plasma levels of a potential biomarker, angiopoietin 2 (ANGPT2) were determined in case-control cohort (77 AAD patients and 82 healthy controls) by enzyme linked immunosorbent assay. Receiver operating characteristic curve (ROC) was used to evaluate the diagnostic power of ANGPT2 for AAD. Transcriptome data demonstrated that a total of 18 genes were significantly up-regulated and 28 genes were significantly down-regulated among AAD tissues (foldchange>3.0, p < 0.01). By bioinformatic analysis, we identified ANGPT2 as a candidate biomarker for blood-based detection of AAD. The qRT-PCR and protein expression demonstrated that ANGPT2 increased 2.4- and 4.2 folds, respectively in aortic tissue of AAD patients. Immunohistochemical staining demonstrated that ANGPT2 was markedly increased in intima of the aortic wall in AAD. Furthermore, ANGPT2 was significantly elevated in AAD patients as compared with controls (median 1625 vs. 383 pg/ml, p < 1E-6). ROC curve analysis showed that ANGPT2 was highly predictive of a diagnosis of type A AAD (area under curve 0.93, p < 1E-6). Sensitivity and specificity were 81 and 90%, respectively at the cutoff value of 833 pg/ml. In conclusion, ANGPT2 could be a promising biomarker for diagnosis of AAD; however, more studies are still needed to verify its specificity in diagnosing of AAD.

Novel biomarkers in cardiovascular surgery

Cardiovascular disease includes health problems related to the heart, arteries and veins and is a significant healthcare problem worldwide. Cardiovascular disease may be acute or chronic and relapses are frequent. Biomarkers involved in this field may help clinicians and surgeons in diagnosis and adequate decision making. Relevant articles searched in the following databases Medline, Scopus, ScienceDirect, were retrieved and analysed. Several biomarkers have been identified and we analyzed those of most importance from a clinical and surgical point of view. Biomarkers can better identify high-risk individuals, facilitate follow-up process, provide information regarding prognosis and better tailor the most appropriate surgical treatment.

Precision Medicine and Precision Nursing: The Era of Biomarkers and Precision Health

Precision health, by means of the support of precision medicine and precision nursing, is able to support clinical decision making in order to tailor optimal health-care decisions, around the individual characteristics of patients. The operational arm of precision health is represented by the use of biomarkers that can give useful information about disease susceptibility, exposure, evolution and response to treatment. Omics, imaging and clinical biomarkers are actually studied for their ability to positively impact health-care management. In this article, we try to address the role of biomarkers in the context of modern medicine and nursing with the view of improving patients care.

Non-Coding RNA Databases in Cardiovascular Research

Cardiovascular diseases (CVDs) are of multifactorial origin and can be attributed to several genetic and environmental components. CVDs are the leading cause of mortality worldwide and they primarily damage the heart and the vascular system. Non-coding RNA (ncRNA) refers to functional RNA molecules, which have been transcribed into DNA but do not further get translated into proteins. Recent transcriptomic studies have identified the presence of thousands of ncRNA molecules across species. In humans, less than 2% of the total genome represents the protein-coding genes. While the role of many ncRNAs is yet to be ascertained, some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been associated with disease progression, serving as useful diagnostic and prognostic biomarkers. A plethora of data repositories specialized in ncRNAs have been developed over the years using publicly available high-throughput data from next-generation sequencing and other approaches, that cover various facets of ncRNA research like basic and functional annotation, expressional profile, structural and molecular changes, and interaction with other biomolecules. Here, we provide a compendium of the current ncRNA databases relevant to cardiovascular research.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

Accurate Prediction of Coronary Heart Disease for Patients With Hypertension From Electronic Health Records With Big Data and Machine-Learning Methods: Model Development and Performance Evaluation

BACKGROUND

Predictions of cardiovascular disease risks based on health records have long attracted broad research interests. Despite extensive efforts, the prediction accuracy has remained unsatisfactory. This raises the question as to whether the data insufficiency, statistical and machine-learning methods, or intrinsic noise have hindered the performance of previous approaches, and how these issues can be alleviated.

OBJECTIVE

Based on a large population of patients with hypertension in Shenzhen, China, we aimed to establish a high-precision coronary heart disease (CHD) prediction model through big data and machine-learning.

METHODS

Data from a large cohort of 42,676 patients with hypertension, including 20,156 patients with CHD onset, were investigated from electronic health records (EHRs) 1-3 years prior to CHD onset (for CHD-positive cases) or during a disease-free follow-up period of more than 3 years (for CHD-negative cases). The population was divided evenly into independent training and test datasets. Various machine-learning methods were adopted on the training set to achieve high-accuracy prediction models and the results were compared with traditional statistical methods and well-known risk scales. Comparison analyses were performed to investigate the effects of training sample size, factor sets, and modeling approaches on the prediction performance.

RESULTS

An ensemble method, XGBoost, achieved high accuracy in predicting 3-year CHD onset for the independent test dataset with an area under the receiver operating characteristic curve (AUC) value of 0.943. Comparison analysis showed that nonlinear models (K-nearest neighbor AUC 0.908, random forest AUC 0.938) outperform linear models (logistic regression AUC 0.865) on the same datasets, and machine-learning methods significantly surpassed traditional risk scales or fixed models (eg, Framingham cardiovascular disease risk models). Further analyses revealed that using time-dependent features obtained from multiple records, including both statistical variables and changing-trend variables, helped to improve the performance compared to using only static features. Subpopulation analysis showed that the impact of feature design had a more significant effect on model accuracy than the population size. Marginal effect analysis showed that both traditional and EHR factors exhibited highly nonlinear characteristics with respect to the risk scores.

CONCLUSIONS

We demonstrated that accurate risk prediction of CHD from EHRs is possible given a sufficiently large population of training data. Sophisticated machine-learning methods played an important role in tackling the heterogeneity and nonlinear nature of disease prediction. Moreover, accumulated EHR data over multiple time points provided additional features that were valuable for risk prediction. Our study highlights the importance of accumulating big data from EHRs for accurate disease predictions.

The impact of epigenetics on cardiovascular disease

Mortality and morbidity from cardiovascular diseases (CVDs) represents a huge burden to society. It is recognized that environmental factors and individual lifestyles play important roles in disease susceptibility, but the link between these external risk factors and our genetics has been unclear. However, the discovery of sequence-independent heritable DNA changes (epigenetics) have helped us to explain the link between genes and the environment. Multiple diverse epigenetic processes, including DNA methylation, histone modification, and the expression of non-coding RNA molecules affect the expression of genes that produce important changes in cellular differentiation and function, influencing the health and adaptability of the organism. CVDs such as congenital heart disease, cardiomyopathy, heart failure, cardiac fibrosis, hypertension, and atherosclerosis are now being viewed as much more complex and dynamic disorders. The role of epigenetics in these and other CVDs is currently under intense scrutiny, and we can expect important insights to emerge, including novel biomarkers and new approaches to enable precision medicine. This review summarizes the recent advances in our understanding of the role of epigenetics in CVD.

Searching for the Genetic Determinants of Peripheral Arterial Disease: A Review of the Literature and Future Directions

Peripheral arterial disease (PAD) is a significant but under-recognized disease that is poorly understood despite population-scale genetic studies. To address this morbid disease, clinicians need additional tools to identify, prevent, and treat patients at risk for PAD. Genetic studies of coronary artery disease have yielded promising results for clinical application, which have thus far been lacking in PAD. In this article, we review recent findings, discuss limitations, and propose future directions of genomic study and clinical application. However, despite many studies, we still lack definitive genetic markers for PAD. This can be attributed to the heterogeneity of PAD's pathogenesis and clinical manifestations, as well as inconsistencies in study methodologies, limitations of current genetic assessment techniques, incompletely comprehended molecular pathophysiology, and confounding generalized atherosclerotic risk factors. The goals of this review are to evaluate the limitations of our current genetic knowledge of PAD and to propose approaches to expedite the identification of valuable markers of PAD.

Effects of EDC-PEI heparinization on allogeneic vascular antigens and inflammation levels via a rat abdominal aorta transplantation model

The objective of this study was to investigate the possibility of increasing the remote patency rate of allogeneic vessel transplantation through studying the effects of N-ethyl-N-(3-dimethylaminopropyl)-carbodiimide and polyethyleneimine (EDC-PEI) heparinization on allogeneic vascular antigens and inflammation levels. Forty rats were randomly divided into the control group, the EDC group, the PEI group and the EDC-PEI group. The rat abdominal aorta was used as the object of study, and the transplanted blood vessels were pretreated with EDC as the water-soluble cross-linking agent and PEI as the heparin-coated carrier. A rat abdominal aorta allogeneic transplantation model was established. Ultrasonic examination was used for observation of patency of proximal and distal anastomosis in each group. The tissue repair after abdominal aorta transplantation in each group was examined by H&E staining. The biomechanics, denaturation temperature and blasting strength of each group were compared. The levels of IL-1, IL-6 and TNF-α in serum of rats were measured by ELISA method, and the expression of MHC-II and α-GAL antigens in blood vessels were detected by immunohistochemistry. There were different degrees of thickening and inflammatory cell aggregation in the abdominal aorta of rats in the control, EDC and PEI groups, but there was no obvious lesion in the EDC-PEI group. Compared with the four groups, the mechanical characteristics of the EDC group decreased significantly, and the stenosis rate of anastomotic stoma in the EDC group was higher than that in the EDC-PEI and PEI groups (P<0.05). The denaturation temperature of the PEI group was lower than that of the EDC and EDC-PEI groups (P<0.05). The mechanical property and vascular bursting strength in the EDC-PEI group were similar to those in the control group. At the same time, it has more significant advantages than the other three groups in removing the vascular antigens MHC-II and α-GAL and reducing the level of inflammatory reaction, thus increasing the remote patency rate of allogeneic vascular transplantation. The inflammatory response and vascular antigenicity after transplantation are effectively reduced via the rat abdominal aorta transplantation model treated with allogeneic EDC-PEI heparinization, which has a higher remote patency rate.

Association of the LIPC rs1532085 SNP and serum lipid traits in the Chinese Maonan and Han populations

The hepatic lipase gene (LIPC) is known to play an important role in lipid and lipoprotein metabolism pathways, but the association of the LIPC rs1532085 single nucleotide polymorphism (SNP) and serum lipid profiles has not been previously reported in different racial/ethnic groups. The present study was to detect the association of the LIPC rs1532085 SNP and several environmental factors with serum lipid levels in the Maonan and Han populations. Genotypes of the LIPC rs1532085 SNP in 833 individuals of Maonan nationality and 801 participants of Han nationality were determined by polymerase chain reaction and restriction fragment length polymorphism. The frequencies of AA, AG, and GG genotypes were 22.34%, 47.70%, and 29.96% in Han, and 24.96%, 51.38%, and 23.64% in Maonan populations (P < 0.05). The frequency of the G allele was 53.80% in Han and 49.33% in Maonan individuals (P < 0.05). The G allele carriers had lower total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), Apolipoprotein (Apo) A1 and ApoB levels in Han than the G allele non-carriers, but not in Maonan. Subgroup analyses indicated that the G allele carriers had lower TC, TG, LDL-C and ApoA1 levels in Han females than the G allele non-carriers (P < 0.05-0.001). Serum lipid parameters in the two ethnic groups were also associated with several environmental factors. These findings revealed that there might be a racial/ethnic- and/or sex-specific association between the LIPC rs1532085 SNP and serum lipid parameters in some populations.

Association of the CYP26A1 rs2068888 polymorphism and serum lipid traits in the Chinese Maonan and Han populations

The cytochrome P450 protein plays an important role in the synthesis of cholesterol and other lipid parameters. But little is known about the association of the single nucleotide polymorphism (SNP) of rs2068888 near cytochrome P450 26A1 gene (CYP26A1) and serum lipid profiles in the Chinese Maonan and Han populations. This study explored such association in the two populations. Genotyping of the CYP26A1 rs2068888 SNP was performed in 833 unrelated individuals of Maonan and 701 participants of Han by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and confirmed by direct sequencing. The genotypic and allelic frequencies of the CYP26A1 rs2068888 SNP were significantly different between the Maonan and Han. The frequencies of AA, AG and GG genotypes were 75.51%, 23.41% and 1.08% in the Maonan population, and 64.62%, 33.10% and 2.28% in the Han population (P < 0.001). The frequency of the G allele was 12.78% in Maonan and 18.83% in Han (P < 0.001). The level of serum total cholesterol (TC) was lower in Maonan than in Han. The G allele carriers had higher serum TC level in Maonan than the G allele non-carriers. Subgroup analyses indicated that the G allele carriers had higher serum TC level in Maonan females. Serum lipid parameters in the two ethnic groups were also associated with several environmental factors. These findings revealed that there may be a racial/ethnic- and/or sex-specific association between the CYP26A1 rs2068888 SNP and serum lipid parameters in some populations.

Transcriptome Profiling in Systems Vascular Medicine

In the post-genomic, big data era, our understanding of vascular diseases has been deepened by multiple state-of-the-art “–omics” approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics and metabolomics. Genome-wide transcriptomic profiling, such as gene microarray and RNA-sequencing, emerges as powerful research tools in systems medicine and revolutionizes transcriptomic analysis of the pathological mechanisms and therapeutics of vascular diseases. In this article, I will highlight the workflow of transcriptomic profiling, outline basic bioinformatics analysis, and summarize recent gene profiling studies performed in vascular cells as well as in human and mice diseased samples. Further mining of these public repository datasets will shed new light on our understanding of the cellular basis of vascular diseases and offer novel potential targets for therapeutic intervention.

The Involvement of miRNA in Carotid-Related Stroke

Cardiovascular disease is the leading cause of morbidity and mortality in developed countries. Stroke is associated with a marked disability burden and has a major economic impact; this is especially true for carotid artery stroke. Major advances in primary and secondary prevention during the last few decades have helped to tackle this public health problem. However, better knowledge of the physiopathology of stroke and its underlying genetic mechanisms is needed to improve diagnosis and therapy. miRNAs are an important, recently identified class of post-transcriptional regulators of gene expression and are known to be involved in cerebrovascular disease. These endogenous, small, noncoding RNAs may have applications as noninvasive biomarkers and therapeutic tools in practice. Here, we review the involvement of several miRNAs in cell-based and whole-animal models of stroke, with a focus on human miRNA profiling studies of carotid artery stroke. Lastly, we describe the miRNAs' potential role as a biomarker of stroke.

The Management of Cardiovascular Risk through Epigenetic Biomarkers

Epigenetic sciences study heritable changes in gene expression not related to changes in the genomic DNA sequence. The most important epigenetic mechanisms are DNA methylation, posttranslational histone modification, and gene regulation by noncoding RNAs, such as microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). Cardiovascular diseases (CVD) are responsible for at least one-third of premature deaths worldwide and represent a heavy burden of healthcare expenditure. We will discuss in this review the most recent findings dealing with epigenetic alterations linked to cardiovascular physiopathology in patients. A particular focus will be put on the way these changes can be translated in the clinic, to develop innovative and groundbreaking biomarkers in CVD field.

microRNAs in the pathophysiology of CKD-MBD: Biomarkers and innovative drugs

microRNAs comprise a novel class of endogenous small non-coding RNAs that have been shown to be implicated in both vascular damage and bone pathophysiology. Chronic kidney disease-mineral bone disorder (CKD-MBD) is characterized by vessel and bone damage secondary to progressive loss of kidney function. In this review, we will describe how several microRNAs have been implicated, in recent years, in cellular and animal models of CKD-MBD, and have been very recently shown to be deregulated in patients with CKD. Particular emphasis has been placed on the endothelial-specific miR-126, a potential biomarker of endothelial dysfunction, and miR-155 and miR-223, which play a role in both vascular smooth muscle cells and osteoclasts, with an impact on the vascular calcification and osteoporosis process. Finally, as these microRNAs may constitute useful targets to prevent or treat complications of CKD-MBD, we will discuss their potential as innovative drugs, describe how they could be delivered in a timely and specific way to vessels and bone by using the most recent techniques such as nanotechnology, viral vectors or CRISPR gene targeting.