A common gene signature of the right ventricle in failing rat and human hearts.
Liane JuridaSebastian WernerFabienne KnappBernd NiemannLing LiDimitri GrünStefanie WirthAxel WeberKnut BeuerleinChristoph LiebetrauChristoph B WiedenrothStefan GuthBaktybek KojonazarovLeili JafariNorbert WeissmannStefan GüntherThomas BraunMarek BartkuhnRalph T SchermulyPeter DorfmüllerXiaoke YinManuel MayrMichael Lienhard SchmitzLaureen CzechKlaus-Dieter SchlüterRainer SchulzSusanne RohrbachMichael KrachtPublished in: Nature cardiovascular research (2024)
The molecular mechanisms of progressive right heart failure are incompletely understood. In this study, we systematically examined transcriptomic changes occurring over months in isolated cardiomyocytes or whole heart tissues from failing right and left ventricles in rat models of pulmonary artery banding (PAB) or aortic banding (AOB). Detailed bioinformatics analyses resulted in the identification of gene signature, protein and transcription factor networks specific to ventricles and compensated or decompensated disease states. Proteomic and RNA-FISH analyses confirmed PAB-mediated regulation of key genes and revealed spatially heterogeneous mRNA expression in the heart. Intersection of rat PAB-specific gene sets with transcriptome datasets from human patients with chronic thromboembolic pulmonary hypertension (CTEPH) led to the identification of more than 50 genes whose expression levels correlated with the severity of right heart disease, including multiple matrix-regulating and secreted factors. These data define a conserved, differentially regulated genetic network associated with right heart failure in rats and humans.
Keyphrases
- pulmonary artery
- pulmonary hypertension
- heart failure
- genome wide
- genome wide identification
- transcription factor
- pulmonary arterial hypertension
- coronary artery
- endothelial cells
- copy number
- dna methylation
- bioinformatics analysis
- atrial fibrillation
- single cell
- oxidative stress
- rna seq
- left ventricular
- genome wide analysis
- induced pluripotent stem cells
- poor prognosis
- gene expression
- acute heart failure
- dna binding
- cardiac resynchronization therapy
- multiple sclerosis
- binding protein
- high glucose
- artificial intelligence
- deep learning
- data analysis
- congenital heart disease
- small molecule
- nucleic acid
- machine learning