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. 2024 Aug 21;9(10):1178-1191.
doi: 10.1016/j.jacbts.2024.05.017. eCollection 2024 Oct.

Proteome-Wide Genetic Investigation of Large Artery Stiffness

Marie-Joe Dib  1   2 , Joe David Azzo  2 , Lei Zhao  3 , Oday Salman  2 , Sushrima Gan  1   2 , Marc L De Buyzere  4 , Tim De Meyer  5 , Christina Ebert  3 , Kushan Gunawardhana  3 , Laura Liu  3 , David Gordon  3 , Dietmar Seiffert  3 , Chang Ching-Pin  3 , Payman Zamani  1   2 , Jordana B Cohen  2   6   7 , Bianca Pourmussa  2 , Seavmeiyin Kun  2 , Dipender Gill  8 , Stephen Burgess  9   10 , Vanessa van Empel  11 , A Mark Richards  12   13 , Jaclyn Dennis  14 , Ali Javaheri  15   16 , Douglas L Mann  15 , Thomas P Cappola  1   2 , Ernst Rietzschel  4 , Julio A Chirinos  1   2
Affiliations

Proteome-Wide Genetic Investigation of Large Artery Stiffness

Marie-Joe Dib et al. JACC Basic Transl Sci. .

Abstract

The molecular mechanisms contributing to large artery stiffness (LAS) are not fully understood. The aim of this study was to investigate the association between circulating plasma proteins and LAS using complementary proteomic and genomic analyses. A total of 106 proteins associated with carotid-femoral pulse-wave velocity, a noninvasive measure of LAS, were identified in 1,178 individuals from the Asklepios study cohort. Mendelian randomization analyses revealed causal effects of 13 genetically predicted plasma proteins on pulse pressure, including cartilage intermediate layer protein-2, high-temperature requirement A serine peptidase-1, and neuronal growth factor-1. These findings suggest potential novel therapeutic targets to reduce LAS and its related diseases.

Keywords: Asklepios study; Mendelian randomization; aortic stiffness; large artery stiffness; proteomics; pulse-wave velocity.

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Conflict of interest statement

Dr Chirinos is supported by National Institutes of Health grants R01-HL 121510, R33-HL-146390, R01HL153646, R01-AG058969, 1R01-HL104106, P01-HL094307, R03-HL146874, and R56-HL136730. Dr Cohen is supported by National Institutes of Health grants K23-HL133843 and R01-HL153646. Dr Gill is supported by the British Heart Foundation Centre of Research Excellence at Imperial College London (grant RE/18/4/34215). Dr Burgess is supported by the Wellcome Trust (grant 225790/Z/22/Z) and the United Kingdom Research and Innovation Medical Research Council (grant MC_UU_00002/7). Dr Zamani is supported by grants R01 HL155599, R01 HL157264, R01 HL149722, U01-HL160277, UH3DK128298. He also receives research support from Amgen. He has consulted for Pfizer and Vyaire. This research was supported by the National Institute for Health Research Cambridge Biomedical Research Centre (grant NIHR203312). The views expressed are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. Dr Chirinos has recently consulted for Bayer, Sanifit, Fukuda-Denshi, Bristol Myers Squibb, Johnson & Johnson, Edwards Lifesciences, Merck, and the Galway-Mayo Institute of Technology; has received University of Pennsylvania research grants from the National Institutes of Health, Fukuda-Denshi, Bristol Myers Squibb, and Microsoft; is named as an inventor on a patent related to the use of inorganic nitrate in heart failure with preserved ejection fraction and patent applications related to the use of plasma and urine protein biomarkers in heart failure with preserved ejection fraction; and has received research device loans from AtCor Medical, Fukuda-Denshi, Uscom, NDD Medical Technologies, Microsoft, and MicroVision Medical. Dr Zamani has received research support from Amgen. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

None
Graphical abstract
Figure 1
Figure 1
Associations Between All Plasma Proteins Measured in the Asklepios Study and Carotid-Femoral Pulse Wave Velocity Volcano plots showing associations between all plasma proteins measured in the Asklepios study and carotid-femoral pulse wave velocity in (A) the unadjusted robust regression model and (B) the model adjusted for age. Multiple instances of the same protein in this plot are due to the presence of multiple aptamers that can bind the same protein in our analyses. Detailed information is available in Supplemental Table 1. These plots show standardized regression estimates against the log10P value. The nominal significance level and the alpha-corrected significance level are represented by dashed lines on the y-axis.
Figure 2
Figure 2
Canonical Pathway Analysis of Proteins Significantly Associated With Carotid-Femoral Pulse-Wave Velocity Canonical pathway analysis of proteins significantly associated with carotid-femoral pulse-wave velocity in the robust linear regression model in the Asklepios study in the (A) unadjusted and (B) age-adjusted models. A principal-component analysis–corrected P value of 0.05 was used to determine the threshold of significance.
Figure 3
Figure 3
Mendelian Randomization Results for the Associations of Genetically Predicted Plasma Protein Levels in the deCODE and Fenland Data Sets With Pulse Pressure Only significant associations (false discovery rate–corrected P < 0.05) for each exposure data set are shown. Mendelian randomization estimates are reported as changes in pulse pressure (millimeters of mercury) per 1-SD change in genetically predicted plasma protein levels.
See this image and copyright information in PMC

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