Multiomics Analysis Provides Novel Pathways Related to Progression of Heart Failure

Wouter Ouwerkerk (Lead / Corresponding author), Joao P. Belo Pereira, Troy Maasland, Johanna E. Emmens, Sylwia Figarska, Jasper Tromp, Andrea Koekemoer, Christopher P. Nelson, Mintu Nath, Simon P. R. Romaine, John G. F. Cleland, Faiez Zannad, Dirk J. van Veldhuisen, Chim C. Lang, Piotr Ponikowski, Gerasimos S. Filippatos, Stefan D. Anker, Marco Metra, Kenneth Dickstein, Leong L. NgRudolf A. de Boer, Natal van Riel, Max Nieuwdorp, Albert K. Groen, Erik S. Stroes, Aeilko H. Zwinderman, Nilesh J. Samani, Carolyn S. P. Lam, Evgeni Levin, Adriaan A. Voors

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)

    Abstract

    Background: Despite major advances in pharmacological treatment for patients with heart failure, residual mortality remains high. This suggests that important pathways are not yet targeted by current heart failure therapies.

    Objectives: We sought integration of genetic, transcriptomic, and proteomic data in a large cohort of patients with heart failure to detect major pathways related to progression of heart failure leading to death.

    Methods: We used machine learning methodology based on stacked generalization framework and gradient boosting algorithms, using 54 clinical phenotypes, 403 circulating plasma proteins, 36,046 transcript expression levels in whole blood, and 6 million genomic markers to model all-cause mortality in 2,516 patients with heart failure from the BIOSTAT-CHF (Systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure) study. Results were validated in an independent cohort of 1,738 patients.

    Results: The mean age of the patients was 70 years (Q1-Q3: 61-78 years), 27% were female, median N-terminal pro–B-type natriuretic peptide was 4,275 ng/L (Q1-Q3: 2,360-8,486 ng/L), and 7% had heart failure with preserved ejection fraction. During a median follow-up of 21 months, 657 (26%) of patients died. The 4 major pathways with a significant association to all-cause mortality were: 1) the PI3K/Akt pathway; 2) the MAPK pathway; 3) the Ras signaling pathway; and 4) epidermal growth factor receptor tyrosine kinase inhibitor resistance. Results were validated in an independent cohort of 1,738 patients.

    Conclusions: A systems biology approach integrating genomic, transcriptomic, and proteomic data identified 4 major pathways related to mortality. These pathways are related to decreased activation of the cardioprotective ERBB2 receptor, which can be modified by neuregulin.
    Original languageEnglish
    Pages (from-to)1921-1931
    Number of pages11
    JournalJournal of the American College of Cardiology
    Volume82
    Issue number20
    Early online date6 Nov 2023
    DOIs
    Publication statusPublished - 14 Nov 2023

    Keywords

    • Heart failure
    • machine learning
    • systems biology
    • heart failure
    • omics

    ASJC Scopus subject areas

    • Cardiology and Cardiovascular Medicine

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