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Metabolites
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Metabolic Profiling of Cardiovascular Disease, 2nd Edition
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Metabolic Profiling of Cardiovascular Disease, 2nd Edition

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Advances in Metabolomics".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 7640

Special Issue Editors

Prof. Dr. Christian Cadeddu Dessalvi

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Guest Editor
Dept. of Medical Science and Public Health – University of Cagliari, 09124 Cagliari, Italy
Interests: cardiovascula disease; heart failure; cardiovascular metabolism; drug cardiotoxicity; non-invasive cardiovascular imaging
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ernesto D’Aloja

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Guest Editor
Dept. of Medical Science and Public Health–University of Cagliari, Cagliari, Italy
Interests: autopsy; bioethics; forensic medicine; forensic pathology; DNA profiling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Vassilios Fanos

E-Mail Website
Guest Editor
Dept of Surgical Sciences–University of Cagliari, Neonatal Intensive Care Unit AOU Cagliari, Cagliari, Italy
Interests: neonatology; nephrology; pharmacology; infections; microbiomics; metabolomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This second issue dedicated to metabolic profiling of cardiovascular disease certifies the growing role of metabolomics in cardiovascular research. During the last decade, both animal and human studies have endorsed the rapid development of metabolomics in this field, offering new insights into the identification of specific metabolic patterns of high prevalence diseases such as coronary artery disease or heart failure. In this Special Issue, our aim is to provide an in-depth view of metabolomics, addressing the current rationale for its application to cardiology, describing relevant data available from animal and human studies. The issue should show the importance of metabolomic application in understanding the mechanisms underlying diseases from a systems biology perspective, and as a new non-invasive tool for diagnosis, grading, and treatment of cardiovascular diseases.

Prof. Dr. Christian Cadeddu Dessalvi
Prof. Dr. Ernesto D’Aloia
Prof. Dr. Vassilios Fanos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • metabolomics
  • cardiovascular diseases
  • diagnosis
  • personalized medicine
  • biomarkers
  • cardiac function
  • cardiovascular metabolism

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Published Papers (3 papers)

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13 pages, 2735 KiB  
Article
Right Ventricular Subclinical Dysfunction in SLE Patients Correlates with Metabolomic Fingerprint and Organ Damage
by Martino Deidda, Antonio Noto, Davide Firinu, Cristina Piras, William Cordeddu, Claudia Depau, Giulia Costanzo, Stefano Del Giacco, Luigi Atzori, Giuseppe Mercuro and Christian Cadeddu Dessalvi
Metabolites 2023, 13(7), 781; https://doi.org/10.3390/metabo13070781 - 22 Jun 2023
Cited by 2 | Viewed by 1167
Abstract
Systemic lupus erythematosus (SLE) is a chronic inflammatory disease, and several studies have suggested possible early RV involvement. Aim of the study was to evaluate the 3D echo parameters of the right ventricle (RV) and the metabolomic profile to correlate both with SLE [...] Read more.
Systemic lupus erythematosus (SLE) is a chronic inflammatory disease, and several studies have suggested possible early RV involvement. Aim of the study was to evaluate the 3D echo parameters of the right ventricle (RV) and the metabolomic profile to correlate both with SLE severity. Forty SLE patients, free of cardiovascular disease, were enrolled and the following 3D parameters were evaluated: the RV ejection fraction (RV-EF), longitudinal strain of the interventricular septum (Septal LS), longitudinal strain of the free wall (Free-LS) and the fractional area change (FAC). In addition, a metabolomic analysis was performed. Direct correlations were observed between TAPSE values and the RV 3D parameters. Then, when splitting the population according to the SDI value, it was found that patients with higher cumulative damage (≥3) had significantly lower FAC, RV-EF, Septal LS, and Free-LS values; the latter three parameters showed a significant correlation with the metabolic profile of the patients. Furthermore, the division based on SDI values identified different metabolic profiles related to the degree of RV dysfunction. The RV dysfunction induced by the chronic inflammatory state present in SLE can be identified early by 3D echocardiography. Its severity seems to be related to systemic organ damage and the results associated with a specific metabolic fingerprint constituted by 2,4-dihydroxybutyric acid, 3,4-dihydroxybutyric acid, citric acid, glucose, glutamine, glycine, linoleic acid, oleic acid, phosphate, urea, and valine. Full article
(This article belongs to the Special Issue Metabolic Profiling of Cardiovascular Disease, 2nd Edition)
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22 pages, 3202 KiB  
Article
Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults
by Natalia E. Moskaleva, Ksenia M. Shestakova, Alexey V. Kukharenko, Pavel A. Markin, Maria V. Kozhevnikova, Ekaterina O. Korobkova, Alex Brito, Sabina N. Baskhanova, Natalia V. Mesonzhnik, Yuri N. Belenkov, Natalia V. Pyatigorskaya, Elena Tobolkina, Serge Rudaz and Svetlana A. Appolonova
Metabolites 2022, 12(12), 1185; https://doi.org/10.3390/metabo12121185 - 27 Nov 2022
Cited by 10 | Viewed by 2416
Abstract
Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors [...] Read more.
Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p < 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling. Full article
(This article belongs to the Special Issue Metabolic Profiling of Cardiovascular Disease, 2nd Edition)
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Other

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23 pages, 3954 KiB  
Systematic Review
Human Gut Microbiota in Coronary Artery Disease: A Systematic Review and Meta-Analysis
by Marcin Choroszy, Kamil Litwinowicz, Robert Bednarz, Tomasz Roleder, Amir Lerman, Takumi Toya, Karol Kamiński, Emilia Sawicka-Śmiarowska, Magdalena Niemira and Beata Sobieszczańska
Metabolites 2022, 12(12), 1165; https://doi.org/10.3390/metabo12121165 - 23 Nov 2022
Cited by 26 | Viewed by 3083
Abstract
In recent years, the importance of the gut microbiome in human health and disease has increased. Growing evidence suggests that gut dysbiosis might be a crucial risk factor for coronary artery disease (CAD). Therefore, we conducted a systematic review and meta-analysis to determine [...] Read more.
In recent years, the importance of the gut microbiome in human health and disease has increased. Growing evidence suggests that gut dysbiosis might be a crucial risk factor for coronary artery disease (CAD). Therefore, we conducted a systematic review and meta-analysis to determine whether or not CAD is associated with specific changes in the gut microbiome. The V3–V4 regions of the 16S rDNA from fecal samples were analyzed to compare the gut microbiome composition between CAD patients and controls. Our search yielded 1181 articles, of which 21 met inclusion criteria for systematic review and 7 for meta-analysis. The alpha-diversity, including observed OTUs, Shannon and Simpson indices, was significantly decreased in CAD, indicating the reduced richness of the gut microbiome. The most consistent results in a systematic review and meta-analysis pointed out the reduced abundance of Bacteroidetes and Lachnospiraceae in CAD patients. Moreover, Enterobacteriaceae, Lactobacillus, and Streptococcus taxa demonstrated an increased trend in CAD patients. The alterations in the gut microbiota composition are associated with qualitative and quantitative changes in bacterial metabolites, many of which have pro-atherogenic effects on endothelial cells, increasing the risk of developing and progressing CAD. Full article
(This article belongs to the Special Issue Metabolic Profiling of Cardiovascular Disease, 2nd Edition)
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