Consensus Transcriptional Landscape of Human End‐Stage Heart Failure

• Verfasst von: Ramirez Flores, Ricardo O. [VerfasserIn]
• Verfasst von: Lanzer, Jan David [VerfasserIn]
• Verfasst von: Holland, Christian H. [VerfasserIn]
• Verfasst von: Leuschner, Florian [VerfasserIn]
• Verfasst von: Most, Patrick [VerfasserIn]
• Verfasst von: Schultz, Jobst-Hendrik [VerfasserIn]
• Verfasst von: Levinson, Rebecca T. [VerfasserIn]
• Verfasst von: Sáez Rodríguez, Julio [VerfasserIn]
• Titel: Consensus Transcriptional Landscape of Human End‐Stage Heart Failure
• Verf.angabe: Ricardo O. Ramirez Flores, BSc; Jan D. Lanzer, MD; Christian H. Holland, MSc; Florian Leuschner, MD; Patrick Most, MD; Jobst‐Hendrik Schultz, MD; Rebecca T. Levinson, PhD; Julio Saez‐Rodriguez, PhD
• E-Jahr: 2021
• Jahr: 31 Mar 2021
• Umfang: 40 S.
• Fussnoten: Gesehen am 25.05.2021
• Titel Quelle: Enthalten in: American Heart AssociationJournal of the American Heart Association
• Ort Quelle: New York, NY : Association, 2012
• Jahr Quelle: 2021
• Band/Heft Quelle: 10(2021), 7, Artikel-ID e019667, Seite 1-40
• ISSN Quelle: 2047-9980
• DOI: doi:10.1161/JAHA.120.019667
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1758395958
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

BackgroundTranscriptomic studies have contributed to fundamental knowledge of myocardial remodeling in human heart failure (HF). However, the key HF genes reported are often inconsistent between studies, and systematic efforts to integrate evidence from multiple patient cohorts are lacking. Here, we aimed to provide a framework for comprehensive comparison and analysis of publicly available data sets resulting in an unbiased consensus transcriptional signature of human end‐stage HF.Methods and ResultsWe curated and uniformly processed 16 public transcriptomic studies of left ventricular samples from 263 healthy and 653 failing human hearts. First, we evaluated the degree of consistency between studies by using linear classifiers and overrepresentation analysis. Then, we meta‐analyzed the deregulation of 14 041 genes to extract a consensus signature of HF. Finally, to functionally characterize this signature, we estimated the activities of 343 transcription factors, 14 signaling pathways, and 182 micro RNAs, as well as the enrichment of 5998 biological processes. Machine learning approaches revealed conserved disease patterns across all studies independent of technical differences. These consistent molecular changes were prioritized with a meta‐analysis, functionally characterized and validated on external data. We provide all results in a free public resource (https://saezlab.shinyapps.io/reheat/) and exemplified usage by deciphering fetal gene reprogramming and tracing the potential myocardial origin of the plasma proteome markers in patients with HF.ConclusionsEven though technical and sampling variability confound the identification of differentially expressed genes in individual studies, we demonstrated that coordinated molecular responses during end‐stage HF are conserved. The presented resource is crucial to complement findings in independent studies and decipher fundamental changes in failing myocardium.