Published May 19, 2020 | Version 1.0.0
Journal article Open

The Reference of the Transcriptional Landscape of Human End-Stage Heart Failure

  • 1. Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
  • 2. Department of Cardiology, Medical University Hospital, Heidelberg, Germany
  • 3. Department of General Internal Medicine and Psychosomatics, Heidelberg University Hospital, Heidelberg, Germany

Description

Data from:  "The Reference of the Transcriptional Landscape of Human End-Stage Heart Failure"
Source code at: https://github.com/saezlab/HF_meta-analysis

Aims: Transcriptomic studies have contributed to fundamental knowledge of myocardial remodeling in human heart failure (HF). However, the agreement on the crucial genes in HF is limited and systematic efforts to integrate evidences of multiple patient cohorts are lacking. Here we aimed to provide an unbiased consensus transcriptional signature of human end-stage HF by comprehensive comparison and analysis of publicly available datasets.

Methods and Results: We curated and uniformly processed 16 public transcriptomic studies of left ventricular samples from 263 healthy and 653 failing human hearts. Transfer learning approaches revealed conserved disease patterns across all studies independent of technical differences. We meta-analyzed the dysregulation of 14041 genes to extract a consensus signature of HF. Estimation of the activities of 343 transcription factors, 14 signalling pathways, and 182 micro RNAs, as well as the enrichment of 5998 biological processes confirmed the established aspects of the functional landscape of the disease and revealed novel ones. We provide all results in a free public resource to facilitate further use and interpretation of the results. We exemplify usage by deciphering fetal gene reprogramming and tracing myocardial origin of the plasma proteome biomarkers in HF patients.

Conclusion: We demonstrated the feasibility of combining transcriptional studies from different HF patient cohorts. In our compendium we provide a robust and consistent collection of molecular markers of end-stage HF that may guide the identification of novel targets with diagnostic or therapeutic relevance.

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