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. 2023 Nov 14;82(20):1906-1920.
doi: 10.1016/j.jacc.2023.09.804.

Plasma Proteomics to Identify Drug _targets for Ischemic Heart Disease

Mohsen Mazidi  1 , Neil Wright  1 , Pang Yao  1 , Christiana Kartsonaki  2 , Iona Y Millwood  2 , Hannah Fry  2 , Saredo Said  1 , Alfred Pozarickij  1 , Pei Pei  3 , Yiping Chen  2 , Daniel Avery  1 , Huaidong Du  2 , Dan Valle Schmidt  1 , Ling Yang  2 , Jun Lv  4 , Canqing Yu  4 , Junshi Chen  5 , Michael Hill  2 , Michael V Holmes  1 , Joanna M M Howson  6 , Richard Peto  1 , Rory Collins  1 , Derrick A Bennett  2 , Robin G Walters  2 , Liming Li  4 , Robert Clarke  7 , Zhengming Chen  8 ; China Kadoorie Biobank Collaborative Group
Collaborators, Affiliations

Plasma Proteomics to Identify Drug _targets for Ischemic Heart Disease

Mohsen Mazidi et al. J Am Coll Cardiol. .

Abstract

Background: Integrated analyses of plasma proteomic and genetic markers in prospective studies can clarify the causal relevance of proteins and discover novel _targets for ischemic heart disease (IHD) and other diseases.

Objectives: The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments.

Methods: We conducted a nested case-cohort study in the China Kadoorie Biobank (CKB) involving 1,971 incident IHD cases and 2,001 subcohort participants who were genotyped and free of prior cardiovascular disease. We measured 1,463 proteins in the stored baseline samples using the OLINK EXPLORE panel. Cox regression yielded adjusted HRs for IHD associated with individual proteins after accounting for multiple testing. Moreover, cis-protein quantitative loci (pQTLs) identified for proteins in genome-wide association studies of CKB and of UK Biobank were used as instrumental variables in separate 2-sample Mendelian randomization (MR) studies involving global CARDIOGRAM+C4D consortium (210,842 IHD cases and 1,378,170 controls).

Results: Overall 361 proteins were significantly associated at false discovery rate <0.05 with risk of IHD (349 positively, 12 inversely) in CKB, including N-terminal prohormone of brain natriuretic peptide and proprotein convertase subtilisin/kexin type 9. Of these 361 proteins, 212 had cis-pQTLs in CKB, and MR analyses of 198 variants in CARDIOGRAM+C4D identified 13 proteins that showed potentially causal associations with IHD. Independent MR analyses of 307 cis-pQTLs identified in Europeans replicated associations for 4 proteins (FURIN, proteinase-activated receptor-1, Asialoglycoprotein receptor-1, and matrix metalloproteinase-3). Further downstream analyses showed that FURIN, which is highly expressed in endothelial cells, is a potential novel _target and matrix metalloproteinase-3 a potential repurposing _target for IHD.

Conclusions: Integrated analyses of proteomic and genetic data in Chinese and European adults provided causal support for FURIN and multiple other proteins as potential novel drug _targets for treatment of IHD.

Keywords: Mendelian randomization; diverse populations; drug _target; genetics; ischemic heart disease; plasma proteomics; prospective studies.

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Conflict of interest statement

Funding Support and Author Disclosures The CKB baseline survey and the first resurvey were supported by the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up and subsequent resurveys have been supported by Wellcome grants to Oxford University (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z) and grants from the National Natural Science Foundation of China (82192901, 82192904, 82192900) and from the National Key Research and Development Program of China (2016YFC0900500). The UK Medical Research Council (MC_UU_00017/1, MC_UU_12026/2, MC_U137686851), Cancer Research UK (C16077/A29186, C500/A16896), and British Heart Foundation (CH/1996001/9454) provide core funding to the Clinical Trial Service Unit and Epidemiological Studies Unit, Oxford University for the project. The proteomic assays were supported by a BHF Intermediate Clinical Research Fellowship to MVH (FS/18/23/33512), Novo Nordisk, and OLINK. DNA extraction and genotyping were supported by GlaxoSmithKline and the UK Medical Research Council (MC-PC-13049, MC-PC-14135). Dr Holmes is currently employed by 23andMe (and owns stock in 23andMe, Inc). Dr Howson is a full-time employee of Novo Nordisk Research Centre Oxford Limited and owns shares in Novo Nordisk. 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
Summary of Study Design, Analytic Approaches, and Key Findings The study design involved observational and genetic analyses in the China Kadoorie Biobank (CKB) and UK Biobank (UKB) studies. The observational associations of proteomics with ischemic heart disease (IHD) were replicated using Mendelian randomization (MR) approaches using instrumental variables discovered in CKB and replicated in UKB. The downstream analyses included phenome-wide associations (PheWAS), knockout models (KO), assessment of enrichment, and functional genome-wide association study analyses (FGWAS), respectively.
Central Illustration
Central Illustration
Plasma Proteomics Identifies Novel Drug _targets for Ischemic Heart Disease The study involved: (A) analyses of associations of 1,463 proteins with ischemic heart disease (IHD) in Chinese adults; (B) confirmation of associations of cis- protein quantitative loci (pQTLs) for such associated proteins using genetic analyses in CARDIOGRAM+C4D (CC4D); (C) replication of cis-pQTLs in Europeans; and (D) downstream analyses to discover novel drug _targets for treatment of IHD. ASGR1 = asialoglycoprotein receptor 1; F2R = proteinase-activated receptor 1; FGWAS = functional genome-wide association study analyses; IHD = ischemic heart disease; KO = knockout; MMP3 = matrix metalloproteinase-3; PheWAS = phenome-wide associations.
Figure 2
Figure 2
Adjusted HRs of IHD Associated With 1,463 Proteins in CKB The volcano plots show the associations of proteins with IHD stratified by OLINK panels in CKB after adjustment for confounding factors. All models were stratified by sex and region and adjusted for age, age2, fasting time, fasting time2, ambient temperature, ambient temperature2, plate identification, education, smoking, alcohol consumption, physical activity, systolic blood pressure (SBP), type 2 diabetes, ApoB/ApoA, and body mass index (BMI). Red, blue, and gray dots denote positive significant, inverse significant, and nonsignificant associations, respectively. Time in study was used as time scale in all models. Apo = apolipoprotein; other abbreviations as in Figure 1.
Figure 3
Figure 3
Adjusted HRs of IHD Associated With Selected Leading Proteins in CKB Forest plot shows adjusted HRs of IHD for proteins most strongly associated with IHD for cardiometabolic, inflammation, neurology, and oncology panels. The numbers of significantly associated proteins on each panel are shown and results for individual proteins are displayed. The models were adjusted for covariates as in Figure 2. The boxes are HRs and the horizontal lines are 95% CIs. The area of each box is inversely proportional to the variance of the log HR. Abbreviations as in Figure 1.
Figure 3
Figure 3
Adjusted HRs of IHD Associated With Selected Leading Proteins in CKB Forest plot shows adjusted HRs of IHD for proteins most strongly associated with IHD for cardiometabolic, inflammation, neurology, and oncology panels. The numbers of significantly associated proteins on each panel are shown and results for individual proteins are displayed. The models were adjusted for covariates as in Figure 2. The boxes are HRs and the horizontal lines are 95% CIs. The area of each box is inversely proportional to the variance of the log HR. Abbreviations as in Figure 1.
Figure 4
Figure 4
Replication of Observational Analyses in CKB in Genetic Analyses in CARDIOGRAM+C4D (A) The HRs (95% CI) of IHD per 1-SD higher protein concentration in CKB after adjustment for confounding factors. (B) The ORs (95% CI) of IHD in CARDIOGRAM+C4D per 1-SD higher protein concentration for these proteins in MR analyses. Symbols and conventions as in Figure 3.
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