Preterm neonatal urinary renal developmental and acute kidney injury metabolomic profiling: an exploratory study

Metabolomic and transcriptomic insights into the mechanisms of renal ischemia-reperfusion injury progression

Renal ischemia-reperfusion injury (IRI) is an important cause of acute kidney injury (AKI). However, the pathophysiological changes and mechanisms during IRI-AKI progression remain unclear. This study aims toinvestigate the potential mechanisms in the progression of IRI-AKI by integrating metabolomics and transcriptomics data, providing a reference for the subsequent identification of biomarkers and therapeutic targets. IRI-AKI rat models with 30 min of ischemia and 24-72 h of reperfusion surgery simulating the progression of AKI were established. Compared to the control group underwent sham surgery (NC group), most of the differentially expressed metabolites (DEMs) in IRI-AKI 24 h and IRI-AKI 72 h decreased, mainly including amino acids, organic acids, and carnitines. Additionally, we found that DEMs were mainly enriched in amino acid-related pathways, among which valine, leucine, and isoleucine biosynthesis were dramatically altered in all comparisons. Transcriptomics revealed that differentially expressed genes (DEGs) were primarily involved in amino acid, lipid, and fatty acid metabolism. By integrating metabolomics and transcriptomics, we found valine, leucine, and isoleucine biosynthesis play key roles in IRI-AKI development. Our findings concluded that valine, leucine, and isoleucine pathways are hubs that potentially connect transcriptomes to metabolomes, providing new insights regarding the pathogenesis of IRI-AKI and its potential biomarkers and therapeutic strategies.

Untargeted and spatial-resolved metabolomics characterize serum and tissue-specific metabolic reprogramming in acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is one of the most common clinical emergencies characterized by rapid progression, difficulty in early diagnosis, and high mortality. Currently, there are no effective AKI early diagnostic methods and treatments. Therefore, identifying new mechanisms of AKI have become urgent for development new targets for early diagnosis and treatment of AKI in the current clinical setting.

METHODS

In this study, systematic analysis and comparison of serum metabolic profiles of clinical AKI patients, chronic kidney disease (CKD) patients, and healthy subjects were performed using untargeted metabolomics. Moreover, the first spatial metabolomic analysis of kidney tissues in an AKI mouse model using MALDI-TOF MS technology was conducted. Differentially expressed metabolites were identified using a comprehensive, publicly available database. The metabolic data obtained were evaluated using principal component analysis, (orthogonal) partial least squares discriminant analysis, and metabolic pathway analysis to explore the unique serum metabolic profile of the patients, as well as to characterize the spatial distribution of differential metabolites in the kidneys of AKI mice.

RESULTS

Significant changes in the metabolite levels of amino acids, carnitine, and lipids were observed in the AKI and CKD groups versus the healthy population, suggesting that kidney injury may lead to abnormalities in various metabolic pathways, such as amino acids, fatty acids, and lipids. The significant difference between the AKI and CKD groups were found for the first time in these indexes including amino acid, carnitine, fatty acid, and lipid levels. Additionally, spatial metabolomics results revealed that amino acid, carnitine, organic acid, and fatty acid metabolites were more likely significantly altered in the renal cortex, while lipid metabolites were both differentially distributed in the cortex and medulla of the AKI group.

CONCLUSION

Abnormalities in the serum metabolism of amino acids, carnitine, and lipids in patients with kidney diseases, such as AKI and CKD, are closely associated with the physiological dysfunction of kidney injury. Metabolic differences between patients with AKI and CKD were compared for the first time, showing that fatty acid oxidative inhibition was more severe in patients with AKI. Furthermore, spatial metabolomics has revealed metabolic reprogramming with tissue heterogeneity in AKI mice model. Our study provides valuable information in the molecular pathological features of AKI in the kidney tissues.

Urine acute kidney injury biomarkers in extremely low gestational age neonates: a nested case control study of 21 candidate urine biomarkers

BACKGROUND

Acute kidney injury (AKI) is common and is associated with poor clinical outcomes in premature neonates. Urine biomarkers hold the promise to improve our understanding and care of patients with kidney disease. Because kidney maturation and gender can impact urine biomarker values in extremely low gestational age neonates (ELGANs), careful control of gestational age (GA) and time is critical to any urine biomarker studies in neonates.

METHODS

To improve our understanding of the potential use of urine biomarkers to detect AKI during the first postnatal weeks, we performed a nested case-control study to evaluate 21 candidate urine AKI biomarkers. Cases include 20 ELGANs with severe AKI. Each case was matched with 2 controls for the same GA week (rounded down to the nearest week), gender, and birth weight (BW) (± 50 g).

RESULTS

Urine cystatin C, creatinine, ghrelin, fibroblast growth factor-23 (FGF23), tissue metalloproteinase 2 (TIMP2) and vascular endothelial growth factor A (VEGFa) concentrations were higher in ELGANs with early severe AKI compared to matched control subjects without AKI. Urine epidermal growth factor (EGF) and uromodulin (UMOD) concentrations are lower in cases than controls. Interleukin (IL)-15 was lower on day 1, but higher on day 8 in cases than controls; while VEGFa was lower on day 1, but higher on day 5 in cases than controls.

CONCLUSION

Urine biomarkers hold the promise to improve our ability to reliably detect kidney injury. Interventional studies are needed to determine the biomarkers' ability to predict outcomes, enhance AKI phenotypes, and improve timely interventions which can prevent the sequalae of AKI in ELGANs. A higher resolution version of the Graphical abstract is available as Supplementary information.

Serum and urinary biomarkers to predict acute kidney injury in premature infants: a systematic review and meta-analysis of diagnostic accuracy

BACKGROUND

Premature infants are at high risk for acute kidney injury (AKI) and current diagnostic criteria are flawed. The objective of this study was to determine the diagnostic accuracy of urine and serum biomarkers not currently used in routine clinical practice to predict AKI in premature infants.

METHOD

A systematic review was performed that followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA). Data were extracted on the diagnostic accuracy of AKI biomarkers using serum creatinine or urine output as the reference standard. Quality and validity were assessed using modified Standards for Reporting Diagnostic Accuracy (STARD) criteria.

RESULTS

We identified 1024 articles, with 15 studies (791 infants) eligible for inclusion. Twenty-seven biomarkers were identified including serum cystatin C and urinary neutrophil gelatinase-associated lipocalin (uNGAL), osteopontin, kidney injury molecule-1, epidermal growth factor, and protein S100-P. However, many were only reported by one study each. A meta-analysis could only be conducted on uNGAL (288 infants from 6 studies) using a hierarchical, random-effects logistic-regression model. uNGAL had a summary sensitivity of 77% (95% CI 58-89%), specificity of 76% (95% CI 57-88%) and AUC-SROC of 0.83 (95% CI 0.80-0.86) for the diagnosis of AKI. By utilising uNGAL, the post-test probability of AKI increased to 52% (95% CI 37-66%) with a positive test and decreased to 9% (95% CI 5-16%) with a negative test if the pre-test probability was 25%.

CONCLUSION

uNGAL shows promise as a diagnostically accurate biomarker for AKI in premature infants.

Urinary metabolomics to develop predictors for pediatric acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is characterized by an abrupt decline in glomerular filtration rate (GFR). We sought to identify separate early urinary metabolomic signatures at AKI onset (with-AKI) and prior to onset of functional impairment (pre-AKI).

METHODS

Pre-AKI (n=15), AKI (n=22), and respective controls (n=30) from two prospective PICU cohort studies provided urine samples which were analyzed by GC-MS and DI-MS mass spectrometry (193 metabolites). The cohort (n=58) was 8.7±6.4 years old and 66% male. AKI patients had longer PICU stays, higher PRISM scores, vasopressors requirement, and respiratory diagnosis and less commonly had trauma or post-operative diagnosis. Urine was collected within 2-3 days after admission and daily until day 5 or 14.

RESULTS

The metabolite classifiers for pre-AKI samples (1.5±1.1 days prior to AKI onset) had a cross-validated area under receiver operator curve (AUC)=0.93 (95%CI 0.85-1.0); with-AKI samples had an AUC=0.94 (95%CI 0.87-1.0). A parsimonious pre-AKI classifier with 13 metabolites was similarly robust (AUC=0.96, 95%CI 0.89-1.0). Both classifiers were similar and showed modest correlation of high-ranking metabolites (tau=0.47, p<0.001).

CONCLUSIONS

This exploratory study demonstrates the potential of a urine metabolite classifier to detect AKI-risk in pediatric populations earlier than the current standard of diagnosis with the need for external validation. A higher resolution version of the Graphical abstract is available as Supplementary information with inner reference to ESM for GA.

A Longitudinal 1H NMR-Based Metabolic Profile Analysis of Urine from Hospitalized Premature Newborns Receiving Enteral and Parenteral Nutrition

Preterm newborns are extremely vulnerable to morbidities, complications, and death. Preterm birth is a global public health problem due to its socioeconomic burden. Nurturing preterm newborns is a critical medical issue because they have limited nutrient stores and it is difficult to establish enteral feeding, which leads to inadequate growth frequently associated with poor neurodevelopmental outcomes. Parenteral nutrition (PN) provides nutrients to preterm newborns, but its biochemical effects are not completely known. To study the effect of PN treatment on preterm newborns, an untargeted metabolomic ¹H nuclear magnetic resonance (NMR) assay was performed on 107 urine samples from 34 hospitalized patients. Multivariate data (Principal Component Analysis, PCA, Orthogonal partial least squares discriminant analysis OPLS-DA, parallel factor analysis PARAFAC-2) and univariate analyses were used to identify the association of specific spectral data with different nutritional types (NTs) and gestational ages. Our results revealed changes in the metabolic profile related to the NT, with the tricarboxylic acid cycle and galactose metabolic pathways being the most impacted pathways. Low citrate and succinate levels, despite higher glucose relative urinary concentrations, seem to constitute the metabolic profile found in the studied critically ill preterm newborns who received PN, indicating an energetic dysfunction that must be taken into account for better nutritional management.

Use of Ultra High Performance Liquid Chromatography with High Resolution Mass Spectrometry to Analyze Urinary Metabolome Alterations Following Acute Kidney Injury in Post-Cardiac Surgery Patients

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Cardiac surgery-associated AKI results in dramatic changes in urinary metabolome.

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Urinary metabolite disorder observed in patients with cardiac surgery-associated AKI.

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When metaboloite disorder was due to ischaemia and medical treatment, kidneys could return to normal.

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This work provides data about urinary metabolic profiles and resources for further research on AKI.

Background

Cardiac surgery-associated acute kidney injury (AKI) can increase the mortality and morbidity, and the incidence of chronic kidney disease, in critically ill survivors. The purpose of this research was to investigate possible links between urinary metabolic changes and cardiac surgery-associated AKI.

Methods

Using ultra-high-performance liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry, non-targeted metabolomics was performed on urinary samples collected from groups of patients with cardiac surgery-associated AKI at different time points, including Before_AKI (uninjured kidney), AKI_Day1 (injured kidney) and AKI_Day14 (recovered kidney) groups. The data among the three groups were analyzed by combining multivariate and univariate statistical methods, and urine metabolites related to AKI in patients after cardiac surgery were screened. Altered metabolic pathways associated with cardiac surgery-induced AKI were identified by examining the Kyoto Encyclopedia of Genes and Genomes database.

Results

The secreted urinary metabolome of the injured kidney can be well separated from the urine metabolomes of uninjured or recovered patients using multivariate and univariate statistical analyses. However, urine samples from the AKI_Day14 and Before_AKI groups cannot be distinguished using either of the two statistical analyses. Nearly 4000 urinary metabolites were identified through bioinformatics methods at Annotation Levels 1–4. Several of these differential metabolites may also perform essential biological functions. Differential analysis of the urinary metabolome among groups was also performed to provide potential prognostic indicators and changes in signalling pathways. Compared with the uninjured kidney group, the patients with cardiac surgery-associated AKI displayed dramatic changes in renal metabolism, including sulphur metabolism and amino acid metabolism.

Conclusions

Urinary metabolite disorder was observed in patients with cardiac surgery-associated AKI due to ischaemia and medical treatment, and the recovered patients’ kidneys were able to return to normal. This work provides data on urine metabolite markers and essential resources for further research on AKI.

New Insights from Metabolomics in Pediatric Renal Diseases

Renal diseases in childhood form a spectrum of different conditions with potential long-term consequences. Given that, a great effort has been made by researchers to identify candidate biomarkers that are able to influence diagnosis and prognosis, in particular by using omics techniques (e.g., metabolomics, lipidomics, genomics, and transcriptomics). Over the past decades, metabolomics has added a promising number of 'new' biomarkers to the 'old' group through better physiopathological knowledge, paving the way for insightful perspectives on the management of different renal diseases. We aimed to summarize the most recent omics evidence in the main renal pediatric diseases (including acute renal injury, kidney transplantation, chronic kidney disease, renal dysplasia, vesicoureteral reflux, and lithiasis) in this narrative review.

A Canadian Study of Cisplatin Metabolomics and Nephrotoxicity (ACCENT): A Clinical Research Protocol

Background:

Cisplatin, a chemotherapy used to treat solid tumors, causes acute kidney injury (AKI), a known risk factor for chronic kidney disease and mortality. AKI diagnosis relies on biomarkers which are only measurable after kidney damage has occurred and functional impairment is apparent; this prevents timely AKI diagnosis and treatment. Metabolomics seeks to identify metabolite patterns involved in cell tissue metabolism related to disease or patient factors. The A Canadian study of Cisplatin mEtabolomics and NephroToxicity (ACCENT) team was established to harness the power of metabolomics to identify novel biomarkers that predict risk and discriminate for presence of cisplatin nephrotoxicity, so that early intervention strategies to mitigate onset and severity of AKI can be implemented.

Objective:

Describe the design and methods of the ACCENT study which aims to identify and validate metabolomic profiles in urine and serum associated with risk for cisplatin-mediated nephrotoxicity in children and adults.

Design:

Observational prospective cohort study.

Setting:

Six Canadian oncology centers (3 pediatric, 1 adult and 2 both).

Patients:

Three hundred adults and 300 children planned to receive cisplatin therapy.

Measurements:

During two cisplatin infusion cycles, serum and urine will be measured for creatinine and electrolytes to ascertain AKI. Many patient and disease variables will be collected prospectively at baseline and throughout therapy. Metabolomic analyses of serum and urine will be done using mass spectrometry. An untargeted metabolomics approach will be used to analyze serum and urine samples before and after cisplatin infusions to identify candidate biomarkers of cisplatin AKI. Candidate metabolites will be validated using an independent cohort.

Methods:

Patients will be recruited before their first cycle of cisplatin. Blood and urine will be collected at specified time points before and after cisplatin during the first infusion and an infusion later during cancer treatment. The primary outcome is AKI, defined using a traditional serum creatinine-based definition and an electrolyte abnormality-based definition. Chart review 3 months after cisplatin therapy end will be conducted to document kidney health and survival.

Limitations:

It may not be possible to adjust for all measured and unmeasured confounders when evaluating prediction of AKI using metabolite profiles. Collection of data across multiple sites will be a challenge.

Conclusions:

ACCENT is the largest study of children and adults treated with cisplatin and aims to reimagine the current model for AKI diagnoses using metabolomics. The identification of biomarkers predicting and detecting AKI in children and adults treated with cisplatin can greatly inform future clinical investigations and practices.

Urinary NMR Profiling in Pediatric Acute Kidney Injury-A Pilot Study

Acute kidney injury (AKI) in critically ill children and adults is associated with significant short- and long-term morbidity and mortality. As serum creatinine- and urine output-based definitions of AKI have relevant limitations, there is a persistent need for better diagnostics of AKI. Nuclear magnetic resonance (NMR) spectroscopy allows for analysis of metabolic profiles without extensive sample manipulations. In the study reported here, we examined the diagnostic accuracy of NMR urine metabolite patterns for the diagnosis of neonatal and pediatric AKI according to the Kidney Disease: Improving Global Outcomes (KDIGO) definition. A cohort of 65 neonatal and pediatric patients (0–18 years) with established AKI of heterogeneous etiology was compared to both a group of apparently healthy children (n = 53) and a group of critically ill children without AKI (n = 31). Multivariate analysis identified a panel of four metabolites that allowed diagnosis of AKI with an area under the receiver operating characteristics curve (AUC-ROC) of 0.95 (95% confidence interval 0.86–1.00). Especially urinary citrate levels were significantly reduced whereas leucine and valine levels were elevated. Metabolomic differentiation of AKI causes appeared promising but these results need to be validated in larger studies. In conclusion, this study shows that NMR spectroscopy yields high diagnostic accuracy for AKI in pediatric patients.

Renal Function Profiles in Preterm Neonates With Birth Asphyxia Within the First 24 H of Life

The characteristics of early renal function in preterm neonates of different gestational ages (GAs) with birth asphyxia (BA) remain unclear. Kidneys are sensitive to oxygen deprivation, and renal insufficiency may occur within 24 h of BA. We aimed to elucidate the renal function profiles within the first 24 h after the development of BA among vulnerable preterm neonates of different GAs. The medical records of 128 preterm neonates born to mothers with normal renal function were retrospectively analyzed. Data regarding the serum creatinine (SCr) and urea nitrogen (BUN) levels in venous blood, estimated creatinine clearance (eCCI) within the first hours after birth, and urinary output (UOP) in the first 24 h after birth were compared between the preterm with BA population and GA-matched population without BA (n = 64 and n = 64, respectively). Significantly higher SCr levels and lower eCCI were observed in mid-late preterm neonates with BA than in preterm neonates without BA (84.05 versus [vs.] 64.20 μmol/L, z = 4.41, p < 0.001; 15.02 vs. 21.30 mL/min/1.73 m², z = 3.57, p < 0.001, respectively). Very preterm neonates showed a higher UOP (2.01 vs. 1.66 mL/kg/h, z = 2.01, p = 0.045) after the development of BA than before. In preterm neonates with BA, the incidence of SCr > 133 μmol/L, CCI < 16 mL/min/1.73 m² and UOP < 1.0 ml/kg/h, was 10.94%, 62.50%, and 20.31%, respectively. Within 24 h after birth, BA was associated with eCCI < 16 mL/min/1.73 m² (p = 0.016, odds ratio = 2.83, 95% confidence interval: 1.210-6.613) in preterm neonates. Different renal function profiles were observed in preterm neonates of different GAs within the first 24 h of life after the development of BA. Candidate therapies based on different renal function statuses will bring these vulnerable patient populations of different GAs closer to receiving precision medicine.

[Application of metabolomics in neonatal clinical practice]

Metabolomics is an emerging and popular subject in the post-genome era, and a large number of studies have been noted on the application of metabolomics in health evaluation, growth and development evaluation, disease diagnosis, and therapeutic efficacy evaluation. As a special period of life, the neonatal period is characterized by rapid cell renewing, consumption of a lot of energy and materials, and changes in metabolic pathways, all of which affect the level of metabolites. However, there is still no reference standard for metabolic level and profile in neonates. This article reviews the current status of metabolic research on neonatal growth and development and common diseases and related clinical application of metabolomics, so as to provide new ideas for nutrition guidance and evaluation, selection of therapeutic regimens, and new drug research in neonates.

[Application of metabolomics in neonatal clinical practice]

Metabolomics is an emerging and popular subject in the post-genome era, and a large number of studies have been noted on the application of metabolomics in health evaluation, growth and development evaluation, disease diagnosis, and therapeutic efficacy evaluation. As a special period of life, the neonatal period is characterized by rapid cell renewing, consumption of a lot of energy and materials, and changes in metabolic pathways, all of which affect the level of metabolites. However, there is still no reference standard for metabolic level and profile in neonates. This article reviews the current status of metabolic research on neonatal growth and development and common diseases and related clinical application of metabolomics, so as to provide new ideas for nutrition guidance and evaluation, selection of therapeutic regimens, and new drug research in neonates.

Acute kidney injury in preterm neonates with ≤30 weeks of gestational age and its risk factors

BACKGROUND

Acute kidney injury (AKI), an abrupt decline in kidney function, is a challenging diagnosis among preterm infants due to some specific features of this population. The aim of this study was to determine the risk factors of developing AKI and the predictive factors for its severity in preterm neonates with less than 31 weeks of gestational age.

METHODS

All neonates with less than 31 weeks of gestational age, admitted in our NICU between January 2012 and December 2015, were included. Maternal and neonatal records about demographics, placental abnormalities, perinatal and neonatal period and evolution in NICU, as well as electrolytic analysis and serum creatinine and urea values during their hospitalization were retrospectively collected and analyzed.

RESULTS

A total of 106 neonates were included. Of those, 24 were diagnosed with AKI, resulting in a prevalence of 22.6%, and 82 were used as controls. Gestational age (OR=0.39; 95% CI=0.2-0.76; P=0.006), congenital malformations (OR=36.93; 95%CI=2.48-550.59; P=0.009), vasoactive drugs (OR=27.06; 95%CI=3.58-204.45; P=0.001), nonsteroidal anti-inflammatory drugs (OR=9.61; 95%CI=1.78-51.73; P=0.008) and sepsis (OR=7.78; 95%CI=1.32-46.04; P=0.024) were found to be independent risk factors. Cardiac surgery was a predictive factor for AKI severity (OR=25; 95%CI=2.09-298.29; P=0.011). The mortality rate in the AKI group was 41.7%.

CONCLUSIONS

AKI in preterm neonates is an important feature that contributes to increase the mortality in NICUs. Thus, it is crucial to know its risk factors to establish prompt diagnosis and prevention and, in this way, be able to improve the prognosis.

Drug-induced renal injury in neonates: challenges in clinical practice and perspectives in drug development

Acute kidney injury (AKI) is frequently diagnosed in the neonatal population, especially in those admitted to intensive care units, and poses several challenges for clinicians mainly because of difficulties in timely identification of renal impairment and the need to administer drugs with potential nephrotoxicity. In this context, research on biomarkers is growing for their implication in the early detection of renal damage and their higher sensitivity in monitoring renal activity, but also as an important tool for drug development. Areas covered: We described the tools currently used to detect renal damage in neonatal settings, their limits and applicability, as well as the role of drugs on renal toxicity occurrence. Subsequently, we discuss current knowledge on new biomarkers for the detection of kidney injury and drug-induced kidney injury in neonates, and the qualification programs developed by regulatory agencies for biomarkers intended as tools in drug development. Expert opinion: Some molecules are emerging as potential biomarkers for early detection of AKI: promising data has demonstrated higher sensitivity and accuracy compared with tools currently used in the clinical setting. In addition, novel techniques (e.g. high power magnetic resonance imaging) to assess long-term consequences of AKI in neonates are in early steps of development.