The modifiable risk landscape of degenerative aortic valve disease

Background Degenerative aortic valvular heart disease (DAVD) is rising rapidly with population ageing. Current international guidelines provide no pharmacological recommendations to prevent DAVD onset or slow progression; management largely relies on surveillance until disease severity warrants surgical or transcatheter intervention. Identifying modifiable risk factors is therefore essential to enable upstream prevention. Purpose To comprehensively identify the modifiable exposome of aortic stenosis (AS) and aortic regurgitation (AR), characterize their distinct risk profiles across clinical endpoints and continuous haemodynamic measures, and quantify the preventable disease burden. Methods We analysed 362,868 UK Biobank participants without baseline valvular disease. An exposome-wide association study (ExWAS) was conducted to test 211 modifiable variables across seven domains. Incident AS/AR and valve-related intervention or mortality were analysed using Cox models. To extend beyond clinical events, we assessed subclinical haemodynamics in a cardiac MRI subcohort with over 43,000 participants. Deep learning-derived flow traits (peak aortic velocity and regurgitation volume) were modelled against exposures using linear regression. Analyses adjusted for age, sex, and assessment centre, and multiple testing was controlled by FDR. We calculated weighted domain scores and population attributable fractions (PAFs) to quantify the multi-domain effect and preventable burden. Results Over a median 13.3 years of follow-up, 4,755 participants developed AS and 1,663 developed AR. ExWAS identified 109 exposures associated with AS, revealing a broad cardiometabolic-inflammatory and psychosocial risk signature (adiposity, insulin resistance, stress-related factors) that was directionally consistent with higher peak aortic velocity and AS-related events. In contrast, AR showed a narrower profile with 30 associated exposures, predominantly reflecting haemodynamic load and structural or inflammatory comorbidities. Across domains, unfavourable exposure profiles were independently associated with higher incidence of AS/AR compared with favourable profiles. Weighted PAFs suggested that 62.0% of AS and 40.7% of AR could be preventable by shifting unfavourable to favourable exposure profiles, mainly driven by medical conditions (17.1% for AS; 13.1% for AR), physical profile (13.4%; 10.1%), and lifestyles (11.9%; 7.2%). Conclusions DAVD may be largely preventable, with distinct modifiable signatures for AS versus AR. These findings support a shift from late-stage intervention to upstream prevention prioritising cardiometabolic inflammation and haemodynamic stress.