NMR-based metabolomics associated with chronic kidney disease in humans and animals: a one health perspective

Benchtop NMR-Based Metabolomics: First Steps for Biomedical Application

Nuclear magnetic resonance (NMR)-based metabolomics is a valuable tool for identifying biomarkers and understanding the underlying metabolic changes associated with various diseases. However, the translation of metabolomics analysis to clinical practice has been limited by the high cost and large size of traditional high-resolution NMR spectrometers. Benchtop NMR, a compact and low-cost alternative, offers the potential to overcome these limitations and facilitate the wider use of NMR-based metabolomics in clinical settings. This review summarizes the current state of benchtop NMR for clinical applications where benchtop NMR has demonstrated the ability to reproducibly detect changes in metabolite levels associated with diseases such as type 2 diabetes and tuberculosis. Benchtop NMR has been used to identify metabolic biomarkers in a range of biofluids, including urine, blood plasma and saliva. However, further research is needed to optimize the use of benchtop NMR for clinical applications and to identify additional biomarkers that can be used to monitor and manage a range of diseases. Overall, benchtop NMR has the potential to revolutionize the way metabolomics is used in clinical practice, providing a more accessible and cost-effective way to study metabolism and identify biomarkers for disease diagnosis, prognosis, and treatment.

Biomarker identification and pathway analysis of Astragalus membranaceus and Curcuma zedoaria couplet medicines on adenine-induced chronic kidney disease in rats based on metabolomics

Background: Chronic kidney disease (CKD) is usually insidious, and most affected individuals are asymptomatic until the disease becomes advanced. The effective treatment of CKD would rely on the incorporation of multidisciplinary approaches. Astragalus membranaceus (AM) and Curcuma zedoaria (CZ) have been widely used in the treatment of CKD. However, the mechanism of AM and CZ in the treatment of CKD is still unclear.

Methods: This study was designed to evaluate the effects of AM and CZ on adenine-induced rats and to investigate the underlying mechanism by using metabolomic analysis. Addition of 0.75% adenine to the diet of rats for 3 weeks induced the animal model of CKD. The rats in the treatment group were treated with AM and CZ (2.1 g/kg/day) for 4 weeks. Blood and kidney samples were collected for biochemical and histological examination. Ultra-high-performance liquid chromatography/Q Exactive HFX mass spectrometer (UHPLC-QE-MS) was applied to analyze metabolic profiling variations in the kidney.

Results: The results showed that AM and CZ could significantly reduce serum creatinine (Scr) and blood urea nitrogen (BUN) levels in CKD rats and alleviate renal pathological injury. By comparing the endogenous components of the normal group and the model group in positive ion mode and negative ion mode, a total of 365 and 155 different metabolites were screened, respectively. A total of 117 and 73 metabolites with significantly different expressions were identified between model group and AM and CZ group in positive ion mode and negative ion mode, respectively. The pivotal pathways affected by AM and CZ included nicotinate and nicotinamide metabolism, and glycine, serine and threonine metabolism. Furthermore, significant changes in metabolites in CKD rats after AM and CZ therapies were observed, including L-Threonine, D-pantothenic acid, and nicotinamide. Moreover, we found that AM and CZ significantly reduced renal fibrosis and inflammation in CKD rats, which may be related to the regulation of SIRT1/JNK signaling pathway.

Conclusion: In conclusion, AM and CZ significantly reduced renal fibrosis and inflammation in CKD rats, which may be related to the regulation of SIRT1/JNK signaling pathway. Furthermore, L-Threonine, D-pantothenic acid, and nicotinamide may be potential biomarkers for the progression and treatment of CKD.

Metabolomic profiling of overnight peritoneal dialysis effluents predicts the peritoneal equilibration test type

This study primarily aimed to evaluate whether peritoneal equilibration test (PET) results can be predicted through the metabolomic analysis of overnight peritoneal dialysis (PD) effluents. From a total of 125 patients, overnight PD effluents on the day of the first PET after PD initiation were analyzed. A modified 4.25% dextrose PET was performed, and the PET type was categorized according to the dialysate-to-plasma creatinine ratio at the 4-h dwell time during the PET as follows: high, high average, low average, or low transporter. Nuclear magnetic resonance (NMR)-based metabolomics was used to analyze the effluents and identify the metabolites. The predictive performances derived from the orthogonal projection to latent structure discriminant analysis (OPLS-DA) modeling of the NMR spectrum were estimated by calculating the area under the curve (AUC) using receiver operating characteristic curve analysis. The OPLS-DA score plot indicated significant metabolite differences between high and low PET types. The relative concentrations of alanine and creatinine were greater in the high transporter type than in the low transporter type. The relative concentrations of glucose and lactate were greater in the low transporter type than in the high transporter type. The AUC of a composite of four metabolites was 0.975 in distinguish between high and low PET types. Measured PET results correlated well with the total NMR metabolic profile of overnight PD effluents.

Nuclear Magnetic Resonance-Based Metabolomics Approach Revealed the Intervention Effect of Using Complementary and Alternative Medicine (CAM) by CKD Patients

Chronic kidney disease (CKD) is the end point of a number of systemic chronic diseases. The prevalence of CKD is increasing worldwide and recent epidemiological studies are showing the high prevalence of renal failure in CKD patients using complementary and alternative medicines (CAMs). Clinicians believe that biochemical profiles of CKD patients using CAM (referred here to as CAM-CKD) may be different compared to those on standard clinical treatment and should be managed differently. The present study aims to explore the potential of the NMR-based metabolomics approach to reveal the serum metabolic disparity between CKD and CAM-CKD patients with respect to normal control (NC) subjects and if the differential metabolic patterns can provide rationale for the efficacy and safety of standard and/or alternative therapies. Serum samples were obtained from 30 CKD patients, 43 CAM-CKD patients, and 47 NC subjects. The quantitative serum metabolic profiles were measured using 1D ¹H CPMG NMR experiments performed at 800 MHz NMR spectrometer. The serum metabolic profiles were compared using various multivariate statistical analysis tools available on MetaboAnalyst (freely available web-based software) such as partial least-squares discriminant analysis (PLS-DA) and random forest (a machine learning) classification method. The discriminatory metabolites were identified based on variable importance in projection (VIP) statistics and further evaluated for statistical significance (i.e., p < 0.05) using either Student t-test or ANOVA statistics. PLS-DA models were capable of clustering CKD and CAM-CKD with considerably high values of Q ² and R ². Compared to CAM-CKD patients, the sera of CKD patients were characterized by (a) elevated levels of urea, creatinine, citrate, glucose, glycerol, and phenylalanine and phenylalanine-to-tyrosine ratio (PTR) and (b) decreased levels of various amino acids (such leucine, isoleucine, valine, and alanine), high-density lipoproteins, lactate, and acetate. These changes suggested that CKD patients manifest severe oxidative stress, hyperglycemia (with dampened glycolysis), increased protein energy wasting, and reduced lipid/membrane metabolism. Statistically significant and strong positive correlation of PTR with serum creatinine levels suggested the role of oxidative stress in the progression of kidney disease. Significant differences in metabolic patterns between CKD and CAM-CKD patients were observed. With respect to NC subjects, the serum metabolic changes were more aberrant in CKD patients compared to CAM-CKD patients. The aberrant metabolic changes in CKD patients with manifestations of higher oxidative stress compared to CAM-CKD patients could explain clinical discrepancies between CKD and CAM-CKD patients and further advocate the use of different treatment strategies for CKD and CAM-CKD patients.

Serum metabolomics of end-stage renal disease patients with depression: potential biomarkers for diagnosis

Background

End-stage renal disease (ESRD) is the final stage during the development of renal failure. Depression is the most common psychiatric disorder in patients with ESRD, which in turn aggravates the progression of renal failure, however, its underlying mechanism remains unclear. This study aimed to reveal the pathogenesis and to discover novel peripheral biomarkers for ESRD patients with depression through metabolomic analysis.

Methods

Ultra-high-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) was used to explore changes of serum metabolites among healthy controls, ESRD patients with or without depression. The differential metabolites between groups were subjected to clustering analysis, pathway analysis, receiver operating characteristic (ROC) curve analysis.

Results

A total of 57 significant serum differential metabolites were identified between ESRD patients with or without depression, which were involved in 19 metabolic pathways, such as energy metabolism, glycerolipid metabolism, and glutamate-centered metabolism. Moreover, the area under the ROC curve of gentisic acid, uric acid, 5-hydroxytryptamine, 2-phosphoglyceric acid, leucyl-phenylalanine, propenyl carnitine, naloxone, pregnenolone, 6-thioxanthene 5'-monophosphate, hydroxyl ansoprazole, zileuton O-glucuronide, cabergoline, PA(34:2), PG(36:1), probucol and their combination was greater than 0.90.

Conclusions

Inflammation, oxidative stress and energy metabolism abnormalities, glycerolipid metabolism, and glutamate-centered metabolism are associated with the pathogenesis of ESRD with depression, which may be promising targets for therapy. Furthermore, the identified differential metabolites may serve as biomarkers for the diagnosis of ESRD patients with depression.