Non-Invasive Biomarkers in Saliva or Urine: Technical and Biological Variability

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Biomarkers".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1422

Special Issue Editor


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Institute of Molecular Biomedicine, Faculty of Medicine, Comenius University, Sasinkova 4, 811 08 Bratislava, Slovakia
Interests: extracellular mitochondrial DNA; endogenous and exogenous deoxyribonuclease; trauma-induced immunomodulation; neutrophil extracellular traps; the role of neutrophil activation in rheumatoid arthritis
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Special Issue Information

Dear Colleagues,

Clinical medicine is changing rapidly. Most diseases can and should be diagnosed before any symptoms occur. Biomarkers are becoming more and more important for the screening and monitoring of pathologies. However, we suffer from a lack of healthcare professionals. In contrast to blood, alternative diagnostic fluids such as saliva and urine can be collected at home and sent by mail. This kind of sampling is non-invasive, simple, cheap, and, especially, does not require a doctor or a nurse. This is of special importance for virtually healthy patients, who do not have time and the need to go to the doctor. It is unfortunate that very few urinary and even less salivary biomarkers have made it to clinical routine use.

This Special Issue will focus on reviews and original articles about emerging urinary and salivary non-invasive biomarkers of diseases. Of special interest are manuscripts about the causes and consequences of the biological and technical variability in the analyzed parameters, which are likely the major hurdles for wider acceptance. Both, clinical and experimental research manuscripts are welcomed.

Dr. Peter Celec
Guest Editor

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Keywords

  • saliva
  • urine
  • non-invasive diagnostics
  • screening
  • biomarkers

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Published Papers (2 papers)

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Research

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24 pages, 8895 KiB  
Article
Urinary Proteome and Exosome Analysis Protocol for the Discovery of Respiratory Diseases Biomarkers
by Laura Martelo-Vidal, Sara Vázquez-Mera, Pablo Miguéns-Suárez, Susana Belén Bravo-López, Heidi Makrinioti, Vicente Domínguez-Arca, Javier de-Miguel-Díez, Alberto Gómez-Carballa, Antonio Salas, Francisco Javier González-Barcala, Francisco Javier Salgado and Juan José Nieto-Fontarigo
Biomolecules 2025, 15(1), 60; https://doi.org/10.3390/biom15010060 - 3 Jan 2025
Viewed by 1115
Abstract
This study aims to develop a protocol for respiratory disease-associated biomarker discovery by combining urine proteome studies with urinary exosome components analysis (i.e., miRNAs). To achieve this, urine was DTT treated to decrease uromodulin, then concentrated and ultracentrifuged. Proteomic analyses of exosome-free urine [...] Read more.
This study aims to develop a protocol for respiratory disease-associated biomarker discovery by combining urine proteome studies with urinary exosome components analysis (i.e., miRNAs). To achieve this, urine was DTT treated to decrease uromodulin, then concentrated and ultracentrifuged. Proteomic analyses of exosome-free urine were performed using LC-MS/MS. Simultaneously, miRNA expression from urine exosomes was measured using either RTqPCR (pre-amplification) or nCounter Nanostring (non-amplication) analyses. We detected 548 different proteins in exosome-free urine samples (N = 5) with high confidence (FDR < 1%), many of them being expressed in different non-renal tissues. Specifically, lung-related proteins were overrepresented (Fold enrichment = 1.31; FDR = 0.0335) compared to whole human proteome, and 10–15% were already described as protein biomarkers for several pulmonary diseases. Urine proteins identified belong to several functional categories important in respiratory pathology. We could confirm the expression of miRNAs previously connected to respiratory diseases (i.e., miR-16-5p, miR-21-5p, miR-146a-5p, and miR-215-5p) in urine exosomes by RTqPCR. Finally, we detected 333 miRNAs using Nanostring, 15 of them up-regulated in T2high asthma (N = 4) compared to T2low asthma (N = 4) and healthy subjects (N = 4). Therefore, this protocol combining the urinary proteome (exosome free) with the study of urinary exosome components (i.e., miRNAs) holds great potential for molecular biomarker discovery of non-renal and particularly respiratory pathologies. Full article
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Review

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16 pages, 261 KiB  
Review
Noninvasive Urinary Biomarkers for Obesity-Related Metabolic Diseases: Diagnostic Applications and Future Directions
by Shumin Zhan, Xuelian Zhou and Junfen Fu
Biomolecules 2025, 15(5), 633; https://doi.org/10.3390/biom15050633 (registering DOI) - 28 Apr 2025
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Abstract
Obesity-related metabolic diseases include conditions linked to obesity, such as type 2 diabetes, hypertension, steatotic liver disease, and polycystic ovary syndrome. These disorders are primarily caused by insulin resistance, chronic inflammation, and excessive fat accumulation. They represent significant health challenges and often remain [...] Read more.
Obesity-related metabolic diseases include conditions linked to obesity, such as type 2 diabetes, hypertension, steatotic liver disease, and polycystic ovary syndrome. These disorders are primarily caused by insulin resistance, chronic inflammation, and excessive fat accumulation. They represent significant health challenges and often remain asymptomatic during their early stages. Traditional diagnostic tools, including blood glucose, lipid levels, blood pressure, and uric acid measurements, provide valuable insights but fall short of fully capturing the complexity of metabolic dysfunction. Consequently, there is a growing need for noninvasive, easily accessible biomarkers, especially those found in urine, to enable more accurate, sensitive, and patient-friendly diagnostic methods. Urine, with its diverse range of metabolites that reflect the body’s metabolic changes, is an ideal sample for early detection. Recent advancements in urine metabolomics and proteomics have highlighted the potential of urinary biomarkers for diagnosing obesity-related metabolic diseases. Despite challenges such as the need for standardized detection techniques and clinical validation, the integration of artificial intelligence and multi-omics approaches holds significant promise for enhancing diagnostic accuracy and advancing disease management strategies. Full article
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