Deciphering the molecular effects of physical activity by a targeted proteomics approach in individuals with heart failure

Physical activity (PA) is essential for preventing chronic disease, including cardiovascular disease. In particular, patients with heart failure (HF) profit from increased PA. Despite the widely recognized benefits of PA, the underlying molecular pathways still remain poorly understood. This study aimed to elucidate the proteomic signature of PA in HF using a targeted proteomics approach. Differences in the molecular signature dependent on the dimension and extent of PA were explored. 

 

The study analyzed 685 individuals with established HF from the MyoVasc Study, a prospective cohort study on chronic heart failure (NCT04064450). All individuals were profiled for 538 proteins in blood plasma using six different panels employing proximity extension assay technology (Olink, Uppsala, Sweden). Physical activity (PA) was assessed across various dimensions using the standardized Short QUestionnaire to ASsess Health-enhancing PA (SQUASH).  A continuous total weekly PA score was calculated. 

Elastic net-regularized linear regression, adjusted for age and sex, was used to select proteins related to the total weekly PA score. Protein-protein interaction networks and pathway enrichment analysis were performed. To determine the clinical relevance of the PA signature, an aggregate score derived from the selected proteins was used in Cox regression models. The score was investigated in relation to cardiovascular risk factors, comorbidities, and subclinical markers.

A total of 56 proteins was found to be related to total weekly PA. The proteins were associated with various molecular pathways, including chemokine- and cytokine-related inflammatory processes, lipoprotein metabolism, growth factor regulation, and blood vessel development. The proteomic PA score was predictive of all-cause death (hazard ratio [95% CI]: 0.63 [0.58; 0.69], p<0.0001) and worsening of HF (hazard ratio [95% CI]: 0.71 [0.63; 0.79], p<0.0001), after adjustment for age and sex, cardiovascular risk factors and comorbidities. Regression models revealed significant associations between the proteomic PA score and several cardiovascular risk factors and comorbidities, for example arterial hypertension and diabetes mellitus. Additionally, associations were found with selected subclinical markers in the area of cardiac structure and function, cardiopulmonary exercise capacity, and heart rate variability.

This targeted proteomics approach identified a protein signature associated with weekly PA and related molecular pathways. The signature was related to various risk factors and subclinical markers of disease, improving the understanding of the mechanisms behind PA in HF. Future proteomic profiling of data over time holds the potential to monitor changes in the selected PA proteins and the progression of HF.