Dissecting the Heart Failure Phenotype Through Phenomics

This article refers to 'Distinguishing heart failure with reduced ejection fraction from heart failure with preserved ejection fraction: A phenomics approach' by B.J. van Essen et al., published in this issue on pages 841-850.Since 2016, patients with heart failure (HF) have been categorized into three groups based on their left ventricular ejection fraction (LVEF): HF with reduced ejection fraction (HFrEF, LVEF ≤40%), HF with mildly reduced EF (HFmrEF, LVEF 41-49%), and HF with preserved ejection fraction (HFpEF, LVEF ≥50%). 1 HFrEF has been extensively studied, but HFpEF represents over 50% of all HF cases. 2 Individuals with HFpEF are typically older, female, and have more often comorbidities such as hypertension, diabetes, obesity, pulmonary or liver disease, and sleep apnoea, compared to those with HFrEF.[3][4][5] These comorbidities likely contribute to HFpEF development through mechanisms like increased ventricular stiffness, inflammation, and oxidative stress.6 A recent study showed that different, although somewhat overlapping, sets of proteins could predict both incident HFrEF and HFpEF.7 Despite progress, the molecular pathways of HFrEF and HFpEF remain only partially understood.Advances in omics technologies offer a comprehensive approach to elucidating the complex molecular pathways and clinical manifestations of HF.Each omics discipline focuses on a specific type of molecule: genomics on DNA sequences, epigenomics on epigenetic modifications, transcriptomics on RNA transcripts, proteomics on proteins, metabolomics on metabolites, and lipidomics on lipids.Historically, HF studies have examined single omics datasets in isolation, often without integrating these findings with clinical data.[8][9][10][11][12] Phenomics, integrating 'phenotypical' and 'omics' data, is a novel discipline seeking to understand the molecular underpinnings of disease manifestations, progression, prognostic markers and treatment responses.13 Through a multi-step process, omics and phenotypic data are collected and analysed using bioinformatics andThe opinions expressed in this article are not necessarily those of the Editors of the European Journal of Heart Failure or of the European Society of Cardiology.