Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors

Personalized transcriptome signatures in a cardiomyopathy stem cell biobank

BACKGROUND

There is growing evidence that pathogenic mutations do not fully explain hypertrophic (HCM) or dilated (DCM) cardiomyopathy phenotypes. We hypothesized that if a patient's genetic background was influencing cardiomyopathy this should be detectable as signatures in gene expression. We built a cardiomyopathy biobank resource for interrogating personalized genotype phenotype relationships in human cell lines.

METHODS

We recruited 308 diseased and control patients for our cardiomyopathy stem cell biobank. We successfully reprogrammed PBMCs (peripheral blood mononuclear cells) into induced pluripotent stem cells (iPSCs) for 300 donors. These iPSCs underwent whole genome sequencing and were differentiated into cardiomyocytes for RNA-seq. In addition to annotating pathogenic variants, mutation burden in a panel of cardiomyopathy genes was assessed for correlation with echocardiogram measurements. Line-specific co-expression networks were inferred to evaluate transcriptomic subtypes. Drug treatment targeted the sarcomere, either by activation with omecamtiv mecarbil or inhibition with mavacamten, to alter contractility.

RESULTS

We generated an iPSC biobank from 300 donors, which included 101 individuals with HCM and 88 with DCM. Whole genome sequencing of 299 iPSC lines identified 78 unique pathogenic or likely pathogenic mutations in the diseased lines. Notably, only DCM lines lacking a known pathogenic or likely pathogenic mutation replicated a finding in the literature for greater nonsynonymous SNV mutation burden in 102 cardiomyopathy genes to correlate with lower left ventricular ejection fraction in DCM. We analyzed RNA-sequencing data from iPSC-derived cardiomyocytes for 102 donors. Inferred personalized co-expression networks revealed two transcriptional subtypes of HCM. The first subtype exhibited concerted activation of the co-expression network, with the degree of activation reflective of the disease severity of the donor. In contrast, the second HCM subtype and the entire DCM cohort exhibited partial activation of the respective disease network, with the strength of specific gene by gene relationships dependent on the iPSC-derived cardiomyocyte line. ADCY5 was the largest hubnode in both the HCM and DCM networks and partially corrected in response to drug treatment.

CONCLUSIONS

We have a established a stem cell biobank for studying cardiomyopathy. Our analysis supports the hypothesis the genetic background influences pathologic gene expression programs and support a role for ADCY5 in cardiomyopathy.

Mechanism of CREB1 in cardiac function of rats with heart failure via regulating the microRNA-376a-3p/TRAF6 axis

Heart failure (HF) is a complicated disease resulting from impaired heart function. CREB1 is a candidate target in heart-concerning diseases. This paper attempts to explore the role of CREB1 in HF. Initially, the HF rat model was established by constricted abdominal aortic surgery and the cardiac function of HF rats was assessed by ultrasonic cardiogram. Levels of CK-MB and LDH and activity of Caspase-3 and Caspase-9 in HF rats were determined. Subsequently, myocardium pathological injury and myocardium apoptosis were detected. Additionally, the interactions between CREB1 and miR-376a-3p and between miR-376a-3p and TRAF6 were verified. The roles of CREB1, miR-376a-3p, and TRAF6 in HF were evaluated. In HF rats, CREB1 and miR-376a-3p were both downregulated while TRAF6 was upregulated. Besides, HF rats had decreased values of EF and FS, elevated levels of CK-MB and LDH, inflammatory infiltration, promoted cardiomyocyte apoptosis, and elevated activity of Caspase-3 and Caspase-9, which were all reversed by CREB1. Additionally, CREB1 activated miR-376a-3p expression, and miR-376a-3p targeted TRAF6 transcription. Both miR-376a-3p knockdown and TRAF6 overexpression annulled the protective role of CREB1 overexpression in cardiac function of HF rats. CREB1 activated miR-376a-3p expression to suppress TRAF6, thereby promoting the cardiac function of HF rats.

Network Embedding Across Multiple Tissues and Data Modalities Elucidates the Context of Host Factors Important for COVID-19 Infection

COVID-19 is a heterogeneous disease caused by SARS-CoV-2. Aside from infections of the lungs, the disease can spread throughout the body and damage many other tissues, leading to multiorgan failure in severe cases. The highly variable symptom severity is influenced by genetic predispositions and preexisting diseases which have not been investigated in a large-scale multimodal manner. We present a holistic analysis framework, setting previously reported COVID-19 genes in context with prepandemic data, such as gene expression patterns across multiple tissues, polygenetic predispositions, and patient diseases, which are putative comorbidities of COVID-19. First, we generate a multimodal network using the prior-based network inference method KiMONo. We then embed the network to generate a meaningful lower-dimensional representation of the data. The input data are obtained via the Genotype-Tissue Expression project (GTEx), containing expression data from a range of tissues with genomic and phenotypic information of over 900 patients and 50 tissues. The generated network consists of nodes, that is, genes and polygenic risk scores (PRS) for several diseases/phenotypes, as well as for COVID-19 severity and hospitalization, and links between them if they are statistically associated in a regularized linear model by feature selection. Applying network embedding on the generated multimodal network allows us to perform efficient network analysis by identifying nodes close by in a lower-dimensional space that correspond to entities which are statistically linked. By determining the similarity between COVID-19 genes and other nodes through embedding, we identify disease associations to tissues, like the brain and gut. We also find strong associations between COVID-19 genes and various diseases such as ischemic heart disease, cerebrovascular disease, and hypertension. Moreover, we find evidence linking PTPN6 to a range of comorbidities along with the genetic predisposition of COVID-19, suggesting that this kinase is a central player in severe cases of COVID-19. In conclusion, our holistic network inference coupled with network embedding of multimodal data enables the contextualization of COVID-19-associated genes with respect to tissues, disease states, and genetic risk factors. Such contextualization can be exploited to further elucidate the biological importance of known and novel genes for severity of the disease in patients.

Identifying molecular insight of synergistic complexities for SARS-CoV-2 infection with pre-existing type 2 diabetes

The ongoing COVID-19 outbreak, caused by SARS-CoV-2, has posed a massive threat to global public health, especially to people with underlying health conditions. Type 2 diabetes (T2D) is lethal comorbidity of COVID-19. However, its pathogenetic link remains unclear. This research aims to determine the genetic factors and processes contributing to the synergistic severity of SARS-CoV-2 infection among T2D patients through bioinformatics approaches. We analyzed two sets of transcriptomic data of SARS-CoV-2 infection obtained from lung epithelium cells and PBMCs, and two sets of T2D data from pancreatic islet cells and PBMCs to identify the associated differentially expressed genes (DEGs) followed by their functional enrichment analyses in terms of protein-protein interaction (PPI) to detect hub-proteins and associated comorbidities, transcription factors (TFs), microRNAs (miRNAs) as well as the potential drug candidates. In PPI analysis, four potential hub-proteins (i.e., BIRC3, C3, MME, and IL1B) were identified among 25 DEGs shared between the disease pair. Enrichment analyses using the mutually overlapped DEGs revealed the most prevalent GO and cell signalling pathways, including TNF signalling, cytokine-cytokine receptor interaction, and IL-17 signalling, which are related to cytokine activities. Furthermore, as significant TFs, we identified IRF1, KLF11, FOSL1, and CREB3L1 while miRNAs including miR-1-3p, 34a-5p, 16–5p, 155–5p, 20a-5p, and let-7b-5p were found to be noteworthy. The findings illustrated the significant association between COVID-19 and T2D at the molecular level. These genetic determinants can further be explored for their specific roles in disease progression and therapeutic intervention, while significant pathways can also be studied as molecular checkpoints. Finally, the identified drug candidates may be evaluated for their potency to minimize the severity of COVID-19 patients with pre-existing T2D.

Effects of Bergamot Polyphenols on Mitochondrial Dysfunction and Sarcoplasmic Reticulum Stress in Diabetic Cardiomyopathy

Cardiovascular disease is the leading cause of death and disability in the Western world. In order to safeguard the structure and the functionality of the myocardium, it is extremely important to adequately support the cardiomyocytes. Two cellular organelles of cardiomyocytes are essential for cell survival and to ensure proper functioning of the myocardium: mitochondria and the sarcoplasmic reticulum. Mitochondria are responsible for the energy metabolism of the myocardium, and regulate the processes that can lead to cell death. The sarcoplasmic reticulum preserves the physiological concentration of the calcium ion, and triggers processes to protect the structural and functional integrity of the proteins. The alterations of these organelles can damage myocardial functioning. A proper nutritional balance regarding the intake of macronutrients and micronutrients leads to a significant improvement in the symptoms and consequences of heart disease. In particular, the Mediterranean diet, characterized by a high consumption of plant-based foods, small quantities of red meat, and high quantities of olive oil, reduces and improves the pathological condition of patients with heart failure. In addition, nutritional support and nutraceutical supplementation in patients who develop heart failure can contribute to the protection of the failing myocardium. Since polyphenols have numerous beneficial properties, including anti-inflammatory and antioxidant properties, this review gathers what is known about the beneficial effects of polyphenol-rich bergamot fruit on the cardiovascular system. In particular, the role of bergamot polyphenols in mitochondrial and sarcoplasmic dysfunctions in diabetic cardiomyopathy is reported.

Bioinformatics and system biology approach to identify the influences of COVID-19 on cardiovascular and hypertensive comorbidities

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected individuals that have hypertension or cardiovascular comorbidities have an elevated risk of serious coronavirus disease 2019 (COVID-19) disease and high rates of mortality but how COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document} and cardiovascular diseases interact are unclear. We therefore sought to identify novel mechanisms of interaction by identifying genes with altered expression in SARS-CoV-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$2$\end{document} infection that are relevant to the pathogenesis of cardiovascular disease and hypertension. Some recent research shows the SARS-CoV-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$2$\end{document} uses the angiotensin converting enzyme-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$2$\end{document} (ACE-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$2$\end{document}) as a receptor to infect human susceptible cells. The ACE2 gene is expressed in many human tissues, including intestine, testis, kidneys, heart and lungs. ACE2 usually converts Angiotensin I in the renin–angiotensin-aldosterone system to Angiotensin II, which affects blood pressure levels. ACE inhibitors prescribed for cardiovascular disease and hypertension may increase the levels of ACE-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$2$\end{document}, although there are claims that such medications actually reduce lung injury caused by COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document}. We employed bioinformatics and systematic approaches to identify such genetic links, using messenger RNA data peripheral blood cells from COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document} patients and compared them with blood samples from patients with either chronic heart failure disease or hypertensive diseases. We have also considered the immune response genes with elevated expression in COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document} to those active in cardiovascular diseases and hypertension. Differentially expressed genes (DEGs) common to COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document} and chronic heart failure, and common to COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document} and hypertension, were identified; the involvement of these common genes in the signalling pathways and ontologies studied. COVID-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$19$\end{document} does not share a large number of differentially expressed genes with the conditions under consideration. However, those that were identified included genes playing roles in T cell functions, toll-like receptor pathways, cytokines, chemokines, cell stress, type 2 diabetes and gastric cancer. We also identified protein–protein interactions, gene regulatory networks and suggested drug and chemical compound interactions using the differentially expressed genes. The result of this study may help in identifying significant targets of treatment that can combat the ongoing pandemic due to SARS-CoV-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$2$\end{document} infection.