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Møller PL, Rohde PD, Dahl JN, Rasmussen LD, Nissen L, Schmidt SE, McGilligan V, Gudbjartsson DF, Stefansson K, Holm H, Bentzon JF, Bøttcher M, Winther S, Nyegaard M. Predicting the presence of coronary plaques featuring high-risk characteristics using polygenic risk scores and targeted proteomics in patients with suspected coronary artery disease. Genome Med 2024; 16:40. [PMID: 38509622 PMCID: PMC10953133 DOI: 10.1186/s13073-024-01313-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 03/12/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND The presence of coronary plaques with high-risk characteristics is strongly associated with adverse cardiac events beyond the identification of coronary stenosis. Testing by coronary computed tomography angiography (CCTA) enables the identification of high-risk plaques (HRP). Referral for CCTA is presently based on pre-test probability estimates including clinical risk factors (CRFs); however, proteomics and/or genetic information could potentially improve patient selection for CCTA and, hence, identification of HRP. We aimed to (1) identify proteomic and genetic features associated with HRP presence and (2) investigate the effect of combining CRFs, proteomics, and genetics to predict HRP presence. METHODS Consecutive chest pain patients (n = 1462) undergoing CCTA to diagnose obstructive coronary artery disease (CAD) were included. Coronary plaques were assessed using a semi-automatic plaque analysis tool. Measurements of 368 circulating proteins were obtained with targeted Olink panels, and DNA genotyping was performed in all patients. Imputed genetic variants were used to compute a multi-trait multi-ancestry genome-wide polygenic score (GPSMult). HRP presence was defined as plaques with two or more high-risk characteristics (low attenuation, spotty calcification, positive remodeling, and napkin ring sign). Prediction of HRP presence was performed using the glmnet algorithm with repeated fivefold cross-validation, using CRFs, proteomics, and GPSMult as input features. RESULTS HRPs were detected in 165 (11%) patients, and 15 input features were associated with HRP presence. Prediction of HRP presence based on CRFs yielded a mean area under the receiver operating curve (AUC) ± standard error of 73.2 ± 0.1, versus 69.0 ± 0.1 for proteomics and 60.1 ± 0.1 for GPSMult. Combining CRFs with GPSMult increased prediction accuracy (AUC 74.8 ± 0.1 (P = 0.004)), while the inclusion of proteomics provided no significant improvement to either the CRF (AUC 73.2 ± 0.1, P = 1.00) or the CRF + GPSMult (AUC 74.6 ± 0.1, P = 1.00) models, respectively. CONCLUSIONS In patients with suspected CAD, incorporating genetic data with either clinical or proteomic data improves the prediction of high-risk plaque presence. TRIAL REGISTRATION https://clinicaltrials.gov/ct2/show/NCT02264717 (September 2014).
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Affiliation(s)
- Peter Loof Møller
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Palle Duun Rohde
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Jonathan Nørtoft Dahl
- Department of Cardiology, Gødstrup Hospital, Herning, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Laust Dupont Rasmussen
- Department of Cardiology, Gødstrup Hospital, Herning, Denmark
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - Louise Nissen
- Department of Cardiology, Gødstrup Hospital, Herning, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Samuel Emil Schmidt
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Victoria McGilligan
- Personalized Medicine Centre, School of Medicine, Ulster University, Derry, Northern Ireland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc, Reykjavik, Iceland
| | - Jacob Fog Bentzon
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Morten Bøttcher
- Department of Cardiology, Gødstrup Hospital, Herning, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Simon Winther
- Department of Cardiology, Gødstrup Hospital, Herning, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
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Lu C, Donners MMPC, Karel J, de Boer H, van Zonneveld AJ, den Ruijter H, Jukema JW, Kraaijeveld A, Kuiper J, Pasterkamp G, Cavill R, Perales-Patón J, Ferrannini E, Goossens P, Biessen EAL. Sex-specific differences in cytokine signaling pathways in circulating monocytes of cardiovascular disease patients. Atherosclerosis 2023; 384:117123. [PMID: 37127497 DOI: 10.1016/j.atherosclerosis.2023.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 03/14/2023] [Accepted: 04/14/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND AND AIMS This study aims to identify sex-specific transcriptional differences and signaling pathways in circulating monocytes contributing to cardiovascular disease. METHODS AND RESULTS We generated sex-biased gene expression signatures by comparing male versus female monocytes of coronary artery disease (CAD) patients (n = 450) from the Center for Translational Molecular Medicine-Circulating Cells Cohort. Gene set enrichment analysis demonstrated that monocytes from female CAD patients carry stronger chemotaxis and migratory signature than those from males. We then inferred cytokine signaling activities based on CytoSig database of 51 cytokine and growth factor regulation profiles. Monocytes from females feature a higher activation level of EGF, IFN1, VEGF, GM-CSF, and CD40L pathways, whereas IL-4, INS, and HMGB1 signaling was seen to be more activated in males. These sex differences were not observed in healthy subjects, as shown for an independent monocyte cohort of healthy subjects (GSE56034, n = 485). More pronounced GM-CSF signaling in monocytes of female CAD patients was confirmed by the significant enrichment of GM-CSF-activated monocyte signature in females. As we show these effects were not due to increased plasma levels of the corresponding ligands, sex-intrinsic differences in monocyte signaling regulation are suggested. Consistently, regulatory network analysis revealed jun-B as a shared transcription factor activated in all female-specific pathways except IFN1 but suppressed in male-activated IL-4. CONCLUSIONS We observed overt CAD-specific sex differences in monocyte transcriptional profiles and cytokine- or growth factor-induced responses, which provide insights into underlying mechanisms of sex differences in CVD.
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Affiliation(s)
- Chang Lu
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht UMC+, Maastricht University, Maastricht, the Netherlands
| | - Marjo M P C Donners
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht UMC+, Maastricht University, Maastricht, the Netherlands.
| | - Joël Karel
- Department of Advanced Computing Sciences, Maastricht University, Maastricht, the Netherlands
| | - Hetty de Boer
- Department of Internal Medicine (Nephrology), Leiden UMC, Leiden, the Netherlands
| | | | - Hester den Ruijter
- Laboratory for Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands; Netherlands Heart Institute, Utrecht, the Netherlands
| | - Adriaan Kraaijeveld
- Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Johan Kuiper
- Division of BioTherapeutics, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | | | - Rachel Cavill
- Department of Advanced Computing Sciences, Maastricht University, Maastricht, the Netherlands
| | - Javier Perales-Patón
- Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University and Heidelberg University Hospital, Heidelberg, Germany; Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany; Joint Research Centre for Computational Biomedicine (JRC COMBINE), Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Ele Ferrannini
- Consiglio Nazionale Delle Ricerche (CNR) Institute of Clinical Physiology, Pisa, Italy
| | - Pieter Goossens
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht UMC+, Maastricht University, Maastricht, the Netherlands
| | - Erik A L Biessen
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht UMC+, Maastricht University, Maastricht, the Netherlands; Institute for Molecular Cardiovascular Research, RWTH Aachen University, Aachen, 52074, Germany
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Mone P, Tesorio T, De Donato A, Cioppa A, Jankauskas SS, Salemme L, Santulli G. A novel urinary proteomic classifier predicts the risk of coronary artery disease. Eur J Prev Cardiol 2023; 30:1535-1536. [PMID: 37075225 PMCID: PMC10562135 DOI: 10.1093/eurjpc/zwad123] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 04/17/2023] [Indexed: 04/21/2023]
Affiliation(s)
- Pasquale Mone
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Neuroimmunology and Inflammation (INI), Albert Einstein College of Medicine, 1300 Morris Park Avenue, 10461 New York City, NY 10461, USA
- University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | | | | | - Angelo Cioppa
- ‘Montevergine’ Clinic, Mercogliano (Avellino), Italy
| | - Stanislovas S Jankauskas
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Neuroimmunology and Inflammation (INI), Albert Einstein College of Medicine, 1300 Morris Park Avenue, 10461 New York City, NY 10461, USA
- University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Luigi Salemme
- ‘Montevergine’ Clinic, Mercogliano (Avellino), Italy
| | - Gaetano Santulli
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Neuroimmunology and Inflammation (INI), Albert Einstein College of Medicine, 1300 Morris Park Avenue, 10461 New York City, NY 10461, USA
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Einstein Institute for Aging Research, Albert Einstein College of Medicine, 1300 Morris Park Avenue, 10461 New York City, NY 10461, USA
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Yazdani AN, Pletsch M, Chorbajian A, Zitser D, Rai V, Agrawal DK. Biomarkers to monitor the prognosis, disease severity, and treatment efficacy in coronary artery disease. Expert Rev Cardiovasc Ther 2023; 21:675-692. [PMID: 37772751 PMCID: PMC10615890 DOI: 10.1080/14779072.2023.2264779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 09/26/2023] [Indexed: 09/30/2023]
Abstract
INTRODUCTION Coronary Artery Disease (CAD) is a prevalent condition characterized by the presence of atherosclerotic plaques in the coronary arteries of the heart. The global burden of CAD has increased significantly over the years, resulting in millions of deaths annually and making it the leading health-care expenditure and cause of mortality in developed countries. The lack of cost-effective strategies for monitoring the prognosis of CAD warrants a pressing need for accurate and efficient markers to assess disease severity and progression for both reducing health-care costs and improving patient outcomes. AREA COVERED To effectively monitor CAD, prognostic biomarkers and imaging techniques play a vital role in risk-stratified patients during acute treatment and over time. However, with over 1,000 potential markers of interest, it is crucial to identify the key markers with substantial utility in monitoring CAD progression and evaluating therapeutic interventions. This review focuses on identifying and highlighting the most relevant markers for monitoring CAD prognosis and disease severity. We searched for relevant literature using PubMed and Google Scholar. EXPERT OPINION By utilizing the markers discussed, health-care providers can improve patient care, optimize treatment plans, and ultimately reduce health-care costs associated with CAD management.
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Affiliation(s)
- Armand N. Yazdani
- Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766
| | - Michaela Pletsch
- Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766
| | - Abraham Chorbajian
- Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766
| | - David Zitser
- Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766
| | - Vikrant Rai
- Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766
| | - Devendra K. Agrawal
- Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766
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Coronary Artery Disease and Aortic Valve Stenosis: A Urine Proteomics Study. Int J Mol Sci 2022; 23:ijms232113579. [PMID: 36362368 PMCID: PMC9693565 DOI: 10.3390/ijms232113579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 10/28/2022] [Accepted: 10/30/2022] [Indexed: 11/09/2022] Open
Abstract
Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AVS) are heart diseases accounting for most cardiac surgeries. These share many risk factors, such as age, diabetes, hypertension, or obesity, and similar pathogenesis, including endothelial disruption, lipid and immune cell infiltration, inflammation, fibrosis, and calcification. Unsuspected CAD and AVS are sometimes detected opportunistically through echocardiography, coronary angiography, and magnetic resonance. Routine biomarkers for early detection of either of these atherosclerotic-rooted conditions would be important to anticipate the diagnosis. With a noninvasive collection, urine is appealing for biomarker assessment. We conducted a shotgun proteomics exploratory analysis of urine from 12 CAD and/or AVS patients and 11 controls to identify putative candidates to differentiate these diseases from healthy subjects. Among the top 20 most dysregulated proteins, TIMP1, MMP2 and vWF stood out, being at least 2.5× increased in patients with CAD/AVS and holding a central position in a network of protein-protein interactions. Moreover, their assessment in an independent cohort (19 CAD/AVS and 10 controls) evidenced strong correlations between urinary TIMP1 and vWF levels and a common cardiovascular risk factor - HDL (r = 0.59, p < 0.05, and r = 0.64, p < 0.01, respectively).
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Chen X, Ma Y, Xie Y, Pu J. Aptamer-based applications for cardiovascular disease. Front Bioeng Biotechnol 2022; 10:1002285. [PMID: 36312558 PMCID: PMC9606242 DOI: 10.3389/fbioe.2022.1002285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Cardiovascular disease (especially atherosclerosis) is a major cause of death worldwide, and novel diagnostic tools and treatments for this disease are urgently needed. Aptamers are single-stranded oligonucleotides that specifically recognize and bind to the targets by forming unique structures in vivo, enabling them to rival antibodies in cardiac applications. Chemically synthesized aptamers can be readily modified in a site-specific way, so they have been engineered in the diagnosis of cardiac diseases and anti-thrombosis therapeutics. Von Willebrand Factor plays a unique role in the formation of thrombus, and as an aptamer targeting molecule, has shown initial success in antithrombotic treatment. A combination of von Willebrand Factor and nucleic acid aptamers can effectively inhibit the progression of blood clots, presenting a positive diagnosis and therapeutic effect, as well as laying a novel theory and strategy to improve biocompatibility paclitaxel drug balloon or implanted stent in the future. This review summarizes aptamer-based applications in cardiovascular disease, including biomarker discovery and future management strategy. Although relevant applications are relatively new, the significant advancements achieved have demonstrated that aptamers can be promising agents to realize the integration of diagnosis and therapy in cardiac research.
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Affiliation(s)
| | | | | | - Jun Pu
- *Correspondence: Yuquan Xie, ; Jun Pu,
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Emfietzoglou M, Mavrogiannis MC, Samaras A, Rampidis GP, Giannakoulas G, Kampaktsis PN. The role of cardiac computed tomography in predicting adverse coronary events. Front Cardiovasc Med 2022; 9:920119. [PMID: 35911522 PMCID: PMC9334665 DOI: 10.3389/fcvm.2022.920119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/28/2022] [Indexed: 11/16/2022] Open
Abstract
Cardiac computed tomography (CCT) is now considered a first-line diagnostic test for suspected coronary artery disease (CAD) providing a non-invasive, qualitative, and quantitative assessment of the coronary arteries and pericoronary regions. CCT assesses vascular calcification and coronary lumen narrowing, measures total plaque burden, identifies plaque composition and high-risk plaque features and can even assist with hemodynamic evaluation of coronary lesions. Recent research focuses on computing coronary endothelial shear stress, a potent modulator in the development and progression of atherosclerosis, as well as differentiating an inflammatory from a non-inflammatory pericoronary artery environment using the simple measurement of pericoronary fat attenuation index. In the present review, we discuss the role of the above in the diagnosis of coronary atherosclerosis and the prediction of adverse cardiovascular events. Additionally, we review the current limitations of cardiac computed tomography as an imaging modality and highlight how rapid technological advancements can boost its capacity in predicting cardiovascular risk and guiding clinical decision-making.
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Affiliation(s)
- Maria Emfietzoglou
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Michail C. Mavrogiannis
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | | | | | | | - Polydoros N. Kampaktsis
- Division of Cardiology, Columbia University Irving Medical Center, New York, NY, United States
- *Correspondence: Polydoros N. Kampaktsis
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