Urine and serum NMR-based metabolomics in pre-procedural prediction of contrast-induced nephropathy

Association between serum methylmalonic acid and chronic kidney disease in adults: a cross-sectional study from NHANES 2013-2014

Introduction

Chronic kidney disease(CKD) is a global medical problem. Serum methylmalonic acid(MMA) is a serum marker associated with many diseases. This study aimed to investigate the association between MMA and CKD.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 were downloaded and analyzed. The association between MMA and CKD was confirmed by using multiple logistic regression modeling. The smooth curve fitting method was used to investigate the nonlinear relationship between them. Subgroup analyses and interaction tests were used to verify the stability of the association between different subgroups. Threshold effect analysis was used to determine the optimal control point for MMA.

Results

There was a unique W-shaped nonlinear relationship between MMA and the risk of CKD, with a positive correlation between them (OR=1.66,95% CI:1.27, 2.17; P=0.0002). As the stage of CKD progressed, MMA levels increased. Age, hypertension, and serum vitamin B12 had significant influences on the association between MMA and the risk of CKD.

Conclusion

Our findings revealed that serum MMA accumulation was positively associated with the risk of CKD. Serum MMA level may be a novel index to predict the development and course of CKD. This study may help in the early identification of people at risk for chronic kidney disease and provide new ideas and approaches for prevention and treatment.

NMR-based metabolomic analysis of plasma from elderly patients with CVD before and after using contrast media

Contrast-induced acute kidney injury (CI-AKI) is a growingly common kidney problem caused by medical procedures involving contrast media (CM), especially in older patients with existing health issues. It is crucial to pinpoint potential biomarkers for the early detection of CI-AKI. Previously, we observed that iodixanol affects glucose, choline, and glutathione metabolism in endothelial cells under laboratory conditions. In this study, we used 1H NMR-based metabolomics to examine the metabolic changes in the blood plasma of elderly patients with cardiovascular disease (CVD) before and after receiving iodixanol. We identified altered metabolites in plasma 24 and 48 h after iodixanol injection compared to levels before injection. Notably, metabolites such as glucose, unsaturated fatty acids (UFA), low-density lipoprotein (LDL)/very low-density lipoprotein (VLDL), pyruvate, choline, and glycine showed potential as biomarkers at 24 h post-injection compared to levels before injection. Similarly, glucose, pyruvate, lactate, choline, and glycine in plasma could serve as potential biomarkers at 48 h post-injection. Iodixanol notably affected pathways related to glycolysis, fatty acid breakdown, and amino acid metabolism according to our metabolic pathway analysis. The altered levels of specific metabolites in plasma could be indicative of CM-induced kidney injury. Overall, this research aids in understanding the physiological mechanisms involved and in identifying early biomarkers and prevention strategies for CI-AKI.

A systematic review of metabolomic findings in adult and pediatric renal disease

Chronic kidney disease (CKD) affects over 0.5 billion people worldwide across their lifetimes. Despite a growingly ageing world population, an increase in all-age prevalence of kidney disease persists. Adult-onset forms of kidney disease often result from lifestyle-modifiable metabolic illnesses such as type 2 diabetes. Pediatric and adolescent forms of renal disease are primarily caused by morphological abnormalities of the kidney, as well as immunological, infectious and inherited metabolic disorders. Alterations in energy metabolism are observed in CKD of varying causes, albeit the molecular mechanisms underlying pathology are unclear. A systematic indexing of metabolites identified in plasma and urine of patients with kidney disease alongside disease enrichment analysis uncovered inborn errors of metabolism as a framework that links features of adult and pediatric kidney disease. The relationship of genetics and metabolism in kidney disease could be classified into three distinct landscapes: (i) Normal genotypes that develop renal damage because of lifestyle and / or comorbidities; (ii) Heterozygous genetic variants and polymorphisms that result in unique metabotypes that may predispose to the development of kidney disease via synergistic heterozygosity, and (iii) Homozygous genetic variants that cause renal impairment by perturbing metabolism, as found in children with monogenic inborn errors of metabolism. Interest in the identification of early biomarkers of onset and progression of CKD has grown steadily in the last years, though it has not translated into clinical routine yet. This systematic review indexes findings of differential concentration of metabolites and energy pathway dysregulation in kidney disease and appraises their potential use as biomarkers.

Limonin mitigates cisplatin-induced acute kidney injury through metabolic reprogramming

BACKGROUND

Acute kidney injury (AKI) is a known complication of cisplatin administration; currently, there are no effective ways to prevent it. Therefore, it largely limited the use of cisplatin in chemotherapy in the clinic. In this study, we reported that Limonin, a triterpenoid compound extracted from citrus, alleviated cisplatin-induced AKI through metabolic reprogramming in the diseased kidneys.

METHODS

Cisplatin was employed to induce AKI in mice. Three groups were set up: Sham, cisplatin + vehicle, and cisplatin + Limonin. Using UHPLC-TOF/MS, we conducted metabolomics to profile the kidneys' endogenous metabolites and metabolic pathways. A network pharmacological method was performed to identify the targets of Limonin on AKI. The human proximal tubular epithelial cell line (HK-2) was applied for in vitro studies.

RESULTS

Limonin preserved serum creatinine and blood urea nitrogen levels after cisplatin-induced AKI. Employing metabolomics, we identified 33 endogenous differentially expressed metabolites and 7 significantly disturbed metabolic pathways in the diseased kidneys within three groups. After AKI, Limonin significantly reduced linoleic acid and its downstream product, arachidonic acid, thus exerting a protective effect on the kidney. The network pharmacological method identified CYP3A4 as a key target of Limonin in treating AKI, while CYP3A4 also serve as a mediator of arachidonic acid metabolism. In vitro, Limonin markedly reduced the level of arachidonic acid and HK-2 cell apoptosis triggered by cisplatin, mainly related to the targeted inhibition of CYP3A4-mediated arachidonic acid metabolism.

CONCLUSION

Limonin ameliorates cisplatin-induced AKI by inhibiting CYP3A4 activity to regulate arachidonic acid metabolism, ultimately preserving kidney function.

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.

Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

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.