Biological Variation of Plasma and Urinary Markers of Acute Kidney Injury in Patients with Chronic Kidney Disease

Urinary biomarkers in kidney disease

BACKGROUND

Chronic kidney disease (CKD) affects many people worldwide and early diagnosis is essential for successful treatment and improved outcome. Unfortunately, current methods are insufficient especially for early disease detection. However, advances in the analytical methods for urinary biomarkers may provide a unique opportunity for diagnosis and management of CKD. This review explores evolving technology and highlights the importance of early marker detection in these patients.

APPROACH

A search strategy was set up using the terms CKD, biomarkers, and urine. The search included 53 studies comprising 37 biomarkers. The value of these biomarkers for CKD are based on their ability to diagnose CKD, monitor progression, assess mortality and nephrotoxicity.

RESULTS

KIM-1 was the best marker for diagnosis as it increased with the development of incident CKD. DKK3 increased in patients with declining eGFR, whereas UMOD decreased in those with declining kidney function. Unfortunately, none fulfilled all criteria to adequately assess mortality and nephrotoxicity.

CONCLUSION

New developments in the field of urinalysis using smart toilets may open several possibilities for urinary biomarkers. This review explored which biomarkers could be used for CKD disease detection and management.

Simultaneous determination of multiple urine biomarkers for kidney injury using SPE combined with LC-MS/MS

BACKGROUND AND OBJECTIVES

Urinary biomarkers such as low molecular weight proteins and small molecular weight metabolites are crucial in the diagnosis of kidney injury. The objective of this study was to develop and preliminarily validate a sensitive and specific method using solid-phase extraction (SPE) in conjunction with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the simultaneous measurement of these biomarkers in human urine.

METHOD

This study presents the development of a solid-phase extraction method integrated with LC-MS/MS analyzing biomarkers including creatinine, urea, β2-microglobulin, α1-microglobulin, and cystatin C in human urine. An enhanced solid-phase cartridge technique was employed for peptide purification and dilution of small molecule metabolites during sample preparation.

RESULTS

The developed LC-MS/MS method achieved satisfactory separation of the five analytes within 15 min. Accuracy levels ranged from -8.6% to 13.6%. Both intra-assay and inter-assay imprecision rates were maintained below 7.9% for all analytes.

CONCLUSIONS

The established LC-MS/MS method effectively quantifies creatinine, urea, β2-microglobulin, α1-microglobulin and cystatin C concurrently. This offers a viable alternative for the detection of kidney injury biomarkers in human urine, demonstrating potential for clinical application in kidney injury diagnosis.

Evaluation of Serum Creatinine Levels with Reference Change Value in Patients Receiving Colistin Treatment

OBJECTIVE

In this study, we aimed to evaluate the serum creatinine (SCr) levels with the reference change value (RCV) in patients receiving colistin treatment.

METHODS

We retrospectively recorded the SCr levels of 47 patients receiving colistin treatment before treatment and on days 3 and 7 after treatment. RCV was calculated with the asymmetrical RCV formula (Z = 1.64, P < .05). Percent (%) increase in the SCr results of the patients was compared with RCV and values exceeding RCV were regarded as statistically significant.

RESULTS

The RCV was calculated as 15.6% for SCr. Compared with pretreatment values, SCr value on day 3 was 32/47 and on day 7 it was 36/47; as these results exceeded RCV, they were considered statistically significant.

CONCLUSION

Use of RCV in the interpretation of results between serial measurements will provide a more rapid and sensitive method when making decisions.

Construction of chronic glomerulonephritis‑related lncRNA‑mRNA regulatory network and lncRNA‑-miRNA‑mRNA ceRNA network by bioinformatics analysis

Long non-coding RNAs (lncRNAs) are ncRNA transcripts >200 nucleotides that are important genetic regulators. LncRNAs can directly regulate mRNA through a lncRNA-mRNA regulatory mode and can also regulate mRNA through competitive binding to micro (mi)RNA, which is generally known as the competitive endogenous RNA (ceRNA) network. The present study evaluated the functional roles and regulatory networks of lncRNAs in chronic glomerulonephritis (CGN). The proliferative ability of mouse glomerular mesangial cells (GMCs) induced by different concentrations of lipopolysaccharide (LPS) was assessed using the Cell Counting Kit-8 assay, and RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs in LPS-induced GMCs. Based on the sequencing results, six lncRNAs were selected for validation using reverse transcription-quantitative PCR (RT-qPCR). Furthermore, the lncRNA-mRNA regulatory network and the lncRNA-miRNA-mRNA ceRNA network were constructed to assess the role and mechanism of CGN-related lncRNAs. To elucidate the biological functions of lncRNAs, Gene Ontology (GO) biological process term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on all mRNAs involved in the lncRNA-mRNA regulatory network and in the ceRNA network. A total of 1,532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were identified using RNA-seq. The results of RT-qPCR validation were consistent with RNA-seq results. An lncRNA-mRNA regulatory network, including 236 lncRNAs and 556 mRNAs, and a ceRNA network, including 6 lncRNAs, 18 miRNAs and 419 mRNAs, were successfully constructed. The GO biological process term enrichment and KEGG pathway enrichment analyses demonstrated that those lncRNAs were often related to inflammatory response and substance metabolism. The present study identified key CGN-related lncRNAs in LPS-induced GMCs, and further demonstrated a global view of the lncRNA-mRNA regulatory network and ceRNA network involved in CGN. These results offered novel insights into the roles of lncRNAs in the pathogenesis of CGN and identified potential diagnostic biomarkers.

Biological variation and reference change value of the estimated glomerular filtration rate in humans: A systematic review and meta-analysis

Background

Knowledge of the biological variation of serum or plasma creatinine (Cr) and the estimated glomerular filtration rate (eGFR) is important for understanding disease dynamics in Chronic Kidney Disease (CKD). The aim of our study was to determine the magnitude of random fluctuation of eGFR by determining its reference change value (RCV).

Methods

We performed a systematic review and meta-analysis of studies on biological variation of Cr. Relevant studies were identified by systematic literature search on PubMed. Additional studies were retrieved from the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Biological Variation Database. Random-effects meta-analysis was conducted to derive an overall estimate of intra-individual variation of creatinine (CV_ICr). Based on our estimate of CV_ICr and RCV for Cr, the RCV for the eGFR was determined.

Results

Among identified studies, 37 met our inclusion criteria. Meta-analysis of all studies yielded a CV_ICr of 5.2% (95% confidence interval [CI] 4.6–5.8%), however high between-study heterogeneity (I² = 82.3%) was found. Exclusion of outliers led to a significant reduction of heterogeneity while still including 85% of all studies and resulted in a slightly lower CV_ICr of 5.0% (95% CI 4.7–5.4%). Assuming an analytical variation of CV_A 1.1%, we found an overall RCV for eGFR of ±16.5%. After exclusion of outlier studies, we found a minimum conservative RCV for eGFR of ±12.5%.

Conclusion

The RCV of the eGFR represents a valuable tool for clinicians to discern true changes in kidney function from random fluctuation.

Reference intervals of urinary kidney injury biomarkers for middle-aged men and women determined by quantitative protein mass spectrometry

BACKGROUND AND AIMS

There is an ongoing need to recognize early kidney injury and its progression in structural chronic pathologies. The proteins NGAL, IGFBP7, TIMP2, KIM-1, CXCL9, TGF-β1, SLC22A2, nephrin, cubilin and uromodulin have been proposed as early kidney injury biomarkers. To guide clinical interpretation, their urinary concentrations should be accompanied by reference intervals, which we here establish in a representative Dutch middle-aged population.

MATERIALS AND METHODS

The 24-h urine samples from 1443 Caucasian middle-aged men and women, were analyzed for the biomarkers by quantitative LC-MS/MS. Biomarker excretion per 24-h were calculated, and urine creatinine and osmolality were measured for dilution normalization. This population was characterized by demographic and anthropometric parameters, comorbid conditions, and conventional kidney function measures.

RESULTS

NGAL, IGFBP7, TIMP2, KIM-1 and uromodulin could be quantified in this population, whereas nephrin, SLC22A2 and CXCL9 were below their detection limits. Urine creatinine and osmolality ( r= -were correlated to urine volume (r = -0.71; -0.74) and to IGFBP7 (r = 0.73; 0.71) and TIMP2 (r = 0.71; 0.69). Crude and normalized biomarker concentrations were affected by sex, but not by age, BMI, smoking, kidney function or common comorbid conditions. The reference intervals (men; women) were 18-108; 21-131 pmol IGFBP7/mmol creatinine, 1- 63; 4-224 pmol NGAL/mmol creatinine, 7-48; 7- 59 pmol TIMP2/mmol creatinine, <1-9; <1-12 pmol KIM-1/mmol creatinine and 0.1-1.2; 0.1-1.7 mg uromodulin/mmol creatinine.

CONCLUSION

We present dilution-normalized and sex-stratified urinary reference intervals of kidney injury biomarkers in a middle-aged Caucasian population.

Biological variation in the serum and urine kidney injury markers of a healthy population measured within 24 hours

BACKGROUND AND AIMS

To explore the biological variation (BV) of kidney injury markers in serum and urine of healthy subjects within 24 hours to assist with interpretation of future studies using these biomarkers in the context of known BV.

MATERIALS AND METHODS

Serum and urine samples were collected every 4 hours (0, 4, 8, 12, 16 and 20 hours) from 31 healthy subjects within 24 hours and serum creatinine (s-Crea), serum β2-microglobin (s-β2MG), serum cystatin C (s-CYSC), serum neutrophil gelatinase-associated lipoprotein (s-NGAL), urine creatinine (u-Crea), urine β2-microglobin (u-β2MG), urine cystatin C (u-CYSC), urine neutrophil gelatinase-associated lipoprotein (u-NGAL) were measured. Outlier and variance homogeneity analyses were performed, followed by CV-ANOVA analysis on trend-corrected data (if relevant), and analytical (CV_A), within-subject (CV_I), and between-subject (CV_G) biological variation were calculated.

RESULTS

The concentration of kidney injury markers in male was higher than that in female, except for u-CYSC and u-NGAL. There were no significant difference in serum and urine kidney injury markers concentration at different time points. Serum CV_I was lower than urine CV_I, serum CV_G was higher than CV_I, and urine CV_G was lower than CV_I. The individual index (II) of serum kidney injury markers was less than 0.6, while the II of urinary kidney injury markers was more than 1.0.

CONCLUSIONS

This study provides new short-term BV data for kidney injury markers in healthy subjects within 24 hours, which are of great significance in explaining other AKI / CKD studies.

Current Knowledge of Selected Cardiovascular Biomarkers in Pediatrics: Kidney Injury Molecule-1, Salusin-α and -β, Uromodulin, and Adropin

Cardiovascular diseases are the leading cause of morbidity and mortality in the modern world. Their common denominator is atherosclerosis, a process beginning in childhood. In pediatrics, the aim of preventive measures is to recognize children and adolescents at risk for accelerated atherosclerosis and possible premature cardiovascular events in adulthood. Several diagnostic procedures and biomarkers are available for cardiovascular risk assessment in adults. However, reliable markers in pediatrics are still insufficiently studied. In this contribution, we discuss five potential biomarkers of particular interest: kidney injury molecule-1, salusin-α and -β, uromodulin, and adropin. Studies regarding the pediatric population are scarce, but they support the evidence from studies in the adult population. These markers might entail both a prognostic and a therapeutic interest.

Development and Provisional Validation of a Multiplex LC-MRM-MS Test for Timely Kidney Injury Detection in Urine

Kidney injury is a complication frequently encountered in hospitalized patients. Early detection of kidney injury prior to loss of renal function is an unmet clinical need that should be targeted by a protein-based biomarker panel. In this study, we aim to quantitate urinary kidney injury biomarkers at the picomolar to nanomolar level by liquid chromatography coupled to tandem mass spectrometry in multiple reaction monitoring mode (LC-MRM-MS). Proteins were immunocaptured from urinary samples, denatured, reduced, alkylated, and digested into peptides before LC-MRM-MS analysis. Stable-isotope-labeled peptides functioned as internal standards, and biomarker concentrations were attained by an external calibration strategy. The method was evaluated for selectivity, carryover, matrix effects, linearity, and imprecision. The LC-MRM-MS method enabled the quantitation of KIM-1, NGAL, TIMP2, IGFBP7, CXCL9, nephrin, and SLC22A2 and the detection of TGF-β1, cubilin, and uromodulin. Two to three peptides were included per protein, and three transitions were monitored per peptide for analytical selectivity. The analytical carryover was <1%, and minimal urine matrix effects were observed by combining immunocapture and targeted LC-MRM-MS analysis. The average total CV of all quantifier peptides was 26%. The linear measurement range was determined per measurand and found to be 0.05–30 nmol/L. The targeted MS-based method enables the multiplex quantitation of low-abundance urinary kidney injury biomarkers for future clinical evaluation.

Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model

IMPORTANCE

Like other clinical biomarkers, trajectories of estimated glomerular filtration rate (eGFR) after kidney transplant are characterized by intra-individual variability. These fluctuations hamper the distinction between alarming graft functional deterioration or harmless fluctuation within the patient-specific expected reference range of eGFR.

OBJECTIVE

To determine whether a deep learning model could accurately predict the patient-specific expected reference range of eGFR after kidney transplant.

DESIGN, SETTING, AND PARTICIPANTS

A multicenter diagnostic study consisted of a derivation cohort of 933 patients who received a kidney transplant between 2004 and 2013 with 100 867 eGFR measurements from University Hospitals Leuven, Belgium, and 2 independent test cohorts: with 39 999 eGFR measurements from 1 170 patients, 1 from University Hospitals Leuven, Belgium, receiving transplants between 2013 and 2018 and 1 from Hannover Medical School, Germany, receiving transplants between 2003 and 2007. Patients receiving a single kidney transplant, with consecutive eGFR measurements were included. Data were analyzed from February 2019 to April 2021.

EXPOSURES

In the derivation cohort 100 867 eGFR measurements were available for analysis and 39 999 eGFR measurements from the independent test cohorts.

MAIN OUTCOMES AND MEASURES

A sequence-to-sequence model was developed for prediction of a patient-specific expected range of eGFR, based on previous eGFR values. The primary outcome was the performance of the deep learning sequence-to-sequence model in the 2 independent cohorts.

RESULTS

In this diagnostic study, a total of 933 patients in the training sets (mean [SD] age, 53.5 [13.3] years; 570 male [61.1%]) and 1170 patients in the independent test sets (cohort 1 [n = 621]: mean [SD] age, 58.5 [12.1] years; 400 male [64.4%]; cohort 2 [n = 549]: mean [SD] age, 50.1 [13.0] years; 316 male [57.6%]) who received a single kidney transplant most frequently from deceased donors, the sequence-to-sequence models accurately predicted future patient-specific eGFR trajectories within the first 3 months after transplant, based on the previous graft eGFR values (root mean square error, 6.4-8.9 mL/min/1.73 m2). The sequence-to-sequence model predictions outperformed the more conventional autoregressive integrated moving average prediction model, at all input/output number of eGFR values.

CONCLUSIONS AND RELEVANCE

In this diagnostic study, a sequence-to-sequence deep learning model was developed and validated for individual forecasting of kidney transplant function. The patient-specific sequence predictions could be used in clinical practice to guide physicians on deviations from the expected intra-individual variability, rather than relating the individual results to the reference range of the healthy population.

AACC Guidance Document on Laboratory Investigation of Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is a sudden episode of kidney damage or failure affecting up to 15% of hospitalized patients and is associated with serious short- and long-term complications, mortality, and health care costs. Current practices to diagnose and stage AKI are variable and do not factor in our improved understanding of the biological and analytical variability of creatinine. In addition, the emergence of biomarkers, for example, cystatin C, insulin-like growth factor binding protein 7, and tissue inhibitor of metalloproteinases 2, and electronic notification tools for earlier detection of AKI, highlights the need for updated recommendations to address these developments.

CONTENT

This AACC Academy guidance document is intended to provide laboratorians and clinicians up-to-date information regarding current best practices for the laboratory investigation of AKI. Topics covered include: clinical indications for further investigating potential AKI, analytical considerations for creatinine assays, the impact of biological variability on diagnostic thresholds, defining "baseline" creatinine, role of traditional markers (urine sodium, fractional excretion of sodium, fractional excretion of urea, and blood urea-to-creatinine ratio), urinary microscopic examination, new biomarkers, improving AKI-associated test utilization, and the utility of automated AKI alerts.

SUMMARY

The previous decade brought us a significant number of new studies characterizing the performance of existing and new biomarkers, as well as potential new tools for early detection and notification of AKI. This guidance document is intended to inform clinicians and laboratorians on the best practices for the laboratory investigation of AKI, based on expert recommendations where the preponderance of evidence is available.

A Review of Specific Biomarkers of Chronic Renal Injury and Their Potential Application in Nonclinical Safety Assessment Studies

A host of novel renal biomarkers have been developed over the past few decades which have enhanced monitoring of renal disease and drug-induced kidney injury in both preclinical studies and in humans. Since chronic kidney disease (CKD) and acute kidney injury (AKI) share similar underlying mechanisms and the tubulointerstitial compartment has a functional role in the progression of CKD, urinary biomarkers of AKI may provide predictive information in chronic renal disease. Numerous studies have explored whether the recent AKI biomarkers could improve upon the standard clinical biomarkers, estimated glomerular filtration rate (eGFR), and urinary albumin to creatinine ratio, for predicting outcomes in CKD patients. This review is an introduction to alternative assays that can be utilized in chronic (>3 months duration) nonclinical safety studies to provide information on renal dysfunction and to demonstrate specific situations where these assays could be utilized in nonclinical drug development. Novel biomarkers such as symmetrical dimethyl arginine, dickkopf homolog 3, and cystatin C predict chronic renal injury in animals, act as surrogates for GFR, and may predict changes in GFR in patients over time, ultimately providing a bridge from preclinical to clinical renal monitoring.

Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes

Objective

Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma; albumin, creatinine, cystatin C, chloride, potassium, sodium and urea.

Content

Relevant studies were identified from a historical BV database as well as by systematic literature searches. Retrieved publications were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC compliant studies with similar design were performed to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV estimates. Out of the 61 identified papers, three received a BIVAC grade A, four grade B, 48 grade C, five grade D grade and one was not appraised as it did not report numerical BV estimates. Most studies were identified for creatinine (n=48). BV estimates derived from the meta-analysis were in general lower than previously reported estimates for all analytes except urea. For some measurands, BV estimates may be influenced by age or states of health, but further data are required.

Summary

This review provides updated global BV estimates for kidney related measurands. For all measurands except for urea, these estimates were lower than previously reported.

Outlook

For the measurands analyzed in this review, there are sufficient well-designed studies available to publish a trustworthy estimate of BV. However, for a number of newly appearing kidney markers no suitable data is available and additional studies are required.

24-hour Serum Creatinine Variation Associates with Short- and Long-Term All-Cause Mortality: A Real-World Insight into Early Detection of Acute Kidney Injury

Real-world evidence describing the variation in serum creatinine (S-Cre) within 24 hours and its prognostic value is unknown. We enrolled 14 912 adults who received two S-Cre measurements within 24 hours at a tertiary hospital between 2003 and 2016. The study population was divided into four groups according to the hospital service settings where the baseline and second S-Cre were measured: Group 1, Outpatient-to-Outpatient; Group 2, Outpatient-to-ED (emergency department) or Inpatient; Group 3, ED-to-ED or Inpatient; and Group 4, Inpatient-to-Inpatient. The main predictors were the difference between the two S-Cre measurements (ΔS-Cre) and the percent change (ΔS-Cre%). The main outcomes were 30-day, 1-year, or 3-year all-cause mortality. A total of 6753 and 8159 patients with an increase and a decrease within-day ΔS-Cre, respectively. Among 6753 patients who had deteriorating ΔS-Cre or ΔS-Cre%, the adjusted hazard ratio (aHR) for 1-year all-cause mortality for each 0.1 mg/dL or 5% change in S-Cre was 1.09 (95% confidence interval [CI]: 1.07, 1.11) and 1.03 (95% CI: 1.03, 1.04). In 8159 patients with improving ΔS-Cre%, the aHR was 0.97 (95% CI: 0.94, 1.00). Groups 3 and 4 had statistically significant positive linear relationships between deteriorating ΔS-Cre% and 30-day and 3-year mortality. The optimal cut-offs for deteriorating ΔS-Cre% for predicting 30-day mortality were approximately 22% for Group 3 and 20% for Group 4. Inpatient within-day deteriorating ΔS-Cre or ΔS-Cre% above 0.2 mg/dL or 20%, respectively, is associated with all-cause mortality. Monitoring 24-hour S-Cre variation identifies acute kidney injury earlier than the conventional criteria.

Proteinuria-take a closer look!

Proteinuria is a hallmark of kidney disease. Therefore, measurement of urine protein content plays a central role in any diagnostic work-up for kidney disease. In many cases, proteinuria analysis is restricted to the measurement of total protein content knowing that very high levels of proteinuria (nephrotic proteinuria) are characteristic of glomerular disease. Still, proteinuria can also be a manifestation of impaired tubular protein reabsorption or even be physiological. This review will discuss the physiology of renal protein handling and give guidance on a more sophisticated analysis of proteinuria differentiating albumin, low-molecular weight proteins and immunoglobulins. These non-invasive tests are available in most routine clinical laboratories and may guide the clinician in the diagnostic process before ordering far more expensive (molecular genetic testing) and/or invasive (kidney biopsy) diagnostics.

European Biological Variation Study (EuBIVAS): Within- and Between-Subject Biological Variation Data for 15 Frequently Measured Proteins

BACKGROUND

The European Biological Variation Study (EuBIVAS) was established to deliver rigorously determined data for biological variation (BV). Here, EuBIVAS-based BV estimates are provided for α1-acid glycoprotein, α1-antitrypsin, albumin, β2-microglobulin, ceruloplasmin, complement component 3, complement component 4, C-reactive protein (CRP), cystatin C, haptoglobin, IgA, IgG, IgM, soluble transferrin receptor (sTfR), and transferrin (Trf), together with their associated analytical performance specifications (APSs) and reference change values (RCVs).

METHOD

Serum samples from weekly blood samplings of 91 healthy study participants (38 males and 53 females, ages 21–69 years old) over 10 consecutive weeks in 6 European laboratories were stored at −80 °C before duplicate analysis on a Roche Cobas c702. Outlier and variance homogeneity analyses were performed followed by CV-ANOVA on trend-corrected data if relevant, to determine BV and analytical variation estimates with CI and the associated RCV.

RESULTS

For the acute phase proteins, several participants experienced mild inflammatory episodes during the study, requiring exclusion of 7% of the 25290 results. Within-subject BV (CVI) estimates for specific proteins obtained in our study were lower than those available in the online 2014 BV database, except for Trf, whereas between-subject BV (CVG) estimates were similar. CVI and CVG estimates for sTfR, which have not previously been published, were 6.0% and 19.1%, respectively.

CONCLUSIONS

In addition to new BV estimates for sTfR, this EuBIVAS substudy generated more demanding APS for frequently requested plasma specific proteins. APS for CRP should not be calculated from BV data except when CRP is used as a risk factor for cardiovascular disease.

Kidney Injury Biomarkers in an Academic Hospital Setting: Where Are We Now?

Acute kidney injury (AKI) is a frequent complication in hospitalised patients and is diagnosed by urinary output and serum creatinine. Serum creatinine is an indirect marker for renal glomerular filtration, but lacks specificity for damage to kidney tissue and the relatively late response to injury precludes early recognition of AKI. Timely diagnosis of kidney injury using biomarkers that provide information about the aetiology of kidney injury is an unmet clinical need. To overcome the suboptimal performance of serum creatinine, injury biomarkers have been proposed that predict AKI in diverse clinical settings. The clinical performance of these markers is considered moderate due to the lack of specificity for kidney tissue or the underlying injury mechanisms, poor test specificity and confounding by interventions or comorbidities. Hence, it is not unequivocally beneficial to implement current kidney injury biomarkers in the clinical laboratory for diagnostic purposes. In this article we review biomarkers that might fulfil AKI-related unmet clinical needs in the academic hospital setting.

A New Criterion for Pediatric AKI Based on the Reference Change Value of Serum Creatinine

BACKGROUND

Current definitions of AKI do not take into account serum creatinine's high variability in children.

METHODS

We analyzed data from 156,075 hospitalized children with at least two creatinine tests within 30 days. We estimated reference change value (RCV) of creatinine on the basis of age and initial creatinine level in children without kidney disease or known AKI risk, and we used these data to develop a model for detecting pediatric AKI on the basis of RCV of creatinine. We defined pediatric AKI according to pediatric reference change value optimized for AKI in children (pROCK) as creatinine increase beyond RCV of creatinine, which was estimated as the greater of 20 μmol/L or 30% of the initial creatinine level.

RESULTS

Of 102,817 children with at least two serum creatinine tests within 7 days, 5432 (5.3%) had AKI as defined by pROCK compared with 15,647 (15.2%) and 10,446 (10.2%) as defined by pediatric RIFLE (pRIFLE) and Kidney Disease Improving Global Outcomes (KDIGO), respectively. Children with pROCK-defined AKI had significantly increased risk of death (hazard ratio, 3.56; 95% confidence interval, 3.15 to 4.04) compared with those without AKI. About 66% of patients with pRIFLE-defined AKI and 51% of patients with KDIGO-defined AKI, mostly children with initial creatinine level of <30 μmol/L, were reclassified as non-AKI by pROCK, and mortality risk in these children was comparable with risk in those without AKI by all definitions.

CONCLUSIONS

pROCK criterion improves detection of "true" AKI in children compared with earlier definitions that may lead to pediatric AKI overdiagnosis.

Biological Variability of Estimated GFR and Albuminuria in CKD

RATIONALE & OBJECTIVE

Determining whether a change in estimated glomerular filtration rate (eGFR) or albuminuria is clinically significant requires knowledge of short-term within-person variability of the measurements, which few studies have addressed in the setting of chronic kidney disease.

STUDY DESIGN

Cross-sectional study with multiple collections over less than 4 weeks.

SETTING & PARTICIPANTS

Clinically stable outpatients with chronic kidney disease (N=50; mean age, 56.8 years; median eGFR, 40mL/min/1.73m²; median urinary albumin-creatinine ratio (UACR), 173mg/g).

EXPOSURE

Repeat measurements from serially collected samples across 3 study visits.

OUTCOMES

Measurements of urine albumin concentration (UAC), UACR, and plasma creatinine, cystatin C, β₂-microglobulin (B2M), and beta trace protein (BTP).

ANALYTICAL APPROACH

We calculated within-person coefficients of variation (CV_w) values and corresponding reference change positive and negative (RCV_pos and RCV_neg) values using log-transformed measurements.

RESULTS

Median CV_w (RCV_pos; RCV_neg) values of filtration markers were 5.4% (+16%; -14%) for serum creatinine, 4.1% (+12%; -11%) for cystatin C, 7.4% (+23%; -18%) for BTP, and 5.6% (+17%; -14%) for B2M. Results for albuminuria were 33.2% (+145%; -59%) for first-morning UAC, 50.6% (+276%; -73%) for random spot UAC, 32.5% (+141%; -58%) for first-morning UACR, and 29.7% (124%; -55%) for random spot UACR. CV_w values for filtration markers were comparable across the range of baseline eGFRs. CV_w values for UAC and UACR were comparable across the range of baseline albuminuria values.

LIMITATIONS

Small sample size limits the ability to detect differences in variability across markers. Participants were recruited and followed up in a clinical and not research setting, so some preanalytical factors could not be controlled.

CONCLUSIONS

eGFR markers appear to have relatively low short-term within-person variability, whereas variability in albuminuria appears to be high, making it difficult to distinguish random variability from meaningful biologic changes.

Biological Variation of Creatinine, Cystatin C, and eGFR over 24 Hours

BACKGROUND

Estimated glomerular filtration rate (eGFR) is widely used in clinical practice. This study assessed the within-subject biological variation (CV_I) of different eGFR equations in people with chronic kidney disease (CKD) and people without CKD. The aims of this study were (a) to determine the 24-h biological variation profiles of creatinine, cystatin C, and eGFR and (b) to determine whether CV_I of creatinine, cystatin C, and eGFR changes on deterioration of glomerular filtration.

METHODS

Hourly blood samples were analyzed from 37 individuals (17 without CKD, 20 with CKD) during 24 h. Creatinine (enzymatic method) and cystatin C were measured using a Cobas 8000 (Roche Diagnostics). eGFR was estimated using the Modification of Diet in Renal Disease and the Chronic Kidney Disease Epidemiology Collaboration based on creatinine and/or cystatin C. Plasma samples were stored at -80 °C before analysis. Outlier and homogeneity analyses were checked before performing a nested ANOVA to determine biological variation.

RESULTS

CV_I of creatinine was higher in people without CKD than in those with CKD (6.4% vs 2.5%) owing primarily to the more profound effect of meat consumption on creatinine variability in individuals with lower baseline creatinine concentrations. Unlike creatinine, cystatin C concentrations were unaffected by meat consumption. Cystatin C showed some diurnal rhythmic variation and less in people with CKD. Reference change values (RCVs) of all eGFR equations were within 13% to 20% in both study groups.

CONCLUSIONS

Despite differences in CV_I of creatinine, the CV_I and RCV of the eGFR equations were relatively similar for people with or without CKD.

Biomarkers for the Early Detection and Prognosis of Acute Kidney Injury

AKI is an increasingly common disorder that is strongly linked to short- and long-term morbidity and mortality. Despite a growing heterogeneity in its causes, providing a timely and certain diagnosis of AKI remains challenging. In this review, we summarize the evolution of AKI biomarker studies over the past few years, focusing on two major areas of investigation: the early detection and prognosis of AKI. We highlight some of the lessons learned in conducting AKI biomarker studies, including ongoing attempts to address the limitations of creatinine as a reference standard and the recent shift toward evaluating the prognostic potential of these markers. Lastly, we suggest current gaps in knowledge and barriers that may be hindering their incorporation into care and a full ascertainment of their value.

Bench to bedside: the next steps for biomarkers in acute kidney injury

No new biomarker of acute kidney injury (AKI) has entered routine clinical practice after a decade of promise, although liver-fatty acid binding protein (L-FABP), neutrophil gelatinase-associated lipoprotein (NGAL), and the combination of tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP-7) are approved for use in some jurisdictions. Acceptance of creatinine as a surrogate of not just glomerular filtration rate (GFR) but also renal injury, changes in nephrologist workloads, failure to establish the added value of each biomarker to current clinical variables across multiple clinical settings, the lack of treatment options, and simply an insufficient passage of time, have all contributed to the lack of progress. Future studies should establish reference intervals for biomarkers, associate biomarkers with meaningful clinical outcomes including mortality and development of chronic kidney disease, and assess the added value to clinical models. The real value of biomarkers will be determined with intervention trials that use an elevated biomarker to triage to treatment. Ideally, such treatments will be linked directly to the physiological processes, which the biomarker identifies.