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Novel Biomarkers and Diagnostic Methods of Cardiovascular Disease
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Novel Biomarkers and Diagnostic Methods of Cardiovascular Disease

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Disease Biomarker".

Deadline for manuscript submissions: closed (10 December 2022) | Viewed by 4362

Special Issue Editors

Dr. Estefanía Tarazón

E-Mail Website
Guest Editor
1. Myocardial Dysfunction and Cardiac Transplantation Unit, Health Research Institute Hospital La Fe (IIS La Fe), Valencia, Spain
2. Center for Biomedical Research Network on Cardiovascular Diseases (CIBERCV), Madrid, Spain
Interests: heart failure; acute cellular rejection; Golgi apparatus; cardiomyopathy
Special Issues, Collections and Topics in MDPI journals
Dr. Esther Rosello-Lleti

E-Mail Website
Guest Editor
Myocardial Dysfunction and Cardiac Transplantation Unit, Health Research Institute Hospital La Fe (IIS La Fe), Valencia, Spain
Interests: heart failure; acute cellular rejection; Golgi apparatus; cardiomyopathy

Special Issue Information

Dear Colleagues,

The understanding of cardiovascular diseases and their management has changed dramatically over the last 30 years with the identification of various pathways and the successful development of effective therapies that target them. This has led to a concomitant reduction in mortality and morbidity and an improvement in the functional capacity and quality of life of these patients. However, there are still major unmet needs in the management of these diseases; they continue to be the number one cause of death globally with the social and economic impact remaining largely unchanged. Therefore, it is of utmost importance to identify novel biomarkers and diagnostic methods through endeavors in basic research areas to better understand the disease mechanisms, identify novel biomarkers for early intervention, improved diagnosis, and experimental medicine for better disease management. This Special Issue in the Journal of Personalized Medicine will encompass both review and original research articles by experts in the field.

Dr. Estefanía Tarazón
Dr. Esther Rosello-Lleti
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. Journal of Personalized Medicine 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 2600 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

  • biomarker
  • cardiovascular diseases
  • diseases management
  • experimental medicine
  • diagnosis

Published Papers (2 papers)

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Research

11 pages, 933 KiB  
Article
Fasting Proinsulin Independently Predicts Incident Type 2 Diabetes in the General Population
by Sara Sokooti, Wendy A. Dam, Tamas Szili-Torok, Jolein Gloerich, Alain J. van Gool, Adrian Post, Martin H. de Borst, Ron T. Gansevoort, Hiddo J. L. Heerspink, Robin P. F. Dullaart and Stephan J. L. Bakker
J. Pers. Med. 2022, 12(7), 1131; https://doi.org/10.3390/jpm12071131 - 12 Jul 2022
Cited by 1 | Viewed by 1651
Abstract
Fasting proinsulin levels may serve as a marker of β-cell dysfunction and predict type 2 diabetes (T2D) development. Kidneys have been found to be a major site for the degradation of proinsulin. We aimed to evaluate the predictive value of proinsulin for the [...] Read more.
Fasting proinsulin levels may serve as a marker of β-cell dysfunction and predict type 2 diabetes (T2D) development. Kidneys have been found to be a major site for the degradation of proinsulin. We aimed to evaluate the predictive value of proinsulin for the risk of incident T2D added to a base model of clinical predictors and examined potential effect modification by variables related to kidney function. Proinsulin was measured in plasma with U-PLEX platform using ELISA immunoassay. We included 5001 participants without T2D at baseline and during a median follow up of 7.2 years; 271 participants developed T2D. Higher levels of proinsulin were associated with increased risk of T2D independent of glucose, insulin, C-peptide, and other clinical factors (hazard ratio (HR): 1.28; per 1 SD increase 95% confidence interval (CI): 1.08–1.52). Harrell’s C-index for the Framingham offspring risk score was improved with the addition of proinsulin (p = 0.019). Furthermore, we found effect modification by hypertension (p = 0.019), eGFR (p = 0.020) and urinary albumin excretion (p = 0.034), consistent with an association only present in participants with hypertension or kidney dysfunction. Higher fasting proinsulin level is an independent predictor of incident T2D in the general population, particularly in participants with hypertension or kidney dysfunction. Full article
(This article belongs to the Special Issue Novel Biomarkers and Diagnostic Methods of Cardiovascular Disease)
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19 pages, 1458 KiB  
Article
Prioritization of Candidate Biomarkers for Degenerative Aortic Stenosis through a Systems Biology-Based In-Silico Approach
by Nerea Corbacho-Alonso, Tamara Sastre-Oliva, Cecilia Corros, Teresa Tejerina, Jorge Solis, Luis F. López-Almodovar, Luis R. Padial, Laura Mourino-Alvarez and Maria G. Barderas
J. Pers. Med. 2022, 12(4), 642; https://doi.org/10.3390/jpm12040642 - 15 Apr 2022
Viewed by 2078
Abstract
Degenerative aortic stenosis is the most common valve disease in the elderly and is usually confirmed at an advanced stage when the only treatment is surgery. This work is focused on the study of previously defined biomarkers through systems biology and artificial neuronal [...] Read more.
Degenerative aortic stenosis is the most common valve disease in the elderly and is usually confirmed at an advanced stage when the only treatment is surgery. This work is focused on the study of previously defined biomarkers through systems biology and artificial neuronal networks to understand their potential role within aortic stenosis. The goal was generating a molecular panel of biomarkers to ensure an accurate diagnosis, risk stratification, and follow-up of aortic stenosis patients. We used in silico studies to combine and re-analyze the results of our previous studies and, with information from multiple databases, established a mathematical model. After this, we prioritized two proteins related to endoplasmic reticulum stress, thrombospondin-1 and endoplasmin, which have not been previously validated as markers for aortic stenosis, and analyzed them in a cell model and in plasma from human subjects. Large-scale bioinformatics tools allow us to extract the most significant results after using high throughput analytical techniques. Our results could help to prevent the development of aortic stenosis and open the possibility of a future strategy based on more specific therapies. Full article
(This article belongs to the Special Issue Novel Biomarkers and Diagnostic Methods of Cardiovascular Disease)
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