Flow-based method for the determination of biomarkers urea and ammoniacal nitrogen in saliva

Bioanalysis ◽  
2020 ◽  
Author(s):  
Yanisa Thepchuay ◽  
Carolina FA Costa ◽  
Raquel BR Mesquita ◽  
Benedita Sampaio-Maia ◽  
Duangjai Nacapricha ◽  
...  

Aim: Salivary urea and ammonium levels are potential biomarkers for chronic kidney disease. A fast and efficient assessment of these compounds in the saliva of healthy and diseased individuals may be a useful tool to monitor kidney function. Materials & methods: Ammonium ions were measured with an ammonia selective electrode after conversion to ammonia gas. A urease reactor was incorporated in the manifold to hydrolyze urea to ammonium, thereby providing values of ammonia from both urea and ammonium ions in the sample. The accuracy of the method was assessed by comparison with a commercially available kit for urea and ammonium determination. Conclusion: A sequential injection method for the biparametric determination of salivary urea and ammonium employing a single sequential injection manifold was successfully applied to samples collected from both healthy volunteers and chronic kidney disease patients.

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Irina Lousa ◽  
Maria João Valente ◽  
Susana Rocha ◽  
Sofia D. Viana ◽  
Inês Preguiça ◽  
...  

Abstract Background and Aims The conventionally used biomarkers for chronic kidney disease (CKD) diagnosis are not very sensitive for early diagnosis. Their values become clinically significant only when kidney damage is advanced, and a substantial filtration capacity has been lost. The reliance on these biomarkers may result in a long-time lapse in diagnosis, compromising the earlier use of successful therapeutic interventions to prevent CKD progression and reduce the risk of other common comorbidities. The study of earlier and more sensitive biomarkers for CKD diagnosis is an important medical need. Potentially new biomarkers reflecting different pathophysiological processes underlying CKD, such as changes in renal function, tubulointerstitial injury, inflammation and fibrosis, have been proposed. The use of a panel of biomarkers is likely to be synergetic in detecting CKD, since there are several different mechanisms by which CKD can initiate. Our aim was to identify markers of renal damage/dysfunction and evaluate their sensitivity for CKD detection, in patients at the earlier stages of the disease, stages 1 and 2. Method This study included 32 healthy controls and 29 CKD patients at stages 1 and 2, categorized according to the KDIGO guidelines, using the CKD-EPI equation based on serum creatinine to estimate the glomerular filtration rate (GFR). Causes of CKD in the studied patients were diabetes mellitus (n = 19), polycystic kidney disease (n = 1) and of unknown cause (n = 7) or other (n = 2). Circulating levels of creatinine and β-trace protein (BTP), as markers of renal function; interleukin 6 (IL-6), as a marker of inflammation; tissue inhibitor metalloproteinase 1 (TIMP 1), as a marker of tubulointerstitial injury; pro B-type natriuretic peptide (proBNP), as a marker of cardio-renal dysfunction; and cell-free DNA (cfDNA), as a marker of cellular damage, were evaluated. Results Compared to controls, we found significantly higher values of all studied markers in CKD patients (stage 1 and stage 2): BTP, TIMP-1, IL-6, pro-BNP, and cfDNA. In CKD patients, GFR was negatively correlated with circulating levels of pro-BNP (r = -0.610, P = 0.004, n = 20) and cfDNA (r = -0.408, P = 0.028, n = 29); and, microalbuminuria was positively correlated with circulating levels of BTP (r = 0.465, P = 0.013, n = 28). The biomarker cfDNA was positively correlated with TIMP-1 (r = 0.445, P = 0.16, n = 29) , a marker of tubulointerstitial injury, and with IL-6 (r = 0.670, P < 0.001, n = 29), a marker of inflammation. All patients presented at least two of the studied biomarkers with higher values than the median value presented by controls. Of all studied biomarkers, BTP was the one that was most altered in patients (86.2% presented higher values than the highest value presented by controls). Conclusion Our results suggest that the studied biomarkers are sensitive to the primary response to renal injury, being significantly elevated in the earlier stages of CKD, particularly BTP. Pro-BNP and cfDNA correlate well with disease severity assessed by GFR. The use of a panel comprising several biomarkers, related with different pathophysiological mechanisms underlying CKD initiation and progression, may increase the potential to detect patients at risk, when compared with the evaluation of each biomarker alone. Further validation for the use of these new potential biomarkers requires larger studies with standardized analytical methodologies. Acknowledgments: This work was supported by Applied Molecular Biosciences Unit (UCIBIO) and financed by FEDER COMPETE2020 funds UIDB/04378/2020 and UIDP/04539/2020 (CIBB); by POCI-01-0145-FEDER-007440; by FCT doctoral grant SFRH/BD/145939/2019; by funds from Portugal Regional Coordination and Development Commissions (Norte-01-0145-FEDER-000024).


2019 ◽  
Author(s):  
Ashani R Lecamwasam ◽  
Mohammadreza Mohebbi ◽  
Elif I Ekinci ◽  
Karen M Dwyer ◽  
Richard Saffery

BACKGROUND The importance of identifying people with diabetes and progressive kidney dysfunction relates to the excess morbidity and mortality of this group. Rates of cardiovascular disease are much higher in people with both diabetes and kidney dysfunction than in those with only one of these conditions. By the time these people are identified in current clinical practice, proteinuria and renal dysfunction are already established, limiting the effectiveness of therapeutic interventions. The identification of an epigenetic or blood metabolite signature or gut microbiome profile may identify those with diabetes at risk of progressive chronic kidney disease, in turn providing targeted intervention to improve patient outcomes. OBJECTIVE This study aims to identify potential biomarkers in people with diabetes and chronic kidney disease (CKD) associated with progressive renal injury and to distinguish between stages of chronic kidney disease. Three sources of biomarkers will be explored, including DNA methylation profiles in blood lymphocytes, the metabolomic profile of blood-derived plasma and urine, and the gut microbiome. METHODS The cross-sectional study recruited 121 people with diabetes and varying stages (stages 1-5) of chronic kidney disease. Single-point data collection included blood, urine, and fecal samples in addition to clinical data such as anthropometric measurements and biochemical parameters. Additional information obtained from medical records included patient demographics, medical comorbidities, and medications. RESULTS Data collection commenced in January 2018 and was completed in June 2018. At the time of submission, 121 patients had been recruited, and 119 samples remained after quality control. There were 83 participants in the early diabetes-associated CKD group with a mean estimated glomerular filtration rate (eGFR) of 61.2 mL/min/1.73 m2 (early CKD group consisting of stage 1, 2, and 3a CKD), and 36 participants in the late diabetic CKD group with a mean eGFR of 23.9 mL/min/1.73 m2 (late CKD group, consisting of stage 3b, 4, and 5), <i>P</i><.001. We have successfully obtained DNA for methylation and microbiome analyses using the biospecimens collected via this protocol and are currently analyzing these results together with the metabolome of this cohort of individuals with diabetic CKD. CONCLUSIONS Recent advances have improved our understanding of the epigenome, metabolomics, and the influence of the gut microbiome on the incidence of diseases such as cancers, particularly those related to environmental exposures. However, there is a paucity of literature surrounding these influencers in renal disease. This study will provide insight into the fundamental understanding of the pathophysiology of CKD in individuals with diabetes, especially in novel areas such as epigenetics, metabolomics, and the kidney-gut axis. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/16277


2021 ◽  
Vol 1 (29) ◽  
pp. 21-27
Author(s):  
S. A. Smakotina ◽  
Yu. A. Bokhanov

Objective. Patients with stage 5 chronic kidney disease.Study objective. Determination of factors affecting cognitive function in patients with CKD-5.Design and methods. The study included young and middle-aged patients (18 to 60 years old) (n = 40), there is a terminal stage of chronic kidney disease (CKD). Exclusion criteria: history of diseases of the central nervous system, brain injury, episodes of cerebrovascular accident with severity, coronary artery disease, chronic heart failure, pregnancy, abuse of alcohol, refusal to participate in the study. In a previous work, patient examination data were obtained on the Status PF hardware complex. Neurodynamic indicators were estimated, including the determination of the time of a simple visual-motor reaction (MTCM) and a complex visual-motor reaction (MPSM), reaction to a moving object (RDO), memory and attention. Using Spearman’s correlation analysis, we evaluated the impact on cognitive functions of a number of factors, presumably related to neurodynamics. The following factors were selected: age, creatinine level, NSE and S100 proteins, hemoglobin level, Beck’s depression points, indicators of personal and situational anxiety.Results. All patients examined on the Status PF software package had mild cognitive impairment in terms of neurodynamics, attention, and memory. The average positive relationship between the level of depression and various indicators of RDO was established: with RDO_average (ρ = 0.405; p = 0.018), with RDO_total delay (ρ = 0.540; p < 0.001), with RDO_average delay (ρ = 0.421; p = 0.007), as well as weak positive – with CEMR average exposure (ρ = 0.358; p = 0.023). An average positive relationship of creatinine level with RDO_O (ρ = 0.438; p = 0.005) is noted. A weak positive relationship between the level of personal anxiety and RDO_total delay (ρ = 0.334; p = 0.035) was revealed. The average negative relationship between hemoglobin level and RDO_total delay (ρ = –0.535; p < 0.001) was revealed. A weak positive relationship between situational anxiety and SEMR is determined by the number of errors (ρ = 0.364; p = 0.021), as well as a weak negative one with the attention volume (ρ = –0.357; p = 0.024). A weak negative relationship of age with visual memory per word was revealed (ρ = –0.362; p = 0.022).Domain of usage. Outpatient and hospital treatment stages of patients with chronic kidney disease case management


2014 ◽  
Vol 6 (11) ◽  
pp. 3706-3712 ◽  
Author(s):  
Anna Schulz ◽  
Falko Boeringer ◽  
Janine Swifka ◽  
Axel Kretschmer ◽  
Mandy Schaefer ◽  
...  

Iohexol (1-N,3-N-bis(2,3-dihydroxypropyl)-5-[N-(2,3-dihydroxypropyl) acetamide-2,4,6-triiodobenzene-1,3-dicarboxamide) is used for accurate determination of the glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients.


2019 ◽  
Author(s):  
Carles Forné ◽  
Serafi Cambray ◽  
Marcelino Bermudez-Lopez ◽  
Elvira Fernandez ◽  
Milica Bozic ◽  
...  

Abstract Background Chronic kidney disease (CKD) patients show an increased burden of atherosclerosis and high risk of cardiovascular events (CVEs). There are several biomarkers described as being associated with CVEs, but their combined effectiveness in cardiovascular risk stratification in CKD has not been tested. The objective of this work is to analyse the combined ability of 19 biomarkers associated with atheromatous disease in predicting CVEs after 4 years of follow-up in a subcohort of the NEFRONA study in individuals with different stages of CKD without previous CVEs. Methods Nineteen putative biomarkers were quantified in 1366 patients (73 CVEs) and their ability to predict CVEs was ranked by random survival forest (RSF) analysis. The factors associated with CVEs were tested in Fine and Gray (FG) regression models, with non-cardiovascular death and kidney transplant as competing events. Results RSF analysis detected several biomarkers as relevant for predicting CVEs. Inclusion of those biomarkers in an FG model showed that high levels of osteopontin, osteoprotegerin, matrix metalloproteinase-9 and vascular endothelial growth factor increased the risk for CVEs, but only marginally improved the discrimination obtained with classical clinical parameters: concordance index 0.744 (95% confidence interval 0.609–0.878) versus 0.723 (0.592–0.854), respectively. However, in individuals with diabetes treated with antihypertensives and lipid-lowering drugs, the determination of these biomarkers could help to improve cardiovascular risk estimates. Conclusions We conclude that the determination of four biomarkers in the serum of CKD patients could improve cardiovascular risk prediction in high-risk individuals.


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