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The Role of Biomarkers in Cardiovascular Diseases
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The Role of Biomarkers in Cardiovascular Diseases

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Cardiovascular Medicine".

Deadline for manuscript submissions: 25 July 2025 | Viewed by 1040

Special Issue Editor

Dr. Giorgia Panichella

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Guest Editor
Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
Interests: cardiac amyloidosis; hypertrophic cardiomyopathy; cardiomyopathies; heart failure; multimodal imaging; translational medicine; clinical cardiology

Special Issue Information

Dear Colleagues,

As is well known, cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality worldwide, underscoring the urgent need for innovative diagnostic and therapeutic strategies. Biomarkers have emerged as critical elements in addressing these challenges, offering valuable insights into disease mechanisms, risk stratification, and treatment response. The advent of omics technologies has further facilitated the identification of thousands of potential biomarkers, significantly expanding the opportunities for improving early detection and predicting outcomes across a broad range of CVDs. However, despite this promise, the journey from biomarker discovery to clinical application is often full of challenges that impede validation and implementation.

The scope of this Special Issue, "The Role of Biomarkers in Cardiovascular Diseases”, is to explore the multifaceted role of both traditional and non-traditional biomarkers in enhancing our understanding of CVDs, improving early detection, and guiding personalized treatment approaches.

We invite researchers and clinicians to submit original research and comprehensive reviews focused on novel and established cardiovascular biomarkers, their pathophysiological relevance, and their use in precision medicine for cardiovascular care. Your contributions are essential to bridge the gap between research and clinical applications, ultimately improving patient outcomes.

Thank you for your participation, and we look forward to your submissions!

Dr. Giorgia Panichella
Guest Editor

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 Clinical Medicine is an international peer-reviewed open access semimonthly 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

  • biomarkers
  • cardiovascular diseases
  • heart failure
  • ischemic heart disease
  • cardiomyopathy
  • risk stratification
  • diagnosis
  • prognosis
  • inflammation

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

14 pages, 1209 KiB  
Article
Investigation of Growth Differentiation Factor 15 as a Prognostic Biomarker for Major Adverse Limb Events in Peripheral Artery Disease
by Ben Li, Farah Shaikh, Houssam Younes, Batool Abuhalimeh, Abdelrahman Zamzam, Rawand Abdin and Mohammad Qadura
J. Clin. Med. 2025, 14(15), 5239; https://doi.org/10.3390/jcm14155239 - 24 Jul 2025
Abstract
Background/Objectives: Peripheral artery disease (PAD) impacts more than 200 million individuals globally and leads to mortality and morbidity secondary to progressive limb dysfunction and amputation. However, clinical management of PAD remains suboptimal, in part because of the lack of standardized biomarkers to predict [...] Read more.
Background/Objectives: Peripheral artery disease (PAD) impacts more than 200 million individuals globally and leads to mortality and morbidity secondary to progressive limb dysfunction and amputation. However, clinical management of PAD remains suboptimal, in part because of the lack of standardized biomarkers to predict patient outcomes. Growth differentiation factor 15 (GDF15) is a stress-responsive cytokine that has been studied extensively in cardiovascular disease, but its investigation in PAD remains limited. This study aimed to use explainable statistical and machine learning methods to assess the prognostic value of GDF15 for limb outcomes in patients with PAD. Methods: This prognostic investigation was carried out using a prospectively enrolled cohort comprising 454 patients diagnosed with PAD. At baseline, plasma GDF15 levels were measured using a validated multiplex immunoassay. Participants were monitored over a two-year period to assess the occurrence of major adverse limb events (MALE), a composite outcome encompassing major lower extremity amputation, need for open/endovascular revascularization, or acute limb ischemia. An Extreme Gradient Boosting (XGBoost) model was trained to predict 2-year MALE using 10-fold cross-validation, incorporating GDF15 levels along with baseline variables. Model performance was primarily evaluated using the area under the receiver operating characteristic curve (AUROC). Secondary model evaluation metrics were accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). Prediction histogram plots were generated to assess the ability of the model to discriminate between patients who develop vs. do not develop 2-year MALE. For model interpretability, SHapley Additive exPlanations (SHAP) analysis was performed to evaluate the relative contribution of each predictor to model outputs. Results: The mean age of the cohort was 71 (SD 10) years, with 31% (n = 139) being female. Over the two-year follow-up period, 157 patients (34.6%) experienced MALE. The XGBoost model incorporating plasma GDF15 levels and demographic/clinical features achieved excellent performance for predicting 2-year MALE in PAD patients: AUROC 0.84, accuracy 83.5%, sensitivity 83.6%, specificity 83.7%, PPV 87.3%, and NPV 86.2%. The prediction probability histogram for the XGBoost model demonstrated clear separation for patients who developed vs. did not develop 2-year MALE, indicating strong discrimination ability. SHAP analysis showed that GDF15 was the strongest predictive feature for 2-year MALE, followed by age, smoking status, and other cardiovascular comorbidities, highlighting its clinical relevance. Conclusions: Using explainable statistical and machine learning methods, we demonstrated that plasma GDF15 levels have important prognostic value for 2-year MALE in patients with PAD. By integrating clinical variables with GDF15 levels, our machine learning model can support early identification of PAD patients at elevated risk for adverse limb events, facilitating timely referral to vascular specialists and aiding in decisions regarding the aggressiveness of medical/surgical treatment. This precision medicine approach based on a biomarker-guided prognostication algorithm offers a promising strategy for improving limb outcomes in individuals with PAD. Full article
(This article belongs to the Special Issue The Role of Biomarkers in Cardiovascular Diseases)
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16 pages, 1700 KiB  
Article
Association Between Plasma Homocysteine, Folate, Vitamin B12 Levels, and Metabolic Dysfunction Indices in Elderly with Arterial Stiffness
by Jintana Sirivarasai, Prapimporn Chattranukulchai Shantavasinkul, Manasid Thitiwiwatkul, Wutarak Monsuwan, Pachara Panpunuan and Piyamitr Sritara
J. Clin. Med. 2025, 14(9), 2998; https://doi.org/10.3390/jcm14092998 - 26 Apr 2025
Viewed by 644
Abstract
Background/Objectives: Arterial stiffness is a prevalent age-related condition that can significantly increase the risk of cardiovascular disease and mortality in older adults. Understanding the factors that contribute to vascular health, including metabolic dysfunction and hyperhomocysteinemia, alongside vitamin B status, is [...] Read more.
Background/Objectives: Arterial stiffness is a prevalent age-related condition that can significantly increase the risk of cardiovascular disease and mortality in older adults. Understanding the factors that contribute to vascular health, including metabolic dysfunction and hyperhomocysteinemia, alongside vitamin B status, is essential for developing effective interventions. This study aimed to explore the relationship between plasma levels of homocysteine, folate, and vitamin B12, as well as various indices of metabolic dysfunction, in elderly individuals with arterial stiffness. Methods: We conducted a cross-sectional analysis involving 884 participants aged 65 and older, assessing arterial stiffness using the cardio/ankle vascular index method. Additionally, we collected fasting blood samples to evaluate plasma homocysteine, folate, vitamin B12 levels, and other relevant biochemical markers. Results: Higher plasma homocysteine levels are significantly correlated with elevated CAVI scores and increased indices of metabolic dysfunction (p < 0.05). Furthermore, a multivariate logistic regression analysis demonstrated that elevated plasma homocysteine levels, along with higher levels of lipid accumulation product (LAP), triglyceride/glucose index (TyG), and visceral adiposity index (VAI), are associated with increased arterial stiffness. Conclusions: These findings suggest that monitoring and optimizing homocysteine, folate, and vitamin B12 levels may be beneficial for preventing or managing arterial stiffness and related metabolic disorders in the elderly population. Full article
(This article belongs to the Special Issue The Role of Biomarkers in Cardiovascular Diseases)
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