Multi-level transcriptome sequencing identifies COL1A1 as a candidate marker in human heart failure progression

Suppression of RCAN1 alleviated lipid accumulation and mitochondrial fission in diabetic cardiomyopathy

BACKGROUND

Although metabolic disturbance is a characteristic of diabetic cardiomyopathy (DbCM), the detailed pathogenesis of DbCM remains unknown.

METHODS

We used a heart transplantation (HTx) cohort to explore the effect of diabetes mellitus on heart failure (HF) progression dependent of myocardium. Microscopic and ultramicroscopic pathology were used to depict the pathological features of human myocardium of DbCM. We performed targeted metabolomics to characterize the metabolic phenotype of human DbCM. Transcriptomics data were analyzed and weighted gene co-expression network analysis was performed to explore the potential upstream regulator for metabolic remodeling of DbCM. In vivo and in vitro experiments were further conducted to demonstrate the therapeutic effects and molecular mechanisms.

RESULTS

DbCM promoted the progression of HF and increased death or HF-rehospitalization after HTx. Lipid accumulation and mitochondrial fission were the obvious pathological features of DbCM myocardium. The concentrations of C14:0-CoA and C16:1-CoA were significantly increased in the myocardium, and they were positively correlated with the accelerated HF progression and RCAN1 expression in DbCM patients. Knockdown of RCAN1 improved cardiac dysfunction, lipid accumulation, and mitochondrial fission in db/db mice. In vitro studies showed that RCAN1 knockdown improved mitochondrial dysfunction in DbCM cardiomyocytes via the RCAN1-p-Drp1 Ser616 axis.

CONCLUSIONS

Diabetes is associated with faster progression of HF and causes poor prognosis after HTx, accompanied by metabolic remodeling in the myocardium. Accumulation of long chain acyl-CoA in the myocardium is the metabolic hallmark of human DbCM and is associated with more rapid disease progression for DbCM patients. Upregulation of RCAN1 in the myocardium is associated with the metabolic signatures of DbCM and RCAN1 is a potential therapeutic target for DbCM.

Therapeutic Potential of Natural Compounds Acting through Epigenetic Mechanisms in Cardiovascular Diseases: Current Findings and Future Directions

Cardiovascular diseases (CVDs) remain a leading global cause of morbidity and mortality. These diseases have a multifaceted nature being influenced by a multitude of biochemical, genetic, environmental, and behavioral factors. Epigenetic modifications have a crucial role in the onset and progression of CVD. Epigenetics, which regulates gene activity without altering the DNA's primary structure, can modulate cardiovascular homeostasis through DNA methylation, histone modification, and non-coding RNA regulation. The effects of environmental stimuli on CVD are mediated by epigenetic changes, which can be reversible and, hence, are susceptible to pharmacological interventions. This represents an opportunity to prevent diseases by targeting harmful epigenetic modifications. Factors such as high-fat diets or nutrient deficiencies can influence epigenetic enzymes, affecting fetal growth, metabolism, oxidative stress, inflammation, and atherosclerosis. Recent studies have shown that plant-derived bioactive compounds can modulate epigenetic regulators and inflammatory responses, contributing to the cardioprotective effects of diets. Understanding these nutriepigenetic effects and their reversibility is crucial for developing effective interventions to combat CVD. This review delves into the general mechanisms of epigenetics, its regulatory roles in CVD, and the potential of epigenetics as a CVD therapeutic strategy. It also examines the role of epigenetic natural compounds (ENCs) in CVD and their potential as intervention tools for prevention and therapy.

Regulation of cardiac fibrosis in mice with TAC/DOCA-induced HFpEF by resistin-like molecule gamma and adenylate cyclase 1

Heart failure with preserved ejection fraction (HFpEF) is one of the major subtypes of heart failure (HF) and no effective treatments for this common disease exist to date. Cardiac fibrosis is central to the pathology of HF and a potential avenue for the treatment of HFpEF. To explore key fibrosis-related genes and pathways in the pathophysiological process of HFpEF, a mouse model of HFpEF was constructed. The relevant gene expression profiles were downloaded from the Gene Expression Omnibus database, and single-sample Gene Set Enrichment Analysis (ssGSEA) was performed targeting fibrosis-related pathways to explore differentially expressed genes (DEGs) in healthy control and HFpEF heart tissues with cross-tabulation analysis of fibrosis-related genes. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the identified fibrosis-related genes. The two most significant DEGs were selected, and further validation was conducted in HFpEF mice. The results indicated that myocardial fibrosis was significantly upregulated in HFpEF mice compared to healthy controls, while the ssGSEA results revealed significant differences in the enrichment of nine fibrosis-related pathways in HFpEF myocardial tissue, with 112 out of 798 DEGs being related to fibrosis. The in vivo results demonstrated that expression levels of resistin-like molecule gamma (Relmg) and adenylate cyclase 1 (Adcy1) in the heart tissues of HFpEF mice were significantly higher and lower, respectively, compared to healthy controls. Taken together, these results suggest that Relmg and Acdy1 as well as the fibrosis process may be potential targets for HFpEF treatment.

Prognostic value of a disintegrin and metalloproteinase Domain-8 in heart failure

Background

Heart failure (HF) is a severe disease threatening people's health. The aim of this study is to find a significant biomarker inducive to predicting the prognosis of HF.

Methods

GSE135055 and GSE161472 datasets were reanalyzed for exploring key genes related to HF. This single-center, prospective, observational cohort study enrolled 298 patients with or without HF from the Cardiology Department of Zhongda Hospital. Levels of ADAM8 were measured using ELISA kits. Major adverse cardiovascular events (MACEs) were defined as the composite end points of the first occurrence of rehospitalization because of HF or cardiac-related death during one-year follow-up.

Results

(1) Bioinformatics analysis showed that ADAM8 was a key gene in HF via mainly regulating the mechanisms of extracellular matrix (ECM) organization. (2) Levels of ADAM8 were significantly increased in the HF group, compared to the non-failing (NF) group (p < 0.001), especially in patients with HFrEF (p < 0.05), and HFmEF (p < 0.05). The prevalence of HF in the high ADAM8 group (≧472.916 pg/mL) was significantly higher than in the low ADAM8 group (<472.916 pg/mL) (41.95 % vs 30.54 %, p < 0.01). (3) Correlation analysis revealed that ADAM8 was negatively correlated to the left ventricular ejection fraction (LVEF) (r = -0.272, p < 0.001). ROC analysis showed that the AUC of ADAM8 in predicting HF and predicting the MACE were 0.701 (p < 0.0001) and 0.683 (p < 0.0001), respectively. (4) Logistic and Cox regression both indicated that high ADAM8 expression can predict adverse prognosis of HF.

Conclusions

ADAM8 may be a risk factor for HF, especially in cases of HFrEF and HFmEF. High ADAM8 expression in plasma was related to the decreased heart function, and can predict the adverse prognosis of HF.

Using Omics to Identify Novel Therapeutic Targets in Heart Failure

Omics refers to the measurement and analysis of the totality of molecules or biological processes involved within an organism. Examples of omics data include genomics, transcriptomics, epigenomics, proteomics, metabolomics, and more. In this review, we present the available literature reporting omics data on heart failure that can inform the development of novel treatments or innovative treatment strategies for this disease. This includes polygenic risk scores to improve prediction of genomic data and the potential of multiomics to more efficiently identify potential treatment targets for further study. We also discuss the limitations of omic analyses and the barriers that must be overcome to maximize the utility of these types of studies. Finally, we address the current state of the field and future opportunities for using multiomics to better personalize heart failure treatment strategies.

Identification of Potential lncRNA-miRNA-mRNA Regulatory Network Contributing to Arrhythmogenic Right Ventricular Cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) can lead to sudden cardiac death and life-threatening heart failure. Due to its high fatality rate and limited therapies, the pathogenesis and diagnosis biomarker of ARVC needs to be explored urgently. This study aimed to explore the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network in ARVC. The mRNA and lncRNA expression datasets obtained from the Gene Expression Omnibus (GEO) database were used to analyze differentially expressed mRNA (DEM) and lncRNA (DElnc) between ARVC and non-failing controls. Differentially expressed miRNAs (DEmiRs) were obtained from the previous profiling work. Using starBase to predict targets of DEmiRs and intersecting with DEM and DElnc, a ceRNA network of lncRNA-miRNA-mRNA was constructed. The DEM and DElnc were validated by real-time quantitative PCR in human heart tissue. Protein-protein interaction network and weighted gene co-expression network analyses were used to identify hub genes. A logistic regression model for ARVC diagnostic prediction was established with the hub genes and their ceRNA pairs in the network. A total of 448 DEMs (282 upregulated and 166 downregulated) were identified, mainly enriched in extracellular matrix and fibrosis-related GO terms and KEGG pathways, such as extracellular matrix organization and collagen fibril organization. Four mRNAs and two lncRNAs, including COL1A1, COL5A1, FBN1, BGN, XIST, and LINC00173 identified through the ceRNA network, were validated by real-time quantitative PCR in human heart tissue and used to construct a logistic regression model. Good ARVC diagnostic prediction performance for the model was shown in both the training set and the validation set. The potential lncRNA-miRNA-mRNA regulatory network and logistic regression model established in our study may provide promising diagnostic methods for ARVC.

Identification of shared molecular mechanisms and diagnostic biomarkers between heart failure and idiopathic pulmonary fibrosis

Background

Heart failure (HF) and idiopathic pulmonary fibrosis (IPF) are global public health concerns. The relationship between HF and IPF is widely acknowledged. However, the interaction mechanisms between these two diseases remain unclear, and early diagnosis is particularly difficult. Through the integration of bioinformatics and machine learning, our work aims to investigate common gene features, putative molecular causes, and prospective diagnostic indicators of IPF and HF.

Methods

The Gene Expression Omnibus (GEO) database provided the RNA-seq datasets for HF and IPF. Utilizing a weighted gene co-expression network analysis (WGCNA), possible genes linked to HF and IPF were found. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were then employed to analyze the genes that were shared by HF and IPF. Using the cytoHubba and iRegulon algorithms, a competitive endogenous RNA (ceRNA) network was built based on seven basic diagnostic indicators. Additionally, hub genes were identified using machine learning approaches. External datasets were used to validate the findings. Lastly, the association between the number of immune cells in tissues and the discovered genes was estimated using the CIBERSORT method.

Results

In total, 63 shared genes were identified between HF- and IPF-related modules using WGCNA. Extracellular matrix (ECM)/structure organization, ECM-receptor interactions, focal, and protein digestion and absorption, were shown to be the most enrichment categories in GO and KEGG enrichment analysis of common genes. Furthermore, a total of seven fundamental genes, including COL1A1, COL3A1, THBS2, CCND1, ASPN, FAP, and S100A12, were recognized as pivotal genes implicated in the shared pathophysiological pathways of HF and IPF, and TCF12 may be the most important regulatory transcription factor. Two characteristic molecules, CCND1 and NAP1L3, were selected as potential diagnostic markers for HF and IPF, respectively, using a support vector machine-recursive feature elimination (SVM-RFE) model. Furthermore, the development of diseases and diagnostic markers may be associated with immune cells at varying degrees.

Conclusions

This study demonstrated that ECM/structure organisation, ECM-receptor interaction, focal adhesion, and protein digestion and absorption, are common pathogeneses of IPF and HF. Additionally, CCND1 and NAP1L3 were identified as potential diagnostic biomarkers for both HF and IPF. The results of our study contribute to the comprehension of the co-pathogenesis of HF and IPF at the genetic level and offer potential biological indicators for the early detection of both conditions.

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here, we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and OVOL2, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy and discovered a role for IL2 STAT5 signaling in heart failure. Our findings underscore the importance of TF activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

Identification of cuproptosis-related genes and immune infiltration in dilated cardiomyopathy

BACKGROUND

Dilated cardiomyopathy (DCM) is a leading cause of heart failure. Cuproptosis is involved in various diseases, although its role in DCM is still unclear. Here, this study aims to investigate the feasibility of using genes related to cuproptosis as diagnostic biomarkers for DCM and the association of their expression with immune infiltration and drug target in cardiac tissue.

METHODS

Gene expression data from nonfailure (NF) and DCM samples were retrieved from the GEO database. Cuproptosis scores were calculated using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was used to screen key modules associated with DCM and cuproptosis. Random forest and least absolute shrinkage and selection operator (LASSO) were applied to identify signature genes. Finally, immune cell infiltration was assessed using ssGSEA. mRNA-miRNA-lncRNA regulatory networks and chemical-drug regulatory networks based on signature genes were analyzed by Cytoscape.

RESULTS

8 modules were aggregated by WGCNA, among which MEblue was significantly associated with cuproptosis scores and DCM. A diagnostic model made up of six signature genes including SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1 was selected. Furthermore, immune infiltration studies showed significant differences between DCM and NF. Drugs networks and ceRNA regulatory network based on six signature genes were successfully constructed.

CONCLUSION

Six signature genes (SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1) were identified as novel diagnostic biomarkers in DCM. In addition, the expression of these genes was associated with immune cell infiltration, suggesting that cuproptosis may be involved in the immune regulation of DCM.

Integrated analysis reveals the dysfunction of intercellular communication and metabolic signals in dilated cardiomyopathy

Aims

Dilated cardiomyopathy refers to a heart muscle condition characterized by structural and functional irregularities in the myocardium that are not related to ischemia. Due to diverse etiologies such as genetic mutations, infections, and exposure to toxins, dilated cardiomyopathy can lead to substantial morbidity and mortality despite advances in the management of heart failure in dilated cardiomyopathy patients. We sought to analyze the characteristics of cell-cell communication and the metabolic signaling pathways in dilated cardiomyopathy.

Methods and results

The single-nucleus sequencing data of left ventricle samples were acquired from two donor datasets and two dilated cardiomyopathy datasets. Three dilated cardiomyopathy bulk-sequencing datasets were included to determine the shared dilated cardiomyopathy-specific alterations in differentially expressed genes and signaling pathways. Using "CellChat," we analyzed intercellular communication to grasp how cell clusters interact and to map out the impaired signaling pathways in both donor and dilated cardiomyopathy conditions. Gene set enrichment analysis was applied to compare the metabolic signaling before and after dilated cardiomyopathy. We showcased how cell clusters exhibited abnormal cell-to-cell signaling transduction and how each cell type displayed dysfunctional metabolic signaling pathways through the integration of various datasets. The crucial ligand-receptor signaling contributing to outgoing or incoming signaling of dilated cardiomyopathy was identified in a cell-type dependent way, and the cell-specific metabolic alterations in glucose, lipid and amino acid were determined. The expression of gene pairs in BMP and NOTCH signal, as well as the gene expression in the arginine metabolism was validated.

Conclusions

We reveal the key signals and metabolic pathways for dilated cardiomyopathy adaptation and maintenance, providing potential targets for dilated cardiomyopathy interference.

Molybdenum exposure induces inflammatory response via the regulatory effects of lncRNA-00072124/miR-308/OSMR crosstalk on JAK/STAT axis in duck kidneys

Molybdenum (Mo) is an essential nutrient in living organisms. Although numerous researchers have noticed the health damage caused by excessive Mo, the underlying mechanism of excessive Mo-induced nephrotoxicity remains poorly understood. A gene crosstalk called competitive endogenous RNAs (ceRNAs) can interpret many regulatory mechanisms molecularly. But there are few researches have tried to explain the damage mechanism of excess Mo to organisms through ceRNAs network. To clarify this, the study explored the changes in lncRNAs and miRNAs expression profiles in the kidney of ducks exposed to excess Mo for 16 weeks. The sequencing results showed that Mo exposure caused differential expression of 144 lncRNAs and 14 miRNAs. The occurrence of inflammation through the JAK/STAT axis was observed and the lncRNA-00072124/miR-308/OSMR axis was verified by a double luciferase reporter assay. Overexpression of miR-308 and RNA interference of OSMR reduced Mo-induced inflammatory factors, while miR-308 knockdown showed the opposite effect. Simultaneously, lncRNA-00072124 affected OSMR function as a ceRNA. Taken together, these results concluded that Mo exposure activated the JAK/STAT axis and induced inflammation mediated by the lncRNA-00072124/miR-308/OSMR crosstalk. The results might provide new views for revealing the toxic effects of excess Mo in duck kidneys.

Identifying OGN as a Biomarker Covering Multiple Pathogenic Pathways for Diagnosing Heart Failure: From Machine Learning to Mechanism Interpretation

BACKGROUND

The pathophysiologic heterogeneity of heart failure (HF) necessitates a more detailed identification of diagnostic biomarkers that can reflect its diverse pathogenic pathways.

METHODS

We conducted weighted gene and multiscale embedded gene co-expression network analysis on differentially expressed genes obtained from HF and non-HF specimens. We employed a machine learning integration framework and protein-protein interaction network to identify diagnostic biomarkers. Additionally, we integrated gene set variation analysis, gene set enrichment analysis (GSEA), and transcription factor (TF)-target analysis to unravel the biomarker-dominant pathways. Leveraging single-sample GSEA and molecular docking, we predicted immune cells and therapeutic drugs related to biomarkers. Quantitative polymerase chain reaction validated the expressions of biomarkers in the plasma of HF patients. A two-sample Mendelian randomization analysis was implemented to investigate the causal impact of biomarkers on HF.

RESULTS

We first identified COL14A1, OGN, MFAP4, and SFRP4 as candidate biomarkers with robust diagnostic performance. We revealed that regulating biomarkers in HF pathogenesis involves TFs (BNC2, MEOX2) and pathways (cell adhesion molecules, chemokine signaling pathway, cytokine-cytokine receptor interaction, oxidative phosphorylation). Moreover, we observed the elevated infiltration of effector memory CD4+ T cells in HF, which was highly related to biomarkers and could impact immune pathways. Captopril, aldosterone antagonist, cyclopenthiazide, estradiol, tolazoline, and genistein were predicted as therapeutic drugs alleviating HF via interactions with biomarkers. In vitro study confirmed the up-regulation of OGN as a plasma biomarker of HF. Mendelian randomization analysis suggested that genetic predisposition toward higher plasma OGN promoted the risk of HF.

CONCLUSIONS

We propose OGN as a diagnostic biomarker for HF, which may advance our understanding of the diagnosis and pathogenesis of HF.

Compound AC1Q3QWB upregulates CDKN1A and SOX17 by interrupting the HOTAIR-EZH2 interaction and enhances the efficacy of tazemetostat in endometrial cancer

Endometrial cancer (EC) is a common malignancy of the female reproductive system, with an escalating incidence. Recurrent/metastatic EC presents a poor prognosis. The interaction between the long non-coding RNA (lncRNA) HOTAIR and the polycomb repressive complex 2 (PRC2) induces abnormal silencing of tumor suppressor genes, exerting a pivotal role in tumorigenesis. We have previously discovered AC1Q3QWB (AQB), a small-molecule compound targeting HOTAIR-EZH2 interaction. In the present study, we unveil that AQB selectively hampers the interaction between HOTAIR and EZH2 within EC cells, thus reversing the epigenetic suppression of tumor suppressor genes. Furthermore, our findings demonstrate AQB's synergistic effect with tazemetostat (TAZ), an EZH2 inhibitor, significantly boosting the expression of CDKN1A and SOX17. This, in turn, induces cell cycle arrest and impedes EC cell proliferation, migration, and invasion. In vivo experiments further validate AQB's potential by enhancing TAZ's anti-tumor efficacy at lower doses. Our results advocate AQB, a recently discovered small-molecule inhibitor, as a promising agent against EC cells. When combined with TAZ, it offers a novel therapeutic strategy for EC treatment.

Distinctive biochemistry profiles associated with hyperuricemia between Tibetans and Hans in China

Purpose

We sought to identify distinct risk factors for hyperuricemia in native Tibetan and immigrant Han populations in Tibet, China.

Methods

Three cohorts of male participants aged between 20 and 40 years were enrolled in this study. Biochemical parameters including serum uric acid (UA), fasting plasma glucose, insulin, lactate dehydrogenase (LDH), thyroxin, blood cell count, aminotransferase, and lipid profiles were analyzed. The association of risk factors with UA levels was evaluated using a multivariable line regression model. The effect of UA level on the biochemical parameters between the Hans and Tibetans was evaluated by two-way ANOVA.

Results

The prevalence of hyperuricemia (≥420 μmol/L) was 24.8% (62/250) in the Hans, similar to 23.8% (29/136) in the Tibetans. In the regression analysis, the risk factors that were significantly associated with UA in Hans did not apply to Tibetans. Tibetans had higher fasting insulin (P<0.05) and LDH (P<0.01) levels, in contrast with lower levels of triglycerides (P<0.05), total cholesterol (P<0.01), and low-density lipoprotein-cholesterol (P<0.01) than Hans in normal UA populations. Biochemistry analysis revealed lower albumin levels (P<0.001) and higher levels of all aminotransaminase and especially alkaline phosphatase (P<0.01) in Tibetans than in Hans in both populations. Compared with Hans, Tibetans had lower serum levels of urea, creatinine, and electrolytes in the normal UA population, which were further exacerbated in the high UA population. Tibetans had comparable white blood cell counts as Hans in both normal and high UA populations. In contrast, the red blood cell count and hemoglobin concentration were much lower in Tibetans than in Hans under high UA conditions.

Conclusions

The distinctive biochemistry between Tibetans and Hans may underlie the different etiologies of hyperuricemia in Tibet, China.

Plasma type I collagen α1 chain in relation to coronary artery disease: findings from a prospective population-based cohort and an acute myocardial infarction prospective cohort in Sweden

OBJECTIVES

To investigate the association between type I collagen α1 chain (COL1α1) levels and coronary artery disease (CAD) by using absolute quantification in plasma. Also, to investigate the correlates of COL1α1 to clinical characteristics and circulating markers of collagen metabolism.

DESIGN

Life conditions, Stress and Health (LSH) study: prospective cohort study, here with a nested case-control design.Assessing Platelet Activity in Coronary Heart Disease (APACHE) study: prospective cohort study.

SETTING

LSH: primary care setting, southeast Sweden.APACHE: cardiology department, university hospital, southeast Sweden.

PARTICIPANTS

LSH: 1007 randomly recruited individuals aged 45-69 (50% women). Exclusion criteria was serious disease. After 13 years of follow-up, 86 cases with primary endpoint were identified and sex-matched/age-matched to 184 controls.

APACHE

125 patients with myocardial infarction (MI), 73 with ST-elevation MI and 52 with non-ST-elevation MI.

EXCLUSION CRITERIA

Intervention study participation, warfarin treatment and short life expectancy.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcome was the association between baseline COL1α1 and first-time major event of CAD, defined as fatal/non-fatal MI or coronary revascularisation after 13 years. Secondary outcomes were the association between the collagen biomarkers PRO-C1 (N-terminal pro-peptide of type I collagen)/C1M (matrix metalloproteinase-mediated degradation of type I collagen) and CAD; temporal change of COL1α1 after acute MI up to 6 months and lastly, correlates between COL1α1 and patient characteristics along with circulating markers of collagen metabolism.

RESULTS

COL1α1 levels were associated with CAD, both unadjusted (HR=0.69, 95% CI=0.56 to 0.87) and adjusted (HR=0.55, 95% CI=0.41 to 0.75). PRO-C1 was associated with CAD, unadjusted (HR=0.62, 95% CI=0.47 to 0.82) and adjusted (HR=0.61, 95% CI=0.43 to 0.86), while C1M was not. In patients with MI, COL1α1 remained unchanged up to 6 months. COL1α1 was correlated to PRO-C1, but not to C1M.

CONCLUSIONS

Plasma COL1α1 was independently and inversely associated with CAD. Furthermore, COL1α1 appeared to reflect collagen synthesis but not degradation. Future studies are needed to confirm whether COL1α1 is a clinically useful biomarker of CAD.

STING regulates the transformation of the proinflammatory macrophage phenotype by HIF1A into autoimmune myocarditis

Macrophages play an essential role in the pathogenesis of autoimmune myocarditis, but the molecular mechanism remains largely unknown. Here, the role of Stimulator of interferon gene (Sting) in autoimmune myocarditis was investigated. Six-week-old male BALB/c mice received two subcutaneous injections of 250 μg α-MyHC peptide to establish experimental autoimmune myocarditis (EAM). With single-cell RNA sequencing analysis of cardiac immune (Cd45+) cells, Sting was found to initiate proinflammatory macrophage differentiation related to the acute EAM phase. Furthermore, proinflammatory macrophages contribute to the pathogenesis of EAM via hypoxia-inducible factor-1α (Hif1α). A higher expression level of Sting was detected in macrophages from myocarditis, which was positively correlated with Hif1α expression. Single-stranded DNA (ssDNA) accumulation in macrophages in myocarditis was observed in the hearts of EAM mice. Pharmacological blockade of STING by C-176 (a specific inhibitor) ameliorated the inflammatory response of EAM and reduced proinflammatory molecule (Ifn-β, Tnf-α, Ccl2, and F4/80) expression and Hif1α expression. In vitro studies revealed that ssDNA activated the expression of Sting; in turn, Sting accelerated proinflammatory molecule expression in mouse macrophages. Inhibition of Hif1α expression could reduce Sting-associated cardiac inflammation and proinflammatory molecule expression. In addition, the expression of STING and ssDNA accumulation in macrophages were observed in human autoimmune myocarditis heart samples. STING activated proinflammatory macrophage via HIF1A, promoting the development of autoimmune myocarditis. The STING signaling pathway might provide a novel mechanism of autoimmune myocarditis and serve as a potential therapeutic target for autoimmune myocarditis patients.

Targeting gut microbiota-derived kynurenine to predict and protect the remodeling of the pressure-overloaded young heart

Pressure-overloaded left ventricular remodeling in young population is progressive and readily degenerate into heart failure. The aims of this study were to identify a plasma metabolite that predicts and is mechanistically linked to the disease. Untargeted metabolomics determined elevated plasma kynurenine (Kyn) in both the patient cohorts and the mice model, which was correlated with remodeling parameters. In vitro and in vivo evidence, combined with single-nucleus RNA sequencing (snRNA-seq), demonstrated that Kyn affected both cardiomyocytes and cardiac fibroblasts by activating aryl hydrocarbon receptors (AHR) to up-regulate hypertrophy- and fibrosis-related genes. Shotgun metagenomics and fecal microbiota transplantation revealed the existence of the altered gut microbiota-Kyn relationship. Supplementation of selected microbes reconstructed the gut microbiota, reduced plasma Kyn, and alleviated ventricular remodeling. Our data collectively discovered a gut microbiota-derived metabolite to activate AHR and its gene targets in remodeling young heart, a process that could be prevented by specific gut microbiota modulation.

Myocardial fibrosis and calcification are attenuated by microRNA-129-5p targeting Asporin and Sox9 in cardiac fibroblasts

Myocardial fibrosis and calcification associate with adverse outcomes in nonischemic heart failure. Cardiac fibroblasts (CF) transition into myofibroblasts (MF) and osteogenic fibroblasts (OF) to promote myocardial fibrosis and calcification. However, common upstream mechanisms regulating both CF-to-MF transition and CF-to-OF transition remain unknown. microRNAs are promising targets to modulate CF plasticity. Our bioinformatics revealed downregulation of miR-129-5p and upregulation of its targets small leucine-rich proteoglycan Asporin (ASPN) and transcription factor SOX9 as common in mouse and human heart failure (HF). We experimentally confirmed decreased miR-129-5p and enhanced SOX9 and ASPN expression in CF in human hearts with myocardial fibrosis and calcification. miR-129-5p repressed both CF-to-MF and CF-to-OF transition in primary CF, as did knockdown of SOX9 and ASPN. Sox9 and Aspn are direct targets of miR-129-5p that inhibit downstream β-catenin expression. Chronic Angiotensin II infusion downregulated miR-129-5p in CF in WT and TCF21-lineage CF reporter mice, and it was restored by miR-129-5p mimic. Importantly, miR-129-5p mimic not only attenuated progression of myocardial fibrosis, calcification marker expression, and SOX9 and ASPN expression in CF but also restored diastolic and systolic function. Together, we demonstrate miR-129-5p/ASPN and miR-129-5p/SOX9 as potentially novel dysregulated axes in CF-to-MF and CF-to-OF transition in myocardial fibrosis and calcification and the therapeutic relevance of miR-129-5p.

Data resources and computational methods for lncRNA-disease association prediction

Increasing interest has been attracted in deciphering the potential disease pathogenesis through lncRNA-disease association (LDA) prediction, regarding to the diverse functional roles of lncRNAs in genome regulation. Whilst, computational models and algorithms benefit systematic biology research, even facilitate the classical biological experimental procedures. In this review, we introduce representative diseases associated with lncRNAs, such as cancers, cardiovascular diseases, and neurological diseases. Current publicly available resources related to lncRNAs and diseases have also been included. Furthermore, all of the 64 computational methods for LDA prediction have been divided into 5 groups, including machine learning-based methods, network propagation-based methods, matrix factorization- and completion-based methods, deep learning-based methods, and graph neural network-based methods. The common evaluation methods and metrics in LDA prediction have also been discussed. Finally, the challenges and future trends in LDA prediction have been discussed. Recent advances in LDA prediction approaches have been summarized in the GitHub repository at https://github.com/sheng-n/lncRNA-disease-methods.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

BACKGROUND

Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.

METHODS

We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.

RESULTS

A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).

CONCLUSIONS

This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Subtyping based on immune cell fractions reveal heterogeneity of cardiac fibrosis in end-stage heart failure

Background

A central issue hindering the development of effective anti-fibrosis drugs for heart failure is the unclear interrelationship between fibrosis and the immune cells. This study aims at providing precise subtyping of heart failure based on immune cell fractions, elaborating their differences in fibrotic mechanisms, and proposing a biomarker panel for evaluating intrinsic features of patients' physiological statuses through subtype classification, thereby promoting the precision medicine for cardiac fibrosis.

Methods

We inferred immune cell type abundance of the ventricular samples by a computational method (CIBERSORTx) based on ventricular tissue samples from 103 patients with heart failure, and applied K-means clustering to divide patients into two subtypes based on their immune cell type abundance. We also designed a novel analytic strategy: Large-Scale Functional Score and Association Analysis (LAFSAA), to study fibrotic mechanisms in the two subtypes.

Results

Two subtypes of immune cell fractions: pro-inflammatory and pro-remodeling subtypes, were identified. LAFSAA identified 11 subtype-specific pro-fibrotic functional gene sets as the basis for personalised targeted treatments. Based on feature selection, a 30-gene biomarker panel (ImmunCard30) established for diagnosing patient subtypes achieved high classification performance, with the area under the receiver operator characteristic curve corresponding to 0.954 and 0.803 for the discovery and validation sets, respectively.

Conclusion

Patients with the two subtypes of cardiac immune cell fractions were likely having different fibrotic mechanisms. Patients' subtypes can be predicted based on the ImmunCard30 biomarker panel. We envision that our unique stratification strategy revealed in this study will unravel advance diagnostic techniques for personalised anti-fibrotic therapy.

An integrated proteomic and transcriptomic signature of the failing right ventricle in monocrotaline induced pulmonary arterial hypertension in male rats

Aim: Pulmonary arterial hypertension (PAH) is an obstructive pulmonary vasculopathy that results in death from right ventricular failure (RVF). There is limited understanding of the molecular mechanisms of RVF in PAH. Methods: In a PAH-RVF model induced by injection of adult male rats with monocrotaline (MCT; 60 mg/kg), we performed mass spectrometry to identify proteins that change in the RV as a consequence of PAH induced RVF. Bioinformatic analysis was used to integrate our previously published RNA sequencing data from an independent cohort of PAH rats. Results: We identified 1,277 differentially regulated proteins in the RV of MCT rats compared to controls. Integration of MCT RV transcriptome and proteome data sets identified 410 targets that are concordantly regulated at the mRNA and protein levels. Functional analysis of these data revealed enriched functions, including mitochondrial metabolism, cellular respiration, and purine metabolism. We also prioritized 15 highly enriched protein:transcript pairs and confirmed their biological plausibility as contributors to RVF. We demonstrated an overlap of these differentially expressed pairs with data published by independent investigators using multiple PAH models, including the male SU5416-hypoxia model and several male rat strains. Conclusion: Multiomic integration provides a novel view of the molecular phenotype of RVF in PAH which includes dysregulation of pathways involving purine metabolism, mitochondrial function, inflammation, and fibrosis.

Identification of hub genes and transcription factor regulatory network for heart failure using RNA-seq data and robust rank aggregation analysis

Background

Heart failure (HF) is the end stage of various cardiovascular diseases with a high mortality rate. Novel diagnostic and therapeutic biomarkers for HF are urgently required. Our research aims to identify HF-related hub genes and regulatory networks using bioinformatics and validation assays.

Methods

Using four RNA-seq datasets in the Gene Expression Omnibus (GEO) database, we screened differentially expressed genes (DEGs) of HF using Removal of Unwanted Variation from RNA-seq data (RUVSeq) and the robust rank aggregation (RRA) method. Then, hub genes were recognized using the STRING database and Cytoscape software with cytoHubba plug-in. Furthermore, reliable hub genes were validated by the GEO microarray datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR) using heart tissues from patients with HF and non-failing donors (NFDs). In addition, R packages “clusterProfiler” and “GSVA” were utilized for enrichment analysis. Moreover, the transcription factor (TF)–DEG regulatory network was constructed by Cytoscape and verified in a microarray dataset.

Results

A total of 201 robust DEGs were identified in patients with HF and NFDs. STRING and Cytoscape analysis recognized six hub genes, among which ASPN, COL1A1, and FMOD were confirmed as reliable hub genes through microarray datasets and qRT-PCR validation. Functional analysis showed that the DEGs and hub genes were enriched in T-cell-mediated immune response and myocardial glucose metabolism, which were closely associated with myocardial fibrosis. In addition, the TF–DEG regulatory network was constructed, and 13 significant TF–DEG pairs were finally identified.

Conclusion

Our study integrated different RNA-seq datasets using RUVSeq and the RRA method and identified ASPN, COL1A1, and FMOD as potential diagnostic biomarkers for HF. The results provide new insights into the underlying mechanisms and effective treatments of HF.

Biomarker screening in preeclampsia: an RNA-sequencing approach based on data from multiple studies

OBJECTIVE

Biomarkers have become important in the prognosis and diagnosis of various diseases. High-throughput methods, such as RNA sequencing facilitate the detection of differentially expressed genes (DEGs), hence potential biomarker candidates. Individual studies suggest long lists of DEGs, hampering the identification of clinically relevant ones. Concerning preeclampsia - a major obstetric burden with high risk for adverse maternal and/or neonatal outcomes - limitations in diagnosis and prediction are still important issues. We, therefore, developed a workflow to facilitate the screening for biomarkers.

METHODS

On the basis of the tool DESeq2, a comprehensive workflow for identifying DEGs was established, analyzing data from several publicly available RNA-sequencing studies. We applied it to four RNA-sequencing datasets (one blood, three placenta) analyzing patients with preeclampsia and normotensive controls. We compared our results with other published approaches and evaluated their performance.

RESULTS

We identified 110 genes that are dysregulated in preeclampsia, observed in at least three of the studies analyzed, six even in all four studies. These included FLT-1, TREM-1, and FN1, which either represent established biomarkers at protein level, or promising candidates based on recent studies. For comparison, using a published meta-analysis approach, 5240 DEGs were obtained.

CONCLUSION

This study presents a data analysis workflow for preeclampsia biomarker screening, capable of identifying promising biomarker candidates, while drastically reducing the numbers of candidates. Moreover, we were also able to confirm its performance for heart failure. This approach can be applied to additional diseases for biomarker identification, and the set of DEGs identified in preeclampsia represents a resource for further studies.

Nonsteroidal Mineralocorticoid Receptor Antagonism by Finerenone—Translational Aspects and Clinical Perspectives across Multiple Organ Systems

Perception of the role of the aldosterone/mineralocorticoid receptor (MR) ensemble has been extended from a previously renal epithelial-centered focus on sodium and volume homeostasis to an understanding of their role as systemic modulators of reactive oxygen species, inflammation, and fibrosis. Steroidal MR antagonists (MRAs) are included in treatment paradigms for resistant hypertension and heart failure with reduced ejection fraction, while more recently, the nonsteroidal MRA finerenone was shown to reduce renal and cardiovascular outcomes in two large phase III trials (FIDELIO-DKD and FIGARO-DKD) in patients with chronic kidney disease and type 2 diabetes, respectively. Here, we provide an overview of the pathophysiologic role of MR overactivation and preclinical evidence with the nonsteroidal MRA finerenone in a range of different disease models with respect to major components of the aggregate mode of action, including interfering with reactive oxygen species generation, inflammation, fibrosis, and hypertrophy. We describe a time-dependent effect of these mechanistic components and the potential modification of major clinical parameters, as well as the impact on clinical renal and cardiovascular outcomes as observed in FIDELIO-DKD and FIGARO-DKD. Finally, we provide an outlook on potential future clinical indications and ongoing clinical studies with finerenone, including a combination study with a sodium–glucose cotransporter-2 inhibitor.

Analysis of transcriptomic responses to SARS-CoV-2 reveals plausible defective pathways responsible for increased susceptibility to infection and complications and helps to develop fast-track repositioning of drugs against COVID-19

Background

To understand the transcriptomic response to SARS-CoV-2 infection, is of the utmost importance to design diagnostic tools predicting the severity of the infection.

Methods

We have performed a deep sampling analysis of the viral transcriptomic data oriented towards drug repositioning. Using different samplers, the basic principle of this methodology the biological invariance, which means that the pathways altered by the disease, should be independent on the algorithm used to unravel them.

Results

The transcriptomic analysis of the altered pathways, reveals a distinctive inflammatory response and potential side effects of infection. The virus replication causes, in some cases, acute respiratory distress syndrome in the lungs, and affects other organs such as heart, brain, and kidneys. Therefore, the repositioned drugs to fight COVID-19 should, not only target the interferon signalling pathway and the control of the inflammation, but also the altered genetic pathways related to the side effects of infection. We also show via Principal Component Analysis that the transcriptome signatures are different from influenza and RSV. The gene COL1A1, which controls collagen production, seems to play a key/vital role in the regulation of the immune system. Additionally, other small-scale signature genes appear to be involved in the development of other COVID-19 comorbidities.

Conclusions

Transcriptome-based drug repositioning offers possible fast-track antiviral therapy for COVID-19 patients. It calls for additional clinical studies using FDA approved drugs for patients with increased susceptibility to infection and with serious medical complications.

Macrophages-Related Genes Biomarkers in the Deterioration of Atherosclerosis

Background

The macrophages are involved in all stages of cardiovascular diseases, demonstrating the correlation between inflammation, atherosclerosis, and myocardial infarction (MI). Here, we aim to investigate macrophages-related genes in the deterioration of atherosclerosis.

Methods

GSE41571 was downloaded and the abundance of immune cells was estimated by utilizing the xCell. By utilizing the limma test and correlation analysis, differentially expressed macrophages-related genes (DEMRGs) were documented. The functional pathways and the protein–protein interaction (PPI) network were analyzed and the hub DEMRGs were obtained. The hub DEMRGs and their interactions were analyzed using NetworkAnalyst 3.0 and for validation, the expressions of hub DEMRGs were analyzed using the GSE135055 and GSE116250 datasets as well as atherosclerosis and MI mice model.

Results

A total of 509 differentially expressed genes (DEGs) were correlated with the abundance of macrophages and were identified as DEMRGs (Pearson correlation coefficients (PCC) &gt; 0.6), which were mainly enriched in extracellular structure organization, lysosomal membrane, MHC protein complex binding, and so on. After screening out, 28 hub DEMRGs were obtained with degrees ≥20, including GNAI1 (degree = 113), MRPS2 (degree = 56), HCK (degree = 45), SOCS3 (degree = 40), NET1 (degree = 28), and so on. After validating using Gene Expression Omnibus (GEO) datasets and the atherosclerosis and MI mice model, eight proteins were validated using ApoE-/- and C57 mice. The expression levels of proteins, including SYNJ2, NET1, FZD7, LCP2, HCK, GNB2, and PPP4C were positively correlated to left ventricular ejection fraction (LVEF), while that of EIF4EBP1 was negatively correlated to LVEF.

Conclusion

The screened hub DEMRGs, SYNJ2, NET1, FZD7, LCP2, HCK, GNB2, EIF4EBP1, and PPP4C, may be therapeutic targets for treatment and prediction in the patients with plaque progression and MI recurrent events. The kit of the eight hub DEMRGs may test plaque progression and MI recurrent events and help in the diagnosis and treatment of MI-induced heart failure (HF), thus decreasing mortality and morbidity.

Epigenetic regulation in cardiovascular disease: mechanisms and advances in clinical trials

Epigenetics is closely related to cardiovascular diseases. Genome-wide linkage and association analyses and candidate gene approaches illustrate the multigenic complexity of cardiovascular disease. Several epigenetic mechanisms, such as DNA methylation, histone modification, and noncoding RNA, which are of importance for cardiovascular disease development and regression. Targeting epigenetic key enzymes, especially the DNA methyltransferases, histone methyltransferases, histone acetylases, histone deacetylases and their regulated target genes, could represent an attractive new route for the diagnosis and treatment of cardiovascular diseases. Herein, we summarize the knowledge on epigenetic history and essential regulatory mechanisms in cardiovascular diseases. Furthermore, we discuss the preclinical studies and drugs that are targeted these epigenetic key enzymes for cardiovascular diseases therapy. Finally, we conclude the clinical trials that are going to target some of these processes.

Single-cell transcriptomics identifies Col1a1 and Col1a2 as hub genes in obesity-induced cardiac fibrosis

Obesity is a risk factor for cardiovascular disease, leading to ventricular dysfunction and cardiac fibrosis, in which non-cardiomyocytes (nonCMs) play an important role. Early detection and treatment of heart illness may help to limit its progression. We screened for key markers of obesity-induced cardiac fibrosis using single-cell transcriptomics techniques. To begin, an obese mouse model was constructed using a high-fat diet. From a pathogenic perspective, pathological alterations in the obesity-induced heart were found. Differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed. Then, to look for hub genes, key modules of DEGs were built. Finally, the cellular location of the hub genes was investigated. In mice, a high-fat diet raised body weight, messed up myocardial shape, and increased cardiac collagen content. NonCMs transcriptome data revealed 15 different cell types, including fibroblasts, immunological cells, and endothelial cells. There were a total of 33 DEGs found, with 22 up-regulated genes and 11 down-regulated genes. DEGs have a high connection with collagen and extracellular matrix (ECM), according to functional enrichment analysis. Col1a1 and Col1a2 scored well in module analysis and hub gene screening, and were chosen as hub genes. Col1a1 and Col1a2 were shown to be mostly expressed by fibroblasts after localization study. As a result, we believe Col1a1 and Col1a2 may be important markers of obesity-induced cardiac fibrosis, in which fibroblasts play a critical role.

Utilization and Potential of RNA-Based Therapies in Cardiovascular Disease

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RNA-based therapeutics have the potential to reach previously “undruggable” pathways in cardiovascular disease

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RNA-based therapeutics constitute a vast array of technologies, including unique forms, chemistries, and modalities of delivery

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Rapid development of RNA-based vaccines was made possible by decades of foundational work

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Specificity and efficacy of targeting and determination of mechanism(s) of action remain a distinct challenge

Cardiovascular disease (CVD) remains the largest cause of mortality worldwide. The development of new effective therapeutics is a major unmet need. The current review focuses broadly on the concept of nucleic acid (NA)–based therapies, considering the use of various forms of NAs, including mRNAs, miRNAs, siRNA, and guide RNAs, the latter specifically for the purpose of CRISPR-Cas directed gene editing. We describe the current state-of-the-art of RNA target discovery and development, the status of RNA therapeutics in the context of CVD, and some of the challenges and hurdles to be overcome.

The Bioinformatical Identification of Potential Biomarkers in Heart Failure Diagnosis and Treatment

Background

Heart failure (HF) is defined as the inability of the heart's systolic and diastolic function to properly discharge blood flow from the veins to the heart. The goal of our research is to look into the possible mechanism that causes HF.

Methods

The GSE5406 database was used for screening the differentially expressed genes (DEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network were applied to analyze DEGs. Besides, cell counting Kit-8 (CCK-8) was conducted to observe the knockdown effect of hub genes on cell proliferation.

Results

Finally, 377 upregulated and 461 downregulated DEGs came out, enriched in the extracellular matrix organization and gap junction. According to GSEA results, Hoft cd4 positive alpha beta memory t cell bcg vaccine age 18–45 yo id 7 dy top 100 deg ex vivo up, Sobolev t cell pandemrix age 18–64 yo 7 dy dn, and so on were significantly related to gene set GSE5406. 7 hub genes, such as COL1A1, UBB, COL3A1, HSP90AA1, MYC, STAT3 and MAPK1, were selected from PPI networks. CCK-8 indicated silencing of STAT3 promoted the proliferation of H9C2 cells and silencing of UBB inhibited the proliferation of H9C2 cells.

Conclusion

Our analysis reveals that COL1A1, UBB, COL3A1, HSP90AA1, MYC, STAT3, and MAPK1 might promote the progression of HF and become the biomarkers for diagnosis and treatment of HF.

Plasma Proteins as Occupational Hazard Risk Monitors for Populations Working in Harsh Environments: A Mendelian Randomization Study

Harsh work environments can include very cold, hot, dusty, and noisy workplaces, as well as exposure in the workplace with chemicals and other fumes, cigarette smoke, and diesel exhaust. Although working in these harsh environments can have a negative effect on health, there are no effective biomarkers for monitoring health conditions until workers develop disease symptoms. Plasma protein concentrations, which reflect metabolism and immune status, have great potential as biomarkers for various health conditions. Using a Mendelian-randomization (MR) design, this study analyzed the effects of these harsh environments on plasma proteins to identify proteins that can be used as biomarkers of health status. Preliminary analysis using inverse variance weighted (IVW) method with a p-value cutoff of 0.05 showed that workplace environments could affect the concentrations of hundreds of plasma proteins. After filtering for sensitivity via MR-Egger, and Weighted Median MR approaches, 28 plasma proteins altered by workplace environments were identified. Further MR analysis showed that 20 of these plasma proteins, including UNC5D, IGFBP1, SCG3, ST3GAL6, and ST3GAL2 are affected by noisy workplace environments; TFF1, RBM39, ACYP2, STAT3, GRB2, CXCL1, EIF1AD, CSNK1G2, and CRKL that are affected by chemical fumes; ADCYAP1, NRSN1, TMEM132A, and CA10 that are affected by passive smoking; LILRB2, and TENM4 that are affected by diesel exhaust, are associated with the risk of at least one disease. These proteins have the potential to serve as biomarkers to monitor the occupational hazards risk of workers working in corresponding environments. These findings also provide clues to study the biological mechanisms of occupational hazards.

FGF21 (Fibroblast Growth Factor 21) Defines a Potential Cardiohepatic Signaling Circuit in End-Stage Heart Failure

BACKGROUND

Extrinsic control of cardiomyocyte metabolism is poorly understood in heart failure (HF). FGF21 (Fibroblast growth factor 21), a hormonal regulator of metabolism produced mainly in the liver and adipose tissue, is a prime candidate for such signaling.

METHODS

To investigate this further, we examined blood and tissue obtained from human subjects with end-stage HF with reduced ejection fraction at the time of left ventricular assist device implantation and correlated serum FGF21 levels with cardiac gene expression, immunohistochemistry, and clinical parameters.

RESULTS

Circulating FGF21 levels were substantially elevated in HF with reduced ejection fraction, compared with healthy subjects (HF with reduced ejection fraction: 834.4 [95% CI, 628.4-1040.3] pg/mL, n=40; controls: 146.0 [86.3-205.7] pg/mL, n=20, P=1.9×10-5). There was clear FGF21 staining in diseased cardiomyocytes, and circulating FGF21 levels negatively correlated with the expression of cardiac genes involved in ketone metabolism, consistent with cardiac FGF21 signaling. FGF21 gene expression was very low in failing and nonfailing hearts, suggesting extracardiac production of the circulating hormone. Circulating FGF21 levels were correlated with BNP (B-type natriuretic peptide) and total bilirubin, markers of chronic cardiac and hepatic congestion.

CONCLUSIONS

Circulating FGF21 levels are elevated in HF with reduced ejection fraction and appear to bind to the heart. The liver is likely the main extracardiac source. This supports a model of hepatic FGF21 communication to diseased cardiomyocytes, defining a potential cardiohepatic signaling circuit in human HF.

Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis

Aims

Heart failure (HF) is a chronic heart disease with a high incidence and mortality. Due to the regulatory complexity of gene coexpression networks, the underlying hub genes regulation in HF remain incompletely appreciated. We aimed to explore potential key modules and genes for HF using weighted gene coexpression network analysis (WGCNA).

Methods and results

The expression profiles by high throughput sequencing of heart tissues samples from HF and non‐HF samples were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HF and non‐HF samples were firstly identified. Then, a coexpression network was constructed to identify key modules and potential hub genes. The biological functions of potential hub genes were analysed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Finally, a protein–protein interaction (PPI) network was constructed using the STRING online tool. A total of 135 DEGs (133 up‐regulated and 2 down‐regulated DEGs) between HF and non‐HF samples were identified in the GSE135055 and GSE123976 datasets. Moreover, a total of 38 modules were screened based on WGCNA in the GSE135055 dataset, and six potential hub genes (UCK2, ASB1, CCNI, CUX1, IRX6, and STX16) were screened from the key module by setting the gene significance over 0.2 and the module membership over 0.8. Furthermore, 78 potential hub genes were obtained by taking the intersection of the 135 DEGs and all genes in the key module, and enrichment analysis revealed that they were mainly involved in the MAPK and PI3K‐AKT signalling pathways. Finally, in a PPI network constructed with the 78 potential hub genes, CUX1 and ASB1 were identified as hub genes in HF because they were also identified as potential hub genes in the WGCNA.

Conclusions

To the best of our knowledge, our study is the first to employ WGCNA to identify the key module and hub genes for HF. Our study identified a module and two genes that might play important roles in HF, which may provide potential biomarkers for the diagnosis of HF and improve our knowledge of the molecular mechanisms underlying HF.

Comprehensive Expression Analysis of Cardiac Fibroblast Growth Factor 23 in Health and Pressure-induced Cardiac Hypertrophy

Enhanced fibroblast growth factor 23 (FGF23) is associated with left ventricular hypertrophy (LVH) in patients with chronic kidney and heart disease. Experimentally, FGF23 directly induces cardiac hypertrophy and vice versa cardiac hypertrophy stimulates FGF23. Besides the bone, FGF23 is expressed by cardiac myocytes, whereas its synthesis in other cardiac cell types and its paracrine role in the heart in health and disease is unknown. By co-immunofluorescence staining of heart tissue of wild-type mice, we show that Fgf23 is expressed by cardiac myocytes, fibroblasts and endothelial cells. Cardiac Fgf23 mRNA and protein level increases from neonatal to six months of age, whereas no age-related changes in bone Fgf23 mRNA expression were noted. Cardiac myocyte-specific disruption of Fgf23 using Cre-LoxP system (Fgf23fl/fl/cre+) caused enhanced mortality, but no differences in cardiac function or structure. Although pressure overload-induced cardiac hypertrophy induced by transverse aortic constriction (TAC) resulted in a slightly worse phenotype with a more severe reduced ejection fraction, higher end-systolic volume and more enlarged systolic LV diameter in Fgf23fl/fl/cre+ mice compared to controls, this was not translated to any worse cellular hypertrophy, fibrosis or chamber remodeling. TAC induced Fgf23 mRNA expression in whole cardiac tissue in both genotypes. Interestingly, co-immunofluorescence staining revealed enhanced Fgf23 synthesis in cardiac fibroblasts and endothelial cells but not in cardiac myocytes. RNA sequencing of isolated adult cardiac myocytes, cardiac fibroblasts and endothelial cells confirmed significantly higher Fgf23 transcription in cardiac fibroblasts and endothelial cells after TAC. Our data indicate that Fgf23 is physiologically expressed in various cardiac cell types and that cardiac fibroblasts and endothelial cells might be an important source of FGF23 in pathological conditions. In addition, investigations in Fgf23fl/fl/cre+ mice suggest that cardiac myocyte-derived FGF23 is needed to maintain cardiac function during pressure overload.

MicroRNA-365 regulates human cardiac action potential duration

Abnormalities of ventricular action potential cause malignant cardiac arrhythmias and sudden cardiac death. Here, we aim to identify microRNAs that regulate the human cardiac action potential and ask whether their manipulation allows for therapeutic modulation of action potential abnormalities. Quantitative analysis of the microRNA targetomes in human cardiac myocytes identifies miR-365 as a primary microRNA to regulate repolarizing ion channels. Action potential recordings in patient-specific induced pluripotent stem cell-derived cardiac myocytes show that elevation of miR-365 significantly prolongs action potential duration in myocytes derived from a Short-QT syndrome patient, whereas specific inhibition of miR-365 normalizes pathologically prolonged action potential in Long-QT syndrome myocytes. Transcriptome analyses in these cells at bulk and single-cell level corroborate the key cardiac repolarizing channels as direct targets of miR-365, together with functionally synergistic regulation of additional action potential-regulating genes by this microRNA. Whole-cell patch-clamp experiments confirm miR-365-dependent regulation of repolarizing ionic current I_ks. Finally, refractory period measurements in human myocardial slices substantiate the regulatory effect of miR-365 on action potential in adult human myocardial tissue. Our results delineate miR-365 to regulate human cardiac action potential duration by targeting key factors of cardiac repolarization.

Multiplex Protein Biomarker Profiling in Patients with Familial Hypercholesterolemia

Familial hypercholesterolemia (FH), is an autosomal dominant disorder caused by mutations in the LDLR, APOB, PCSK9, and APOE genes and is characterized by high plasma levels of total and low-density lipoprotein (LDL) cholesterol. Our study aimed to analyze the influences of two different therapies on a wide spectrum of plasma protein biomarkers of cardiovascular diseases. Plasma from FH patients under hypolipidemic therapy (N = 18; men = 8, age 55.4 ± 13.1 years) and patients under combined long-term LDL apheresis/hypolipidemic therapy (N = 14; men = 7; age 58.0 ± 13.6 years) were analyzed in our study. We measured a profile of 184 cardiovascular disease (CVD) associated proteins using a proximity extension assay (PEA). Hypolipidemic therapy significantly (all p < 0.01) influenced 10 plasma proteins (TM, DKK1, CCL3, CD4, PDGF subunit B, AGRP, IL18, THPO, and LOX1 decreased; ST2 increased). Under combined apheresis/hypolipidemic treatment, 18 plasma proteins (LDLR, PCSK9, MMP-3, GDF2, CTRC, SORT1, VEGFD, IL27, CCL24, and KIM1 decreased; OPN, COL1A1, KLK6, IL4RA, PLC, TNFR1, GLO1, and PTX3 increased) were significantly affected (all p < 0.006). Hypolipidemic treatment mainly affected biomarkers involved in vascular endothelial maintenance. Combined therapy influenced proteins that participate in cholesterol metabolism and inflammation.

Chronic Ethanol Exposure Induces Deleterious Changes in Cardiomyocytes Derived from Human Induced Pluripotent Stem Cells

Chronic alcohol consumption in adults can induce cardiomyopathy, arrhythmias, and heart failure. In newborns, prenatal alcohol exposure can increase the risk of congenital heart diseases. Understanding biological mechanisms involved in the long-term alcohol exposure-induced cardiotoxicity is pivotal to the discovery of therapeutic strategies. In this study, cardiomyocytes derived from human pluripotent stem cells (hiPSC-CMs) were treated with clinically relevant doses of ethanol for various durations up to 5 weeks. The treated cells were characterized for their cellular properties and functions, and global proteomic profiling was conducted to understand the molecular changes associated with long-term ethanol exposure. Increased cell death, oxidative stress, deranged Ca²⁺ handling, abnormal action potential, altered contractility, and suppressed structure development were observed in ethanol-treated cells. Many dysregulated proteins identified by global proteomic profiling were involved in apoptosis, heart contraction, and extracellular collagen matrix. In addition, several signaling pathways including the Wnt and TGFβ signaling pathways were affected due to long-term ethanol treatment. Therefore, chronic ethanol treatment of hiPSC-CMs induces cardiotoxicity, impairs cardiac functions, and alters protein expression and signaling pathways. This study demonstrates the utility of hiPSC-CMs as a novel model for chronic alcohol exposure study and provides the molecular mechanisms associated with long-term alcohol exposure in human cardiomyocytes.

Blood Plasma Biomarkers for Woody Breast Disease in Commercial Broilers

Woody breast (WB) myopathy results in poor muscle quality. The increasing incidence of WB over the last several years indicates a need for improved prediction or early diagnosis. We hypothesized that the use of body fluids, including blood, may be more suitable than breast muscle tissue in developing a minimally invasive diagnostic tool for WB detection. To identify potential early-age-biomarkers that may represent the potential onset of WB, blood samples were collected from 100, 4 wks old commercial male broilers. At 8 wks of age, WB conditions were scored by manual palpation. A total of 32 blood plasma samples (eight for each group of WB and non-WB control birds at two time points, 4 wks and 8 wks) were subjected to shotgun proteomics and untargeted metabolomics to identify differentially abundant plasma proteins and metabolites in WB broilers compared to non-WB control (Con) broilers. From the proteomics assay, 25 and 16 plasma proteins were differentially abundant (p < 0.05) in the 4 and 8 wks old samples, respectively, in WB compared with Con broilers. Of those, FRA10A associated CGG repeat 1 (FRAG10AC1) showed >2-fold higher abundance in WB compared with controls. In the 8 wks old broilers, 4 and 12 plasma proteins displayed higher and lower abundances, respectively, in WB compared with controls. Myosin heavy chain 9 (MYH9) and lipopolysaccharide binding protein (LBP) showed more than 2-fold higher abundances in WB compared with controls, while transferrin (TF) and complement C1s (C1S) showed more than 2-fold lower abundances compared with controls. From the untargeted metabolomics assay, 33 and 19 plasma metabolites were differentially abundant in birds at 4 and 8 wks of age, respectively, in WB compared with controls. In 4 wks old broilers, plasma 3-hydroxybutyric acid (3-HB) and raffinose concentrations showed the highest and lowest fold changes, respectively, in WB compared with controls. The blood plasma 3-HB and raffinose concentrations were confirmed with targeted biochemical assays. Blood biomarkers, such as 3-HB and raffinose, may be suitable candidate targets in the prediction of WB onset at early ages.

A Novel Gene Signature to Predict Survival Time and Incident Ventricular Arrhythmias in Patients with Dilated Cardiomyopathy

The mortality in nonischaemic dilated cardiomyopathy (NIDCM) patients is still at a high level; sudden death in NIDCM can be caused by ventricular tachycardia. It is necessary to explore the pathogenesis of ventricular arrhythmias (VA) in NIDCM. Differentially expressed genes (DEGs) were identified by comparing the gene expression of NIDCM patients with or without VA in the gene expression profile of GSE135055. A total of 228 DEGs were obtained, and 3 genes were screened out to be significantly related to the survival time of NIDCM patients. We established a prediction model on two-gene (TOMM22, PPP2R5A) signature for the survival time of NIDCM patients. The area under the curve (AUC) was 0.75 calculated by the ROC curve analysis. These risk genes are probably new targets for exploring the pathogenesis of NIDCM with VA; the prediction model for survival time and incident ventricular arrhythmias is useful in clinical decision making for individual treatment.

Impact of cardiac fibrosis and collagens on right ventricular failure and acute kidney injury in patients after continuous-flow left ventricular assist devices

OBJECTIVES

We aim to investigate the impact of cardiac fibrosis and collagens on right ventricular failure (RVF) and acute kidney injury (AKI) in patients receiving continuous flow left ventricular assist devices.

METHODS

Heart tissues from 34 patients were obtained from continuous flow left ventricular assist device insertion sites and corresponding clinical data were collected. The participants were divided into 2 groups according to the extent of the cardiac fibrosis or collagens.

RESULTS

Overall, 18 patients developed RVF with 14 receiving right ventricular assist device (RVAD), and 22 patients developed AKI with 12 needing new-onset renal replacement therapy. Higher collagen I (Col1) was significantly associated with increased incidences of RVF (76.5% vs 29.4%, P = 0.015), RVAD support (64.7% vs 17.6%, P = 0.013) and stage 3 AKI (58.8% vs 17.6%, P = 0.032), and patients with higher Col1 were more prone to renal replacement therapy (52.9% vs 17.6%, P = 0.071). Receiver operating characteristic curves showed that Col1 had good predictive effects on RVF [area under the curve (AUC) = 0.806, P = 0.002], RVAD support (AUC = 0.789, P = 0.005), stage 3 AKI (AUC = 0.740, P = 0.020) and renal replacement therapy (AUC = 0.731, P = 0.028) after continuous-flow left ventricular assist device. Moreover, patients with higher Col1 had significantly longer postoperative duration of mechanical ventilation, duration of intensive care unit stay and hospital length of stay (all P < 0.05). Cardiac fibrosis, collagen III (Col3) and Col1/Col3 shared similar results or trends with Col1.

CONCLUSIONS

Cardiac fibrosis and related collagens in the apical left ventricular tissue are associated with increased risks of RVF, RVAD use and worse renal function. Further study is warranted owing to the small sample size.

Impedimetric and Plasmonic Sensing of Collagen I Using a Half-Antibody-Supported, Au-Modified, Self-Assembled Monolayer System

This research presents an electrochemical immunosensor for collagen I detection using a self-assembled monolayer (SAM) of gold nanoparticles (AuNPs) and covalently immobilized half-reduced monoclonal antibody as a receptor; this allowed for the validation of the collagen I concentration through two different independent methods: electrochemically by Electrochemical Impedance Spectroscopy (EIS), and optically by Surface Plasmon Resonance (SPR). The high unique advantage of the proposed sensor is based on the performance of the stable covalent immobilization of the AuNPs and enzymatically reduced half-IgG collagen I antibodies, which ensured their appropriate orientation onto the sensor's surface, good stability, and sensitivity properties. The detection of collagen type I was performed in a concentration range from 1 to 5 pg/mL. Moreover, SPR was utilized to confirm the immobilization of the monoclonal half-antibodies and sensing of collagen I versus time. Furthermore, EIS experiments revealed a limit of detection (LOD) of 0.38 pg/mL. The selectivity of the performed immunosensor was confirmed by negligible responses for BSA. The performed approach of the immunosensor is a novel, innovative attempt that enables the detection of collagen I with very high sensitivity in the range of pg/mL, which is significantly lower than the commonly used enzyme-linked immunosorbent assay (ELISA).

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

INTRODUCTION

Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules.

METHODS

The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein-protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed.

RESULTS

A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene-miRNA regulatory network and target gene-TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed.

CONCLUSION

The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

Exploration of Potential Genetic Biomarkers for Heart Failure: A Systematic Review

Patients with heart failure (HF) often present with signs and symptoms that are often nonspecific and with a wide differential diagnosis, making diagnosis and prognosis of HF by clinical presentation alone challenging. Our knowledge on genetic diversity is rapidly evolving with high-throughput DNA sequencing technology, which makes a great potential for genetic biomarker development. The present review attempts to provide a comprehensive review on the modification of major genetic components in HF patients and to explore the potential application of these components as clinical biomarkers in the diagnosis and in monitoring the progress of HF. The literature search was conducted using six databases, resulting in the inclusion of eighteen studies in the review. The findings of these studies were summarized narratively. An appraisal of the reporting quality of the included studies was conducted using a twelve-item checklist adapted from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. The findings showed that changes in genetic components in patients with HF compared to healthy controls could be noninvasive diagnostic or prognostic tools for HF with higher specificity and sensitivity in comparison with the traditional biomarkers. This review provided evidence for the potential of developing genetic biomarkers of HF.

Distinct Murine Pancreatic Transcriptomic Signatures during Chronic Pancreatitis Recovery

We have previously demonstrated that the pancreas can recover from chronic pancreatitis (CP) lesions in the cerulein-induced mouse model. To explore how pancreatic recovery is achieved at the molecular level, we used RNA-sequencing (seq) and profiled transcriptomes during CP transition to recovery. CP was induced by intraperitoneally injecting cerulein in C57BL/6 mice. Time-matched controls (CON) were given normal saline. Pancreata were harvested from mice 4 days after the final injections (designated as CP and CON) or 4 weeks after the final injections (designated as CP recovery (CPR) and control recovery (CONR)). Pancreatic RNAs were extracted for RNA-seq and quantitative (q) PCR validation. Using RNA-seq, we identified a total of 3,600 differentially expressed genes (DEGs) in CP versus CON and 166 DEGs in CPR versus CONR. There are 132 DEGs overlapped between CP and CPR and 34 DEGs unique to CPR. A number of selected pancreatic fibrosis-relevant DEGs were validated by qPCR. The top 20 gene sets enriched from DEGs shared between CP and CPR are relevant to extracellular matrix and cancer biology, whereas the top 10 gene sets enriched from DEGs specific to CPR are pertinent to DNA methylation and specific signaling pathways. In conclusion, we identified a distinct set of DEGs in association with extracellular matrix and cancer cell activities to contrast CP and CPR. Once during ongoing CP recovery, DEGs relevant to DNA methylation and specific signaling pathways were induced to express. The DEGs shared between CP and CPR and the DEGs specific to CPR may serve as the unique transcriptomic signatures and biomarkers for determining CP recovery and monitoring potential therapeutic responses at the molecular level to reflect pancreatic histological resolution.

MicroRNA-138 suppresses glioblastoma proliferation through downregulation of CD44

Tumor suppressive microRNAs (miRNAs) are increasingly implicated in the development of anti-tumor therapy by reprogramming gene network that are aberrantly regulated in cancer cells. This study aimed to determine the therapeutic potential of putative tumor suppressive miRNA, miR-138, against glioblastoma (GBM). Whole transcriptome and miRNA expression profiling analyses on human GBM patient tissues identified miR-138 as one of the significantly downregulated miRNAs with an inverse correlation with CD44 expression. Transient overexpression of miR-138 in GBM cells inhibited cell proliferation, cell cycle, migration, and wound healing capability. We unveiled that miR-138 negatively regulates the expression of CD44 by directly binding to the 3' UTR of CD44. CD44 inhibition by miR-138 resulted in an inhibition of glioblastoma cell proliferation in vitro through cell cycle arrest as evidenced by a significant induction of p27 and its translocation into nucleus. Ectopic expression of miR-138 also increased survival rates in mice that had an intracranial xenograft tumor derived from human patient-derived primary GBM cells. In conclusion, we demonstrated a therapeutic potential of tumor suppressive miR-138 through direct downregulation of CD44 for the treatment of primary GBM.

Single-Cell Transcriptomic Atlas of Different Human Cardiac Arteries Identifies Cell Types Associated With Vascular Physiology

[Figure: see text].

Genome-wide identification and functional prediction of long non-coding RNAs in Sprague-Dawley rats during heat stress

Background

Heat stress (HS) is a major stress event in the life of an animal, with detrimental upshots in production and health. Long-non-coding RNAs (lncRNAs) play an important role in many biological processes by transcriptional regulation. However, no research has been reported on the characterization and functionality of lncRNAs in heat-stressed rats.

Results

We studied expression levels of lncRNAs in rats during HS, using strand-specific RNA sequencing. Six rats, three in each of Control (22 ± 1 °C) and H120 (42 °C for 120 min) experimental groups, were used to screen for lncRNAs in their liver and adrenal glands. Totally, 4498 and 7627 putative lncRNAs were identified in liver and adrenal glands of the Control and H120 groups, respectively. The majority of lncRNAs were relatively shorter and contained fewer exons than protein-coding transcripts. In total, 482 (174 up-regulated and 308 down-regulated) and 271 (126 up-regulated and 145 down-regulated) differentially-expressed lncRNAs (DElncRNAs, P < 0.05) were identified in the liver and adrenal glands of the Control and H120 groups, respectively. Furthermore, 1274, 121, and 73 target differentially-expressed genes (DEGs) in the liver were predicted to interact with DElncRNAs based on trans−/cis- and sequence similarity regulatory modes. Functional annotation analyses indicated that these DEGs were mostly significantly enriched in insulin signalling, myeloid leukaemia, and glucagon signalling pathways. Similarly, 437, 73 and 41 target DEGs in the adrenal glands were mostly significantly enriched in the cell cycle (trans-prediction) and lysosome pathways (cis-prediction). The DElncRNAs interacting with DEGs that encode heat shock proteins (HSPs) may play an important role in HS response, which include Hsf4, Dnaja1, Dnajb4, Hsph1 and Hspb1 in the liver, and Dnajb13 and Hspb8 in the adrenal glands. The strand-specific RNA sequencing findings were also further verified through RT-qPCR.

Conclusions

This study is the first to provide a detailed characterization and functional analysis of expression levels of lncRNAs in liver and adrenal glands of heat-stressed rats, which provides basis for further studies on the biological functions of lncRNAs under heat stress in rats and other mammalian species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07421-8.

Global tissue transcriptomic analysis to improve genome annotation and unravel skin pigmentation in goldfish

Goldfish is an ornamental fish with diverse phenotypes. However, the limited genomic resources of goldfish hamper our understanding of the genetic basis for its phenotypic diversity. To provide enriched genomic resources and infer possible mechanisms underlying skin pigmentation, we performed a large-scale transcriptomic sequencing on 13 adult goldfish tissues, larvae at one- and three-days post hatch, and skin tissues with four different color pigmentation. A total of 25.52 Gb and 149.80 Gb clean data were obtained using the PacBio and Illumina platforms, respectively. Onto the goldfish reference genome, we mapped 137,674 non-redundant transcripts, of which 5.54% was known isoforms and 78.53% was novel isoforms of the reference genes, and the remaining 21,926 isoforms are novel isoforms of additional new genes. Both skin-specific and color-specific transcriptomic analyses showed that several significantly enriched genes were known to be involved in melanogenesis, tyrosine metabolism, PPAR signaling pathway, folate biosynthesis metabolism and so on. Thirteen differentially expressed genes across different color skins were associated with melanogenesis and pteridine synthesis including mitf, ednrb, mc1r, tyr, mlph and gch1, and xanthophore differentiation such as pax7, slc2a11 and slc2a15. These transcriptomic data revealed pathways involved in goldfish pigmentation and improved the gene annotation of the reference genome.