Biosensor Innovations for Acute Kidney Injury (AKI) and Chronic Kidney Disease (CKD) Diagnostics.

Progression From Acute Kidney Injury to Chronic Kidney Disease: A Pediatric Perspective

Nomenclature for kidney function and disease: Executive summary and glossary from a Kidney Disease: Improving Global Outcomes (KDIGO) consensus conference

Introduction Nowadays, laboratory evaluation of renal damage is based on conventional poorly-sensitive and poorly-specific markers, such as serum creatinine, urea and electrolyte levels. This stimulated continuous research on novel biochemical markers suitable for diagnosis and monitoring of acute kidney injury (AKI) and chronic kidney disease (CKD). Aim The aim of this paper was to review available evidence regarding novel biomarkers of kidney damage. Material and methods The review of available literature was conducted, using search terms ‘kidney damage biomarker’ and ‘kidney injury biomarker.’ Results and discussion Cystatin C, neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, liver-type fatty acid binding protein, selected urinary enzymes (e.g. N-acetyl-β-glucosidase) and low-molecular-weight proteins (e.g. β-2 microglobulin) seem to be the most promising biomarkers of both AKI and CKD. In turn, asymmetric dimethylarginine, inflammatory/fibrosis parameters (e.g. monocyte chemoattractant protein, transforming growth factor-β1) and Klotho-FGF23 axis raise most interest as the most selective markers of CKD. Conclusions Owing continuing progress in nephrology laboratory diagnostics, novel biomarkers of kidney damage are likely to be introduced in routine clinical practice.

Do Children With Acute Kidney Injury Require Long-term Evaluation for CKD?

Background and Aims The current diagnostic criteria for acute kidney injury (AKI) predict the need for dialysis and early mortality, but are less useful to predict long-term outcomes. Acute kidney disease (AKD) defines patients with AKI or subacute loss of kidney function lasting for more than 7 days, which should predict better subsequent chronic kidney disease (CKD). The aim of this study was to investigate the risk factors and prognosis of AKD and to compare different types of acute/subacute renal impairment among Chinese inpatients. Method From a cohort of 450,000 patients consecutive admitted from June 1, 2012, to March 31, 2018 to five district hospitals, complete data were available from 71,041 inpatients. AKI and AKD were diagnosed based on the Acute Disease Quality Initiative Criteria 2017. Based on this diagnostic criterion of AKI and AKD, patients were classified as having (1) AKI Recover, if Scr back to baseline value within 7 days (renal impairment duration of less than 7 days or rapid recovery within 7 days), and (2) AKD with AKI, if a condition in which stage 1 or greater AKI was present ≥ 7 days after an AKI initiating event (continuous AKI progressing to AKD), (3) AKD without AKI, if Scr levels increased slowly but lasted more than 7 days (subacute AKD without meeting the AKI criterion). Results Of 71,041 inpatients, 16,098 (22.66%) patients developed AKI or AKD. 5,895 (8.30%) AKI patients recovered within 7 days (AKI Recover), 5,623 (7.91%) were followed by AKD and 4,580 (6.44%) patients developed AKD without AKI. Thus, AKI and AKD are frequent complications in Chinese inpatients (Fig 1). Compared to AKI recover or AKD without AKI, patients with AKI followed by AKD had higher hospital mortality (16.59% vs. 3.82% vs. 2.12%, P<0.05) and more de novo CKD (8.95% vs. 7.29% vs. 5.48%, P<0.05). Mortality was proportional to stages of AKI and AKD (P for trend <0.05), while AKI followed by AKD was associated with a higher risk of long-term mortality (hazard ratio (HR) 4.51, 4.32-4.71, P<0.05) as compared to AKD without AKI (HR 2.25, 2.13-2.39, P<0.05) and AKI Recover (HR 1.18, 1.09-1.26, P<0.05). The AKI criterion yielded a higher risk for overall survival and a lower risk for de novo CKD than the AKD criterion, indicating that both criteria imply persistent kidney damage but that a rapid decline in excretory kidney function implies higher mortality risks while a persistent decline may rather result in de novo CKD (Fig 2). Meanwhile, these associations between different kidney injury criteria and outcomes had good generalizability and were constant across different genders, surgeries, and comorbidities (Fig 2). The AKD criterion was robustly associated with overall survival (area under the receiver operating characteristic curve (AUROC) 0.71) and de novo CKD (AUROC 0.71), while AKI criterion showed a relatively lower ability to fitting risk of overall survival (AUROC 0.65, P<0.05) and CKD (AUROC 0.63, P<0.05). Moreover, combining AKI and AKD was strongly associated with long-term mortality (AUROC 0.725) and de novo CKD (AUROC 0.72) compared to each single criterion of AKI or AKD (Fig 3). Conclusion (1) Adding AKD as a definition for renal failure lasting >7 days up to 90 days is of clinical importance in addition to the existing definitions for AKI and CKD. (2) These findings suggest research activities and clinical practice should also focus on AKD, which is far more accurate to predict subsequent de novo CKD.

On Being Better Kidney Doctors: Understanding Trajectories, Probabilities, Predictability, and People

Chronic kidney disease (CKD) is a major health and economic burden within Australia. Estimated glomerular filtration rate (eGFR) and albuminuria (Alb) are used to determine if a patient has CKD, but these routine clinical kidney function measurements are inadequate when predicting progressive CKD. This thesis addressed two themes: firstly, clinical CKD biobanking within Australia; and secondly, improving clinical and research outcomes for CKD patients by developing a prognostic clinical tool.Four aims were completed. i) To establish a clinical biobank, termed the CKD Biobank, within Queensland, Australia and develop this into a bioresource. 100 CKD patients, consisting of patients with diabetic nephropathy, vascular diseases, genetic kidney diseases, glomerulonephritis, and a range of other primary kidney diseases, were recruited. In approximately 80% of these patients, baseline bio-specimens were collected alongside clinical data.ii) To address the need for a better definition of progressive CKD and to identify a robust definition of progressive kidney function decline. A systematic review was conducted to identify definitions of progressive kidney function decline currently used in research. A range of definitions was identified and subsequently investigated within the CKD Queensland Registry. A ≥30% decline in eGFR from baseline was found to be robust in distinguishing between patients who experienced a progressive decline in kidney function and those who did not.iii) To use the CKD Queensland Registry and CKD Biobank to identify biomarkers of progressive CKD. Discovery-based and hypothesis-based approaches were used, within the CKD Queensland Registry and the CKD Biobank, respectively, to identify novel and emerging biomarkers of progressive CKD. Several biomarkers were identified that characterised the pathophysiological mechanisms of CKD, with varying capacity to distinguish between progressive and non-progressive CKD.iv) To develop a novel prognostic clinical tool, termed the “distinguishing risk of progressive CKD” (DROP CKD) tool, for differentiating between progressive and non-progressive CKD patients at baseline biomarker measurements. The DROP CKD tool was a predictive model calculated by linear discriminant analysis and constructed from biomarkers that differed between progressive and non-progressive CKD patients. A step-backwards approach was used for biomarker selection to maximise accuracy of the DROP CKD tool.Three hypotheses were investigated. i) A biobank, designed for a specific application that overcomes the ethics, governance, and quality control hurdles, will prove a valuable bioresource. The CKD Biobank has proved a useful bioresource, not only for this thesis, but for several other research projects. The CKD Biobank was utilised for investigating progressive CKD biomarkers and developing the DROP CKD tool for predicting progressive CKD. This Biobank was used, additionally, to supply bio-specimens from healthy controls for a discovery-based project to identify metabolites with prognostic capabilities in kidney cancer, and bio-specimens from diabetic nephropathy and glomerulonephritis CKD patients for research concerning presence of coagulation proteases in urine.ii) Progressive and non-progressive CKD will be characterised by biomarkers of kidney function, tissue injury, inflammation, oxidative stress, tissue repair, fibrosis, and comorbidities of CKD within the venous blood or urine of CKD patients. Compared to non-progressive patients, progressive patients of the CKD Queensland Registry and the CKD Biobank were characterised as having reduced kidney function, being anaemic, having an altered electrolyte-water balance, metabolic acidosis, dyslipidaemia, and as having mineral and bone disease. Progressive CKD patients of the CKD Biobank were further characterised by tissue injury, inflammation, and hypercoagulability while progressive CKD patients of the CKD Queensland Registry were only additionally characterised by eosinophilia.iii) A panel of the biomarkers, measured at baseline, will accurately predict progressive CKD. Biomarkers that were observed as differing between progressive and non-progressive CKD patients of the CKD Biobank were utilised to develop the DROP CKD tool. Through the step-backwards method, a biomarker panel consisting of eGFR, serum creatinine, cystatin-c, urea, tumour necrosis factor (TNF)-α, TNF Receptor-I, TNF Receptor-II, stem cell factor, tryptase, neutrophil gelatinase-associated lipocalin, tissue factor, bicarbonate, calculated osmolality, and haematocrit were observed as having an accuracy of 95.5% when predicting progressive CKD based on baseline biomarker expression. Moreover, the DROP CKD tool was more accurate than traditional kidney function measurements for determining progressive CKD.This thesis attempted to expand upon CKD biobanking capabilities and improve clinical and research outcomes for CKD patients by developing a novel prognostic clinical tool for predicting progression of CKD. Several avenues of research are still required to produce translatable results that will improve patient outcomes. Defining progressive CKD requires further investigation to identify a definition that robustly characterises a “progressive” decline in kidney function, accounting for the non-linear nature of eGFR decline and associating with meaningful clinical outcomes without underdiagnosing progression. Additional biomarker discovery is needed to identify novel biomarkers which can characterise progressive CKD. Finally, pre-existing and novel biomarkers need to be combined into a panel that can predict progressive CKD. This panel must be assayed in a minimally-invasive, efficient, manner, and communicate clinically-meaningful information to inform clinical management of CKD patients.

Evaluation of urine biomarkers of kidney injury in polycystic kidney disease

Cellular senescence is the irreversible growth arrest subsequent to oncogenic mutations, DNA damage, or metabolic insult. Senescence is associated with ageing and chronic age associated diseases such as cardiovascular disease and diabetes. The involvement of cellular senescence in acute kidney injury (AKI) and chronic kidney disease (CKD) is not fully understood. However, recent studies suggest that such patients have a higher-than-normal level of cellular senescence and accelerated ageing. This study aimed to discover key biomarkers of senescence in AKI and CKD patients compared to other chronic ageing diseases in controls using OLINK proteomics. We show that senescence proteins CKAP4 (p-value < 0.0001) and PTX3 (p-value < 0.0001) are upregulated in AKI and CKD patients compared with controls with chronic diseases, suggesting the proteins may play a role in overall kidney disease development. CKAP4 was found to be differentially expressed in both AKI and CKD when compared to UHCs; hence, this biomarker could be a prognostic senescence biomarker of both AKI and CKD.

World Kidney Day 2013: Acute Kidney Injury—Global Health Alert

Elevated urine neutrophil gelatinase-associated lipocalin can diagnose acute kidney injury in patients with chronic kidney diseases

Novel biomarkers of acute kidney injury: time for implementation?

Cancer and the Kidney: The Growth of Onco-nephrology

Predicting Post-Heart Transplant Composite Renal Outcome Risk in Adults: A Machine Learning Decision Tool

Urinary IL-18 is an early predictive biomarker of acute kidney injury after cardiac surgery