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Multiomics Analysis Provides Novel Pathways Related to Progression of Heart Failure
Wouter Ouwerkerk1, Joao P Belo Pereira2, Troy Maasland3
1Department of Dermatology, Amsterdam Infection and Immunity Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; National Heart Centre Singapore, Singapore.
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.
Insights
Integrating multi-omics data in heart failure patients revealed four key mortality pathways, including PI3K/Akt and MAPK signaling. Targeting these pathways may improve outcomes for heart failure (HF) patients.
Area of Science:
- Cardiovascular Research
- Systems Biology
- Genomics and Proteomics
Background:
- Despite advancements in heart failure (HF) pharmacotherapy, high residual mortality persists, indicating untargeted pathways.
- Current HF treatments do not address all critical biological mechanisms driving disease progression and mortality.
Purpose of the Study:
- To integrate multi-omics data (genetic, transcriptomic, proteomic) in a large heart failure cohort.
- To identify key molecular pathways associated with all-cause mortality in heart failure patients.
- To discover novel therapeutic targets for heart failure.
Main Methods:
- Employed machine learning (stacked generalization, gradient boosting) on data from 2,516 heart failure patients (BIOSTAT-CHF study).
- Integrated clinical phenotypes, plasma proteins, whole blood transcript levels, and genomic markers.
- Validated findings in an independent cohort of 1,738 patients.
Main Results:
- Identified four major pathways significantly associated with all-cause mortality: PI3K/Akt, MAPK, Ras signaling, and EGFR tyrosine kinase inhibitor resistance.
- The study cohort comprised older adults (mean age 70) with advanced HF (median NT-proBNP 4,275 ng/L).
- Observed a 26% mortality rate over a median follow-up of 21 months, with results confirmed in a validation cohort.
Conclusions:
- A systems biology approach successfully identified four critical pathways linked to heart failure mortality.
- These pathways involve decreased activation of the ERBB2 receptor, potentially modifiable by neuregulin.
- Findings suggest novel therapeutic strategies targeting these identified pathways for heart failure management.
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