Shared proteomic landscape between arteriosclerosis and cardiovascular endpoints: a Mendelian randomization and observational study integrating AlphaFold3 for structural prediction
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background
Atherosclerosis and arteriosclerosis are major contributors to cardiovascular disease (CVD), yet their shared and distinct molecular underpinnings remain incompletely understood. This study integrates proteomics, Bayesian colocalization, and Mendelian randomization (MR), and structural modelling to explore the shared and distinct plasma proteome associated with arteriosclerosis and atherosclerosis across different vascular beds.
Methods
We leveraged cis -pQTLs for 5,813 unique proteins from the UK Biobank (UKB) Pharma Proteomics Project (N=54,219) and deCODE genetics (N=35,559) and assessed the association with five arteriosclerotic/atherosclerotic markers, as well as eight cardiovascular events, using Bayesian colocalization and bidirectional MR. We validated the findings through tissue-specific transcriptomics, observational data from UKB, and AlphaFold3 for structural prediction. Finally, mediation analysis evaluated the role of vascular traits in linking proteins to CVD risk.
Results
We prioritized ten proteins potentially causally associated with both the arteriosclerotic/atherosclerotic markers and cardiovascular events. Five of them (ANGPTL4, APOB, BRAP, LPA, and ZPR1), were associated with increased levels of arteriosclerosis/ atherosclerosis and risk of CVD, whereas four (DUSP13, FN1, IL6R, and MMP12) were associated with reduced levels of arteriosclerosis/ atherosclerosis and risk of CVD. ABO was associated with increased risk of peripheral artery disease (PAD) and CVD but inversely related to ASI. Mediation analyses estimated that LPA’s effect on stroke was primarily mediated through carotid plaque (92.4%), while DUSP13’s effect on coronary artery disease was primarily mediated via PAD (91.0%). Observational analyses and transcriptomic validation corroborated these associations. Structural modelling using AlphaFold3 identified key functional variants in several proteins, including ANGPTL4 and FN1, potentially underlying the pathogenic mechanists.
Conclusions
The present study elucidates the shared and distinct proteomic signatures across arteriosclerosis, atherosclerosis, and cardiovascular disease, underscoring the importance of vascular-bed-specific mechanisms. These identified proteins offer promising avenues for biomarker-driven risk stratification and therapeutic interventions, with potential for dual-purpose interventions across vascular territories.
