With the rapid development of artificial intelligence (AI) and machine learning (ML), as well as the arrival of the big data era, technological innovations have occurred in the field of ...cardiovascular medicine. First, the diagnosis of cardiovascular diseases (CVDs) is highly dependent on assistive examinations, the interpretation of which is time consuming and often limited by the knowledge level and clinical experience of doctors; however, AI could be used to automatically interpret the images obtained in auxiliary examinations. Second, some of the predictions of the incidence and prognosis of CVDs are limited in clinical practice by the use of traditional prediction models, but there may be occasions when AI-based prediction models perform well by using ML algorithms. Third, AI has been used to assist precise classification of CVDs by integrating a variety of medical data from patients, which helps better characterize the subgroups of heterogeneous diseases. To help clinicians better understand the applications of AI in CVDs, this review summarizes studies relating to AI-based diagnosis, prediction, and classification of CVDs. Finally, we discuss the challenges of applying AI to cardiovascular medicine.
Owing to the prevalence and high mortality rates of cardiac diseases, a more detailed characterization of the human heart is necessary; however, this has been largely impeded by the cellular ...diversity of cardiac tissue and limited access to samples. Here, we show transcriptome profiling of 21,422 single cells-including cardiomyocytes (CMs) and non-CMs (NCMs)-from normal, failed and partially recovered (left ventricular assist device treatment) adult human hearts. Comparative analysis of atrial and ventricular cells revealed pronounced inter- and intracompartmental CM heterogeneity as well as compartment-specific utilization of NCM cell types as major cell-communication hubs. Systematic analysis of cellular compositions and cell-cell interaction networks showed that CM contractility and metabolism are the most prominent aspects that are correlated with changes in heart function. We also uncovered active engagement of NCMs in regulating the behaviour of CMs, exemplified by ACKR1
-endothelial cells, injection of which preserved cardiac function after injury. Beyond serving as a rich resource, our study provides insights into cell-type-targeted intervention of heart diseases.
From highly aligned extracellular fibrils to the cells, a multilevel ordered hierarchy in valve leaflets is crucial for their biological function. Cardiac valve pathology most frequently involves a ...disruption in normal structure-function correlations through abnormal and complex interaction of cells, extracellular matrix, and their environment. At present, effective treatment for valve disease is limited and frequently ends with surgical repair or replacement with a mechanical or artificial biological cardiac valve, which comes with insuperable complications for many high-risk patients including aged and pediatric populations. Therefore, there is a critical need to fully appreciate the pathobiology of valve disease in order to develop better, alternative therapies. To date, the majority of studies have focused on delineating valve disease mechanisms at the cellular level. However, the cellular heterogeneity and function is still unclear. In this review, we summarize the body of work on valve cells, with a particular focus on the discoveries about valve cells heterogeneity and functions using single-cell RNA sequencing. We conclude by discussing state-of-the-art strategies for deciphering heterogeneity of these complex cell types, and argue this knowledge could translate into the improved personalized treatment of cardiac valve disease.
Display omitted
•Overview the application of single-cell RNA-sequencing technologies for studying heart valve development and disease.•Presentation of limitations and strengths of single-cell RNA-sequencing application in valvular science.•Review of novel cell subtypes implicated in heart valve development and disease using single-cell RNA-sequencing methods.
Targeted therapy refers to exploiting the specific therapeutic drugs against the pathogenic molecules (a protein or a gene) or cells. The drug specifically binds to disease-causing molecules or cells ...without affecting normal tissue, thus enabling personalized and precision treatment. Initially, therapeutic drugs included antibodies and small molecules, (e.g. nucleic acid drugs). With the advancement of the biology technology and immunotherapy, the gene editing and cell editing techniques are utilized for the disease treatment. Currently, targeted therapies applied to treat cardiovascular diseases (CVDs) mainly include protein drugs, gene editing technologies, nucleic acid drugs and cell therapy. Although targeted therapy has demonstrated excellent efficacy in pre-clinical and clinical trials, several limitations need to be recognized and overcome in clinical application, (e.g. off-target events, gene mutations, etc.). This review introduces the mechanisms of different targeted therapies, and mainly describes the targeted therapy applied in the CVDs. Furthermore, we made comparative analysis to clarify the advantages and disadvantages of different targeted therapies. This overview is expected to provide a new concept to the treatment of the CVDs.
Silent hypoxia has emerged as a unique feature of coronavirus disease 2019 (COVID-19). In this study, we show that mucins are accumulated in the bronchoalveolar lavage fluid (BALF) of COVID-19 ...patients and are upregulated in the lungs of severe respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected mice and macaques. We find that induction of either interferon (IFN)-β or IFN-γ upon SARS-CoV-2 infection results in activation of aryl hydrocarbon receptor (AhR) signaling through an IDO-Kyn-dependent pathway, leading to transcriptional upregulation of the expression of mucins, both the secreted and membrane-bound, in alveolar epithelial cells. Consequently, accumulated alveolar mucus affects the blood-gas barrier, thus inducing hypoxia and diminishing lung capacity, which can be reversed by blocking AhR activity. These findings potentially explain the silent hypoxia formation in COVID-19 patients, and suggest a possible intervention strategy by targeting the AhR pathway.
Post-polyploid diploidization associated with descending dysploidy and interspecific introgression drives plant genome evolution by unclear mechanisms. Raphanus is an economically and ecologically ...important Brassiceae genus and model system for studying post-polyploidization genome evolution and introgression. Here, we report the de novo sequence assemblies for 11 genomes covering most of the typical sub-species and varieties of domesticated, wild and weedy radishes from East Asia, South Asia, Europe, and America. Divergence among the species, sub-species, and South/East Asian types coincided with Quaternary glaciations. A genus-level pan-genome was constructed with family-based, locus-based, and graph-based methods, and whole-genome comparisons revealed genetic variations ranging from single-nucleotide polymorphisms (SNPs) to inversions and translocations of whole ancestral karyotype (AK) blocks. Extensive gene flow occurred between wild, weedy, and domesticated radishes. High frequencies of genome reshuffling, biased retention, and large-fragment translocation have shaped the genomic diversity. Most variety-specific gene-rich blocks showed large structural variations. Extensive translocation and tandem duplication of dispensable genes were revealed in two large rearrangement-rich islands. Disease resistance genes mostly resided on specific and dispensable loci. Variations causing the loss of function of enzymes modulating gibberellin deactivation were identified and could play an important role in phenotype divergence and adaptive evolution. This study provides new insights into the genomic evolution underlying post-polyploid diploidization and lays the foundation for genetic improvement of radish crops, biological control of weeds, and protection of wild species' germplasms.
A genus-level pan-genome was constructed through de novo genome assemblies of 11 accessions covering most of the typical sub-species and varieties of domesticated, wild, and weedy radishes from East Asia, South Asia, Europe, and America. This study provides new insights into the genomic evolution underlying post-polyploid diploidization and lays the foundation for genetic improvement of radish crops, biological control of weeds, and protection of wild species' germplasms.
MicroRNAs (miRNAs) are non-coding RNAs that function as regulators of gene expression and thereby contribute to the complex disease phenotypes. Hypertrophic cardiomyopathy (HCM) and Dilated ...cardiomyopathy (DCM) can cause sudden cardiac death and eventually develop into heart failure. However, they have different clinical and pathophysiological phenotype and the expressional spectrum of miRNAs in left ventricles of HCM and DCM has never been compared before.
This study selected 30 human left ventricular heart samples belonged to three diagnostic groups (Control, HCM, DCM). Each group has ten samples. Based on previous findings, the expression of 13 different microRNAs involving heart failure and hypertrophy (miR-1-3p, miR-10b, miR-21, miR-23a, miR-27a, miR-29a, miR-133a-3p, miR-142-3p, miR-155, miR-199a-3p, miR-199a-5p, miR-214, miR-497) was measured. 17 HCM patients were included as second group to validate the associations.
We found miR-155, miR-10b and miR-23a were highly expressed in both HCM and DCM compared with control. MiR-214 was downregulated and miR-21 was upregulated in DCM but not in HCM. We also identified miR-1-3p and miR-27a expressed significantly different between HCM and DCM and both miRNAs downregulated in HCM. And only miR-1-3p correlated with left ventricular end diastolic diameter (LVEDD) and left ventricular ejection fraction (LVEF) that reflected the cardiac function in HCM. A second HCM group also confirmed this correlation. We then predicted Chloride voltage-gated channel 3 (Clcn3) as a direct target gene of miR-1-3p using bioinformatics tools and confirmed it by Luciferase reporter assay.
Our data demonstrated that different cardiomyopathies had unique miRNA expression pattern. And the expression levels of miR-1-3p and miR-27a had disease-specificity and sensitivity in HCM, whereas only miR-1-3p was significantly associated with left ventricular function in HCM identifying it as a potential target to improve the cardiac function in end-stage HCM. We also provide Clcn3 as a direct target of miR-1-3p which sheds light on the mechanism of HCM.
Heart failure (HF) has been recognized as a global pandemic with a high rate of hospitalization, morbidity, and mortality. Although numerous advances have been made, its representative molecular ...signatures remain largely unknown, especially the role of genes in HF progression. The aim of the present prospective follow-up study was to reveal potential biomarkers associated with the progression of heart failure.
We generated multi-level transcriptomic data from a cohort of left ventricular heart tissue collected from 21 HF patients and 9 healthy donors. By using Masson staining to calculate the fibrosis percentage for each sample, we applied lasso regression model to identify the genes associated with fibrosis as well as progression. The genes were further validated by immunohistochemistry (IHC) staining in the same cohort and qRT-PCR using another independent cohort (20 HF and 9 healthy donors). Enzyme-linked immunosorbent assay (ELISA) was used to measure the plasma level in a validation cohort (139 HF patients) for predicting HF progression.
Based on the multi-level transcriptomic data, we examined differentially expressed genes mRNAs, microRNAs, and long non-coding RNAs (lncRNAs) in the study cohort. The follow-up functional annotation and regulatory network analyses revealed their potential roles in regulating extracellular matrix. We further identified several genes that were associated with fibrosis. By using the survival time before transplantation, COL1A1 was identified as a potential biomarker for HF progression and its upregulation was confirmed by both IHC and qRT-PCR. Furthermore, COL1A1 content ≥ 256.5 ng/ml in plasma was found to be associated with poor survival within 1 year of heart transplantation from heart failure hazard ratio (HR) 7.4, 95% confidence interval (CI) 3.5 to 15.8, Log-rank p value < 1.0 × 10
.
Our results suggested that COL1A1 might be a plasma biomarker of HF and associated with HF progression, especially to predict the 1-year survival from HF onset to transplantation.
"
," small cells contain huge secrets. The vasculature is composed of many multifunctional cell subpopulations, each of which is involved in the occurrence and development of cardiovascular diseases. ...Single-cell transcriptomics captures the full picture of genes expressed within individual cells, identifies rare or
cell subpopulations, analyzes single-cell trajectory and stem cell or progenitor cell lineage conversion, and compares healthy tissue and disease-related tissue at single-cell resolution. Single-cell transcriptomics has had a profound effect on the field of cardiovascular research over the past decade, as evidenced by the construction of cardiovascular cell landscape, as well as the clarification of cardiovascular diseases and the mechanism of stem cell or progenitor cell differentiation. The classification and proportion of cell subpopulations in vasculature vary with species, location, genotype, and disease, exhibiting unique gene expression characteristics in organ development, disease progression, and regression. Specific gene markers are expected to be the diagnostic criteria, therapeutic targets, or prognostic indicators of diseases. Therefore, treatment of vascular disease still has lots of potentials to develop. Herein, we summarize the cell clusters and gene expression patterns in normal vasculature and atherosclerosis, aortic aneurysm, and pulmonary hypertension to reveal vascular heterogeneity and new regulatory factors of cardiovascular disease in the use of single-cell transcriptomics and discuss its current limitations and promising clinical potential.