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. 2024 Feb 6;83(5):577-591.
doi: 10.1016/j.jacc.2023.11.021.

Large-Scale Proteomics Identifies Novel Biomarkers and Circulating Risk Factors for Aortic Stenosis

Khaled Shelbaya  1 , Victoria Arthur  1 , Yimin Yang  1 , Pranav Dorbala  1 , Leo Buckley  1 , Brian Claggett  1 , Hicham Skali  1 , Line Dufresne  2 , Ta-Yu Yang  2 , James C Engert  2 , George Thanassoulis  2 , James Floyd  3 , Thomas R Austin  3 , Anna Bortnick  4 , Jorge Kizer  5 , Renata C C Freitas  1 , Sasha A Singh  1 , Elena Aikawa  1 , Ron C Hoogeveen  6 , Christie Ballantyne  6 , Bing Yu  7 , Josef Coresh  8 , Michael J Blaha  8 , Kunihiro Matsushita  8 , Amil M Shah  9
Affiliations

Large-Scale Proteomics Identifies Novel Biomarkers and Circulating Risk Factors for Aortic Stenosis

Khaled Shelbaya et al. J Am Coll Cardiol. .

Abstract

Background: Limited data exist regarding risk factors for aortic stenosis (AS). The plasma proteome is a promising phenotype for discovery of novel biomarkers and potentially causative mechanisms.

Objectives: The aim of this study was to discover novel biomarkers with potentially causal associations with AS.

Methods: We measured 4,877 plasma proteins (SomaScan aptamer-affinity assay) among ARIC (Atherosclerosis Risk In Communities) study participants in mid-life (visit 3 [V3]; n = 11,430; age 60 ± 6 years) and in late-life (V5; n = 4,899; age 76 ± 5 years). We identified proteins cross-sectionally associated with aortic valve (AV) peak velocity (AVmax) and dimensionless index by echocardiography at V5 and with incident AV-related hospitalization after V3 with the use of multivariable linear and Cox proportional hazard regression. We assessed associations of candidate proteins with changes in AVmax over 6 years and with AV calcification with the use of cardiac computed tomography, replicated analysis in an independent sample, performed Mendelian randomization, and evaluated gene expression in explanted human AV tissue.

Results: Fifty-two proteins cross-sectionally were associated with AVmax and dimensionless index at V5 and with risk of incident AV-related hospitalization after V3. Among 3,413 participants in the Cardiovascular Health Study, 6 of those proteins were significantly associated with adjudicated moderate or severe AS, including matrix metalloproteinase 12 (MMP12), complement C1q tumor necrosis factor-related protein 1 (C1QTNF1), and growth differentiation factor-15. MMP12 was also associated with greater increase in AVmax over 6 years, greater degree of AV calcification, and greater expression in calcific compared with normal or fibrotic AV tissue. C1QTNF1 had consistent potential causal effects on both AS and AVmax according to Mendelian randomization analysis.

Conclusions: These findings identify MMP12 as a potential novel circulating biomarker of AS risk and C1QTNF1 as a new putative target to prevent AS progression.

Keywords: aortic stenosis; echocardiography; epidemiology; proteomics.

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Conflict of interest statement

Funding Support and Author Disclosures The ARIC study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, under contract nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, and HHSN268201700004I. This study was also supported by NIH/NHLBI grants R01HL135008, R01HL143224, R01HL150342, R01HL148218, R01HL160025, and K24HL152008 to Dr Shah; R01HL136592 to Drs Matsushita and Blaha; R01HL141917 and R01 HL147095 to Dr Aikawa; K23HL146982 to Dr Bortnick; R01HL144483 to Dr Austin; R01HL142599 and R01HL149706 to Dr Floyd; R01HL128550 to Dr Thanassoulis; and K23HL150311, ASN/KidneyCure Carl W. Gottschalk Research Scholar Grant, and BWH Khoury Innovation Fund to Dr Buckley. Dr Thanassoulis is a Chercheur Boursier Clinicien—Senior from the Fonds de Recherche du Québec—Santé and holds operating grants from the Heart and Stroke Foundation of Canada. Drs Thanassoulis and Engert hold an operating grant from the Canadian Institutes for Health Research. Dr Skali has received consulting fees from Astellas; and has received research support from ABT Associates. Dr Thanassoulis has received consulting fees or participated in advisory boards or speakers bureau for Ionis Pharmaceuticals, Amgen, Sanofi, Novartis, HLS Therapeutics, New Amsterdam, and Silence. Dr Bortnick was the site principal investigator for a clinical trial by CSL-Behring; has received an unrestricted educational grant to her institution from Zoll; and has received a modest honorarium from ClearView Healthcare, outside the present work. Dr Kizer has stock ownership in Abbott, Bristol Myers Squibb, Johnson & Johnson, Medtronic, Merck, and Pfizer. Dr Aikawa is a Scientific Advisory Board member for Elastrin Therapeutics. Dr Hoogeveen has received consulting fees and research funds from Denka Seiken through Baylor College of Medicine, outside the present work. Dr Coresh is a member of the SomaLogic Scientific Advisory Board. Dr Blaha has Advisory Board membership for Novartis, Novo Nordisk, Bayer, Roche, Merck, Vectura, Boehringer Ingelheim, 89BioConsulting, Kowa, and Scene Health. Dr Matsushita has received honoraria from Fukuda Denshi and Kowa, outside the present work. Dr Shah has received consulting fees from Philips Ultrasound; and has received research funds from Novartis through Brigham and Women’s Hospital. The funders had no role in the design and conduct of this study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

FIGURE 1
FIGURE 1. Plasma Proteomics Associations With AV Hemodynamics and Incident AV-Related Hospitalization
(A) Cross-sectional associations of 4,877 aptamers with aortic valve peak velocity (AVmax) at visit 5; (B) associations of 946 AVmax-associated aptamers assessed at visit 3 with incident AV-hospitalizations after visit 3; (C) plot of beta-coefficient for associations with AVmax at visit 5 (x-axis) and HR for incident AV-related hospitalization after visit 3 (y-axis); (D) cross-sectional associations of 84 AVmax- and AV hospitalization–associated proteins with AV dimensionless index (DI) at visit 5. AV = aortic valve; BF@ = the statistical significance is Bonferroni corrected for the specified number of tests; FDR = false discovery rate.
FIGURE 1
FIGURE 1. Plasma Proteomics Associations With AV Hemodynamics and Incident AV-Related Hospitalization
(A) Cross-sectional associations of 4,877 aptamers with aortic valve peak velocity (AVmax) at visit 5; (B) associations of 946 AVmax-associated aptamers assessed at visit 3 with incident AV-hospitalizations after visit 3; (C) plot of beta-coefficient for associations with AVmax at visit 5 (x-axis) and HR for incident AV-related hospitalization after visit 3 (y-axis); (D) cross-sectional associations of 84 AVmax- and AV hospitalization–associated proteins with AV dimensionless index (DI) at visit 5. AV = aortic valve; BF@ = the statistical significance is Bonferroni corrected for the specified number of tests; FDR = false discovery rate.
FIGURE 2
FIGURE 2. Associations of Key Candidate Proteins With AV Hemodynamics and Calcification
(A) Heatmap of beta-coefficients for cross-sectional associations of candidate proteins with echocardiographic metrics of AV hemodynamics at visit 5 with candidate proteins clustered by means of hierarchic clustering. Only false discovery rate–significant associations are colored; (B) associations of candidate proteins assessed at study visit 5 with extent of AV calcification according to computed tomography at visit 7, with the use of multivariable ordinal regression; (C) restricted cubic spline of the association of macrophage metalloelastase 12 (MMP12) level assessed at visit 5 with the change in AVpeak over 6 years from visit 5 to 7. AOV_VTI = aortic valve velocity-time integral; AVA = aortic valve area; AVAi = AVA indexed to body surface area; DI = dimensionless index calculated as LVOT_VTI/AOV_VTI; LVOT_VTI = left ventricular outflow tract velocity-time integral; MG = mean gradient; Svi = stroke volume indexed to body surface area; other abbreviations as in Figure 1.
FIGURE 3
FIGURE 3. Key Candidate Proteins External Validation With Incident Aortic Stenosis in CHS
Plot of HR for incident AV-related hospitalization after visit 3 in the ARIC (Atherosclerosis Risk In Communities) study (x-axis) vs HR for incident adjudicated moderate or severe aortic stenosis in the CHS (Cardiovascular Health Study) for 52 key candidate proteins. AV = aortic valve; BF = Bonferroni corrected; FDR = false discovery rate.
FIGURE 4
FIGURE 4. Results of MR Analyses
(A) Mendelian randomization (MR) analyses for severe aortic stenosis (AS) for 42 candidate proteins with available genetic instruments. Manhattan plot demonstrates P values of MR analyses. Forest plot demonstrates direction and magnitude of effect of genetically higher protein levels for significant protein quantitative trait loci (pQTLs). (B) MR analyses for peak aortic valve velocity for LMAN2 and C1QTNF1. Hatched line indicates nominal significance (P < 0.05); solid purple and red lines indicate significance after Bonferroni multiple testing correction for number of proteins and number of pQTLs tested, respectively. pQTLs: red = nonsignificant; blue = nominally significant, green = significant after multiple testing correction for number of pQTLs tested; In Forest plot: blue = trans-pQTL; red = multi-Pqtl instrumental variable comprising both cis– and trans-–single-nucleotide polymorphisms.
FIGURE 5
FIGURE 5. Transcriptomic Analyses of Candidate Protein Genes From Explanted AV Tissue
(A) Comparison of transcript numbers in calcific vs normal AV tissue segments; (B) comparison of transcript numbers in calcific vs fibrotic AV tissue segments; (C) comparison of transcript numbers in fibrotic vs normal AV tissue segments. Red bars indicate significant between-group differences. AV = aortic valve.
CENTRAL ILLUSTRATION
CENTRAL ILLUSTRATION. Schematic Overview of Study Design
Protein discovery through consistent associations with aortic valve (AV) hemodynamics and events, followed by additional analyses. ARIC = Atherosclerosis Risk In Communities; CT = computed tomography; DI = dimensionless index.
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References

    1. Nkomo VT, Gardin JM, Skelton TN, Gottdiener JS, Scott CG, Enriquez-Sarano M. Burden of valvular heart diseases: a population-based study. Lancet. 2006;368:1005–1011. - PubMed
    1. Coffey S, Roberts-Thomson R, Brown A, et al. Global epidemiology of valvular heart disease. Nature Reviews Cardiology. 2021. - PubMed
    1. d’Arcy JL, Coffey S, Loudon MA, et al. Large-scale community echocardiographic screening reveals a major burden of undiagnosed valvular heart disease in older people: the OxVALVE population cohort study. Eur Heart J 2016;37:3515–3522. - PMC - PubMed
    1. Osnabrugge RL, Mylotte D, Head SJ, et al. Aortic stenosis in the elderly: disease prevalence and number of candidates for transcatheter aortic valve replacement: a meta-analysis and modeling study. J Am Coll Cardiol 2013;62:1002–1012. - PubMed
    1. Miller JD, Weiss RM, Serrano KM, et al. Lowering plasma cholesterol levels halts progression of aortic valve disease in mice. Circulation. 2009;119:2693–2701. - PMC - PubMed

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