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Measured and Genetically Predicted Protein Levels and Cardiovascular Diseases in UK Biobank and China Kadoorie Biobank

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Publisher Springer Nature
Date 2024 Sep 25
PMID 39322770
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Abstract

Several large-scale studies have measured plasma levels of the proteome in individuals with cardiovascular diseases (CVDs). However, since the majority of such proteins are interrelated, it is difficult for observational studies to distinguish which proteins are likely to be of etiological relevance. Here we evaluate whether plasma levels of 2,919 proteins measured in 52,164 UK Biobank participants are associated with incident myocardial infarction, ischemic stroke or heart failure. Of those proteins, 126 were associated with all three CVD outcomes and 118 were associated with at least one CVD in the China Kadoorie Biobank. Mendelian randomization and colocalization analyses indicated that genetically determined levels of 47 and 18 proteins, respectively, were associated with CVDs, including FGF5, PROCR and FURIN. While the majority of protein-CVD observational associations were noncausal, these three proteins showed evidence to support potential causality and are therefore promising targets for drug treatment for CVD outcomes.

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References
1.
Lind L, Zanetti D, Ingelsson M, Gustafsson S, Arnlov J, Assimes T . Large-Scale Plasma Protein Profiling of Incident Myocardial Infarction, Ischemic Stroke, and Heart Failure. J Am Heart Assoc. 2021; 10(23):e023330. PMC: 9075402. DOI: 10.1161/JAHA.121.023330. View

2.
Surendran P, Drenos F, Young R, Warren H, Cook J, Manning A . Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension. Nat Genet. 2016; 48(10):1151-1161. PMC: 5056636. DOI: 10.1038/ng.3654. View

3.
Finan C, Gaulton A, Kruger F, Lumbers R, Shah T, Engmann J . The druggable genome and support for target identification and validation in drug development. Sci Transl Med. 2017; 9(383). PMC: 6321762. DOI: 10.1126/scitranslmed.aag1166. View

4.
Lind L, Arnlov J, Lindahl B, Siegbahn A, Sundstrom J, Ingelsson E . Use of a proximity extension assay proteomics chip to discover new biomarkers for human atherosclerosis. Atherosclerosis. 2015; 242(1):205-10. DOI: 10.1016/j.atherosclerosis.2015.07.023. View

5.
Davey Smith G, Holmes M, Davies N, Ebrahim S . Mendel's laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues. Eur J Epidemiol. 2020; 35(2):99-111. PMC: 7125255. DOI: 10.1007/s10654-020-00622-7. View