Integrated Left Ventricular Global Transcriptome and Proteome Profiling in Human End-Stage Dilated Cardiomyopathy

Unveiling shared biomarkers and therapeutic targets between systemic lupus erythematosus and heart failure through bioinformatics analysis

Background

Systemic lupus erythematosus (SLE) is frequently accompanied by various complications, with cardiovascular diseases being particularly concerning due to their high mortality rate. Although there is clinical evidence suggesting a potential correlation between SLE and heart failure (HF), the underlying shared mechanism is not fully understood. Therefore, it is imperative to explore the potential mechanisms and shared therapeutic targets between SLE and HF.

Methods

The SLE and HF datasets were downloaded from the NCBI Gene Expression Omnibus database. Differentially expressed genes (DEGs) in both SLE and HF were performed using "limma" R package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genes (KEGG) analyses were conducted to analyze the enriched functions and pathways of DEGs in both SLE and HF datasets. Protein-Protein Interaction network (PPI) and the molecular complex detection (MCODE) plugins in the Cytoscape software were performed to identify the shared hub genes between SLE and HF datasets. R package "limma" was utilized to validate the expression of hub genes based on SLE (GSE122459) and HF (GSE196656) datasets. CIBERSORT algorithm was utilized to analyze the immune cell infiltration of SLE and HF samples based on SLE (GSE112087) and HF (GSE116250) datasets. A weighted gene co-expression network analysis (WGCNA) network was established to further validate the hub genes based on HF dataset (GSE116250). Molecular biology techniques were conducted to validate the hub genes.

Results

999 shared DGEs were identified between SLE and HF datasets, which were mainly enriched in pathways related to Th17 cell differentiation. 5 shared hub genes among the common DGEs between SLE and HF datasets were screened and validated, including HSP90AB1, NEDD8, RPLP0, UBB, and UBC. Additionally, 5 hub genes were identified in the central part of the MEbrown module, showing the strongest correlation with dilated cardiomyopathy. HSP90AB1 and UBC were upregulated in failing hearts compared to non-failing hearts, while UBB, NEDD8, and RPLP0 did not show significant changes.

Conclusion

HSP90AB1 and UBC are closely related to the co-pathogenesis of SLE and HF mediated by immune cell infiltration. They serve as promising molecular markers and potential therapeutic targets for the treatment of SLE combined with HF.

Proteome-wide Characterization and Pathophysiology Correlation in Non-ischemic Cardiomyopathies

BACKGROUND AND OBJECTIVES

Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue-based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies.

METHODS

Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography-mass spectrometry. Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings.

RESULTS

The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes.

CONCLUSIONS

Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

Baicalin alleviates angiotensin II-induced cardiomyocyte apoptosis and autophagy and modulates the AMPK/mTOR pathway

As a main extraction compound from Scutellaria baicalensis Georgi, Baicalin exhibits various biological activities. However, the underlying mechanism of Baicalin on hypertension-induced heart injury remains unclear. In vivo, mice were infused with angiotensin II (Ang II; 500 ng/kg/min) or saline using osmotic pumps, followed by intragastrically administrated with Baicalin (5 mg/kg/day) for 4 weeks. In vitro, H9C2 cells were stimulated with Ang II (1 μM) and treated with Baicalin (12.5, 25 and 50 μM). Baicalin treatment significantly attenuated the decrease in left ventricular ejection fraction and left ventricular fractional shortening, increase in left ventricular mass, left ventricular systolic volume and left ventricular diastolic volume of Ang II infused mice. Moreover, Baicalin treatment reversed 314 differentially expressed transcripts in the cardiac tissues of Ang II infused mice, and enriched multiple enriched signalling pathways (including apoptosis, autophagy, AMPK/mTOR signalling pathway). Consistently, Baicalin treatment significantly alleviated Ang II-induced cell apoptosis in vivo and in vitro. Baicalin treatment reversed the up-regulation of Bax, cleaved-caspase 3, cleaved-caspase 9, and the down-regulation of Bcl-2. Meanwhile, Baicalin treatment alleviated Ang II-induced increase of autophagosomes, restored autophagic flux, and down-regulated LC3II, Beclin 1, as well as up-regulated SQSTM1/p62 expression. Furthermore, autophagy inhibitor 3-methyladenine treatment alleviated the increase of autophagosomes and the up-regulation of Beclin 1, LC3II, Bax, cleaved-caspase 3, cleaved-caspase 9, down-regulation of SQSTM1/p62 and Bcl-2 expression after Ang II treated, which similar to co-treatment with Baicalin. Baicalin treatment reduced the ratio of p-AMPK/AMPK, while increased the ratio of p-mTOR/mTOR. Baicalin alleviated Ang II-induced cardiomyocyte apoptosis and autophagy, which might be related to the inhibition of the AMPK/mTOR pathway.

Circular RNA-circPan3 attenuates cardiac hypertrophy via miR-320-3p/HSP20 axis

BACKGROUND

Circular RNAs are enriched in cardiac tissue and play important roles in the pathogenesis of heart diseases. In this study, we aimed to investigate the regulatory mechanism of a conserved heart-enriched circRNA, circPan3, in cardiac hypertrophy.

METHODS

Cardiac hypertrophy was induced by isoproterenol. The progression of cardiomyocyte hypertrophy was assessed by sarcomere organization staining, cell surface area measurement, and expression levels of cardiac hypertrophy markers. RNA interactions were detected by RNA pull-down assays, and methylated RNA immunoprecipitation was used to detect m6A level.

RESULTS

The expression of circPan3 was downregulated in an isoproterenol-induced cardiac hypertrophy model. Forced expression of circPan3 attenuated cardiomyocyte hypertrophy, while inhibition of circPan3 aggravated cardiomyocyte hypertrophy. Mechanistically, circPan3 was an endogenous sponge of miR-320-3p without affecting miR-320-3p levels. It elevated the expression of HSP20 by endogenously interacting with miR-320-3p. In addition, circPan3 was N6-methylated. Stimulation by isoproterenol downregulated the m6A eraser ALKBH5, resulting in N6-methylation and destabilization of circPan3.

CONCLUSIONS

Our research is the first to report that circPan3 has an antihypertrophic effect in cardiomyocytes and revealed a novel circPan3-modulated signalling pathway involved in cardiac hypertrophy. CircPan3 inhibits cardiac hypertrophy by targeting the miR-320-3p/HSP20 axis and is regulated by ALKBH5-mediated N6-methylation. This pathway could provide potential therapeutic targets for cardiac hypertrophy.

Identification of cuproptosis-related molecular subtypes and a novel predictive model of COVID-19 based on machine learning

Background

To explicate the pathogenic mechanisms of cuproptosis, a newly observed copper induced cell death pattern, in Coronavirus disease 2019 (COVID-19).

Methods

Cuproptosis-related subtypes were distinguished in COVID-19 patients and associations between subtypes and immune microenvironment were probed. Three machine algorithms, including LASSO, random forest, and support vector machine, were employed to identify differentially expressed genes between subtypes, which were subsequently used for constructing cuproptosis-related risk score model in the GSE157103 cohort to predict the occurrence of COVID-19. The predictive values of the cuproptosis-related risk score were verified in the GSE163151 cohort, GSE152418 cohort and GSE171110 cohort. A nomogram was created to facilitate the clinical use of this risk score, and its validity was validated through a calibration plot. Finally, the model genes were validated using lung proteomics data from COVID-19 cases and single-cell data.

Results

Patients with COVID-19 had higher significantly cuproptosis level in blood leukocytes compared to patients without COVID-19. Two cuproptosis clusters were identified by unsupervised clustering approach and cuproptosis cluster A characterized by T cell receptor signaling pathway had a better prognosis than cuproptosis cluster B. We constructed a cuproptosis-related risk score, based on PDHA1, PDHB, MTF1 and CDKN2A, and a nomogram was created, which both showed excellent predictive values for COVID-19. And the results of proteomics showed that the expression levels of PDHA1 and PDHB were significantly increased in COVID-19 patient samples.

Conclusion

Our study constructed and validated an cuproptosis-associated risk model and the risk score can be used as a powerful biomarker for predicting the existence of SARS-CoV-2 infection.

APOA2: New Target for Molecular Hydrogen Therapy in Sepsis-Related Lung Injury Based on Proteomic and Genomic Analysis

Target biomarkers for H₂ at both the protein and genome levels are still unclear. In this study, quantitative proteomics acquired from a mouse model were first analyzed. At the same time, functional pathway analysis helped identify functional pathways at the protein level. Then, bioinformatics on mRNA sequencing data were conducted between sepsis and normal mouse models. Differential expressional genes with the closest relationship to disease status and development were identified through module correlation analysis. Then, common biomarkers in proteomics and transcriptomics were extracted as target biomarkers. Through analyzing expression quantitative trait locus (eQTL) and genome-wide association studies (GWAS), colocalization analysis on Apoa2 and sepsis phenotype was conducted by summary-data-based Mendelian randomization (SMR). Then, two-sample and drug-target, syndrome Mendelian randomization (MR) analyses were all conducted using the Twosample R package. For protein level, protein quantitative trait loci (pQTLs) of the target biomarker were also included in MR. Animal experiments helped validate these results. As a result, Apoa2 protein or mRNA was identified as a target biomarker for H₂ with a protective, causal relationship with sepsis. HDL and type 2 diabetes were proven to possess causal relationships with sepsis. The agitation and inhibition of Apoa2 were indicated to influence sepsis and related syndromes. In conclusion, we first proposed Apoa2 as a target for H₂ treatment.

Distinct Transcriptomic and Proteomic Profile Specifies Patients Who Have Heart Failure With Potential of Myocardial Recovery on Mechanical Unloading and Circulatory Support

BACKGROUND

Extensive evidence from single-center studies indicates that a subset of patients with chronic advanced heart failure (HF) undergoing left ventricular assist device (LVAD) support show significantly improved heart function and reverse structural remodeling (ie, termed "responders"). Furthermore, we recently published a multicenter prospective study, RESTAGE-HF (Remission from Stage D Heart Failure), demonstrating that LVAD support combined with standard HF medications induced remarkable cardiac structural and functional improvement, leading to high rates of LVAD weaning and excellent long-term outcomes. This intriguing phenomenon provides great translational and clinical promise, although the underlying molecular mechanisms driving this recovery are largely unknown.

METHODS

To identify changes in signaling pathways operative in the normal and failing human heart and to molecularly characterize patients who respond favorably to LVAD unloading, we performed global RNA sequencing and phosphopeptide profiling of left ventricular tissue from 93 patients with HF undergoing LVAD implantation (25 responders and 68 nonresponders) and 12 nonfailing donor hearts. Patients were prospectively monitored through echocardiography to characterize their myocardial structure and function and identify responders and nonresponders.

RESULTS

These analyses identified 1341 transcripts and 288 phosphopeptides that are differentially regulated in cardiac tissue from nonfailing control samples and patients with HF. In addition, these unbiased molecular profiles identified a unique signature of 29 transcripts and 93 phosphopeptides in patients with HF that distinguished responders after LVAD unloading. Further analyses of these macromolecules highlighted differential regulation in 2 key pathways: cell cycle regulation and extracellular matrix/focal adhesions.

CONCLUSIONS

This is the first study to characterize changes in the nonfailing and failing human heart by integrating multiple -omics platforms to identify molecular indices defining patients capable of myocardial recovery. These findings may guide patient selection for advanced HF therapies and identify new HF therapeutic targets.

Multi-Omics Profiling in PGM3 and STAT3 Deficiencies: A Tale of Two Patients

Hyper-IgE Syndrome (HIES) is a heterogeneous group of primary immune-deficiency disorders characterized by elevated levels of IgE, eczema, and recurrent skin and lung infections. HIES that is autosomally dominant in the signal transducer and activator of transcription 3 (STAT3), and autosomal recessive mutations in phosphoglucomutase 3 (PGM3) have been reported in humans. An early diagnosis, based on clinical suspicion and immunological assessments, is challenging. Patients' metabolomics, proteomics, and cytokine profiles were compared to DOCK 8-deficient and atopic dermatitis patients. The PGM3 metabolomics profile identified significant dysregulation in hypotaurine, hypoxanthine, uridine, and ribothymidine. The eight proteins involved include bifunctional arginine demethylase and lysyl hydroxylase (JMJD1B), type 1 protein phosphatase inhibitor 4 (PPI 4), and platelet factor 4 which aligned with an increased level of the cytokine GCSF. Patients with STAT3 deficiency, on the other hand, showed significant dysregulation in eight metabolites, including an increase in protocatechuic acid, seven proteins including ceruloplasmin, and a plasma protease C1 inhibitor, in addition to cytokine VEGF being dysregulated. Using multi-omics profiling, we identified the dysregulation of endothelial growth factor (EGFR) and tumor necrosis factor (TNF) signaling pathways in PGM3 and STAT3 patients, respectively. Our findings may serve as a stepping stone for larger prospective HIES clinical cohorts to validate their future use as biomarkers.

Proteomic profiling reveals dysregulated mitochondrial complex subunits responsible for myocardial toxicity induced by SiNPs

The relationship between environmental exposure to silica nanoparticles (SiNPs) and adverse cardiac outcomes has received more attention. Our recent work has revealed a size-dependent impact of the intratracheal instilled SiNPs on cardiac health of ApoE^-/- mice using nanoscale SiNPs-60 and submicro-sized SiNPs-300, but the underlying mechanism of action still remains unclear. Hence, we identified proteins and protein networks perturbed by SiNPs in myocardial tissues of ApoE^-/- mice by using LC-MS/MS-based quantitative proteomics. A set of 435 differentially expressed proteins (DEPs) were screened in response to SiNPs, which mainly enriched in the mitochondria and functioned in cell metabolism, biosynthesis and signal transduction. KEGG analysis showed that DEPs were significantly associated with oxidative phosphorylation and cardiomyopathy. The protein-protein interaction (PPI) network revealed 9 DEPs (e.g., Ndufs1, Ndufv1, Cox4i1) as potential biomarkers of SiNPs-induced myocardial toxicity. Of note, all the 9 candidate proteins were subunits of mitochondria respiratory chain complex, and their expressions were dependent on particle size, which were remarkably down-regulated by SiNPs-60 but not by SiNPs-300. More importantly, the correlation analysis verified the 9 dysregulated mitochondria complex protein subunits strongly correlated to the biochemical and functional indexes of cardiac injury in response to SiNPs. In conclusion, our study firstly provided significant proteomic insights into the potential molecular mechanisms underlying SiNPs-elicited cardiotoxicity, with the dysregulated mitochondrial complex subunits as core regulatory molecules. Overall, our study would provide the scientific basis for the molecular actions and mechanisms of toxicity induced by SiNPs.

Multi-omics assessment of dilated cardiomyopathy using non-negative matrix factorization

Dilated cardiomyopathy (DCM), a myocardial disease, is heterogeneous and often results in heart failure and sudden cardiac death. Unavailability of cardiac tissue has hindered the comprehensive exploration of gene regulatory networks and nodal players in DCM. In this study, we carried out integrated analysis of transcriptome and methylome data using non-negative matrix factorization from a cohort of DCM patients to uncover underlying latent factors and covarying features between whole-transcriptome and epigenome omics datasets from tissue biopsies of living patients. DNA methylation data from Infinium HM450 and mRNA Illumina sequencing of n = 33 DCM and n = 24 control probands were filtered, analyzed and used as input for matrix factorization using R NMF package. Mann-Whitney U test showed 4 out of 5 latent factors are significantly different between DCM and control probands (P<0.05). Characterization of top 10% features driving each latent factor showed a significant enrichment of biological processes known to be involved in DCM pathogenesis, including immune response (P = 3.97E-21), nucleic acid binding (P = 1.42E-18), extracellular matrix (P = 9.23E-14) and myofibrillar structure (P = 8.46E-12). Correlation network analysis revealed interaction of important sarcomeric genes like Nebulin, Tropomyosin alpha-3 and ERC-protein 2 with CpG methylation of ATPase Phospholipid Transporting 11A0, Solute Carrier Family 12 Member 7 and Leucine Rich Repeat Containing 14B, all with significant P values associated with correlation coefficients >0.7. Using matrix factorization, multi-omics data derived from human tissue samples can be integrated and novel interactions can be identified. Hypothesis generating nature of such analysis could help to better understand the pathophysiology of complex traits such as DCM.

Genetic Catalytic Inactivation of GRK5 Impairs Cardiac Function in Mice Via Dysregulated P53 Levels

GRK5's catalytic activity in regulating basal and stressed cardiac function has not been studied. Herein, we studied knock-in mice in which GRK5 was mutated to render it catalytically inactive (K215R). At baseline, GRK5-K215R mice showed a marked decline in cardiac function with increased apoptosis and fibrosis. In vitro, restriction of GRK5 inside the nucleus of cardiomyocytes resulted in enhanced cell death along with higher p53 levels. Moreover, in fibroblasts, we demonstrated that K215R mutation promoted the transition into myofibroblast phenotype. This study provides novel insight into the biological actions of GRK5, that are essential for its future targeting.

Transcriptomic Signatures of End-Stage Human Dilated Cardiomyopathy Hearts with and without Left Ventricular Assist Device Support

Left ventricular assist device (LVAD) use in patients with dilated cardiomyopathy (DCM) can lead to a differential response in the LV and right ventricle (RV), and RV failure remains the most common complication post-LVAD insertion. We assessed transcriptomic signatures in end-stage DCM, and evaluated changes in gene expression (mRNA) and regulation (microRNA/miRNA) following LVAD. LV and RV free-wall tissues were collected from end-stage DCM hearts with (n = 8) and without LVAD (n = 8). Non-failing control tissues were collected from donated hearts (n = 6). Gene expression (for mRNAs/miRNAs) was determined using microarrays. Our results demonstrate that immune response, oxygen homeostasis, and cellular physiological processes were the most enriched pathways among differentially expressed genes in both ventricles of end-stage DCM hearts. LV genes involved in circadian rhythm, muscle contraction, cellular hypertrophy, and extracellular matrix (ECM) remodelling were differentially expressed. In the RV, genes related to the apelin signalling pathway were affected. Following LVAD use, immune response genes improved in both ventricles; oxygen homeostasis and ECM remodelling genes improved in the LV and, four miRNAs normalized. We conclude that LVAD reduced the expression and induced additional transcriptomic changes of various mRNAs and miRNAs as an integral component of the reverse ventricular remodelling in a chamber-specific manner.

A Network-Based Methodology to Identify Subnetwork Markers for Diagnosis and Prognosis of Colorectal Cancer

The development of reliable methods for identification of robust biomarkers for complex diseases is critical for disease diagnosis and prognosis efforts. Integrating multi-omics data with protein-protein interaction (PPI) networks to investigate diseases may help better understand disease characteristics at the molecular level. In this study, we developed and tested a novel network-based method to detect subnetwork markers for patients with colorectal cancer (CRC). We performed an integrated omics analysis using whole-genome gene expression profiling and copy number alterations (CNAs) datasets followed by building a gene interaction network for the significantly altered genes. We then clustered the constructed gene network into subnetworks and assigned a score for each significant subnetwork. We developed a support vector machine (SVM) classifier using these scores as feature values and tested the methodology in independent CRC transcriptomic datasets. The network analysis resulted in 15 subnetwork markers that revealed several hub genes that may play a significant role in colorectal cancer, including PTP4A3, FGFR2, PTX3, AURKA, FEN1, INHBA, and YES1. The 15-subnetwork classifier displayed over 98 percent accuracy in detecting patients with CRC. In comparison to individual gene biomarkers, subnetwork markers based on integrated multi-omics and network analyses may lead to better disease classification, diagnosis, and prognosis.

Alterations in the Plasma Proteome Induced by SARS-CoV-2 and MERS-CoV Reveal Biomarkers for Disease Outcomes for COVID-19 Patients

Purpose

This study aimed to understand the pathophysiology of host responses to infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/(COVID-19) and Middle East respiratory syndrome coronavirus (MERS-CoV) and to identify proteins for patient stratification with different grades of illness severity.

Patients and Methods

Peripheral blood samples from 43 patients with different grades of COVID-19, 7 MERS-CoV patients admitted to the ICU, and 10 healthy subjects were analyzed using label-free quantitative liquid chromatography–mass spectrometry (LC–MS).

Results

We identified 193 and 91 proteins that differed significantly between COVID-19 and MERS-CoV sample groups, respectively, and 49 overlapped between datasets. Only 10 proteins are diagnostic of asymptomatic cases, 12 are prognostic of recovery from severe illness, and 28 are prognostic of a fatal outcome of COVID-19. These proteins are implicated in virus-specific/related signaling networks. Notable among the top canonical pathways are humoral immunity, inflammation, acute-phase response signaling, liver X receptor/retinoid X receptor (LXR/RXR) activation, coagulation, and the complement system. Furthermore, we confirmed positive viral shedding in 11.76% of 51 additional peripheral blood samples, indicating that caution should be taken to avoid the possible risk of transfusion of infected blood products.

Conclusion

We identified COVID-19 and MERS-CoV protein panels that have potential as biomarkers and might assist in the prognosis of SARS-CoV-2 infection. The identified markers further our understanding of COVID-19 disease pathophysiology and may have prognostic or therapeutic potential in predicting or managing host cell responses to human COVID-19 and MERS-CoV infections.

Quantitative proteomics analysis reveals unique but overlapping protein signatures in HIV infections

BACKGROUND

Human immunodeficiency virus-1 (HIV-1) exploits human host factors to complete its life cycle. Hence, discovery of HIV-regulated host proteins markers would better our understanding of the virus life-cycle and its contribution to pathogenesis and discovery of objective diagnostic and prognostic molecules.

METHODS

We conducted holistic total proteomics analysis of three closely related study populations including patients with HIV type-1 (HIV-1) and HIV type-2 (HIV-2) as well as HIV-1 elite controllers (HIV-1-EC). Peripheral blood plasma (PBP) samples were subjected to label-free quantitative liquid-chromatography tandem mass-spectrometry (LC-MS/MS).

RESULTS

Over 314 unique PBP protein species were identified of which 100 (approx. 32%) were significantly differentially expressed (≥2 to ∞ - fold-change; p < 0.05) between the three sample cohorts. Of the 100 proteins, 91 were significantly changed between pairs of HIV-1 versus HIV-1-EC, while 83 of the 100 proteins differed significantly between HIV-2 and HIV-1-EC. Interestingly, 76 proteins (87.5%) overlap between the two data sets indicating that majority of these proteins share similar expression changes between HIV-1 and HIV-2 sample groups. Two of the identified proteins, XRCC5 and PSME1, were implicated in the early phase of the pathway network for HIV life cycle, while others were involved in infectious disease and disease of signal transduction. Among them were MAP2K1, RPL23A, RPS3, CALR, PRDX1, SOD2, LMNB1, PHB, and FGB. Despite the high degree of similarity in protein profiles of HIV-1 and HIV-2, six proteins differed significantly including ETFB, PHB2, S100A9, LMO2, PPP3R1 and Vif, a fragment of virion infectivity factor of HIV-1. Additionally, 15 proteins were uniquely expressed, and one of them (LSP1) is present only in HIV-1-EC but absent in HIV1 and HIV-2 and vice versa for the rest 14 proteins.

CONCLUSIONS

Altogether, we have identified HIV-specific/related protein expression changes that might potentially be capable of early diagnosis and prognosis of HIV diseases and other related infectious diseases.

Cardiac dopamine D1 receptor triggers ventricular arrhythmia in chronic heart failure

Pathophysiological roles of cardiac dopamine system remain unknown. Here, we show the role of dopamine D1 receptor (D1R)-expressing cardiomyocytes (CMs) in triggering heart failure-associated ventricular arrhythmia. Comprehensive single-cell resolution analysis identifies the presence of D1R-expressing CMs in both heart failure model mice and in heart failure patients with sustained ventricular tachycardia. Overexpression of D1R in CMs disturbs normal calcium handling while CM-specific deletion of D1R ameliorates heart failure-associated ventricular arrhythmia. Thus, cardiac D1R has the potential to become a therapeutic target for preventing heart failure-associated ventricular arrhythmia.

Biomolecular Databases and Subnetwork Identification Approaches of Interest to Big Data Community: An Expert Review

Next-generation sequencing approaches and genome-wide studies have become essential for characterizing the mechanisms of human diseases. Consequently, many researchers have applied these approaches to discover the genetic/genomic causes of common complex and rare human diseases, generating multiomics big data that span the continuum of genomics, proteomics, metabolomics, and many other system science fields. Therefore, there is a significant and unmet need for biological databases and tools that enable and empower the researchers to analyze, integrate, and make sense of big data. There are currently large number of databases that offer different types of biological information. In particular, the integration of gene expression profiles and protein-protein interaction networks provides a deeper understanding of the complex multilayered molecular architecture of human diseases. Therefore, there has been a growing interest in developing methodologies that integrate and contextualize big data from molecular interaction networks to identify biomarkers of human diseases at a subnetwork resolution as well. In this expert review, we provide a comprehensive summary of most popular biomolecular databases for molecular interactions (e.g., Biological General Repository for Interaction Datasets, Kyoto Encyclopedia of Genes and Genomes and Search Tool for The Retrieval of Interacting Genes/Proteins), gene-disease associations (e.g., Online Mendelian Inheritance in Man, Disease-Gene Network, MalaCards), and population-specific databases (e.g., Human Genetic Variation Database), and describe some examples of their usage and potential applications. We also present the most recent subnetwork identification approaches and discuss their main advantages and limitations. As the field of data science continues to emerge, the present analysis offers a deeper and contextualized understanding of the available databases in molecular biomedicine.

Potentially Critical Roles of NDUFB5, TIMMDC1, and VDAC3 in the Progression of Septic Cardiomyopathy Through Integrated Bioinformatics Analysis

Septic cardiomyopathy (SC) is a rare and harmful cardiovascular disease with decreased left ventricular (LV) output and multiple organ failure, which poses a serious threat to human life. Despite the advances in SC, its diagnostic basis and treatment methods are limited, and the specific diagnostic biomarkers and its candidate regulatory targets have not yet been fully established. In this study, the GSE79962 gene expression profile was retrieved, with 20 patients with SC and 11 healthy donors as control. Weighted gene coexpression network analysis (WGCNA) was employed to investigate gene modules that were strongly correlated with clinical phenotypes. Blue module was found to be most significantly related to SC. Moreover, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the coexpression genes in blue module and showed that it was associated with metabolic pathways, oxidative phosphorylation, and cardiac muscle contraction. Furthermore, a total of 10 hub genes NDUFB5, TIMMDC1, VDAC3, COQ10A, MRPL16 (mitochondrial ribosomal protein L16), C3orf43, TMEM182, DLAT, NDUFA8, and PDHB (pyruvate dehydrogenase E1 beta subunit) in the blue module were identified at transcriptional level and further validated at translational level in myocardium of an lipopolysaccharide-induced septic cardiac dysfunction mouse model. Overall, the results of quantitative real-time polymerase chain reaction were consistent with most of the microarray analysis results. Intriguingly, we observed that the highest change was NDUFB5, TIMMDC1, and VDAC3. These identified and validated genes provided references that would advance the understanding of molecular mechanisms of SC. Taken together, using WGCNA, the hub genes NDUFB5, TIMMDC1, and VDAC3 might serve as potential biomarkers for diagnosis and/or therapeutic targets for precise treatment of SC in the future.

An atypical pulmonary fibrosis is associated with co-inheritance of mutations in the calcium binding protein genes S100A3 and S100A13

BACKGROUND

Pulmonary fibrosis is one of the leading indications for lung transplantation. The disease, which is of unknown aetiology, can be progressive, resulting in distortion of the extracellular matrix (ECM), inflammation, fibrosis and eventual death.

METHODS

13 patients born to consanguineous parents from two unrelated families presenting with interstitial lung disease were clinically investigated. Nine patients developed respiratory failure and subsequently died. Molecular genetic investigations were performed on patients' whole blood or archived tissues, and cell biological investigations were performed on patient-derived fibroblasts.

RESULTS

The combination of a unique pattern of early-onset lung fibrosis (at 12-15 years old) with distinctive radiological findings, including 1) traction bronchiectasis, 2) intralobular septal thickening, 3) shrinkage of the secondary pulmonary lobules mainly around the bronchovascular bundles and 4) early type 2 respiratory failure (elevated blood carbon dioxide levels), represents a novel clinical subtype of familial pulmonary fibrosis. Molecular genetic investigation of families revealed a hypomorphic variant in S100A3 and a novel truncating mutation in S100A13, both segregating with the disease in an autosomal recessive manner. Family members that were either heterozygous carriers or wild-type normal for both variants were unaffected. Analysis of patient-derived fibroblasts demonstrated significantly reduced S100A3 and S100A13 expression. Further analysis demonstrated aberrant intracellular calcium homeostasis, mitochondrial dysregulation and differential expression of ECM components.

CONCLUSION

Our data demonstrate that digenic inheritance of mutations in S100A3 and S100A13 underlie the pathophysiology of pulmonary fibrosis associated with a significant reduction of both proteins, which suggests a calcium-dependent therapeutic approach for management of the disease.

An 85-Gene Coexpression Module for Progression of Hypertension-Induced Spontaneous Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) represents the most lethal form of stroke. We sought to identify potential genes that might contribute to progression of hypertension-induced spontaneous ICH (HIS-ICH). RNA-sequencing data set of cerebral vessel samples from HIS-ICH mice and normal mice was obtained from the Gene Expression Omnibus. Differential expression genes in HIS-ICH samples were obtained compared with normal samples followed by functional enrichment analysis. What is more, we explored the potential gene coexpression module (GCM) for HIS-ICH progression by using weighted gene coexpression network analysis. We further conducted protein-protein interaction network analysis for genes contained in GCM that was closely correlated with HIS-ICH to disclose their biological interactions. As a result, 554 genes were found to aberrantly express in HIS-ICH mice compared with normal mice, which were mainly associated with cancer-related pathways in addition to some well-known ICH-related pathways. A total of 28 GCMs were obtained, and darkturquoise module that contained 85 genes, which were closely associated with mitochondrion and hydrolase activity, was significantly correlated with HIS-ICH progression. Besides, we identified dense biological interactions among some genes in darkturquoise, such as Psma gene family and Hsp90a gene family. This study should shed new light on HIS-ICH progression and its treatment.

Genetic and non-genetic determinants of clinical phenotypes in cardiomyopathy

Cardiomyopathy, a leading cause of death worldwide, is etiologically and phenotypically heterogeneous and is caused by a combination of genetic and non-genetic factors. Major genomic determinants of dilated cardiomyopathy (DCM) are titin truncating mutations and lamin A/C mutations. Patients with these two genotypes show critically different phenotypes, including penetrance, coexistence with a conduction system abnormality, cardiac prognosis, and treatment response. The transcriptomic and epigenomic characteristics of DCM include activation of the DNA damage response, metabolic reprogramming, and dedifferentiation. The proteomic and metabolomic signatures of the DCM heart include a rigorous dependency for free fatty acids, activation of the stress response, and metabolic reprogramming. Proteomic and metabolomic analyses of blood show a distinct immune response and an unexpected link with pathology-specific microbiota in DCM. The direct integration of multi-omics data will not only elucidate inter-omics associations but also enable omics-based patient stratification, which will lead to a deeper understanding of cardiomyopathy and the development of precision medicine in cardiology.

Comparative proteomic analysis of mouse models of pathological and physiological cardiac hypertrophy, with selection of biomarkers of pathological hypertrophy by integrative Proteogenomics

To determine fundamental characteristics of pathological cardiac hypertrophy, protein expression profiles in two widely accepted models of cardiac hypertrophy (swimming-trained mouse for physiological hypertrophy and pressure-overload-induced mouse for pathological hypertrophy) were compared using a label-free quantitative proteomics approach. Among 3955 proteins (19,235 peptides, false-discovery rate < 0.01) identified in these models, 486 were differentially expressed with a log2 fold difference ≥ 0.58, or were detected in only one hypertrophy model (each protein from 4 technical replicates, p < .05). Analysis of gene ontology biological processes and KEGG pathways identified cellular processes enriched in one or both hypertrophy models. Processes unique to pathological hypertrophy were compared with processes previously identified in cardiac-hypertrophy models. Individual proteins with differential expression in processes unique to pathological hypertrophy were further confirmed using the results of previous targeted functional analysis studies. Using a proteogenomic approach combining transcriptomic and proteomic analyses, similar patterns of differential expression were observed for 23 proteins and corresponding genes associated with pathological hypertrophy. A total of 11 proteins were selected as early-stage pathological-hypertrophy biomarker candidates, and the results of western blotting for five of these proteins in independent samples confirmed the patterns of differential expression in mouse models of pathological and physiological cardiac hypertrophy.

In-depth proteomic profiling of left ventricular tissues in human end-stage dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is caused by reduced left ventricular (LV) myocardial function, which is one of the most common causes of heart failure (HF). We performed iTRAQ-coupled 2D-LC-MS/MS to profile the cardiac proteome of LV tissues from healthy controls and patients with end-stage DCM. We identified 4263 proteins, of which 125 were differentially expressed in DCM tissues compared to LV controls. The majority of these were membrane proteins related to cellular junctions and neuronal metabolism. In addition, these proteins were involved in membrane organization, mitochondrial organization, translation, protein transport, and cell death process. Four key proteins involved in the cell death process were also detected by western blotting, indicated that cell death was activated in DCM tissues. Furthermore, S100A1 and eEF2 were enriched in the “cellular assembly and organization” and “cell cycle” networks, respectively. We verified decreases in these two proteins in end-stage DCM LV samples through multiple reaction monitoring (MRM). These observations demonstrate that our understanding of the mechanisms underlying DCM can be deepened through comparison of the proteomes of normal LV tissues with that from end-stage DCM in humans.

Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain.

SIGNIFICANCE

Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several proteins with biomarker potential have been identified and successfully validated.

Evidence of a Cardiovascular Function for Microtubule-Associated Protein Tau

Aggregation of tau protein into intracellular deposits is a pathognomonic feature of tauopathies such as Alzheimer's disease (AD) and lowering tau is a prominent therapeutic strategy under development. However, the physiological function of tau protein is not well known, particularly in the periphery. Lowering tau protein risks disrupting its physiological role leading to unwanted effects. In this study, the presence of tau protein in cardiac tissue is confirmed and the functional role in the cardiovascular system and the consequences of its loss were explored. Isolated right and left atria and small mesenteric arteries from wild type and tau deficient (KO) mice of two age groups (13 and 23 months old) were used to assess cardiovascular phenotypes. Tau KO mice showed an increased systolic blood pressure and cardiac hypertrophy at 13 months, which was accompanied by a significantly lower right atrial rate and a subtle decrease in the maximum contractility to calcium, isoprenaline, and electrical sympathetic nerve stimulation. Aging tau KO mice to 23 months resulted in cardiac hypertrophy with significantly attenuated left atrial contractility, increased blood pressure, and sensitivity of isolated mesenteric arteries to angiotensin II contraction and isoprenaline relaxation compared to their younger counterparts. This study supports a functional role of tau in the heart and loss of this protein leads to a deterioration in cardiovascular performance which worsens with age. Taken together, these results provide insight into the peripheral function of tau protein, and give caution to the therapeutic strategy of lowering tau protein.

GRK2 as a therapeutic target for heart failure

INTRODUCTION

G protein-coupled receptor (GPCR) kinase-2 (GRK2) is a regulator of GPCRs, in particular β-adrenergic receptors (ARs), and as demonstrated by decades of investigation, it has a pivotal role in the development and progression of cardiovascular disease, like heart failure (HF). Indeed elevated levels and activity of this kinase are able to promote the dysfunction of both cardiac and adrenal α- and β-ARs and to dysregulate other protective signaling pathway, such as sphingosine 1-phospate and insulin. Moreover, recent discoveries suggest that GRK2 can signal independently from GPCRs, in a 'non-canonical' manner, via interaction with non-GPCR molecule or via its mitochondrial localization. Areas covered: Based on this premise, GRK2 inhibition or its genetic deletion has been tested in several disparate animal models of cardiovascular disease, showing to protect the heart from adverse remodeling and dysfunction. Expert opinion: HF is one of the leading cause of death worldwide with enormous health care costs. For this reason, the identification of new therapeutic targets like GRK2 and strategies such as its inhibition represents a new hope in the fight against HF development and progression. Herein, we will update the readers about the 'state-of-art' of GRK2 inhibition as a potent therapeutic strategy in HF.

Characterization of developmental defects in the forebrain resulting from hyperactivated mTOR signaling by integrative analysis of transcriptomic and proteomic data

Hyperactivated mTOR signaling in the developing brain has been implicated in multiple forms of pathology including tuberous sclerosis complex (TSC). To date, various phenotypic defects such as cortical lamination irregularity, subependymal nodule formation, dysmorphic astrocyte differentiation and dendritic malformation have been described for patients and animal models. However, downstream networks affected in the developing brain by hyperactivated mTOR signaling have yet to be characterized. Here, we present an integrated analysis of transcriptomes and proteomes generated from wild-type and Tsc1/Emx1-Cre forebrains. This led to comprehensive lists of genes and proteins whose expression levels were altered by hyperactivated mTOR signaling. Further incorporation of TSC patient data followed by functional enrichment and network analyses pointed to changes in molecular components and cellular processes associated with neuronal differentiation and morphogenesis as the key downstream events underlying developmental and morphological defects in TSC. Our results provide novel and fundamental molecular bases for understanding hyperactivated mTOR signaling-induced brain defects which can in turn facilitate identification of potential diagnostic markers and therapeutic targets for mTOR signaling-related neurological disorders.

Abnormal expression of long non-coding RNAs in myocardial infarction

Myocardial infarction (MI) is the leading cause of fatality worldwide. Our study aimed to investigate the dysregulated long non-coding RNA (lncRNA) in MI and elucidate the mechanism of it in MI. The lncRNA and mRNA expression profiling of the whole left ventricular tissue of MI mice model (8 mice) and Sham group (8 mice) was obtained based on microarray analysis. Differentially expressed lnRNAs/mRNA (DELs/DEMs) were identified in MI. DELs/DEMs co-expression network construction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to predict the biological functions of DEMs. Quantitative real-time polymerase chain reaction (qRT-PCR) was subjected to validate the abnormally expressed DELs in left ventricular tissues of MI mice model. Total of 168 DELs (37 up- and 131 down-regulated) and 126 DEMs (87 up- and 39 down-regulated) were identified in MI compared with Sham group. The co-expression network of candidate DELs and DEMs was constructed, which covered 219 nodes and 1775 edges. The qRT-PCR validation results indicated that ENSMUST00000124047 was significantly down-regulated in MI group and AK166279 was significantly up-regulated in MI group. ENSMUST00000121611 and NR_015515 had the up-regulated tendency in MI group compared with Sham group. The DEMs in MI were significantly enriched in 41 signaling pathways including complement and coagulation cascades, cytokine-cytokine receptor interaction and chemokine signaling pathway. The expression profiling of dysregulated DELs in MI was identified. Our results might provide useful information for exploring the pathogenesis mechanism of MI.