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Shared proteomic landscape between arteriosclerosis and cardiovascular endpoints: a Mendelian randomization and
Jingxian Huang1,2, Devendra Meena1,2,3, Margaux Achtari1
1Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, White City Campus, 90 Wood Lane, London, W12 0BZ, UK.
Aims:
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 co-localization, Mendelian randomization (MR), and structural modelling to explore the shared and distinct plasma proteome associated with arteriosclerosis and atherosclerosis across different vascular beds.
Methods And Results:
We leveraged cis-protein quantitative trait loci (pQTLs) for 5813 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 co-localization and bidirectional MR. We validated and replicated the findings through independent proteomics datasets, 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. We prioritized 10 proteins potentially causally associated with both the arteriosclerotic/atherosclerotic markers and cardiovascular events. Five of them (ANGPTL4, apolipoprotein B [APOB], BRAP, lipoprotein(a) [LPA], and ZPR1) were associated with increased levels of arteriosclerosis/atherosclerosis and risk of CVD, whereas four (DUSP13, FN1, IL6R, and matrix metalloproteinase 12 [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 arterial stiffness index (ASI). Of these, seven were replicated in an independent pQTLs data source from the Fenland study. Mediation analyses estimated that LPA's effect on stroke was primarily mediated through carotid plaque (92.4%). 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.
Conclusion:
The present study elucidates the shared and distinct proteomic signatures across arteriosclerosis, atherosclerosis, and CVD, 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.
