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Inflammatory and Metabolic Biomarkers in Disease Prediction and Prognosis
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Inflammatory and Metabolic Biomarkers in Disease Prediction and Prognosis

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Biochemistry".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1113

Editor

Dr. Recep Dokuyucu

E-Mail Website
Guest Editor
Department of Physiology, Medical Specialty Training Center (TUSMER), 06420 Ankara, Türkiye
Interests: inflammatory biomarkers; metabolic indices; cardiovascular diseases; critical care; neuroinflammation; endocrine disorders; composite inflammatory scores; risk stratification; prognostic modeling; artificial intelligence in medicine; personalized medicine; clinical biochemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Inflammation is a fundamental biological process involved in the initiation, progression, and prognosis of a wide spectrum of diseases, including cardiovascular, neurological, oncological, and metabolic disorders. In recent years, there has been increasing interest in identifying novel inflammatory and metabolic biomarkers that can enhance early diagnosis, risk stratification, and prognostic assessment in clinical practice. Particularly, composite indices derived from routine laboratory parameters—such as inflammatory ratios and integrated metabolic scores—have emerged as practical, cost-effective, and reliable tools in predicting disease severity and clinical outcomes.

This Special Issue provides a comprehensive platform for high-quality research focusing on the role of inflammation-related biomarkers across various disease states. We welcome original research articles, systematic analyses, and reviews that investigate the diagnostic and prognostic value of inflammatory and metabolic markers in both acute and chronic conditions. Special emphasis will be placed on studies evaluating novel indices, multi-parameter predictive models, and their real-world clinical applications.

Furthermore, we encourage submissions that integrate advanced analytical approaches, including machine learning, artificial intelligence, and precision medicine frameworks, to better understand the complex interplay between inflammation and disease mechanisms. By bringing together multidisciplinary perspectives, this Special Issue seeks to contribute to the advancement of personalized and evidence-based clinical strategies, ultimately improving patient outcomes.

Dr. Recep Dokuyucu
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • inflammation
  • biomarkers
  • metabolic indices
  • triglyceride-glucose index
  • inflammatory ratios
  • risk stratification
  • prognosis
  • cardiovascular diseases
  • critical care
  • neuroinflammation
  • endocrine disorders
  • composite inflammatory scores
  • artificial intelligence
  • personalized medicine
  • clinical biochemistry

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Published Papers (2 papers)

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Research

18 pages, 1049 KB  
Article
Serum S100B and Suicidal Ideation in Major Depressive Disorder: Evidence for a Trauma-Mediated Neurobiological Pathway
by Celal Yaşamalı, Şengül Kocamer Şahin, Bahadır Demir, Gülçin Elboğa and Abdurrahman Altındağ
Int. J. Mol. Sci. 2026, 27(11), 4736; https://doi.org/10.3390/ijms27114736 - 25 May 2026
Viewed by 343
Abstract
Serum S100B has been proposed as a peripheral biomarker associated with neuroinflammatory and astroglial stress-related processes in major depressive disorder (MDD). This study aimed to evaluate serum S100B levels in patients with MDD and suicidal ideation and to investigate whether childhood trauma mediates [...] Read more.
Serum S100B has been proposed as a peripheral biomarker associated with neuroinflammatory and astroglial stress-related processes in major depressive disorder (MDD). This study aimed to evaluate serum S100B levels in patients with MDD and suicidal ideation and to investigate whether childhood trauma mediates the relationship between suicide probability and S100B levels. This study included patients with MDD and suicidal ideation (n = 29), patients with MDD without suicidal ideation (n = 30), and healthy controls (n = 29). Serum S100B levels were measured before and after treatment in patients with suicidal ideation. Suicide Probability Scale (SPS), Childhood Trauma Questionnaire (CTQ), and Rosenberg Self-Esteem Scale (RSES) scores were assessed. Group comparisons were performed using Mann–Whitney U and Kruskal–Wallis tests with Dunn–Bonferroni post hoc analysis. Logistic regression and mediation analyses were conducted to examine the relationships among suicide probability, childhood trauma, and S100B levels. Pre-treatment serum S100B levels were significantly higher in patients with MDD and suicidal ideation compared with healthy controls (median 10.95 vs. 8.97 pg/mL, p = 0.001), whereas post-treatment levels did not differ between groups (median 7.84 vs. 8.97 pg/mL, p = 0.323). Within-group analysis demonstrated a significant reduction in S100B levels after treatment (Z = −3.359, p < 0.001). Additional three-group comparison revealed a significant overall difference in S100B levels among the study groups (H = 8.17, p = 0.017). Logistic regression analysis showed that serum S100B levels were independently associated with suicidal ideation (OR = 1.14, 95% CI 1.02–1.27, p = 0.021). Mediation analyses demonstrated a significant indirect effect of suicide probability on S100B levels through childhood trauma (Sobel Z = −2.45, p = 0.014). Serum S100B levels were elevated during the acute phase of MDD with suicidal ideation and decreased following treatment; however, the specificity of this longitudinal change to suicidality could not be determined within the present study design. The relationship between suicide probability and S100B levels appears to be mediated by childhood trauma, suggesting that S100B may reflect trauma-related neurobiological vulnerability rather than a disease-specific biomarker of suicidality. These findings support a potential association between peripheral glial-related biomarkers and stress-responsive neurobiological processes underlying suicidality. Full article
(This article belongs to the Special Issue Inflammatory and Metabolic Biomarkers in Disease Prediction and Prognosis)
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14 pages, 745 KB  
Article
Association of Serum Vitamin D and Hematological Parameters with SARS-CoV-2 PCR Positivity: A Combined Biomarker Approach in Asymptomatic Children
by Mehmet Almacioglu, Ipek Kocer and Demet Ari
Int. J. Mol. Sci. 2026, 27(10), 4393; https://doi.org/10.3390/ijms27104393 - 14 May 2026
Viewed by 417
Abstract
Vitamin D has been implicated in immune modulation and susceptibility to respiratory infections, including COVID-19. However, data in asymptomatic pediatric populations, particularly those with household exposure, remain limited. This study aimed to investigate the association between serum vitamin D levels and hematological parameters [...] Read more.
Vitamin D has been implicated in immune modulation and susceptibility to respiratory infections, including COVID-19. However, data in asymptomatic pediatric populations, particularly those with household exposure, remain limited. This study aimed to investigate the association between serum vitamin D levels and hematological parameters with SARS-CoV-2 PCR positivity in asymptomatic children, and to evaluate their potential role in early risk stratification. This retrospective study included 127 asymptomatic children (aged 2–18 years) with confirmed household exposure to COVID-19. Participants were classified as PCR-positive (n = 74) or PCR-negative (n = 53). Serum 25(OH)D3 levels and hematological parameters were analyzed. Univariate and multivariable logistic regression analyses were performed to identify independent predictors. Receiver operating characteristic (ROC) curve analysis was used to assess discriminative performance, and a combined multimarker model was constructed. Serum vitamin D levels were significantly lower in PCR-positive children compared to PCR-negative children (17 ± 8 vs. 27 ± 11 ng/mL, p = 0.001). White blood cell (p = 0.002), platelet (p = 0.01), and neutrophil counts (p = 0.01) were significantly reduced, while basophil counts were higher in PCR-positive children (p = 0.02). In multivariable analysis, vitamin D (OR: 0.87, 95% CI: 0.82–0.93, p < 0.001), platelet (p = 0.02), neutrophil (p = 0.02), and basophil counts (p = 0.01) remained independent predictors. ROC analysis showed that vitamin D had moderate discriminative performance (AUC: 0.75, 95% CI: 0.67–0.83), while platelet (AUC: 0.64), neutrophil (AUC: 0.61), and basophil (AUC: 0.62) counts showed modest performance. The combined multimarker model demonstrated improved predictive ability (AUC: 0.80, 95% CI: 0.72–0.88), with sensitivity of 71.6% and specificity of 68.2%. Additionally, vitamin D deficiency was significantly more frequent in PCR-positive children (43% vs. 19%, p = 0.003). Conclusions: Lower vitamin D levels and associated hematological alterations are independently associated with SARS-CoV-2 PCR positivity in asymptomatic children. A combined biomarker approach may improve early risk stratification using simple and routinely available parameters. Further prospective studies are needed to validate these findings and clarify the role of vitamin D in preventive strategies. Full article
(This article belongs to the Special Issue Inflammatory and Metabolic Biomarkers in Disease Prediction and Prognosis)
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