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Biomedicines
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Biomarkers in Chronic Kidney Disease
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Biomarkers in Chronic Kidney Disease

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 20650

Special Issue Editors

Prof. Dr. Francisco Herrera-Gómez

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Guest Editor
1. Kidney Resuscitation and Acute Purification Therapies, Sanidad de Castilla y León and University of Valladolid, Zamora and Valladolid, Spain
2. Transplantation Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
Interests: pharmacoepidemiology; pharmacometrics; pharmaceutical regulatory sciences; biopharmaceuticals; nanopharmaceuticals
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. F. Javier Álvarez

E-Mail Website
Guest Editor
Pharmacological Big Data Laboratory, Faculty of Medicine, University of Valladolid, 47005 Valladolid, Spain
Interests: psychoneuropharmacology; psychopharmacology; pharmacoepidemiology; toxicology; substance abuse
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the evaluation of the real impact of medicines along the wide spectrum of chronic kidney disease (CKD), authentic treatment-effect modifiers, i.e., markers of the effect of medicines, and independent prognostic factors, i.e., markers of the likely progress of a disease regardless of the treatment given, are urgently needed in order to personalize therapies in this population. Also known as a predictive biomarker, the status of treatment effect modifiers changes in accordance with the effect of a given medicine, so it may be used to discern between good and poor responders. Prognostic biomarkers do not change but allow identifying those patients with a better (or worse) prognosis. Importantly, overall information on biomarkers for patients into the kidney disease-improving global outcomes (KDIGO) glomerular filtration rate (GFR) categories G3a to G5 is scarce: Potential markers present a paradoxical effect, mostly evident among end-stage kidney disease (ESKD) patients, compared to individuals with normal kidney function (NKF) or patients in early stages of CKD (KDIGO GFR categories G1 to G2). This Special Issue on Biomarkers in Chronic Kidney Disease is thus aimed as a compilation of original research articles and review articles on potential candidates to predictive and prognostic biomarkers in this susceptible population.

Prof. Dr. Francisco Herrera-Gómez
Prof. Dr. F. Javier Álvarez
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. Biomedicines 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

  • biomarkers
  • chronic kidney disease
  • end-stage kidney disease
  • susceptible population
  • treatment-effect modifiers
  • prognosis
  • personalized medicine
  • translational medicine
  • humans

Published Papers (7 papers)

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Editorial

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4 pages, 208 KiB  
Editorial
Healthcare Data for Achieving a More Personalized Treatment of Chronic Kidney Disease
by Francisco Herrera-Gómez and F. Javier Álvarez
Biomedicines 2021, 9(5), 488; https://doi.org/10.3390/biomedicines9050488 - 29 Apr 2021
Viewed by 1295
Abstract
The current concept of healthcare incites a more personalized treatment of diseases. To this aim, biomarkers are needed to improve decision-making facing chronic kidney disease (CKD) patients. Prognostic markers provided by real-world (observational) evidence are proposed in this Special Issue entitled “Biomarkers in [...] Read more.
The current concept of healthcare incites a more personalized treatment of diseases. To this aim, biomarkers are needed to improve decision-making facing chronic kidney disease (CKD) patients. Prognostic markers provided by real-world (observational) evidence are proposed in this Special Issue entitled “Biomarkers in Chronic Kidney Disease”, with the intention to identify high-risk patients. These markers do not target measurable parameters in patients but clinical endpoints that may be in turn transformed to benefits under the effect of future interventions. Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)

Research

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16 pages, 2573 KiB  
Article
Gut Microbiome Composition Remains Stable in Individuals with Diabetes-Related Early to Late Stage Chronic Kidney Disease
by Ashani Lecamwasam, Tiffanie M. Nelson, Leni Rivera, Elif I. Ekinci, Richard Saffery and Karen M. Dwyer
Biomedicines 2021, 9(1), 19; https://doi.org/10.3390/biomedicines9010019 - 29 Dec 2020
Cited by 11 | Viewed by 3061
Abstract
(1) Background: Individuals with diabetes and chronic kidney disease display gut dysbiosis when compared to healthy controls. However, it is unknown whether there is a change in dysbiosis across the stages of diabetic chronic kidney disease. We investigated a cross-sectional study of patients [...] Read more.
(1) Background: Individuals with diabetes and chronic kidney disease display gut dysbiosis when compared to healthy controls. However, it is unknown whether there is a change in dysbiosis across the stages of diabetic chronic kidney disease. We investigated a cross-sectional study of patients with early and late diabetes associated chronic kidney disease to identify possible microbial differences between these two groups and across each of the stages of diabetic chronic kidney disease. (2) Methods: This cross-sectional study recruited 95 adults. DNA extracted from collected stool samples were used for 16S rRNA sequencing to identify the bacterial community in the gut. (3) Results: The phylum Firmicutes was the most abundant and its mean relative abundance was similar in the early and late chronic kidney disease group, 45.99 ± 0.58% and 49.39 ± 0.55%, respectively. The mean relative abundance for family Bacteroidaceae, was also similar in the early and late group, 29.15 ± 2.02% and 29.16 ± 1.70%, respectively. The lower abundance of Prevotellaceae remained similar across both the early 3.87 ± 1.66% and late 3.36 ± 0.98% diabetic chronic kidney disease groups. (4) Conclusions: The data arising from our cohort of individuals with diabetes associated chronic kidney disease show a predominance of phyla Firmicutes and Bacteroidetes. The families Ruminococcaceae and Bacteroidaceae represent the highest abundance, while the beneficial Prevotellaceae family were reduced in abundance. The most interesting observation is that the relative abundance of these gut microbes does not change across the early and late stages of diabetic chronic kidney disease, suggesting that this is an early event in the development of diabetes associated chronic kidney disease. We hypothesise that the dysbiotic microbiome acquired during the early stages of diabetic chronic kidney disease remains relatively stable and is only one of many risk factors that influence progressive kidney dysfunction. Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)
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12 pages, 1146 KiB  
Article
Advanced Glycation End Products (AGE) and Soluble Forms of AGE Receptor: Emerging Role as Mortality Risk Factors in CKD
by Elena Dozio, Simone Vettoretti, Lara Caldiroli, Silvia Nerini-Molteni, Lorenza Tacchini, Federico Ambrogi, Piergiorgio Messa and Massimiliano M. Corsi Romanelli
Biomedicines 2020, 8(12), 638; https://doi.org/10.3390/biomedicines8120638 - 21 Dec 2020
Cited by 25 | Viewed by 2771
Abstract
Advanced glycation end-products (AGE) can promote chronic kidney disease (CKD) progression and CKD-related morbidities. The soluble receptor for AGE (sRAGE) is a potential biomarker of inflammation and oxidative stress. Here, we explored the role of AGE, glycated albumin, sRAGE and its different forms, [...] Read more.
Advanced glycation end-products (AGE) can promote chronic kidney disease (CKD) progression and CKD-related morbidities. The soluble receptor for AGE (sRAGE) is a potential biomarker of inflammation and oxidative stress. Here, we explored the role of AGE, glycated albumin, sRAGE and its different forms, cRAGE and esRAGE, as prognostic factors for mortality in 111 advanced CKD patients. The median follow-up time was 39 months. AGE were quantified by fluorescence, sRAGE and its forms by ELISA. Malnutrition was screened by the Malnutrition Inflammation Score (MIS). The Cox proportional hazards regression model was used to assess the association of variables with all-cause mortality. Mean levels of sRAGE, esRAGE and cRAGE were 2318 ± 1224, 649 ± 454 and 1669 ± 901 pg/mL. The mean value of cRAGE/esRAGE was 2.82 ± 0.96. AGE were 3026 ± 766 AU and MIS 6.0 ± 4.7. eGFR correlated negatively with AGE, sRAGE, esRAGE and cRAGE, but not with cRAGE/esRAGE. Twenty-eight patients died. No difference was observed between diabetic and non-diabetic patients. Starting dialysis was not associated with enhanced risk of death. AGE, esRAGE and cRAGE/esRAGE were independently associated with all-cause mortality. AGE, esRAGE and cRAGE/esRAGE may help to stratify overall mortality risk. Implementing the clinical evaluation of CKD patients by quantifying these biomarkers can help to improve patient outcomes. Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)
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16 pages, 954 KiB  
Article
Development of a Biomarker Panel to Distinguish Risk of Progressive Chronic Kidney Disease
by Evan Owens, Ken-Soon Tan, Robert Ellis, Sharon Del Vecchio, Tyrone Humphries, Erica Lennan, David Vesey, Helen Healy, Wendy Hoy and Glenda Gobe
Biomedicines 2020, 8(12), 606; https://doi.org/10.3390/biomedicines8120606 - 14 Dec 2020
Cited by 9 | Viewed by 2352
Abstract
Chronic kidney disease (CKD) patients typically progress to kidney failure, but the rate of progression differs per patient or may not occur at all. Current CKD screening methods are sub-optimal at predicting progressive kidney function decline. This investigation develops a model for predicting [...] Read more.
Chronic kidney disease (CKD) patients typically progress to kidney failure, but the rate of progression differs per patient or may not occur at all. Current CKD screening methods are sub-optimal at predicting progressive kidney function decline. This investigation develops a model for predicting progressive CKD based on a panel of biomarkers representing the pathophysiological processes of CKD, kidney function, and common CKD comorbidities. Two patient cohorts are utilised: The CKD Queensland Registry (n = 418), termed the Biomarker Discovery cohort; and the CKD Biobank (n = 62), termed the Predictive Model cohort. Progression status is assigned with a composite outcome of a ≥30% decline in eGFR from baseline, initiation of dialysis, or kidney transplantation. Baseline biomarker measurements are compared between progressive and non-progressive patients via logistic regression. In the Biomarker Discovery cohort, 13 biomarkers differed significantly between progressive and non-progressive patients, while 10 differed in the Predictive Model cohort. From this, a predictive model, based on a biomarker panel of serum creatinine, osteopontin, tryptase, urea, and eGFR, was calculated via linear discriminant analysis. This model has an accuracy of 84.3% when predicting future progressive CKD at baseline, greater than eGFR (66.1%), sCr (67.7%), albuminuria (53.2%), or albumin-creatinine ratio (53.2%). Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)
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14 pages, 1059 KiB  
Article
Amino Acid Metabolites Associated with Chronic Kidney Disease: An Eight-Year Follow-Up Korean Epidemiology Study
by Hansongyi Lee, Han Byul Jang, Min-Gyu Yoo, Sang Ick Park and Hye-Ja Lee
Biomedicines 2020, 8(7), 222; https://doi.org/10.3390/biomedicines8070222 - 17 Jul 2020
Cited by 41 | Viewed by 3598
Abstract
The discovery of metabolomics-based biomarkers has been a focus of recent kidney dysfunction research. In the present study, we aimed to identify metabolites associated with chronic kidney disease (CKD) in the general population using a cross-sectional study design. At baseline, 6.5% of subjects [...] Read more.
The discovery of metabolomics-based biomarkers has been a focus of recent kidney dysfunction research. In the present study, we aimed to identify metabolites associated with chronic kidney disease (CKD) in the general population using a cross-sectional study design. At baseline, 6.5% of subjects had CKD. Pearson correlation analysis showed that 28 metabolites were significantly associated with estimated glomerular filtration rate (eGFR) after Bonferroni correction. Among these metabolites, 4 acylcarnitines, 12 amino acids, 4 biogenic amines, 1 phosphatidylcholine, and 1 sphingolipid were associated with CKD (p < 0.05). After eight years, 13.5% of subjects had CKD. Three amino acid metabolites were positively associated with new-onset CKD: citrulline [odds ratio (OR): 2.41, 95% confidence interval (CI): 1.26–4.59], kynurenine (OR: 1.98, 95% CI: 1.05–3.73), and phenylalanine (OR: 2.68, 95% CI: 1.00–7.16). The kynurenine:tryptophan ratio was also associated with CKD (OR: 3.20; 95% CI: 1.57–6.51). The addition of multiple metabolites significantly improved the CKD prediction by C statistics (0.756–0.85, p < 0.0001), and the net reclassification improvement was 0.84 (95% CI: 0.72–0.96). Elevated hs-C reactive protein (CRP) was associated with new-onset CKD (OR: 1.045, 95% CI: 1.005–1.086); however, this association disappeared following adjustment with the kynurenine:tryptophan ratio. The levels of citrulline and kynurenine and their ratio to tryptophan in CKD patients with proteinuria were worse than those with one or neither characteristic. Together, the results of this study demonstrate that amino acid metabolites are associated with CKD eight years after initial metabolite assessment. These results could improve the identification of subjects at high risk of CKD who have modified amino acid metabolism. Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)
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Review

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15 pages, 1942 KiB  
Review
Sarcopenia in Chronic Kidney Disease: Focus on Advanced Glycation End Products as Mediators and Markers of Oxidative Stress
by Elena Dozio, Simone Vettoretti, Giuseppe Lungarella, Piergiorgio Messa and Massimiliano M. Corsi Romanelli
Biomedicines 2021, 9(4), 405; https://doi.org/10.3390/biomedicines9040405 - 09 Apr 2021
Cited by 22 | Viewed by 3708
Abstract
Sarcopenia is common in chronic kidney disease (CKD), and it is independently associated with morbidity and mortality. Advanced glycation end products (AGE) are mainly known as aging products. In CKD, AGE accumulate due to increased production and reduced kidney excretion. The imbalance between [...] Read more.
Sarcopenia is common in chronic kidney disease (CKD), and it is independently associated with morbidity and mortality. Advanced glycation end products (AGE) are mainly known as aging products. In CKD, AGE accumulate due to increased production and reduced kidney excretion. The imbalance between oxidant/antioxidant capacities in CKD patients is one of the main factors leading to AGE synthesis. AGE can, in turn, promote CKD progression and CKD-related complications by increasing reactive oxygen species generation, inducing inflammation, and promoting fibrosis. All these derangements can further increase AGE and uremic toxin accumulation and promote loss of muscle mass and function. Since the link between AGE and sarcopenia in CKD is far from being fully understood, we revised hereby the data supporting the potential contribution of AGE as mediators of oxidative stress in the pathogenesis of sarcopenia. Understanding how AGE and oxidative stress impact the onset of sarcopenia in CKD may help to identify new potential markers of disease progression and/or therapeutic targets. Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)
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14 pages, 494 KiB  
Review
Potential for Novel Biomarkers in Diabetes-Associated Chronic Kidney Disease: Epigenome, Metabolome, and Gut Microbiome
by Ashani Lecamwasam, Elif I. Ekinci, Richard Saffery and Karen M. Dwyer
Biomedicines 2020, 8(9), 341; https://doi.org/10.3390/biomedicines8090341 - 10 Sep 2020
Cited by 3 | Viewed by 2787
Abstract
Diabetes-associated chronic kidney disease is a pandemic issue. Despite the global increase in the number of individuals with this chronic condition together with increasing morbidity and mortality, there are currently only limited therapeutic options to slow disease progression. One of the reasons for [...] Read more.
Diabetes-associated chronic kidney disease is a pandemic issue. Despite the global increase in the number of individuals with this chronic condition together with increasing morbidity and mortality, there are currently only limited therapeutic options to slow disease progression. One of the reasons for this is that the current-day “gold standard” biomarkers lack adequate sensitivity and specificity to detect early diabetic chronic kidney disease (CKD). This review focuses on the rapidly evolving areas of epigenetics, metabolomics, and the gut microbiome as potential sources of novel biomarkers in diabetes-associated CKD and discusses their relevance to clinical practice. However, it also highlights the problems associated with many studies within these three areas—namely, the lack of adequately powered longitudinal studies, and the lack of reproducibility of results which impede biomarker development and clinical validation in this complex and susceptible population. Full article
(This article belongs to the Special Issue Biomarkers in Chronic Kidney Disease)
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