What are the predictors of cardiovascular aging?

New research highlights several genetic variations and environmental factors to play a role in cardiovascular aging.

Cardiovascular disease is a leading cause of death globally, with aging being a primary risk factor for its development and progression. Cardiovascular aging is a structural and functional change in the heart that occurs mostly in older individuals [1]. It can affect different organ systems leading to irreparable accumulation of damage.

A few common hallmarks of cardiovascular aging include loss of proteostasis, disabled macroautophagy, mitochondrial dysfunction, epigenetic alterations, genomic instability, dysregulated neurohormonal signaling, cell senescence and inflammation [2]. Maintaining a good cardiovascular health is important for a healthy lifespan and a longer life.

Longevity.Technology: Immunological, metabolic and biophysical factors may lead to cellular senescence and end-organ damage that affects the circulatory system as well as the heart. A common pathway of cardiovascular aging involves changes in tissue compliance leading to vascular remodeling, interstitial fibrosis and diastolic dysfunction. Non-invasive imaging can help to assess such changes and determine how an individual’s cardiovascular system has aged as compared with a normal population.

A new study published in Nature Communications uses machine learning approaches for quantification of cardiovascular age from conduction traits from electrocardiograms, image-derived traits of vascular function, as well as cardiac motion and myocardial fibrosis in 39,559 participants of the UK Biobank [3].

“We first trained a machine learning model to define healthy cardiovascular aging in a development set determined to be free of cardiac, respiratory and metabolic disease, using a gradient boosting algorithm (CatBoost),” says the team of researchers [3]. They computed an age-delta to determine the difference between chronological and predicted age. Following this, they analyzed cardiovascular age-delta association with traditional cardiovascular risk factors as well as identified phenotypes associated with age-delta.

The results reported that there were no correlations between chronological age and cardiovascular age; however, there was a strong correlation between chronological age and predicted age. Arterial distensibility, in both ascending and descending aorta was found to be the strongest predictor of age-delta.

Several morphological and functional changes in the heart were reported with age, including a decrease in left ventricular volume and an increase in wall thickness, along with regional changes in left ventricular diastolic relaxation and systolic contraction. As per regression analyses, age-delta was reported to be associated with metabolic and circulatory disorders, having the strongest associations with hypertension and diabetes. It was also observed to be higher in males with obesity and females with coronary artery disease. Other factors that adversely impacted cardiovascular aging involved serum levels of LDL, triglyceride and apolipoprotein B, alcohol consumption, as well as smoking [3].

The results also reported associations between cardiovascular age-delta and major adverse cardiovascular events in a covariate-adjusted model. Additionally, beta-blockers and metformin medications were reported to increase cardiovascular age while calcium-channel blockers were found to be favorable for cardiovascular age. Variation in a cardiomyopathy-associated gene (TTN) was observed in antihypertensive responses and pro-inflammatory activity with aging. Overall, 10.5% single nucleotide polymorphisms (SNPs)-based heritability of cardiovascular aging was reported which suggests non-genetic contributors play a major role in aging. Finally, rare variants were identified in two genes that were also associated with cardiovascular aging, these were Mitochondrial Calcium Uptake Family Member 3 (MICU3) and Triggering Receptor Expressed On Myeloid Cells 2 (TREM2).

The researchers conclude that cardiovascular aging is affected by common and rare genetic variants, certain prescribed medications, as well as cardiometabolic risk factors. However, further research is required involving diverse populations and a longer follow up period to confirm such findings.

[1] https://www.frontiersin.org/articles/10.3389/fcvm.2021.728228/full
[2] https://pubmed.ncbi.nlm.nih.gov/37193857/
[3] https://www.nature.com/articles/s41467-023-40566-6