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.

The authors have declared no competing interest.

We acknowledge support from the Imperial College British Heart Foundation Centre for Research Excellence (RE/18/4/34215), the UK Dementia Research Institute at Imperial College London (MC_PC_17114), and the NIHR Imperial Biomedical Research Centre (BRC).

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The UKB-PPP data are available at http://ukb-ppp.gwas.eu, and the deCODE genetics proteomics data can be accessed at https://www.decode.com/summarydata/. GWAS summary statistics for ASI and CAC are available from the GWAS Catalog (https://www.ebi.ac.uk/gwas/) under accession numbers GCST008403 and GCST90278456, respectively. Data for cIMT and carotid plaque were obtained from dbGaP under CHARGE study accession number phs000930.v6.p1, and for PAD under accession number phs001672.v2.p1. Stroke and its subtypes are available via the GWAS Catalog (GCST90104534 to GCST90104563). Summary statistics CAD, myocardial infarction, and heart failure are also accessible through the GWAS Catalog under accession numbers GCST005194, GCST011365, and GCST009541, respectively.

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The UKB-PPP data are available at http://ukb-ppp.gwas.eu, and the deCODE genetics proteomics data can be accessed at https://www.decode.com/summarydata/. GWAS summary statistics for ASI and CAC are available from the GWAS Catalog (https://www.ebi.ac.uk/gwas/) under accession numbers GCST008403 and GCST90278456, respectively. Data for cIMT and carotid plaque were obtained from dbGaP under CHARGE study accession number phs000930.v6.p1, and for PAD under accession number phs001672.v2.p1. Stroke and its subtypes are available via the GWAS Catalog (GCST90104534 to GCST90104563). Summary statistics CAD, myocardial infarction, and heart failure are also accessible through the GWAS Catalog under accession numbers GCST005194, GCST011365, and GCST009541, respectively.