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Proteomic profiling for detection of early-stage heart failure in the community
Nicholas Cauwenberghs1, František Sabovčik1, Alessio Magnus1
1Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Campus Sint Rafaël, Kapucijnenvoer 7, Box 7001, Leuven, B-3000, Belgium.
Insights
Researchers identified 13 key proteins linked to early heart failure stages. Proteomic phenomapping effectively identified individuals at high risk for cardiac remodelling and dysfunction, aiding early detection.
Area of Science:
- Cardiology
- Proteomics
- Biomarker Discovery
Background:
- Heart remodelling and dysfunction are complex processes.
- Circulating biomarkers can offer insights into the molecular mechanisms of heart disease.
- Early detection of heart failure is crucial for effective management.
Purpose of the Study:
- To identify circulating protein biomarkers associated with early stages of heart failure.
- To explore the utility of proteomic profiling and machine learning in detecting cardiac abnormalities.
- To stratify individuals into distinct phenogroups based on protein profiles for risk assessment.
Main Methods:
- A cohort of 575 community-based participants underwent echocardiography and proteomic profiling using the CVD II panel.
- Partial least squares-discriminant analysis (PLS-DA) and eXtreme Gradient Boosting (XGBoost) were employed to identify key proteins.
- Gaussian mixture modelling was used for unbiased clustering to construct phenogroups based on influential proteins.
Main Results:
- Thirteen proteins, including placental growth factor, kidney injury molecule-1, and matrix metalloproteinase-7, were identified as important for detecting cardiac abnormalities.
- Proteomic phenomapping divided the cohort into two distinct phenogroups.
- One phenogroup (n=118) exhibited an unfavourable cardiovascular risk profile and increased risk of echocardiographic abnormalities (P < 0.0001).
Conclusions:
- Proteins associated with renal function, extracellular matrix remodelling, angiogenesis, and inflammation are linked to early heart failure.
- Proteomic phenomapping is a valuable tool for discriminating individuals at high risk for cardiac remodelling and dysfunction.
- This approach aids in the early identification and risk stratification of individuals with early-stage heart failure.
Aims:
Biomarkers may provide insights into molecular mechanisms underlying heart remodelling and dysfunction. Using a targeted proteomic approach, we aimed to identify circulating biomarkers associated with early stages of heart failure.
Methods And Results:
A total of 575 community-based participants (mean age, 57 years; 51.7% women) underwent echocardiography and proteomic profiling (CVD II panel, Olink Proteomics). We applied partial least squares-discriminant analysis (PLS-DA) and a machine learning algorithm [eXtreme Gradient Boosting (XGBoost)] to identify key proteins associated with echocardiographic abnormalities. We used Gaussian mixture modelling for unbiased clustering to construct phenogroups based on influential proteins in PLS-DA and XGBoost. Of 87 proteins, 13 were important in PLS-DA and XGBoost modelling for detection of left ventricular remodelling, left ventricular diastolic dysfunction, and/or left atrial reservoir dysfunction: placental growth factor, kidney injury molecule-1, prostasin, angiotensin-converting enzyme-2, galectin-9, cathepsin L1, matrix metalloproteinase-7, tumour necrosis factor receptor superfamily members 10A, 10B, and 11A, interleukins 6 and 16, and α1-microglobulin/bikunin precursor. Based on these proteins, the clustering algorithm divided the cohort into two distinct phenogroups, with each cluster grouping individuals with a similar protein profile. Participants belonging to the second cluster (n = 118) were characterized by an unfavourable cardiovascular risk profile and adverse cardiac structure and function. The adjusted risk of presenting echocardiographic abnormalities was higher in this phenogroup than in the other (P < 0.0001).
Conclusions:
We identified proteins related to renal function, extracellular matrix remodelling, angiogenesis, and inflammation to be associated with echocardiographic signs of early-stage heart failure. Proteomic phenomapping discriminated individuals at high risk for cardiac remodelling and dysfunction.
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