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Search Results (1,018)

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11 pages, 564 KiB  
Article
Pre-Hospital Point-of-Care Troponin: Is It Possible to Anticipate the Diagnosis? A Preliminary Report
by Cristian Lazzari, Sara Montemerani, Cosimo Fabrizi, Cecilia Sacchi, Antoine Belperio, Marilena Fantacci, Giovanni Sbrana, Agostino Ognibene, Maurizio Zanobetti and Simone Nocentini
Diagnostics 2025, 15(2), 220; https://doi.org/10.3390/diagnostics15020220 (registering DOI) - 19 Jan 2025
Viewed by 79
Abstract
Background: Thanks to the evolution of laboratory medicine, point-of-care testing (POCT) for troponin levels in the blood (hs-cTn) has been greatly improved in order to quickly diagnose acute myocardial infarction (AMI) with an accuracy similar to standard laboratory tests. The rationale of [...] Read more.
Background: Thanks to the evolution of laboratory medicine, point-of-care testing (POCT) for troponin levels in the blood (hs-cTn) has been greatly improved in order to quickly diagnose acute myocardial infarction (AMI) with an accuracy similar to standard laboratory tests. The rationale of the HEART POCT study is to propose the application of the 0/1 h European Society of Cardiology (ESC) algorithm in the pre-hospital setting using a POCT device (Atellica VTLi). Methods: This is a prospective study comparing patients who underwent pre-hospital point-of-care troponin testing (Atellica VTLi) with a control group that underwent standard hospital-based troponin testing (Elecsys). The primary objectives were to determine if the 0/1 h algorithm of the Atellica VTLi is non-inferior to the standard laboratory method for diagnosing AMI and to analyze rule-out/rule-in times and emergency department (ED) stay times. The secondary objective was to evaluate the feasibility of pre-hospital troponin testing. Results: The Atellica VTLi demonstrated reasonable sensitivity for detecting AMI, with sensitivity increasing from 60% at the first measurement (time 0) to 80% at the second measurement (time 1 h). Both the Atellica VTLi and the Elecsys method showed high negative predictive value (NPV), indicating that a negative troponin result effectively ruled out AMI in most cases. Patients in the Atellica VTLi group experienced significantly shorter times to diagnosis and discharge from the emergency department compared to the control group (Elecsys). This highlights a potential benefit of point-of-care testing: streamlining the diagnostic and treatment processes. Conclusions: POCT allows for rapid troponin measurement, leading to a faster diagnosis of non-ST-segment elevation myocardial infarction (NSTEMI). This enables earlier initiation of appropriate treatment, potentially improving patient outcomes and the efficiency of emergency department operations. POCT could be particularly beneficial in pre-hospital settings, enabling faster triage and transportation of patients to appropriate care centers. Full article
(This article belongs to the Section Point-of-Care Diagnostics and Devices)
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<p>Project timeline from 112 activation to Emergency Room transport.</p>
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13 pages, 2499 KiB  
Systematic Review
The Role of Impella in Cardiogenic Shock Complicated by an Acute Myocardial Infarction: A Meta-Analysis
by Kiarash Sassani, Christian Waechter, Styliani Syntila, Julian Kreutz, Birgit Markus, Nikolaos Patsalis, Davide Di Vece, Bernhard Schieffer, Christian Templin and Georgios Chatzis
J. Clin. Med. 2025, 14(2), 611; https://doi.org/10.3390/jcm14020611 (registering DOI) - 18 Jan 2025
Viewed by 216
Abstract
Background: Emerging evidence suggests the role of mechanical circulatory support (MCS) devices in the therapy of refractory cardiogenic shock (CS). However, largerandomized trials addressing the role of Impella in the therapy of infarct-associated CS are sparse. As such, evidence coming from comprehensive retrospective [...] Read more.
Background: Emerging evidence suggests the role of mechanical circulatory support (MCS) devices in the therapy of refractory cardiogenic shock (CS). However, largerandomized trials addressing the role of Impella in the therapy of infarct-associated CS are sparse. As such, evidence coming from comprehensive retrospective studies or meta-analyses is of major importance in order to clarify the role of the Impella device in this setting. Methods: Only clinical trials involving patients receiving Impella 2.5 and Impella CP for treatment of CS caused in terms of acute coronary syndrome (ACS) were included in this meta-analysis. The primary endpoint was 30-day mortality, with major bleeding and ischemic vascular complications serving as secondary endpoints. Results: A total of 18 observational retrospective studies (2617 patients with CS and Impella implantation) were included in this analysis. The mean age of the total participants was 64.7 ± 2.93 years. A mean mortality incidence of 45% was found between all included participants. The ischemia rate was in total 8.5 ± 4.4%, and the incidence of bleeding was 13.9 ± 5.6%. Conclusions: The 30-day mortality rate for patients with ACS-associated CS treated with Impella remains high. The high complication rates underline the importance of Impella use in only a very well-selected population of patients. Full article
(This article belongs to the Section Cardiology)
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<p>Flow chart of the included studies.</p>
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<p>(<b>a</b>) Effect of Impella on 30-day mortality. (<b>b</b>) Funnel plot of Impella on mortality [<a href="#B10-jcm-14-00611" class="html-bibr">10</a>,<a href="#B14-jcm-14-00611" class="html-bibr">14</a>,<a href="#B15-jcm-14-00611" class="html-bibr">15</a>,<a href="#B16-jcm-14-00611" class="html-bibr">16</a>,<a href="#B17-jcm-14-00611" class="html-bibr">17</a>,<a href="#B18-jcm-14-00611" class="html-bibr">18</a>,<a href="#B19-jcm-14-00611" class="html-bibr">19</a>,<a href="#B20-jcm-14-00611" class="html-bibr">20</a>,<a href="#B21-jcm-14-00611" class="html-bibr">21</a>,<a href="#B22-jcm-14-00611" class="html-bibr">22</a>,<a href="#B23-jcm-14-00611" class="html-bibr">23</a>,<a href="#B24-jcm-14-00611" class="html-bibr">24</a>,<a href="#B25-jcm-14-00611" class="html-bibr">25</a>,<a href="#B26-jcm-14-00611" class="html-bibr">26</a>,<a href="#B27-jcm-14-00611" class="html-bibr">27</a>,<a href="#B28-jcm-14-00611" class="html-bibr">28</a>,<a href="#B29-jcm-14-00611" class="html-bibr">29</a>,<a href="#B30-jcm-14-00611" class="html-bibr">30</a>].</p>
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<p>(<b>a</b>) Forest plot of Impella on ischemia complication. (<b>b</b>) Funnel plot of Impella on ischemia complication [<a href="#B10-jcm-14-00611" class="html-bibr">10</a>,<a href="#B14-jcm-14-00611" class="html-bibr">14</a>,<a href="#B15-jcm-14-00611" class="html-bibr">15</a>,<a href="#B16-jcm-14-00611" class="html-bibr">16</a>,<a href="#B17-jcm-14-00611" class="html-bibr">17</a>,<a href="#B18-jcm-14-00611" class="html-bibr">18</a>,<a href="#B19-jcm-14-00611" class="html-bibr">19</a>,<a href="#B20-jcm-14-00611" class="html-bibr">20</a>,<a href="#B22-jcm-14-00611" class="html-bibr">22</a>,<a href="#B24-jcm-14-00611" class="html-bibr">24</a>,<a href="#B25-jcm-14-00611" class="html-bibr">25</a>,<a href="#B26-jcm-14-00611" class="html-bibr">26</a>,<a href="#B28-jcm-14-00611" class="html-bibr">28</a>,<a href="#B29-jcm-14-00611" class="html-bibr">29</a>,<a href="#B30-jcm-14-00611" class="html-bibr">30</a>].</p>
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<p>(<b>a</b>) Effect of Impella on bleeding complication. (<b>b</b>) Funnel plot of Impella on bleeding complication [<a href="#B10-jcm-14-00611" class="html-bibr">10</a>,<a href="#B14-jcm-14-00611" class="html-bibr">14</a>,<a href="#B15-jcm-14-00611" class="html-bibr">15</a>,<a href="#B16-jcm-14-00611" class="html-bibr">16</a>,<a href="#B17-jcm-14-00611" class="html-bibr">17</a>,<a href="#B18-jcm-14-00611" class="html-bibr">18</a>,<a href="#B19-jcm-14-00611" class="html-bibr">19</a>,<a href="#B20-jcm-14-00611" class="html-bibr">20</a>,<a href="#B22-jcm-14-00611" class="html-bibr">22</a>,<a href="#B23-jcm-14-00611" class="html-bibr">23</a>,<a href="#B24-jcm-14-00611" class="html-bibr">24</a>,<a href="#B25-jcm-14-00611" class="html-bibr">25</a>,<a href="#B26-jcm-14-00611" class="html-bibr">26</a>,<a href="#B27-jcm-14-00611" class="html-bibr">27</a>,<a href="#B28-jcm-14-00611" class="html-bibr">28</a>,<a href="#B29-jcm-14-00611" class="html-bibr">29</a>,<a href="#B30-jcm-14-00611" class="html-bibr">30</a>].</p>
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25 pages, 1769 KiB  
Review
Research Progress and Clinical Translation Potential of Coronary Atherosclerosis Diagnostic Markers from a Genomic Perspective
by Hanxiang Liu, Yuchen Zhang, Yueyan Zhao, Yuzhen Li, Xiaofeng Zhang, Lingyu Bao, Rongkai Yan, Yixin Yang, Huixian Zhou, Jinming Zhang and Siyuan Song
Genes 2025, 16(1), 98; https://doi.org/10.3390/genes16010098 (registering DOI) - 18 Jan 2025
Viewed by 216
Abstract
Objective: Coronary atherosclerosis (CAD) is characterized by arterial intima lipid deposition, chronic inflammation, and fibrous tissue proliferation, leading to arterial wall thickening and lumen narrowing. As the primary cause of coronary heart disease and acute coronary syndrome, CAD significantly impacts global health. Recent [...] Read more.
Objective: Coronary atherosclerosis (CAD) is characterized by arterial intima lipid deposition, chronic inflammation, and fibrous tissue proliferation, leading to arterial wall thickening and lumen narrowing. As the primary cause of coronary heart disease and acute coronary syndrome, CAD significantly impacts global health. Recent genetic studies have demonstrated CAD’s polygenic and multifactorial nature, providing molecular insights for early diagnosis and risk assessment. This review analyzes recent advances in CAD-related genetic markers and evaluates their diagnostic potential, focusing on their applications in diagnosis and risk stratification within precision medicine. Methods: We conducted a systematic review of CAD genomic studies from PubMed and Web of Science databases, analyzing findings from genome-wide association studies (GWASs), gene sequencing, transcriptomics, and epigenomics research. Results: GWASs and sequencing studies have identified key genetic variations associated with CAD, including JCAD/KIAA1462, GUCY1A3, PCSK9, and SORT1, which regulate inflammation, lipid metabolism, and vascular function. Transcriptomic and epigenomic analyses have revealed disease-specific gene expression patterns, DNA methylation signatures, and regulatory non-coding RNAs (miRNAs and lncRNAs), providing new approaches for early detection. Conclusions: While genetic marker research in CAD has advanced significantly, clinical implementation faces challenges including marker dynamics, a lack of standardization, and integration with conventional diagnostics. Future research should prioritize developing standardized guidelines, conducting large-scale prospective studies, and enhancing multi-omics data integration to advance genomic diagnostics in CAD, ultimately improving patient outcomes through precision medicine. Full article
(This article belongs to the Special Issue Genomic Approaches for Disease Diagnosis and Prognosis)
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<p>Pathological cascade in coronary atherosclerosis development. This figure illustrates the progression of coronary atherosclerosis, beginning with vascular endothelial cell (VEC) dysfunction caused by genetic predispositions (e.g., <span class="html-italic">JCAD</span>, <span class="html-italic">NOS3</span>), oxidative stress factors (arterial shear stress, dyslipidemia, and smoking), and familial hypercholesterolemia (<span class="html-italic">PCSK9</span>, <span class="html-italic">LDLR</span>, <span class="html-italic">APOB</span>). LDL infiltration into the arterial wall promotes foam cell formation, driven by impaired LDL metabolism (<span class="html-italic">SORT1</span>). The resulting inflammatory response involves cytokines such as TNF-α, IL-6, and MCP-1, which stimulate smooth muscle cell (SMC) proliferation and migration. These processes contribute to vascular remodeling, lumen narrowing, and fibrous cap formation, which may ultimately lead to rupture, foam cell apoptosis, and advanced atherosclerotic lesions.</p>
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<p>GWAS-identified genes and their role in coronary artery disease pathophysiology. This figure highlights the molecular pathways involving key genes identified through GWASs that contribute to coronary artery disease (CAD). Lipid metabolism: Genes such as <span class="html-italic">PCSK9</span> and <span class="html-italic">LDLR</span> regulate low-density lipoprotein (LDL) cholesterol levels. Gain-of-function mutations in <span class="html-italic">PCSK9</span> lead to hypercholesterolemia and increased CAD risk by affecting LDL uptake and degradation. Endothelial cell function: The <span class="html-italic">JCAD/KIAA1462</span> gene encodes a protein critical for endothelial cell adhesion and vascular integrity. Variants impair endothelial cell function, promoting CAD development. Smooth muscle contraction/relaxation: The <span class="html-italic">GUCY1A3</span> gene encodes soluble guanylyl cyclase (sGC), a mediator of smooth muscle relaxation. Mutations disrupt vascular tone and contribute to CAD risk. Inflammatory response: Genes like <span class="html-italic">IL6R</span> influence cytokine signaling, contributing to vascular inflammation and lesion progression. MicroRNAs such as <span class="html-italic">miR-126</span> and <span class="html-italic">miR-33</span> further modulate inflammatory and lipid transport pathways.</p>
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<p>Clinical applications of genetic markers in coronary artery disease. This figure summarizes the integration of genetic markers and their clinical utility in diagnosing and managing coronary artery disease (CAD) across different stages. Genetic markers and miRNAs: Key markers such as <span class="html-italic">PCSK9</span>, <span class="html-italic">SORT1</span>, <span class="html-italic">JCAD</span>, <span class="html-italic">NOS3,</span> and associated miRNAs (<span class="html-italic">miR-148a</span>, <span class="html-italic">miR-33</span>, <span class="html-italic">miR-122</span>) are identified from blood samples. These markers are linked to lipid metabolism, vascular inflammation, and endothelial function, contributing to CAD risk stratification and management. Risk stratification: Patients are categorized into high-risk (e.g., <span class="html-italic">PCSK9/SORT1</span> mutations), intermediate-risk (e.g., <span class="html-italic">JCAD/NOS3</span> variants), and low-risk groups based on genetic profiles, guiding interventions such as statins, <span class="html-italic">PCSK9</span> inhibitors, or regular monitoring. Disease stage diagnosis: Genetic and inflammatory markers like <span class="html-italic">IL6R</span>, <span class="html-italic">NOS2A</span>, and <span class="html-italic">IL1Ars2297518</span> are utilized to differentiate between early-stage CAD (characterized by inflammatory infiltration with markers like IL-6 and TNF-α) and advanced-stage CAD (associated with plaque rupture and infarction, mediated by MMP-9). Clinical applications: These markers facilitate early disease detection, dynamic monitoring of disease progression, and personalized interventions to reduce CAD risk and improve patient outcomes.</p>
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16 pages, 757 KiB  
Article
Therapeutic Inertia in Dyslipidemia Management for Secondary Cardiovascular Prevention: Results from the Italian ITACARE-P Network
by Andrea Faggiano, Anna Gualeni, Lucia Barbieri, Gian Francesco Mureddu, Elio Venturini, Francesco Giallauria, Marco Ambrosetti, Matteo Ruzzolini, Francesco Maranta, Maria Vittoria Silverii, Laura Garau, Davide Garamella, Raffaele Napoli, Luigi Maresca, Gaetano Luca Panetta, Antonio Maggi, Stefano Carugo, Francesco Fattirolli and Pompilio Faggiano
J. Clin. Med. 2025, 14(2), 493; https://doi.org/10.3390/jcm14020493 - 14 Jan 2025
Viewed by 237
Abstract
Background/Objectives: This study assessed the proportion of secondary cardiovascular prevention patients who achieved low-density lipoprotein (LDL) cholesterol targets as per the 2019 ESC/EAS Dyslipidemia Guidelines. We also evaluated whether lipid-lowering therapies (LLTs) were adjusted in patients not meeting targets and analyzed the likelihood [...] Read more.
Background/Objectives: This study assessed the proportion of secondary cardiovascular prevention patients who achieved low-density lipoprotein (LDL) cholesterol targets as per the 2019 ESC/EAS Dyslipidemia Guidelines. We also evaluated whether lipid-lowering therapies (LLTs) were adjusted in patients not meeting targets and analyzed the likelihood of these modifications achieving recommended levels. Methods: A multicenter, cross-sectional observational study retrospectively reviewed medical records of 1909 outpatients in 9 Italian cardiac rehabilitation/secondary prevention clinics from January 2023 to June 2024. Inclusion criteria included prior atherosclerotic cardiovascular disease (ASCVD) and recent LDL-cholesterol levels. Data included demographics, ASCVD presentation, lipid profiles, and LLTs. Patients at very high risk had LDL targets of ≤55 mg/dL, or ≤40 mg/dL for recurrent events within 2 years. Clinicians’ approaches to LLT modification in patients not at target were recorded, with LLT efficacy estimated based on percentage distance from LDL-cholesterol targets. Results: Of the 1909 patients, 41.3% met the LDL-cholesterol target. Predictors of achieving targets included male gender, cardiac rehabilitation, recent acute coronary syndrome, diabetes, and triple therapy (statin + ezetimibe + PCSK9 inhibitors). Conversely, a target of ≤40 mg/dL, lack of therapy, and monotherapy were negative predictors. Among 1074 patients not at target, LLT modifications were proposed for 48.6%. Predictors of LLT modification included recent ASCVD events, cardiac rehabilitation, and greater percentage distance from the LDL target, while advanced age and an LDL target of ≤40 mg/dL were negative predictors. However, only 42.3% of modified therapies were predicted to be effective in reaching LDL targets. Conclusions: Despite 2019 ESC/EAS guidelines, a significant proportion of high-risk patients did not achieve LDL targets, and proposed LLT modifications were often insufficient. More intensive LLT regimens are needed to improve outcomes in this population. Full article
(This article belongs to the Section Cardiology)
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<p>Different lipid-lowering therapies in patients who achieved versus those who did not achieve low-density lipoprotein cholesterol (LDL-c) targets. PCSK9-i: proprotein convertase subtilisin/kexin type 9 serine protease inhibitors.</p>
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<p>Patient groups stratified by percentage distance from low-density lipoprotein cholesterol (LDL-c ≤ 6%, 7–25%, &gt;25%) and lipid-lowering therapy (LLT) modification status.</p>
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<p>Types of lipid-lowering therapy (LLT) modifications and implementations prescribed. PCSK9-i: proprotein convertase subtilisin/kexin type 9 serine protease inhibitors.</p>
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16 pages, 1769 KiB  
Review
Perioperative Risk: Short Review of Current Approach in Non Cardiac Surgery
by Andreea Boghean, Cristian Guțu and Dorel Firescu
J. Cardiovasc. Dev. Dis. 2025, 12(1), 24; https://doi.org/10.3390/jcdd12010024 - 13 Jan 2025
Viewed by 404
Abstract
The rate of major surgery is constantly increasing worldwide, and approximately 85% are non-cardiac surgery. More than half of patients over 45 years presenting for non-cardiac surgical interventions have cardiovascular risk factors, and the most common: chronic coronary syndrome and history of stroke. [...] Read more.
The rate of major surgery is constantly increasing worldwide, and approximately 85% are non-cardiac surgery. More than half of patients over 45 years presenting for non-cardiac surgical interventions have cardiovascular risk factors, and the most common: chronic coronary syndrome and history of stroke. The preoperative cardiovascular risk is determined by the comorbidities, the clinical condition before the intervention, the urgency, duration or type. Cardiovascular risk scores are necessary tools to prevent perioperative cardiovascular morbidity and mortality and the most frequently used are Lee/RCRI (Revised Cardiac Risk Index), APACHE II (Acute Physiology and Chronic Health Evaluation), POSSUM (Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity), The American University of Beirut (AUB)-HAS2. To reduce the perioperative risk, there is a need for an appropriate preoperative risk assessment, as well as the choice of the type and timing of surgical intervention. Quantification of surgical risk as low, intermediate, and high is useful in identifying the group of patients who are at risk of complications such as myocardial infarction, thrombosis, arrhythmias, heart failure, stroke or even death. Currently there are not enough studies that can differentiate the risk according to gender, race, elective versus emergency procedure, the value of cardiac biomarkers. Full article
(This article belongs to the Section Cardiovascular Clinical Research)
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<p>Total risk estimated by the interaction between the surgical risk and the patient’s cardiovascular risk. The red arrows signify the probability of perioperative cardiovascular complications (adapted according to the ESC 2022 guidelines).</p>
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<p>Pre-operative assessment before non-cardiac surgery.</p>
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<p>Level of evidence AHA/ACC and ESC.</p>
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25 pages, 1030 KiB  
Systematic Review
Osteopontin as a Biomarker for Coronary Artery Disease
by Georgia R. Layton, Ibrahim Antoun, Alice Copperwheat, Zaidhan Latif Khan, Sanjay S. Bhandari, Riyaz Somani, André Ng and Mustafa Zakkar
Cells 2025, 14(2), 106; https://doi.org/10.3390/cells14020106 - 13 Jan 2025
Viewed by 374
Abstract
Osteopontin (OPN) is a sialylated phosphoprotein highly expressed in atherosclerosis and upregulated in settings of both acute and chronic inflammation. It is hypothesised that plasma levels of OPN may correlate with the presence of coronary artery disease, “CAD”. This offers potential as a [...] Read more.
Osteopontin (OPN) is a sialylated phosphoprotein highly expressed in atherosclerosis and upregulated in settings of both acute and chronic inflammation. It is hypothesised that plasma levels of OPN may correlate with the presence of coronary artery disease, “CAD”. This offers potential as a point-of-care testing biomarker for early diagnosis, disease monitoring, and prognosis. This review evaluates the current literature on the association between plasma OPN levels and coronary artery disease and what is currently known to support its potential as a biomarker for future practice. Electronic searches of MEDLINE and EMBASE databases were undertaken from inception until July 2024. Thirty-three studies met the inclusion criteria. All studies were observational, with gross heterogeneity in methods used to analyse the association of plasma OPN with clinical characteristics. They included case series, case–control, cross-sectional, and cohort study designs. OPN has been linked to higher cardiovascular risk and unfavourable cardiovascular outcomes. However, the evidence regarding the direct assessment of CAD severity using tools like the SYNTAX or TIMI scores, which focus on anatomical complexity and risk factors, is less definitive. This suggests that OPN may be a more precise reflection of the inflammatory processes and atherosclerotic activity contributing to unfavourable outcomes rather than a direct indicator of the anatomical severity of CAD itself. Consequently, OPN is increasingly perceived as a marker of a poor prognosis rather than a tool for assessing the severity of coronary artery lesions. Full article
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<p>Summary of the currently established relationships of OPN within coronary artery disease physiology and its common treatment modalities (percutaneous stenting and coronary artery bypass grafting). [IL6, interleukin-6; MDA, malondialdehyde; OPN, osteopontin; VSMCs, vascular smooth muscle cells].</p>
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<p>2020 [<a href="#B11-cells-14-00106" class="html-bibr">11</a>] diagram detailing the summary of article assessment and included paper selection.</p>
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13 pages, 1535 KiB  
Article
Prevalence of Vitamin K2 Deficiency and Its Association with Coronary Artery Disease: A Case–Control Study
by Sameh A. Ahmed, Abdulaziz A. Yar, Anas M. Ghaith, Rayan N. Alahmadi, Faisal A. Almaleki, Hassan S. Alahmadi, Waleed H. Almaramhy, Ahmed M. Alsaedi, Man K. Alraddadi and Hussein M. Ismail
Diseases 2025, 13(1), 12; https://doi.org/10.3390/diseases13010012 - 11 Jan 2025
Viewed by 486
Abstract
Background/Objectives: Vitamin K2 analogs are associated with decreased vascular calcification, which may provide protective benefits for individuals with coronary artery disease (CAD) by stimulating anti-calcific proteins like matrix Gla protein and adjusting innate immune responses. This study addresses a significant gap in understanding [...] Read more.
Background/Objectives: Vitamin K2 analogs are associated with decreased vascular calcification, which may provide protective benefits for individuals with coronary artery disease (CAD) by stimulating anti-calcific proteins like matrix Gla protein and adjusting innate immune responses. This study addresses a significant gap in understanding the association between serum levels of vitamin K2 analogs in different CAD types and examines their correlations with clinical risk parameters in CAD patients. Methods: This case–control study enrolled CAD patients and healthy controls to assess and compare serum concentrations of two vitamin K2 analogs including menaquinone-4 (MK-4) and menaquinone-7 (MK-7) via ultra-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS). CAD risk factors were evaluated and related to serum levels of vitamin K2 analogs. The CAD group was further subdivided into stable angina, STEMI, NSTEMI, and unstable angina groups to investigate potential differences in vitamin K2 analog levels. Results: Patients experiencing acute coronary syndrome exhibited notably reduced serum levels of MK-4 and MK-7 (1.61 ± 0.66, and 1.64 ± 0.59 ng/mL, respectively) in comparison to the control group (2.29 ± 0.54, and 2.16 ± 0.46 ng/mL, respectively), with MK-4 and MK-7 displaying stronger associations with CAD risk indicators. Notable variations in vitamin K2 analog levels were found between CAD patients and control groups (p < 0.001). Unstable angina patients showed the lowest serum levels of MK-4 and MK-7. Conclusions: The present study demonstrated a higher prevalence rate of vitamin K2 deficiency among patients with CAD. The most pronounced decrease in MK-4 and MK-7 was observed in unstable angina patients. Moreover, these outcomes indicate the imperative requirement for an integrative approach that incorporates metabolic, lipid, and vitamin K2-related pathways in the risk stratification and management of CAD. Full article
(This article belongs to the Section Cardiology)
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<p>Serum levels of vitamin K2 analogs <b>±</b> SEM in CAD patients (Stable angina (n = 24), STEMI (n = 48), NSTEMI (n = 17), and unstable angina (n = 10)) groups and control (n = 81) group.</p>
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<p>Box and whisker plot for serum levels of vitamin K2 analogs ± SEM in CAD patients (stable angina (n = 24), STEMI (n = 48), NSTEMI (n = 17), unstable angina (n = 10)) groups.</p>
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<p>Scatterplots with regression lines for the relationship between serum troponin levels and MK-4 levels (<b>A</b>), serum troponin levels and MK-7 levels (<b>B</b>), LV ejection fraction and MK-4 levels (<b>C</b>), and LV ejection fraction and MK-7 levels (<b>D</b>).</p>
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15 pages, 2558 KiB  
Article
Plasma Levels of Propionylcarnitine Improved Prediction of Heart Failure and All-Cause Mortality in Patients with Stable Coronary Artery Disease
by Jairo Lumpuy-Castillo, Francisco J. Rupérez, Berta Porto, Carmen Cristóbal, Nieves Tarín, Ana Isabel Huelmos, Joaquín Alonso, Jesús Egido, Ignacio Mahíllo-Fernández, Lorenzo López-Bescós, José Tuñón and Óscar Lorenzo
Biomolecules 2025, 15(1), 27; https://doi.org/10.3390/biom15010027 - 29 Dec 2024
Viewed by 423
Abstract
Background: Plasma metabolites could be suitable as predictive biomarkers for cardiovascular pathologies or death, thereby improving the prediction of protein biomarkers. The release of acylcarnitines may be altered after coronary artery disease (CAD) in subjects with recurrent clinical outcomes, and this could be [...] Read more.
Background: Plasma metabolites could be suitable as predictive biomarkers for cardiovascular pathologies or death, thereby improving the prediction of protein biomarkers. The release of acylcarnitines may be altered after coronary artery disease (CAD) in subjects with recurrent clinical outcomes, and this could be used as a prognosis tool. Methods: Patients with stable coronary artery disease (SCAD) who had suffered an acute coronary syndrome 6–9 months before were followed for up to 4.3 years for adverse events. Soluble pro-inflammatory/fibrotic proteins, and a panel of 13 amino acids and 13 acylcarnitines, were evaluated by ELISA and metabolomics analyses as potential predictors of a primary outcome [heart failure (HF) or death]. Results: Among 139 patients (67.0 years old, BMI = 28.6 kg/m2, and 71.2% male), 25 developed the primary outcome after a mean follow-up of 2.2 years. These patients showed increased plasma levels of NT-proBNP (1300 vs. 250 pg/mL; p < 0.001), pro-inflammatory/fibrotic MCP-1 (1.7 vs. 1.4 × 102 pg/mL; p = 0.043), Gal-3 (12.7 vs. 7.9 ng/mL; p < 0.001), and NGAL (2.7 vs. 1.6 × 102 ng/mL; p < 0.001), and lower acetyl- and propionylcarnitines (0.59 vs. 0.99 µM, p = 0.007, and 3.22 vs. 6.49 × 10−2 µM, p < 0.001, respectively). Instead, plasma amino acids were not significantly changed. Through a multivariable logistic regression analysis, a combined model of age, Gal-3, and the NGAL/propionylcarnitine ratio showed the highest prediction for HF or death (AUC = 0.88, sensitivity = 0.8, and specificity = 0.81; p < 0.001). Conclusions: Patients with SCAD led to recurrent HF or all-cause death. Interestingly, increased levels of plasma NGAL and Gal-3, and a reduction in propionylcarnitine, could predict the occurrence of these events. Full article
(This article belongs to the Special Issue New Insights into Cardiometabolic Diseases)
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<p>Risk factors, comorbidities, and treatments. A bar chart representing the relative frequencies of risk factors and comorbidities (<b>a</b>), and pharmacological treatments (<b>b</b>), in each group of patients with or without the primary outcome. The <span class="html-italic">p</span>-values were obtained from the Chi-square or Fisher’s exact tests, supplemented by the Z-test for proportions. * <span class="html-italic">p</span>-value &lt; 0.05, ** <span class="html-italic">p</span>-value &lt; 0.01, and *** <span class="html-italic">p</span>-value &lt; 0.001. LMCA, left main coronary artery; PAD, peripheral artery disease; LVEF, left ventricular ejection fraction; PTCA, percutaneous transluminal coronary angioplasty; MRA, mineralocorticoid receptor antagonists; ARBs, angiotensin II receptor blocker; CCBs, calcium channel blockers; ACEIs, angiotensin-converting enzyme inhibitors.</p>
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<p>Simple logistic regression analysis of risk factors for HF or all-cause death. A binary logistic regression followed by a receiver operating characteristic (ROC) analysis was applied. The forest plot displays the odds ratios (ORs) and 95% confidence intervals (CIs) for each univariable model. eGFR, estimated glomerular filtration rate; C2:0, acetylcarnitine; C3:0, propionylcarnitine. NT-proBNP, N-terminal pro-brain natriuretic peptide; MCP-1, monocyte chemotactic protein 1; Gal-3, galectin-3; NGAL, neutrophil gelatinase-associated lipocalin. Those values of the area under the ROC curve (AUC) greater than 0.7 (in bold) were used for further analysis. * <span class="html-italic">p</span> = 0.05 vs. C3:0 (by DeLong’s test).</p>
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<p>Multivariable logistic regression and ROC analysis for the predictive factors. Top, Model “A”, represents the initial model obtained by using the forward stepwise method (NGAL/C3:0); Model “B” reflects the incorporation of Gal-3 into the previous model, and Model “C” shows the final model achieved by the stepwise procedure. The odds ratio (OR) with 95% confidence interval (CI), <span class="html-italic">p</span>-value, and area under the ROC curve (AUC) with 95%CI are exposed for each model. Bottom, ROC curves (AUC) obtained by using the leave-one-out (LOO) cross-validation method. C3:0, propionylcarnitine; Gal-3, galectin-3; NGAL, neutrophil gelatinase-associated lipocalin.</p>
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<p>Potential evolution of SCAD to HF or all-cause death. After the occlusion of the coronary artery, the cardiac cell may induce mitochondrial adaptations (i.e., switch of energetic substrate and the subsequent reduction in SCAC) followed by pro-inflammatory (i.e., NGAL) and pro-fibrotic (i.e., Gal-3) overexpression. However, some patients might enforce and prolong this cardiac remodeling, which could lead to HF or worse evolution SCAC, short-chain acylcarnitines.</p>
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18 pages, 2672 KiB  
Article
Newly Initiated Statin Treatment Is Associated with Decreased Plasma Coenzyme Q10 Level After Acute ST-Elevation Myocardial Infarction
by Erika Csengo, Hajnalka Lorincz, Eva Csosz, Andrea Guba, Bettina Karai, Judit Toth, Sara Csiha, Gyorgy Paragh, Mariann Harangi and Gergely Gyorgy Nagy
Int. J. Mol. Sci. 2025, 26(1), 106; https://doi.org/10.3390/ijms26010106 - 26 Dec 2024
Viewed by 534
Abstract
Coenzyme Q10 (CoQ10) plays a crucial role in facilitating electron transport during oxidative phosphorylation, thus contributing to cellular energy production. Statin treatment causes a decrease in CoQ10 levels in muscle tissue as well as in serum, which may contribute to the musculoskeletal side [...] Read more.
Coenzyme Q10 (CoQ10) plays a crucial role in facilitating electron transport during oxidative phosphorylation, thus contributing to cellular energy production. Statin treatment causes a decrease in CoQ10 levels in muscle tissue as well as in serum, which may contribute to the musculoskeletal side effects. Therefore, we aimed to assess the effect of newly initiated statin treatment on serum CoQ10 levels after acute ST-elevation myocardial infarction (STEMI) and the correlation of CoQ10 levels with key biomarkers of subclinical or clinically overt myopathy. In this study, we enrolled 67 non-diabetic, statin-naïve early-onset STEMI patients with preserved renal function. Plasma CoQ10 level was determined by ultra-high-performance liquid chromatography–tandem mass spectrometry (UPLC/MS-MS), while the myopathy marker serum fatty acid-binding protein 3 (FABP3) level was measured with enzyme-linked immunosorbent assay (ELISA) at hospital admission and after 3 months of statin treatment. The treatment significantly decreased the plasma CoQ10 (by 43%) and FABP3 levels (by 79%) as well as total cholesterol, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B100 (ApoB100), and oxidized LDL (oxLDL) levels. The change in CoQ10 level showed significant positive correlations with the changes in total cholesterol, LDL-C, ApoB100, and oxLDL levels, while it did not correlate with the change in FABP3 level. Our results prove the CoQ10-reducing effect of statin treatment and demonstrate its lipid-lowering efficacy but contradict the role of CoQ10 reduction in statin-induced myopathy. Full article
(This article belongs to the Special Issue Lipid Metabolism in Human Health and Diseases)
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<p>Median (<b>a</b>,<b>b</b>) or mean (<b>c</b>–<b>f</b>) and individual levels of plasma CoQ10 (<b>a</b>) and serum levels of FABP3 (<b>b</b>), total cholesterol (<b>c</b>), LDL-C (<b>d</b>), Apo B100 (<b>e</b>), and oxLDL (<b>f</b>) in patients with STEMI (<span class="html-italic">n</span> = 67) at admission (baseline) and after the 3-month statin therapy. Abbreviations: Apo B100, apolipoprotein B100; CoQ10, Coenzyme Q10; FABP3, fatty acid-binding protein-3; LDL-C, low-density lipoprotein cholesterol; oxLDL, oxidized LDL.</p>
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<p>Correlations between the change in serum levels of total cholesterol (<b>a</b>), LDL-C (<b>b</b>), Apo B100 (<b>c</b>), and oxLDL (<b>d</b>) and the change in plasma CoQ10 level in patients with STEMI (<span class="html-italic">n</span> = 67) during the 3-month statin therapy. Abbreviations: Apo B100, apolipoprotein B100; CoQ10, Coenzyme Q10; LDL-C, low-density lipoprotein cholesterol; oxLDL, oxidized LDL.</p>
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12 pages, 896 KiB  
Article
Platelets, Biomarkers of Coagulation and Fibrinolysis, and Early Coronary Stent Thrombosis
by Lukas Galli, Alexander Sator, Stephanie Schauer, Konstantin Bräu, Johannes Bernhard, Christian Hengstenberg, Clemens Gangl, Rayyan Hemetsberger, Christian Roth, Rudolf Berger, Konstantin A. Krychtiuk and Walter S. Speidl
J. Clin. Med. 2025, 14(1), 56; https://doi.org/10.3390/jcm14010056 - 26 Dec 2024
Viewed by 393
Abstract
Background/Objectives: Acute stent thrombosis (ST) is a rare yet severe complication following percutaneous coronary intervention (PCI). Herein, we investigated the possible association between routinely available coagulation and fibrinolysis markers with early ST. Methods: Within a single-center registry, we investigated the association [...] Read more.
Background/Objectives: Acute stent thrombosis (ST) is a rare yet severe complication following percutaneous coronary intervention (PCI). Herein, we investigated the possible association between routinely available coagulation and fibrinolysis markers with early ST. Methods: Within a single-center registry, we investigated the association between the preprocedural platelet count, plasma levels of fibrinogen and D-Dimer, and the incidence of early ST in the first 30 days after PCI. Results: Out of 10,714 consecutive patients who underwent PCI using drug-eluting stents (DESs), the preprocedural platelet count, fibrinogen, and D-Dimer measurements were available in 6337, 6155, and 956 patients, respectively. Fifty-eight patients (0.92%) experienced an early ST within 30 days after PCI. Compared with those without ST, patients with early ST showed significantly elevated preprocedural platelet counts (p < 0.05) and fibrinogen levels (p < 0.05). D-Dimer levels were not associated with early ST. Patients in the fifth quintile of platelet count had a significantly increased risk for early ST (HR 2.43; 95% CI 1.43–4.14; p = 0.001) compared with patients in the lower four quintiles. In addition, patients in the fifth quintile of fibrinogen also had a significantly increased risk for early ST (HR 1.86; 95% CI 1.07–3.26; p < 0.05) compared with patients in the lower four quintiles. These associations were independent of clinical risk factors, the number of stents, the presence of acute coronary syndromes, and white blood cell count. Conclusions: Preprocedural platelet counts and fibrinogen plasma levels can identify patients at elevated risk of early ST after implantation of DESs in addition to procedure-level and device-related risk factors. Full article
(This article belongs to the Section Cardiology)
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<p>Preprocedural coagulation parameters and early stent thrombosis. Preprocedural platelet count (<b>A</b>), plasma levels of fibrinogen (<b>B</b>), and plasma levels of D-Dimer (<b>C</b>) in patients with and without definite early (&lt;30 days) stent thrombosis.</p>
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<p>Kaplan–Meier curves for early stent thrombosis according to quintiles of coagulation parameters. Patients were stratified according to preprocedural platelet count (<b>A</b>) and plasma levels of fibrinogen (<b>B</b>) above and below the fifth quintile. Patients with platelet count and fibrinogen in the fifth quintile (platelets high and fibrinogen high) showed a markedly increased rate of definite, early (&lt;30 days) ST. Patients with platelet count and fibrinogen in the four lower quintiles (platelet low, fibrinogen low) showed the lowest rate of ST (<b>C</b>). The <span class="html-italic">p</span>-value was calculated by log-rank test.</p>
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15 pages, 8637 KiB  
Article
SSL5-AnxA5 Fusion Protein Constructed Based on Human Atherosclerotic Plaque scRNA-Seq Data Preventing the Binding of Apoptotic Endothelial Cells, Platelets, and Inflammatory Cells
by Yifei Zhao, Xingyu He, Teng Hu, Tianli Xia, Fangyang Huang, Changming Li, Yiming Li, Fei Chen, Mao Chen, Jun Ma and Yong Peng
Biomedicines 2025, 13(1), 8; https://doi.org/10.3390/biomedicines13010008 - 24 Dec 2024
Viewed by 379
Abstract
Background and aims: Coronary obstruction following plaque rupture is a critical pathophysiological change in the progression of stable angina (SAP) to acute coronary syndrome (ACS). The accumulation of platelets and various inflammatory cells on apoptotic endothelial cells is a key factor in arterial [...] Read more.
Background and aims: Coronary obstruction following plaque rupture is a critical pathophysiological change in the progression of stable angina (SAP) to acute coronary syndrome (ACS). The accumulation of platelets and various inflammatory cells on apoptotic endothelial cells is a key factor in arterial obstruction after plaque rupture. Through single-cell sequencing analysis (scRNA-seq) of plaques from SAP and ACS patients, we identified significant changes in the annexin V and P-selectin glycoprotein ligand 1 pathways. Staphylococcal superantigen-like 5 (SSL5) is an optimal antagonist P-selectin glycoprotein ligand 1 (PSGL1), while annexin V (AnxA5) can precisely detect dead cells in vivo. We constructed the SSL5-AnxA5 fusion protein and observed its role in preventing the interaction between apoptotic endothelial cells, platelets, and inflammatory cells. Methods: The scRNA-seq data were extracted from the Gene Expression Omnibus (GEO) database. Single-cell transcriptome analysis results and cell–cell communication were analyzed to identify the ACS and SAP cell clusters and elucidate the intercellular communication differences. Then, we constructed and verified a fusion protein comprising SSL5 and AnxA5 domains via polymerase chain reaction (PCR) and Western blot. The binding capacity of the fusion protein to P-selectin and apoptotic cells was evaluated by flow cytometry and AnxA5-FITC apoptosis detection kit, respectively. Furthermore, co-incubation and immunofluorescence allowed us to describe the mediation effect of it between inflammatory cells and endothelial cells or activated platelets. Results: Our analysis of the scRNA-seq data showed that SELPLG (PSGL1 gene) and ANNEXIN had higher information flowing in ACS compared to SAP. The SELPLG signaling pathway network demonstrated a higher number of interactions in ACS, while the ANNEXIN signaling pathway network revealed stronger signaling from macrophages toward monocytes in ACS compared to SAP. Competition binding experiments with P-selectin showed that SSL5-AnxA5 induced a decrease in the affinity of PSGL1. SSL5-AnxA5 effectively inhibited the combination of endothelial cells with inflammatory cells and the interaction of activated platelets with inflammatory cells. Additionally, this fusion protein exhibited remarkable capability in binding to apoptotic cells. Conclusions: The bifunctional protein SSL5-AnxA5 exhibits promising potential as a protective agent against local inflammation in arterial tissues, making it an excellent candidate for PSGL1-related therapeutic interventions. Full article
(This article belongs to the Special Issue Angiogenesis and Related Disorders)
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<p>Analysis of single-cell RNA sequencing data in the ACS and SAP groups. (<b>A</b>) UMAP plots showing cell clusters from the ACS and SAP groups. Each dot represents a single cell, color-coded by cluster identity. Cells from both the ACS and SAP groups are distributed across multiple clusters, representing different cell types. (<b>B</b>) Heatmap displaying the expression levels of marker genes across the identified clusters (0–16). (<b>C</b>) UMAP plot showing the annotation of major cell types across both the ACS and SAP groups. (<b>D</b>) Dot plot showing the expression of key marker genes across the identified cell types. (<b>E</b>) Uniform manifold approximation and projection (UMAP) plot showing the distribution of major cell types in the ACS and SAP groups. (<b>F</b>) Stacked bar plot displaying the proportion of different cell types in the ACS and SAP groups. Each bar represents the relative abundance of major cell types, allowing for a comparison of the cell composition between the two groups.</p>
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<p>Comparative analysis of the signaling pathways between the ACS and SAP groups. (<b>A</b>) Bar plot comparing the relative information flow of the signaling pathways between the ACS (red) and SAP (blue) groups. Pathways are ranked based on their contribution to cell–cell communication. (<b>B</b>) Heatmap showing the overall signaling patterns for the ACS (<b>left</b>) and SAP (<b>right</b>) groups. Each square represents the communication strength between a source and a target cell type for a given pathway, with darker colors indicating stronger signaling interactions. (<b>C</b>) Heatmap of the outgoing signaling patterns, comparing the ACS (<b>left</b>) and SAP (<b>right</b>) groups. The signaling strength is color-coded, with darker green representing higher outgoing signaling levels for each cell type. (<b>D</b>) Circle plots showing the number of interactions between cell types in the ACS (<b>left</b>) and SAP (<b>right</b>) groups. The thickness of the lines represents the number of interactions, with thicker lines indicating stronger communication between cell types. (<b>E</b>) Network diagrams illustrating the <span class="html-italic">SELPLG</span> signaling pathway in the ACS (<b>left</b>) and SAP (<b>right</b>) groups. The lines represent interactions between different cell types, with the line thickness indicating the strength of the interaction. (<b>F</b>) Network diagrams illustrating the <span class="html-italic">ANNEXIN</span> signaling pathway in the ACS (<b>left</b>) and SAP (<b>right</b>) groups. (<b>G</b>) Heatmaps comparing the differential number of interactions (<b>left</b>) and the interaction strength (<b>right</b>) between cell types in the ACS and SAP groups. The color intensity represents the degree of difference, with red indicating higher interactions/strength in SAP and blue indicating higher values in ACS. (<b>H</b>) Heatmaps of the <span class="html-italic">SELPLG</span> signaling pathway showing the differential expression of signaling components between the ACS (<b>left</b>) and SAP (<b>right</b>) groups. The color intensity indicates the relative strength of the signaling, with red representing higher expression and blue representing lower expression.</p>
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<p>The preparation and purification of SSL5-AnxA5. (<b>A</b>) Schematic illustration of the SSL5-AnxA5 sequence. (<b>B</b>) Agarose gel electrophoresis analysis of SSL5, linker, AnxA5 and SSL5-AnxA5. (<b>C</b>) SDS-PAGE analysis of nickel agarose affinity chromatography purification of SSL5-AnxA5, M: protein marker; 1: loading sample; 2: flow-through; 3: 20 mM imidazole elution fraction; 4–5: 50 mM imidazole elution fractions; 6: 500 mM imidazole elution fraction. (<b>D</b>) SDS-PAGE analysis of the final protein purification, M: protein marker; 1: target proteins. (<b>E</b>) Western blot analysis of the final protein purification, M: protein marker; 1: target proteins.</p>
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<p>SSL5-AnxA5 binds to PSGL-1 and apoptosis cells. (<b>A</b>) The binding capacity of SSL5-AnxA5 to U937 cell-surface PSGL1. The dark purple area means the binding percentage of P-selectin with PSGL1 in the surface of U937. (<b>B</b>) Statistical results of the binding capacity of SSL5-AnxA5 to U937 cell-surface PSGL1 (n = 3, * <span class="html-italic">p</span> &lt; 0.010; vs. saline group). (<b>C</b>) The binding capacity of SSL5-AnxA5 to apoptosis cells comparing to AnxA5. (<b>D</b>) Statistical results of the binding capacity of SSL5-AnxA5 to apoptosis cells comparing to AnxA5 (n = 3, * <span class="html-italic">p</span> &lt; 0.010; vs. AnxA5 group).</p>
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<p>SSL5-AnxA5 inhibits the interaction of inflammatory cells. (<b>A</b>) SSL5-AnxA5 inhibits interaction of the HUVECs and THP-1. (<b>B</b>) Statistical results of the inhibition capacity of SSL5-AnxA5 in different concentrations (n = 3, * <span class="html-italic">p</span> &lt; 0.010; vs. saline group). (<b>C</b>) SSL5-AnxA5 against the combination of activated platelets with neutrophils. (<b>D</b>) SSL5-AnxA5 against the combination of activated platelets with monocytes. (<b>E</b>) Statistical results of combination between monocytes or neutrophils with platelets in different groups (n = 3, * <span class="html-italic">p</span> &lt; 0.010; vs. saline group).</p>
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13 pages, 4535 KiB  
Article
Tocilizumab in COVID-19: A Double-Edged Sword?
by Bartosz Kudliński, Jacek Zawadzki, Wiktoria Kulińska, Jagoda Kania, Magdalena Murkos, Marta Stolińska, Dominika Zgoła, Anna Noga and Paweł Nowak
Biomedicines 2024, 12(12), 2924; https://doi.org/10.3390/biomedicines12122924 - 23 Dec 2024
Viewed by 498
Abstract
Background/Objectives: SARS-CoV-2 was responsible for the global pandemic. Approximately 10–15% of patients with COVID-19 developed respiratory failure with adult acute respiratory distress syndrome (ARDS), which required treatment in the Intensive Care Unit (ICU). The cytokine storm observed in severe COVID-19 was frequently handled [...] Read more.
Background/Objectives: SARS-CoV-2 was responsible for the global pandemic. Approximately 10–15% of patients with COVID-19 developed respiratory failure with adult acute respiratory distress syndrome (ARDS), which required treatment in the Intensive Care Unit (ICU). The cytokine storm observed in severe COVID-19 was frequently handled with steroids. Synergically, tocilizumab, an anti-interleukin-6 receptor monoclonal antibody, gained popularity as a cytokine storm-suppressing agent. However, immunosuppression was proven to increase the predisposition to infections with resistant bacteria. Our study aimed to assess the relationship between positive tests for secondary infections and the survival of patients with severe COVID-19-attributed ARDS treated with immunosuppressive agents. Methods: This study included 342 patients qualified for the ICU and mechanical ventilation (MV). The patients were divided based on the type of immunomodulating therapy and the culture tests results. Results: The results showed the highest survival rate among patients <61 years, favoring the combined treatment (tocilizumab + steroids). Atrial fibrillation (AF) and coronary heart disease (CHD) correlated with a lower survival rate than other comorbidities. Tocilizumab was associated with an increased risk of positive pathogen cultures, which could potentially cause secondary infections; however, the survival rate among these patients was higher. Conclusions: MV and ICU procedures as well as the application of tocilizumab significantly decreased the mortality rate in patients with severe COVID-19-related ARDS. The suppression of cytokine storms played a crucial role in survival. Tocilizumab was found to be both efficient and safe despite the ‘side effect’ of the increased risk of positive results for secondary infections. Full article
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<p>The probability of survival of COVID-19 patients in the ICU in relation to sex, age, and therapy described by the Kaplan–Meyer curves: (<b>A</b>) Survival probability by sex, with a trend favoring females, though without sufficient statistical significance. (<b>B</b>) Survival probability by therapy, favoring tocilizumab + steroids with marginal statistical significance (<span class="html-italic">p</span> = 0.051). (<b>C</b>) Survival probability by age, with a trend favoring younger patients, which is statistically significant (<span class="html-italic">p</span> &lt; 0.001). Age (years); types of therapy used: steroids, tocilizumab + steroids.</p>
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<p>Age comparison to treatment methods described by the Kaplan–Meyer curves. The differences between the curves are statistically significant (<span class="html-italic">p</span> &lt; 0.05). Regardless of the therapy used, younger patients have a higher survival chance than older ones. Tocilizumab combined with steroids appears to improve outcomes mostly in middle-aged patients (41–60 years), but the effect is less pronounced in the oldest cohort (≥61 years).</p>
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<p>Survival probability of patients with comorbidities such as AF and CHD described by the Kaplan–Meyer curves. The groups of patients suffering from the diseases are smaller in size, though there is a high statistical difference in survival probability favoring patients without CHD (<b>B</b>) and AF (<b>A</b>) in severe COVID-19 (respectively, <span class="html-italic">p</span> = 0.025, <span class="html-italic">p</span> = 0.008). AF—atrial fibrillation, CHD—coronary heart disease.</p>
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<p>Quality chart of patients showing proportions of age, presence of AF, CHD, and mortality with regard to applied therapy. The therapy including tocilizumab + steroids was more frequently used in patients &lt;40 y.o., without AF and/or CHD. The difference between the therapies (toci + steroids vs. steroids) was greater in patients who died (29.3% vs. 70.7%) compared to patients who survived (42.9% vs. 57.1%). AF—atrial fibrillation, CHD—coronary heart disease.</p>
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<p>Potential secondary infections in all patients described by the Kaplan–Meyer curves: (<b>A</b>) The survival probability regarding NDM infection favoring patients with NDM, which is statistically significant (<span class="html-italic">p</span> &lt; 0.0001). The statistical significance is marginal (<span class="html-italic">p</span> = 0.051) in the case of <span class="html-italic">A. baumanii</span> (<b>B</b>) with the same trend, though there is no statistical significance in mortality prediction in the case of VRE and GRE (<b>C</b>,<b>D</b>). The patients with NDM are also the most proportional compared to the patients without secondary infection regarding numbers, meaning it was the most popular SI. NDM—<span class="html-italic">Klebsiella pneumoniae</span> New Delhi metallo-β-lactamase-resistant, VRE—Vancomycin-resistant Enterococcus, <span class="html-italic">A. baumanii—Acinetobacter baumanii</span>, and GRE—Glycopeptide-resistant Enterococcus.</p>
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<p>Probability of survival in potential secondary infections with <span class="html-italic">A. baumanii</span> and NDM and the therapy used, described by the Kaplan–Meyer curves. There is a statistical significance in the case of mortality prediction in NDM (<b>B</b>) and <span class="html-italic">A. baumanii</span> (<b>A</b>) in regard to the therapy used (<span class="html-italic">p</span> &lt; 0.009, <span class="html-italic">p</span> &lt; 0.02), favoring patients treated with tocilizumab + steroids and having NDM (+) or <span class="html-italic">A. baumanii</span> (+). On the contrary, patients treated with steroids only, with no secondary infections, were more likely to die. NDM—<span class="html-italic">Klebsiella pneumoniae</span> New Delhi metallo-β-lactamase-resistant, and <span class="html-italic">A. baumanii—Acinetobacter baumanii.</span></p>
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12 pages, 1037 KiB  
Article
Elevated miRNA-499 Levels in Early Phase of Non-ST Elevation Acute Coronary Syndromes Predict Increased Long-Term Risk of Major Adverse Cardiac Events
by Dawid Miśkowiec, Ewa Szymczyk, Paulina Wejner-Mik, Błażej Michalski, Piotr Lipiec, Michał Simiera, Karolina Kupczyńska and Jarosław D. Kasprzak
J. Clin. Med. 2024, 13(24), 7803; https://doi.org/10.3390/jcm13247803 - 20 Dec 2024
Viewed by 418
Abstract
Background/Objectives: Available data suggest the diagnostic potential of testing microRNAs (miRs) in myocardial infarction, but their prognostic value remains unclear. To evaluate the prognostic value of circulating miRs (miR-1, miR-21, miR-133a, miR-208 and miR-499) for predicting major adverse cardiac events (MACEs), including [...] Read more.
Background/Objectives: Available data suggest the diagnostic potential of testing microRNAs (miRs) in myocardial infarction, but their prognostic value remains unclear. To evaluate the prognostic value of circulating miRs (miR-1, miR-21, miR-133a, miR-208 and miR-499) for predicting major adverse cardiac events (MACEs), including death, non-fatal myocardial infarction (MI) or cardiovascular rehospitalization, in patients with non-ST segment elevation acute coronary syndromes (NSTE-ACS). Methods: Our prospective, single-center, observational study included patients (pts) with NSTE-ACS admitted <24 h after symptoms onset and pts with confirmed stable coronary artery disease (SCAD) as controls. Relative expression of miRs was calculated, and subjects were categorized according to miRs expression on hospital admission into two groups (≤median and >median). Results: Overall, 103 NSTE-ACS (52 NSTEMI/51 UA) and 47 SCAD pts (median age 66 years, 67% male) were included. During the median 895 (581–1134) days of the follow-up, MACE occurred in 75 (50%) patients: 20 (13%) died, 28 (19%) presented with MI, and 65 (43%) were readmitted due to cardiovascular reasons. Incidence of MI, rehospitalization and MACE was significantly higher in pts with elevated (>median) miR-499 [MI: 34.3% vs. 7.3%; HR = 6.0 (2.8–12.7) for rehospitalization; 53.7% vs. 36.2%, HR = 2.3 (1.4–3.8) for MACE; 62.7% vs. 42%, HR = 2.4 (1.5–3.8)] for hospital readmission. In the Cox proportional hazards regression model, miR-499 expression above the median level [HR = 1.8 (1.1–3.1)], high-sensitivity cardiac troponin T [HR = 1.2 (1.02–1.5)], diabetes [HR = 1.7 (1.1–2.8)] and percutaneous intervention during hospital stay [HR = 2.1 (1.1–3.8)] were identified as independent predictors of MACE in long-term observation, even after adjustment for covariates. Conclusions: Elevated miR-499 level on hospital admission in NSTE-ACS is related to an increased rate of MACE in the 2.5-year follow-up. Full article
(This article belongs to the Special Issue Diagnosis, Monitoring, and Treatment of Myocardial Infarction)
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<p>The study flow diagram. NSTE-ACS—ang. non-ST segment elevation acute coronary syndrome; STEMI—ST segment elevation myocardial infarction; NSTEMI—ang. non-ST segment elevation myocardial infarction; UA—ang. unstable angina; SCAD—ang. stable coronary artery disease.</p>
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<p>(<b>A</b>–<b>E</b>) Kaplan–Meier event-free survival curves for freedom from major adverse cardiac events in long-term observation according to particular miRNA levels on hospital admission (above or equal to the median value and below the median value: (<b>A</b>) miRNA-1; (<b>B</b>) miRNA-21; (<b>C</b>) miRNA-208a, (<b>D</b>) miRNA-133a; (<b>E</b>) miRNA 499.</p>
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21 pages, 1179 KiB  
Systematic Review
Cytokine Gene Variants as Predisposing Factors for the Development and Progression of Coronary Artery Disease: A Systematic Review
by Fang Li, Yingshuo Zhang, Yichao Wang, Xiaoyan Cai and Xiongwei Fan
Biomolecules 2024, 14(12), 1631; https://doi.org/10.3390/biom14121631 - 19 Dec 2024
Viewed by 573
Abstract
Coronary artery disease (CAD) is the most prevalent form of cardiovascular disease. A growing body of research shows that interleukins (ILs), such as IL-8, IL-18 and IL-16, elicit pro-inflammatory responses and may play critical roles in the pathologic process of CAD. Single nucleotide [...] Read more.
Coronary artery disease (CAD) is the most prevalent form of cardiovascular disease. A growing body of research shows that interleukins (ILs), such as IL-8, IL-18 and IL-16, elicit pro-inflammatory responses and may play critical roles in the pathologic process of CAD. Single nucleotide polymorphisms (SNPs), capable of generating functional modifications in IL genes, appear to be associated with CAD risk. This study aims to evaluate the associations of ten previously identified SNPs of the three cytokines with susceptibility to or protection of CAD. A systematic review and meta-analysis were conducted using Pubmed, EMBASE, WOS, CENTRAL, CNKI, CBM, Weipu, WANFANG Data and Google Scholar databases for relevant literature published up to September 2024. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for the four genetic models of the investigated SNPs in overall and subgroups analyses. Thirty-eight articles from 16 countries involving 14574 cases and 13001 controls were included. The present meta-analysis revealed no significant association between CAD and IL-8-rs2227306 or five IL-16 SNPs (rs8034928, rs3848180, rs1131445, rs4778889 and rs11556218). However, IL-8-rs4073 was significantly associated with an increased risk of CAD across all genetic models. In contrast, three IL-18 (rs187238, rs1946518 and rs1946519) variants containing minor alleles were associated with decreased risks of CAD under all models. Subgroups analyses by ethnicity indicated that IL-8-rs4073 conferred a significantly higher risk of CAD among Asians, including East, South and West Asians (allelic OR = 1.46, homozygous OR = 1.96, heterozygous OR = 1.47, dominant OR = 1.65), while it showed an inversely significant association with CAD risk in Caucasians (homozygous OR = 0.82, dominant OR = 0.85). Additionally, IL-18-rs187238 and IL-18-rs1946518 were significantly associated with reduced CAD risks in East Asians (for rs187238: allelic OR = 0.72, homozygous OR = 0.33, heterozygous OR = 0.73, dominant OR = 0.71; for rs1946518: allelic OR = 0.62, homozygous OR = 0.38, heterozygous OR = 0.49, dominant OR = 0.45). IL-18-rs187238 also demonstrated protective effects in Middle Eastern populations (allelic OR = 0.76, homozygous OR = 0.63, heterozygous OR = 0.72, dominant OR = 0.71). No significant associations were observed in South Asians or Caucasians for these IL-18 SNPs. Consistent with the overall analysis results, subgroups analyses further highlighted a significant association between IL-8-rs4073 and increased risk of acute coronary syndrome (heterozygous OR = 0.72). IL-18-rs187238 was significantly associated with decreased risks of myocardial infarction (MI) (allelic OR = 0.81, homozygous OR = 0.55, dominant OR = 0.80) and multiple vessel stenosis (allelic OR = 0.54, heterozygous OR = 0.45, dominant OR = 0.45). Similarly, IL-18-rs1946518 was significantly associated with reduced MI risk (allelic OR = 0.75, heterozygous OR = 0.68). These findings support the role of cytokine gene IL-8 and IL-18 variants as predisposing factors for the development and progression of CAD. Full article
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<p>Location of the SNPs on the cytokine genes (<b>A</b>) IL-8, (<b>B</b>) IL-18 and (<b>C</b>) IL-16.</p>
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<p>PRISMA flow chart of study inclusion and exclusion. <b>*</b> indicated one article contributed to the meta-analysis of both IL-8 and IL-16.</p>
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<p>Forest plots of the associations between SNPs rs4073 and rs2227306 of IL-8 and coronary artery disease in the four genetic models [<a href="#B11-biomolecules-14-01631" class="html-bibr">11</a>,<a href="#B12-biomolecules-14-01631" class="html-bibr">12</a>,<a href="#B20-biomolecules-14-01631" class="html-bibr">20</a>,<a href="#B24-biomolecules-14-01631" class="html-bibr">24</a>,<a href="#B25-biomolecules-14-01631" class="html-bibr">25</a>,<a href="#B26-biomolecules-14-01631" class="html-bibr">26</a>,<a href="#B27-biomolecules-14-01631" class="html-bibr">27</a>,<a href="#B28-biomolecules-14-01631" class="html-bibr">28</a>,<a href="#B29-biomolecules-14-01631" class="html-bibr">29</a>,<a href="#B30-biomolecules-14-01631" class="html-bibr">30</a>,<a href="#B31-biomolecules-14-01631" class="html-bibr">31</a>,<a href="#B32-biomolecules-14-01631" class="html-bibr">32</a>,<a href="#B33-biomolecules-14-01631" class="html-bibr">33</a>,<a href="#B34-biomolecules-14-01631" class="html-bibr">34</a>]. (<b>A</b>) A vs. T, (<b>B</b>) AA vs. TT, (<b>C</b>) TA vs. TT, (<b>D</b>) AA/TA vs. TT, (<b>E</b>) T vs. C, (<b>F</b>) TT vs. CC, (<b>G</b>) CT vs. CC, (<b>H</b>) TT/CT vs. CC. <b>*</b> indicated two independent cohorts for investigation of rs4073 and rs2227306 polymorphisms included in one publication.</p>
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<p>Forest plots of the association between SNPs rs187238, rs1946518 and rs1946519 of IL-18 and coronary artery disease in the four genetic models [<a href="#B13-biomolecules-14-01631" class="html-bibr">13</a>,<a href="#B14-biomolecules-14-01631" class="html-bibr">14</a>,<a href="#B15-biomolecules-14-01631" class="html-bibr">15</a>,<a href="#B16-biomolecules-14-01631" class="html-bibr">16</a>,<a href="#B17-biomolecules-14-01631" class="html-bibr">17</a>,<a href="#B35-biomolecules-14-01631" class="html-bibr">35</a>,<a href="#B36-biomolecules-14-01631" class="html-bibr">36</a>,<a href="#B37-biomolecules-14-01631" class="html-bibr">37</a>,<a href="#B38-biomolecules-14-01631" class="html-bibr">38</a>,<a href="#B39-biomolecules-14-01631" class="html-bibr">39</a>,<a href="#B40-biomolecules-14-01631" class="html-bibr">40</a>,<a href="#B41-biomolecules-14-01631" class="html-bibr">41</a>,<a href="#B42-biomolecules-14-01631" class="html-bibr">42</a>,<a href="#B43-biomolecules-14-01631" class="html-bibr">43</a>,<a href="#B44-biomolecules-14-01631" class="html-bibr">44</a>,<a href="#B45-biomolecules-14-01631" class="html-bibr">45</a>,<a href="#B47-biomolecules-14-01631" class="html-bibr">47</a>,<a href="#B48-biomolecules-14-01631" class="html-bibr">48</a>]. (<b>A</b>) C vs. G, (<b>B</b>) CC vs. GG, (<b>C</b>) GC vs. GG, (<b>D</b>) CC/GC vs. GG, (<b>E</b>) A vs. C, (<b>F</b>) AA vs. CC, (<b>G</b>) CA vs. CC, (<b>H</b>) AA/CA vs. CC., (<b>I</b>) T vs. G, (<b>J</b>) TT vs. GG, (<b>K</b>) GT vs. GG, (<b>L</b>) TT/GT vs. GG.</p>
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<p>Forest plots of the association between SNPs rs8034928, rs3848180, rs1131445, rs4778889 and rs11556218 of IL-16 and coronary artery disease in the allelic model [<a href="#B18-biomolecules-14-01631" class="html-bibr">18</a>,<a href="#B19-biomolecules-14-01631" class="html-bibr">19</a>,<a href="#B20-biomolecules-14-01631" class="html-bibr">20</a>,<a href="#B49-biomolecules-14-01631" class="html-bibr">49</a>,<a href="#B50-biomolecules-14-01631" class="html-bibr">50</a>,<a href="#B51-biomolecules-14-01631" class="html-bibr">51</a>]. (<b>A</b>) C vs. T, (<b>B</b>) G vs. T, (<b>C</b>) C vs. T, (<b>D</b>) C vs. T and (<b>E</b>) G vs. T. <b>*</b> indicates two independent cohorts for investigation of rs11556218 polymorphism included in one publication.</p>
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<p>The influence of each study by the removal of individual studies for SNPs rs4073 of IL-8, rs187238 and rs1946518 of IL-18 and rs11556218 of IL-16 and coronary artery disease in the allelic model [<a href="#B11-biomolecules-14-01631" class="html-bibr">11</a>,<a href="#B12-biomolecules-14-01631" class="html-bibr">12</a>,<a href="#B13-biomolecules-14-01631" class="html-bibr">13</a>,<a href="#B14-biomolecules-14-01631" class="html-bibr">14</a>,<a href="#B15-biomolecules-14-01631" class="html-bibr">15</a>,<a href="#B16-biomolecules-14-01631" class="html-bibr">16</a>,<a href="#B17-biomolecules-14-01631" class="html-bibr">17</a>,<a href="#B18-biomolecules-14-01631" class="html-bibr">18</a>,<a href="#B19-biomolecules-14-01631" class="html-bibr">19</a>,<a href="#B20-biomolecules-14-01631" class="html-bibr">20</a>,<a href="#B24-biomolecules-14-01631" class="html-bibr">24</a>,<a href="#B25-biomolecules-14-01631" class="html-bibr">25</a>,<a href="#B26-biomolecules-14-01631" class="html-bibr">26</a>,<a href="#B27-biomolecules-14-01631" class="html-bibr">27</a>,<a href="#B28-biomolecules-14-01631" class="html-bibr">28</a>,<a href="#B29-biomolecules-14-01631" class="html-bibr">29</a>,<a href="#B30-biomolecules-14-01631" class="html-bibr">30</a>,<a href="#B31-biomolecules-14-01631" class="html-bibr">31</a>,<a href="#B32-biomolecules-14-01631" class="html-bibr">32</a>,<a href="#B33-biomolecules-14-01631" class="html-bibr">33</a>,<a href="#B34-biomolecules-14-01631" class="html-bibr">34</a>,<a href="#B35-biomolecules-14-01631" class="html-bibr">35</a>,<a href="#B36-biomolecules-14-01631" class="html-bibr">36</a>,<a href="#B37-biomolecules-14-01631" class="html-bibr">37</a>,<a href="#B38-biomolecules-14-01631" class="html-bibr">38</a>,<a href="#B39-biomolecules-14-01631" class="html-bibr">39</a>,<a href="#B40-biomolecules-14-01631" class="html-bibr">40</a>,<a href="#B41-biomolecules-14-01631" class="html-bibr">41</a>,<a href="#B43-biomolecules-14-01631" class="html-bibr">43</a>,<a href="#B44-biomolecules-14-01631" class="html-bibr">44</a>,<a href="#B45-biomolecules-14-01631" class="html-bibr">45</a>,<a href="#B47-biomolecules-14-01631" class="html-bibr">47</a>,<a href="#B48-biomolecules-14-01631" class="html-bibr">48</a>,<a href="#B50-biomolecules-14-01631" class="html-bibr">50</a>,<a href="#B51-biomolecules-14-01631" class="html-bibr">51</a>]. (<b>A</b>) A vs. T, (<b>B</b>) C vs. G, (<b>C</b>) A vs. C, (<b>D</b>) G vs. T. <b>*</b> indicated two independent cohorts for investigation of rs4073 polymorphism included in one publication. <sup>#</sup> indicated two independent cohorts for investigation of rs11556218 polymorphism included in one publication.</p>
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<p>Begg’s funnel plot analysis for publication bias between SNPs rs4073 of IL-8, rs187238 and rs1946518 of IL-18 and rs11556218 of IL-16 and coronary artery disease risk in allelic model. (<b>A</b>) A vs. T, (<b>B</b>) C vs. G, (<b>C</b>) A vs. C, (<b>D</b>) G vs. T.</p>
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13 pages, 795 KiB  
Article
Irisin Predicts Poor Clinical Outcomes in Patients with Heart Failure with Preserved Ejection Fraction and Low Levels of N-Terminal Pro-B-Type Natriuretic Peptide
by Tetiana A. Berezina, Oleksandr O. Berezin, Evgen V. Novikov, Michael Lichtenauer and Alexander E. Berezin
Biomolecules 2024, 14(12), 1615; https://doi.org/10.3390/biom14121615 - 17 Dec 2024
Viewed by 708
Abstract
Background: Despite existing evidence of the high predictive value of natriuretic peptides (NPs) in patients with heart failure (HF), patients treated with guideline-directed therapy who have low or near-normal NP levels are unlikely to be correctly stratified for risk of clinical outcomes. The [...] Read more.
Background: Despite existing evidence of the high predictive value of natriuretic peptides (NPs) in patients with heart failure (HF), patients treated with guideline-directed therapy who have low or near-normal NP levels are unlikely to be correctly stratified for risk of clinical outcomes. The aim of this study is to detect plausible predictors for poor one-year clinical outcomes in patients with HFpEF and low NT-proBNP treated with in accordance with conventional guidelines. Methods: A total of 337 patients with HF with preserved ejection fraction (HFpEF) who had low levels of N-terminal natriuretic pro-peptide (NT-proBNP) at discharge due to optimal guideline-based therapy were enrolled in the study. The course of the observation was 3 years. Echocardiography and the assessment of conventional hematological and biochemical parameters, including NT-proBNP, tumor necrosis factor-alpha, high-sensitivity C-reactive protein (hs-CRP), adropin, irisin, visfatin, and fetuin-A, were performed at baseline and at the end of the study. Results: Three-year cumulative clinical endpoints (cardiovascular death, myocardial infarction or unstable angina or acute coronary syndrome, worsening HF, sudden cardiac death, or cardiac-related surgery or all-cause death) were detected in 104 patients, whereas 233 did not meet the endpoint. After adjusting for an age ≥ 64 years and a presence of atrial fibrillation, diabetes mellitus, chronic kidney disease (CKD) stages 1–3 and dilated cardiomyopathy, the multivariable Cox regression analysis showed that an irisin level of ≤7.2 ng/mL was an independent predictor of cumulative clinical endpoint. Moreover, patients with levels of irisin > 7.2 ng/mL had a better Kaplan–Meier survival rate than those with a lower serum irisin level (≤7.2 ng/mL). Conclusions: Multivariable analysis showed that an age ≥ 64 years; the presence of atrial fibrillation, diabetes mellitus, CKD stages 1–3 and dilated cardiomyopathy; an LAVI ≥ 39 mL/m2; and serum levels of hs-CRP ≥ 6.10 mg/L, irisin ≤ 7.2 ng/mL, and visfatin ≤ 1.1 ng/mL were predictors of poor clinical outcomes in HFpEF with low levels of NT-proBNP. A serum level of irisin ≤ 7.2 ng/mL could emerge as valuable biomarker for predicting long-term prognosis among HFpEF patients with low or near-normal levels of NT-proBNP. Full article
(This article belongs to the Special Issue New Insights into Cardiometabolic Diseases)
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<p>Flowchart of the study design. Abbreviations: ACS, acute coronary syndrome; CV, cardiovascular; ESRD, end-stage renal disease; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HFmrEF, heart failure with mildly reduced ejection fraction; LVEF, left ventricular ejection fraction; MI, myocardial infarct; TNF-alpha, tumor necrosis factor-alpha; hs-CRP, high-sensitivity C-reactive protein; hs-TrT, high-sensitivity troponin T; NT-proBNP, N-terminal natriuretic pro-peptide.</p>
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<p>Kaplan–Meier curves for 3-year cumulative clinical endpoint. Abbreviations: OR, odds ratio; CI, confidence interval.</p>
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