Environmental and genetic predictors of human cardiovascular ageing

Area of Science:

• Cardiovascular Biology
• Genetics
• Computational Biology

Background:

• Cardiovascular ageing involves progressive structural changes and functional decline due to accumulated cellular damage.
• Factors like biophysical, metabolic, and immunological stress overwhelm repair mechanisms, leading to fibrosis and senescence.
• The genetic underpinnings of cardiovascular ageing remain largely unknown.

Purpose of the Study:

• To investigate the genetic architecture of cardiovascular ageing.
• To quantify cardiovascular age using machine learning and diverse physiological traits.
• To identify genetic variants and factors influencing accelerated cardiovascular ageing.

Main Methods:

• Utilized machine learning to quantify cardiovascular age from UK Biobank data (39,559 participants).
• Integrated image-derived traits (vascular function, cardiac motion, fibrosis) and electrocardiogram data.
• Performed genome-wide association studies to identify genetic variants associated with cardiovascular age.

Main Results:

• Identified significant associations between cardiovascular ageing and genetic variants in genes regulating sarcomere homeostasis, immune response, and stress response.
• Cardiovascular ageing is accelerated by cardiometabolic risk factors.
• Discovered potential modifying effects of prescribed medications on cardiovascular ageing.

Conclusions:

• Revealed insights into mechanisms driving premature cardiovascular ageing through large-scale multi-trait modeling.
• Highlighted the role of specific genetic pathways in cardiovascular ageing.
• Identified potential molecular targets for attenuating age-related cardiovascular decline.