Urinary metabolomics to develop predictors for pediatric acute kidney injury

New approaches to acute kidney injury

Acute kidney injury (AKI) is a common and serious clinical syndrome that involves complex interplay between different cellular, molecular, metabolic and immunologic mechanisms. Elucidating these pathophysiologic mechanisms is crucial to identify novel biomarkers and therapies. Recent innovative methodologies and the advancement of existing technologies has accelerated our understanding of AKI and led to unexpected new therapeutic candidates. The aim of this review is to introduce and update the reader about recent developments applying novel technologies in omics, imaging, nanomedicine and artificial intelligence to AKI research, plus to provide examples where this can be translated to improve patient care.

An Overview of Pre-Analytical Factors Impacting Metabolomics Analyses of Blood Samples

Discrepant sample processing remains a significant challenge within blood metabolomics research, introducing non-biological variation into the measured metabolome and biasing downstream results. Inconsistency during the pre-analytical phase can influence experimental processes, producing metabolome measurements that are non-representative of in vivo composition. To minimize variation, there is a need to create and adhere to standardized pre-analytical protocols for blood samples intended for use in metabolomics analyses. This will allow for reliable and reproducible findings within blood metabolomics research. In this review article, we provide an overview of the existing literature pertaining to pre-analytical factors that influence blood metabolite measurements. Pre-analytical factors including blood tube selection, pre- and post-processing time and temperature conditions, centrifugation conditions, freeze-thaw cycles, and long-term storage conditions are specifically discussed, with recommendations provided for best practices at each stage.

Deliverables from Metabolomics in Kidney Disease: Adenine, New Insights, and Implication for Clinical Decision-Making

BACKGROUND

Chronic kidney disease (CKD) presents a persistent global health challenge, characterized by complex pathophysiology and diverse progression patterns. Metabolomics has emerged as a valuable tool in unraveling the intricate molecular mechanisms driving CKD progression.

SUMMARY

This comprehensive review provides a summary of recent progress in the field of metabolomics in kidney disease with a focus on spatial metabolomics to shed important insights to enhancing our understanding of CKD progression, emphasizing its transformative potential in early disease detection, refined risk assessment, and the development of targeted interventions to improve patient outcomes.

KEY MESSAGE

Through an extensive analysis of metabolic pathways and small-molecule fluctuations, bulk and spatial metabolomics offers unique insights spanning the entire spectrum of CKD, from early stages to advanced disease states. Recent advances in metabolomics technology have enabled spatial identification of biomarkers to provide breakthrough discoveries in predicting CKD trajectory and enabling personalized risk assessment. Furthermore, metabolomics can help decipher the complex molecular intricacies associated with kidney diseases for exciting novel therapeutic approaches. A recent example is the identification of adenine as a key marker of kidney fibrosis for diabetic kidney disease using both untargeted and targeted bulk and spatial metabolomics. The metabolomics studies were critical to identify a new biomarker for kidney failure and to guide new therapeutics for diabetic kidney disease. Similar approaches are being pursued for acute kidney injury and other kidney diseases to enhance precision medicine decision-making.

CKD Urine Metabolomics: Modern Concepts and Approaches

One of the primary challenges regarding chronic kidney disease (CKD) diagnosis is the absence of reliable methods to detect early-stage kidney damage. A metabolomic approach is expected to broaden the current diagnostic modalities by enabling timely detection and making the prognosis more accurate. Analysis performed on urine has several advantages, such as the ease of collection using noninvasive methods and its lower protein and lipid content compared with other bodily fluids. This review highlights current trends in applied analytical methods, major discoveries concerning pathways, and investigated populations in the context of urine metabolomic research for CKD over the past five years. Also, we are presenting approaches, instrument upgrades, and sample preparation modifications that have improved the analytical parameters of methods. The onset of CKD leads to alterations in metabolism that are apparent in the molecular composition of urine. Recent works highlight the prevalence of alterations in the metabolic pathways related to the tricarboxylic acid cycle and amino acids. Including diverse patient cohorts, using numerous analytical techniques with modifications and the appropriate annotation and explanation of the discovered biomarkers will help develop effective diagnostic models for different subtypes of renal injury with clinical applications.

Metabolomics in Acute Kidney Injury: The Clinical Perspective

BACKGROUND

Acute kidney injury (AKI) affects increasing numbers of hospitalized patients worldwide. The diagnosis of AKI is made too late in most individuals since it is still based on dynamic changes in serum creatinine. In recent years, new AKI biomarkers have been identified; however, none of these can reliably replace serum creatinine yet. Metabolomic profiling (metabolomics) allows the concomitant detection and quantification of large numbers of metabolites from biological specimens. The current article aims to summarize clinical studies on metabolomics in AKI diagnosis and risk prediction.

METHODS

The following databases were searched for references: PubMed, Web of Science, Cochrane Library, and Scopus, and the period lasted from 1940 until 2022. The following terms were utilized: 'AKI' OR 'Acute Kidney Injury' OR 'Acute Renal Failure' AND 'metabolomics' OR 'metabolic profiling' OR 'omics' AND 'risk' OR 'death' OR 'survival' OR 'dialysis' OR 'KRT' OR 'kidney replacement therapy' OR 'RRT' OR 'renal replacement therapy' OR 'recovery of kidney function' OR 'renal recovery' OR 'kidney recovery' OR 'outcome'. Studies on AKI risk prediction were only selected if metabolomic profiling allowed differentiation between subjects that fulfilled a risk category (death or KRT or recovery of kidney function) and those who did not. Experimental (animal-based) studies were not included.

RESULTS

In total, eight studies were identified. Six studies were related to the diagnosis of AKI; two studies were performed on metabolic analysis in AKI risk (death) prediction. Metabolomics studies in AKI already helped to identify new biomarkers for AKI diagnosis. The data on metabolomics for AKI risk prediction (death, KRT, recovery of kidney function), however, are very limited.

CONCLUSIONS

Both the heterogenous etiology and the high degree of pathogenetic complexity of AKI most likely require integrated approaches such as metabolomics and/or additional types of '-omics' studies to improve clinical outcomes in AKI.