Plasma and urinary amino acid metabolomic profiling in patients with different levels of kidney function

Impact of Combined Macronutrient Diet on Amino Acids and Amines Plasma Levels

Background: Nutritional biomarkers are essential for assessing the impact of dietary interventions on health. Amino Acids (AA) serve as potential biomarkers due to their role in metabolic pathways, although the influence of combining macronutrients on AA metabolism remains unclear. Objective: This study aims to evaluate the effects of combining macronutrients (fat, protein, and fiber) on AA metabolism. Methods: A dietary intervention was conducted with 41 participants who were assigned to two groups: the Protein Fat (PF) group and the Protein Fat and Fiber (PFF) group. AA concentration was measured using LC-MS/MS. Results: Our findings indicated that combining macronutrients reduced plasma levels of AA with statistically significant differences between the two diets (p < 0.05 for EAA and BCAA; p < 0,01 for NEAA and AAA). Metabolic profile analysis showed differences between the groups, especially at 55 days (55 D) (R2X: 0.749; R2Y: 0.589; Q2: 0.582, p < 0.001) and 98 days (98 D) (R2X: 0.886; R2Y: 0.7; Q2: 0.605, p < 0.001). Five metabolites (leucine, asparagine, alanine, cysteine, and creatine) were the most influential factors in group differentiation (VIP score), with values ranging between 1.04 and 1.75. Conclusions: The combination of macronutrients led to a significant reduction in plasma amino acids and amines in the PFF group, with recovery post-intervention. These findings highlight the possibility that these metabolites are related to different health statuses.

Targeted Analysis of Serum and Urinary Metabolites for Early Chronic Kidney Disease

Chronic kidney disease (CKD) has become one of the most rapidly advancing diseases of the century, contributing significantly to increased mortality and morbidity. Metabolomics presents a promising approach to understanding CKD pathogenesis and identifying novel biomarkers for early diagnosis. This study evaluated serum and urine metabolomic profiles in CKD patients with declining glomerular filtration rates (eGFR). Using targeted metabolomics, we quantified seven potential metabolites in blood and urine samples from 20 healthy individuals and 99 CKD patients staged by eGFR according to the KDIGO guidelines. The analysis was conducted using ultra-high performance liquid chromatography combined with electrospray ionization quadrupole time-of-flight mass spectrometry. The metabolites investigated included L-phenylalanine, L-methionine, arginine, indoxyl sulfate, kynurenic acid, and L-acetylcarnitine. Quantitative assessments were performed using pure standards and validated through methods such as the limit of detection (LOD) and limit of quantification (LOQ). The findings identified potential biomarkers for early CKD diagnosis: in serum, L-phenylalanine, L-methionine, arginine, kynurenic acid, and indoxyl sulfate, while L-acetylcarnitine was significant in urine. These biomarkers could provide valuable insights into CKD progression and support in developing more effective diagnostic tools for early intervention.

Amino acid metabolism in kidney health and disease

Amino acids form peptides and proteins and are therefore considered the main building blocks of life. The kidney has an important but under-appreciated role in the synthesis, degradation, filtration, reabsorption and excretion of amino acids, acting to retain useful metabolites while excreting potentially harmful and waste products from amino acid metabolism. A complex network of kidney transporters and enzymes guides these processes and moderates the competing concentrations of various metabolites and amino acid products. Kidney amino acid metabolism contributes to gluconeogenesis, nitrogen clearance, acid-base metabolism and provision of fuel for tricarboxylic acid cycle and urea cycle intermediates, and is thus a central hub for homeostasis. Conversely, kidney disease affects the levels and metabolism of a variety of amino acids. Here, we review the metabolic role of the kidney in amino acid metabolism and describe how different diseases of the kidney lead to aberrations in amino acid metabolism. Improved understanding of the metabolic and communication routes that are affected by disease could provide new mechanistic insights into the pathogenesis of kidney diseases and potentially enable targeted dietary or pharmacological interventions.

Targeted and untargeted serum NMR metabolomics to reveal initial kidney disease in diabetes mellitus

Serum 1H NMR metabolomics has been used as a diagnostic tool for screening type 2 diabetes (T2D) with chronic kidney disease (CKD) as comorbidity. This work aimed to evaluate 1H NMR data to detect the initial kidney damage and CKD in T2D subjects, through multivariate statistical analysis. Clinical data and biochemical parameters were obtained for classifying five experimental groups using KDIGO guidelines: Control (healthy subjects), T2D, T2D-CKD-mild, T2D-CKD-moderate, and T2D-CKD-severe. Serum 1H NMR spectra were recorded to follow two strategies: one based on metabolite-to-creatinine (Met/Cr) ratios as targeted metabolomics, and the second one based on untargeted metabolomics from the 1H NMR profile. A prospective biomarkers panel of the early stage of T2D-CKD based in metabolite-to-creatinine ratio (ornithine/Cr, serine/Cr, mannose/Cr, acetate/Cr, acetoacetate/Cr, formate/Cr, and glutamate/Cr) was proposed. Later, a statistical model based on non-targeted metabolomics was used to predict initial CKD, and its metabolic pathway analysis allowed identifying the most affected pathways: phenylalanine, tyrosine, and tryptophan biosynthesis; valine, leucine, and isoleucine degradation; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and histidine metabolism. Nonetheless, further studies with a larger cohort are advised to precise ranges in metabolite-to-creatinine ratios and evaluate the prediction pertinency to detect initial CKD in T2D patients in both statistical models proposed.

Metabolic Crosstalk in Multimorbidity: Identifying Compensatory Effects Among Diabetes, Hypertension, and Dyslipidemia

Context

Metabolomics is becoming increasingly popular for detecting markers that indicate the presence of a specific disease. However, it is usually applied to studying individual ailments, yielding results that may not be directly relevant to people with multiple health conditions.

Objective

Our study proposes a different approach to explore metabolic crosstalk between various disease states.

Design Setting and Patients

We conducted a study on subjects at medium to high risk of developing coronary artery disease. We measured the plasma levels of 83 metabolites using nuclear magnetic resonance and analyzed the connections between these metabolites and various risk factors such as diabetes, hypertension, and dyslipidemia. Linear regression and multivariate analysis were combined for this purpose.

Results

Inspection of the metabolic maps created by our analysis helped us efficiently compare profiles. In this way, it was possible to discover opposing metabolic features among single conditions and their combination. Furthermore, we found compensating metabolic effects between diabetes, hypertension, and dyslipidemia involving mainly ketone body metabolism and fatty acid β-oxidation.

Conclusion

Our study introduces a novel approach to investigating how metabolism reacts to the simultaneous presence of multiple health conditions. This has allowed the detection of potential compensatory effects between diabetes, hypertension, and dyslipidemia, highlighting the complexity of metabolic crosstalk in patients with comorbidities. A better understanding of metabolic crosstalk like this could aid in developing focused treatments, resulting in improved therapeutic results.

Evidence for a relationship between genetic polymorphisms of the L-DOPA transporter LAT2/4F2hc and risk of hypertension in the context of chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) and hypertension are chronic diseases affecting a large portion of the population frequently coexistent and interdependent. The inability to produce/use adequate renal dopamine may contribute to the development of hypertension and renal dysfunction. The heterodimeric amino acid transporter LAT2/4F2hc (SLC7A8/SLC3A2 genes) promotes the uptake of L-DOPA, the natural precursor of dopamine. We examined the plausibility that SLC7A8/SLC3A2 gene polymorphisms may contribute to hypertensive CKD by affecting the L-DOPA uptake.

METHODS

421 subjects (203 men and 218 women, mean age of 78.9 ± 9.6 years) were recruited and divided in four groups according to presence/absence of CKD, defined as reduced estimated glomerular filtration rate (eGFR < 60 ml/min/m2) calculated using the creatinine-based Berlin Initiative Study-1 (BIS1) equation, and to presence/absence of hypertension (systolic blood pressure ≥ 140 and/or diastolic blood pressure ≥ 90 mmHg). Subjects were analysed for selected SNPs spanning the SLC7A8 and SLC3A2 loci by Sequenom MassARRAY iPLEX platform.

RESULTS

The most significant SNP at the SLC3A2 (4F2hc) locus was rs2282477-T/C, with carriers of the C-allele having a lower chance to develop hypertension among CKD affected individuals [OR = 0.33 (CI 0.14-0.82); p = 0.016]. A similar association with hypertensive CKD was found for the SLC7A8 (LAT2) rs3783436-T/C, whose C-allele resulted associated with decreased risk of hypertension among subjects affected by CKD [OR = 0.56 (95% CI 0.35-0.90; p = 0.017]. The two variants were predicted to be potentially functional.

CONCLUSIONS

The association between SLC3A2 and SLC7A8 variants to hypertension development in patients with renal failure could be linked to changes in L-DOPA uptake and consequently dopamine synthesis. Although the associations do not survive correction for Bonferroni multiple testing, and additional research is needed, our study opens new avenues for future basic and translational research in the field of hypertensive CKD.

Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients

Objective

The co-occurrence of kidney disease in patients with type 2 diabetes (T2D) is a major public health challenge. Although early detection and intervention can prevent or slow down the progression, the commonly used estimated glomerular filtration rate (eGFR) based on serum creatinine may be influenced by factors unrelated to kidney function. Therefore, there is a need to identify novel biomarkers that can more accurately assess renal function in T2D patients. In this study, we employed an interpretable machine-learning framework to identify plasma metabolomic features associated with GFR in T2D patients.

Methods

We retrieved 1626 patients with type 2 diabetes (T2D) in Liaoning Medical University First Affiliated Hospital (LMUFAH) as a development cohort and 716 T2D patients in Second Affiliated Hospital of Dalian Medical University (SAHDMU) as an external validation cohort. The metabolite features were screened by the orthogonal partial least squares discriminant analysis (OPLS-DA). We compared machine learning prediction methods, including logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost). The Shapley Additive exPlanations (SHAP) were used to explain the optimal model.

Results

For T2D patients, compared with the normal or elevated eGFR group, glutarylcarnitine (C5DC) and decanoylcarnitine (C10) were significantly elevated in GFR mild reduction group, and citrulline and 9 acylcarnitines were also elevated significantly (FDR<0.05, FC > 1.2 and VIP > 1) in moderate or severe reduction group. The XGBoost model with metabolites had the best performance: in the internal validate dataset (AUROC=0.90, AUPRC=0.65, BS=0.064) and external validate cohort (AUROC=0.970, AUPRC=0.857, BS=0.046). Through the SHAP method, we found that C5DC higher than 0.1μmol/L, Cit higher than 26 μmol/L, triglyceride higher than 2 mmol/L, age greater than 65 years old, and duration of T2D more than 10 years were associated with reduced GFR.

Conclusion

Elevated plasma levels of citrulline and a panel of acylcarnitines were associated with reduced GFR in T2D patients, independent of other conventional risk factors.

Serum and Urine Metabolites and Kidney Function

Key Points

We provide an atlas of cross-sectional and longitudinal serum and urine metabolite associations with eGFR and urine albumin-creatinine ratio in an older community-based cohort. Metabolic profiling in serum and urine provides distinct and complementary insights into disease.

Background

Metabolites represent a read-out of cellular processes underlying states of health and disease.

Methods

We evaluated cross-sectional and longitudinal associations between 1255 serum and 1398 urine known and unknown (denoted with “X” in name) metabolites (Metabolon HD4, 721 detected in both biofluids) and kidney function in 1612 participants of the Atherosclerosis Risk in Communities study. All analyses were adjusted for clinical and demographic covariates, including for baseline eGFR and urine albumin-creatinine ratio (UACR) in longitudinal analyses.

Results

At visit 5 of the Atherosclerosis Risk in Communities study, the mean age of participants was 76 years (SD 6); 56% were women, mean eGFR was 62 ml/min per 1.73 m2 (SD 20), and median UACR level was 13 mg/g (interquartile range, 25). In cross-sectional analysis, 675 serum and 542 urine metabolites were associated with eGFR (Bonferroni-corrected P < 4.0E-5 for serum analyses and P < 3.6E-5 for urine analyses), including 248 metabolites shared across biofluids. Fewer metabolites (75 serum and 91 urine metabolites, including seven metabolites shared across biofluids) were cross-sectionally associated with albuminuria. Guanidinosuccinate; N2,N2-dimethylguanosine; hydroxy-N6,N6,N6-trimethyllysine; X-13844; and X-25422 were significantly associated with both eGFR and albuminuria. Over a mean follow-up of 6.6 years, serum mannose (hazard ratio [HR], 2.3 [1.6–3.2], P = 2.7E-5) and urine X-12117 (HR, 1.7 [1.3–2.2], P = 1.9E-5) were risk factors of UACR doubling, whereas urine sebacate (HR, 0.86 [0.80–0.92], P = 1.9E-5) was inversely associated. Compared with clinical characteristics alone, including the top five endogenous metabolites in serum and urine associated with longitudinal outcomes improved the outcome prediction (area under the receiver operating characteristic curves for eGFR decline: clinical model=0.79, clinical+metabolites model=0.87, P = 8.1E-6; for UACR doubling: clinical model=0.66, clinical+metabolites model=0.73, P = 2.9E-5).

Conclusions

Metabolomic profiling in different biofluids provided distinct and potentially complementary insights into the biology and prognosis of kidney diseases.

Blood biomarkers improve the prediction of prevalent and incident severe chronic kidney disease

BACKGROUND

The prevalence of chronic kidney disease (CKD) is high. Identification of cases with CKD or at high risk of developing it is important to tailor early interventions. The objective of this study was to identify blood metabolites associated with prevalent and incident severe CKD, and to quantify the corresponding improvement in CKD detection and prediction.

METHODS

Data from four cohorts were analyzed: Singapore Epidemiology of Eye Diseases (SEED) (n = 8802), Copenhagen Chronic Kidney Disease (CPH) (n = 916), Singapore Diabetic Nephropathy (n = 714), and UK Biobank (UKBB) (n = 103,051). Prevalent CKD (stages 3-5) was defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2; incident severe CKD as CKD-related mortality or kidney failure occurring within 10 years. We used multivariable regressions to identify, among 146 blood metabolites, those associated with CKD, and quantify the corresponding increase in performance.

RESULTS

Chronic kidney disease prevalence (stages 3-5) and severe incidence were 11.4% and 2.2% in SEED, and 2.3% and 0.2% in UKBB. Firstly, phenylalanine (Odds Ratio [OR] 1-SD increase = 1.83 [1.73, 1.93]), tyrosine (OR = 0.75 [0.71, 0.79]), docosahexaenoic acid (OR = 0.90 [0.85, 0.95]), citrate (OR = 1.41 [1.34, 1.47]) and triglycerides in medium high density lipoprotein (OR = 1.07 [1.02, 1.13]) were associated with prevalent stages 3-5 CKD. Mendelian randomization analyses suggested causal relationships. Adding these metabolites beyond traditional risk factors increased the area under the curve (AUC) by 3% and the sensitivity by 7%. Secondly, lactate (HR = 1.33 [1.08, 1.64]) and tyrosine (HR = 0.74 [0.58, 0.95]) were associated with incident severe CKD among individuals with eGFR < 90 mL/min/1.73 m2 at baseline. These metabolites increased the c-index by 2% and sensitivity by 5% when added to traditional risk factors.

CONCLUSION

The performance improvements of CKD detection and prediction achieved by adding metabolites to traditional risk factors are modest and further research is necessary to fully understand the clinical implications of these findings.

Colonic microflora and plasma metabolite-based comparative analysis of unilateral ureteral obstruction-induced chronic kidney disease after treatment with the Chinese medicine FuZhengHuaYuJiangZhuTongLuo and AST-120

Background

Many researchers have investigated the use of Chinese herbs to delay the progression of chronic kidney disease (CKD) through their effects on colonic microflora and microbiota-derived metabolites. However, whether FuZhengHuaYuJiangZhuTongLuo (FZHY) has effects that are similar to those of AST-120 on CKD needs to be elucidated.

Methods

In this study, we compared the effects of FZHY and AST-120 on the colonic microbiota and plasma metabolites in the CKD rat model. We developed a unilateral ureteral obstruction (UUO)-induced CKD rat model and then administered FZHY and AST-120 to these model rats. Non-targeted metabolomic LC-MS analysis, 16S rRNA sequencing, and histopathological staining were performed on plasma, stool, and kidney tissues, respectively, and the joint correlation between biomarkers and metabolites of candidate bacteria was analyzed.

Results

Our results showed that administering FZHY and AST-120 effectively ameliorated UUO-induced abnormal renal function and renal fibrosis and regulated the composition of microbiota and metabolites. Compared to the UUO model group, the p_Firmicutes and o_Peptostreptococcales_Tissierellales were increased, while 14 negative ion metabolites were upregulated and 21 were downregulated after FZHY treatment. Additionally, 40 positive ion metabolites were upregulated and 63 were downregulated. On the other hand, AST-120 treatment resulted in an increase in the levels of g_Prevotellaceae_NK3B31_group and f_Prevotellaceae, as well as 12 upregulated and 23 downregulated negative ion metabolites and 56 upregulated and 63 downregulated positive ion metabolites. Besides, FZHY increased the levels of candidate bacterial biomarkers that were found to be negatively correlated with some poisonous metabolites, such as 4-hydroxyretinoic acid, and positively correlated with beneficial metabolites, such as l-arginine. AST-120 increased the levels of candidate bacterial biomarkers that were negatively correlated with some toxic metabolites, such as glycoursodeoxycholic acid, 4-ethylphenol, and indole-3-acetic acid.

Conclusion

FZHY and AST-120 effectively reduced kidney damage, in which, the recovery of some dysregulated bacteria and metabolites are probably involved. As their mechanisms of regulation were different, FZHY might play a complementary role to AST-120 in treating CKD.

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.

A Review from a Clinical Perspective: Recent Advances in Biosensors for the Detection of L-Amino Acids

The field of biosensors is filled with reports and designs of various sensors, with the vast majority focusing on glucose sensing. However, in addition to glucose, there are many other important analytes that are worth investigating as well. In particular, L-amino acids appear as important diagnostic markers for a number of conditions. However, the progress in L-amino acid detection and the development of biosensors for L-amino acids are still somewhat insufficient. In recent years, the need to determine L-amino acids from clinical samples has risen. More clinical data appear to demonstrate that abnormal concentrations of L-amino acids are related to various clinical conditions such as inherited metabolic disorders, dyslipidemia, type 2 diabetes, muscle damage, etc. However, to this day, the diagnostic potential of L-amino acids is not yet fully established. Most likely, this is because of the difficulties in measuring L-amino acids, especially in human blood. In this review article, we extensively investigate the 'overlooked' L-amino acids. We review typical levels of amino acids present in human blood and broadly survey the importance of L-amino acids in most common conditions which can be monitored or diagnosed from changes in L-amino acids present in human blood. We also provide an overview of recent biosensors for L-amino acid monitoring and their advantages and disadvantages, with some other alternative methods for L-amino acid quantification, and finally we outline future perspectives related to the development of biosensing devices for L-amino acid monitoring.

Metabolome panels as potential noninvasive biomarkers for primary glomerulonephritis sub-types: meta-analysis of profiling metabolomics studies

Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease's underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ - 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.

Evaluation of amino acids and other related metabolites levels in end-stage renal disease (ESRD) patients on hemodialysis by LC/MS/MS and GC/MS

End-stage renal disease (ESRD) is a rapidly increasing health problem, and every year, about 2 million ESRD cases are reported worldwide. Hemodialysis (HD) is the vital renal reinstatement therapy for ESRD, and HD patterns play a crucial role in patients' health. Plasma metabolomics is the potential approach to understanding the HD process, effectiveness, and patterns. The lack of protein vitality is a primary problem for HD patients, and the quantities of amino acids intracellularly and in the blood are considered to be a symbolic index of protein metabolism and nutrition conditions. In the current study, LC/MS/MS and GC/MS methods were developed for 29 targeted plasma metabolites and validated as per ICH bioanalytical method validation M10 guidelines. The 29 metabolites included 20 proteinogenic amino acids and nine other related metabolites. The methods were employed to measure the absolute quantities (µM) of the targeted metabolites in HD patients (n=60) before and after dialysis (PRE-HD and POST-HD), and compared with the healthy control (HC) group (n=60). Phenylacetylglutamine was found to be higher in both PRE-HD (72.88±14.5 µM) and POST-HD (26.62±7.9 µM), when compared to HC (1.61±0.6 µM). On the other hand, glutamic acid was lower in PRE-HD (14.90±6.5 µM), and POST-HD (13.6±6.1 µM) than that of HC (245.4±37.8 µM). The dialytic loss was found to be 52-45% for arginine, lysine, and histidine, while it was 38-26% for glycine, cysteine, proline, alanine, threonine, glutamine, valine, and methionine. The dialytic loss was low (≤12%) for aspartic acid, glutamic acid, asparagine, leucine, tyrosine, tryptophan, and isoleucine. Graphical abstract adapted from mass spectrometry templates by Biorender.com retrieved from https://app.biorender.com/biorender-templates .

Novel Insights into the Adverse Health Effects of per- and Polyfluoroalkyl Substances on the Kidney via Human Urine Metabolomics

Per- and polyfluoroalkyl substances (PFAS) receive significant research attention due to their potential adverse effects on human health. Evidence shows that the kidney is one of the target organs of PFAS. In occupational exposure scenarios, high PFAS concentrations may adversely affect kidney metabolism, but whether this effect is reflected in the small metabolic molecules contained in urine remains unknown. In this study, 72 matched serum and urine samples from occupational workers of a fluorochemical manufactory as well as 153 urine samples from local residents were collected, and 23 PFAS levels were quantified. The concentrations of Σ23PFAS in the serum and urine samples of workers were 5.43 ± 1.02 μg/mL and 201 ± 46.9 ng/mL, respectively, while the Σ23PFAS concentration in the urine of the residents was 6.18 ± 0.76 ng/mL. For workers, high levels of urinary PFAS were strongly correlated with levels in serum (r = 0.57-0.93), indicating that urinary PFAS can be a good indicator for serum PFAS levels. Further, a urine nontargeted metabolomics study was conducted. The results of association models, including Bayesian kernel machine regression, demonstrated positive correlations between urinary PFAS levels and key small kidney molecules. A total of eight potential biomarkers associated with PFAS exposure were identified, and all of them showed significant positive correlations with markers of kidney function. These findings provide the first evidence that urine can serve as a matrix to indicate the adverse health effects of high levels of exposure to PFAS on the kidneys.

Precision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience

Purpose of review

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) for which many treatments exist that have been shown to prevent CKD progression and kidney failure. However, DKD is a complex and heterogeneous etiology of CKD with a spectrum of phenotypes and disease trajectories. In this narrative review, we discuss precision medicine approaches to DKD, including genomics, metabolomics, proteomics, and their potential role in the management of diabetes mellitus and DKD. A patient and caregivers of patients with lived experience with CKD were involved in this review.

Sources of information

Original research articles were identified from MEDLINE and Google Scholar using the search terms "diabetes," "diabetic kidney disease," "diabetic nephropathy," "chronic kidney disease," "kidney failure," "dialysis," "nephrology," "genomics," "metabolomics," and "proteomics."

Methods

A focused review and critical appraisal of existing literature regarding the precision medicine approaches to the diagnosis, prognosis, and treatment of diabetes and DKD framed by a patient partner's/caregiver's lived experience.

Key findings

Distinguishing diabetic nephropathy from CKD due to other types of DKD and non-DKD is challenging and typically requires a kidney biopsy for a diagnosis. Biomarkers have been identified to assist with the prediction of the onset and progression of DKD, but they have yet to be incorporated and evaluated relative to clinical standard of care CKD and kidney failure risk prediction tools. Genomics has identified multiple causal genetic variants for neonatal diabetes mellitus and monogenic diabetes of the young that can be used for diagnostic purposes and to specify antiglycemic therapy. Genome-wide-associated studies have identified genes implicated in DKD pathophysiology in the setting of type 1 and 2 diabetes but their translational benefits are lagging beyond polygenetic risk scores. Metabolomics and proteomics have been shown to improve diagnostic accuracy in DKD, have been used to identify novel pathways involved in DKD pathogenesis, and can be used to improve the prediction of CKD progression and kidney failure as well as predict response to DKD therapy.

Limitations

There are a limited number of large, high-quality prospective observational studies and no randomized controlled trials that support the use of precision medicine based approaches to improve clinical outcomes in adults with or at risk of diabetes and DKD. It is unclear which patients may benefit from the clinical use of genomics, metabolomics and proteomics along the spectrum of DKD trajectory.

Implications

Additional research is needed to evaluate the role of the use of precision medicine for DKD management, including diagnosis, differentiation of diabetic nephropathy from other etiologies of DKD and CKD, short-term and long-term risk prognostication kidney outcomes, and the prediction of response to and safety of disease-modifying therapies.

Prognostic Significance of Amino Acid and Biogenic Amines Profiling in Chronic Kidney Disease

There is a pressing need for more precise biomarkers of chronic kidney disease (CKD). Plasma samples from 820 subjects [231 with CKD, 325 with end-stage kidney disease (ESKD) and 264 controls] were analyzed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) to determine a metabolic profile of 28 amino acids (AAs) and biogenic amines to test their value as markers of CKD risk and progression. The kynurenine/tryptophan ratio showed the strongest correlation with estimated glomerular filtration rate values (coefficient = -0.731, p < 0.0001). Models created with orthogonal partial least squares-discriminant analysis (OPLS-DA) containing the metabolic signature showed a high goodness of fit and predictability for controls/CKD (R2X:0.73:R2Y:0.92:Q2:0.92, p < 0.0001) and lower values for CKD/ESKD (R2X:0.56:R2Y:0.59:Q2:0.55, p < 0.0001). Based on generated VIP scores, the most relevant markers for segregating samples into control/CKD and CKD/ESKD groups were citrulline (1.63) and tryptophan (1.47), respectively. ROC analysis showed that the addition of the metabolic profile to a model including CKD classic risk factors improved the AUC from 86.7% (83.6-89.9) to 100% (100-100) for CKD risk (p < 0.0001) and from 63.0% (58.2-67.8) to 96.5% (95.3-97.8) for the risk of progression from CKD to ESKD (p < 0.0001). Plasma concentrations of AAs and related amines may be useful as diagnostic biomarkers of kidney disease, both for CKD risk and for progression of CKD patients to ESKD.

Urinary metabolites associate with the presence of diabetic kidney disease in type 2 diabetes and mediate the effect of inflammation on kidney complication

AIMS

Diabetic kidney disease (DKD) is the one of the leading causes of end-stage kidney disease. Unraveling novel biomarker signatures capable to identify patients with DKD is favorable for tackle the burden. Here, we investigated the possible association between urinary metabolites and the presence of DKD in type 2 diabetes (T2D), and further, whether the associated metabolites improve discrimination of DKD and mediate the effect of inflammation on kidney involvement was evaluated.

METHODS

Two independent cohorts comprising 192 individuals (92 DKD) were analyzed. Urinary metabolites were analyzed by targeted metabolome profiling  and inflammatory cytokine IL-18 were measured by ELISA. Differentially expressed metabolites were selected and mediation analysis was carried out.

RESULTS

Seven potential metabolite biomarkers (i.e., S-Adenosyl-L-homocysteine, propionic acid, oxoadipic acid, leucine, isovaleric acid, isobutyric acid, and indole-3-carboxylic acid) were identified using the discovery and validation design. In the pooled analysis, propionic acid, oxoadipic acid, leucine, isovaleric acid, isobutyric acid, and indole-3-carboxylic acid were markedly and independently associated with DKD. The composite index of 7 potential metabolite biomarkers (CMI) mediated 32.99% of the significant association between the inflammatory IL-18 and DKD. Adding the metabolite biomarkers improved the discrimination of DKD.

CONCLUSIONS

In T2D, several associated urinary metabolites were identified to improve the prediction of DKD. Whether interventions aimed at reducing CMI also reduce the risk of DKD especially in patients with high IL-18 needs further investigations.

Serum and urine metabolomic biomarkers for predicting prognosis in patients with immunoglobulin A nephropathy

BACKGROUND

Immunoglobulin A nephropathy (IgAN) is the most prevalent form of glomerulonephritis worldwide. Prediction of disease progression in IgAN can help to provide individualized treatment based on accurate risk stratification.

METHODS

We performed proton nuclear magnetic resonance-based metabolomics analyses of serum and urine samples from healthy controls, non-progressor (NP), and progressor (P) groups to identify metabolic profiles of IgAN disease progression. Metabolites that were significantly different between the NP and P groups were selected for pathway analysis. Subsequently, we analyzed multivariate area under the receiver operating characteristic (ROC) curves to evaluate the predictive power of metabolites associated with IgAN progression.

RESULTS

We observed several distinct metabolic fingerprints of the P group involving the following metabolic pathways: glycolipid metabolism; valine, leucine, and isoleucine biosynthesis; aminoacyl-transfer RNA biosynthesis; glycine, serine, and threonine metabolism; and glyoxylate and dicarboxylate metabolism. In multivariate ROC analyses, the combinations of serum glycerol, threonine, and proteinuria (area under the curve [AUC], 0.923; 95% confidence interval [CI], 0.667-1.000) and of urinary leucine, valine, and proteinuria (AUC, 0.912; 95% CI, 0.667-1.000) showed the highest discriminatory ability to predict IgAN disease progression.

CONCLUSION

This study identified serum and urine metabolites profiles that can aid in the identification of progressive IgAN and proposed perturbed metabolic pathways associated with the identified metabolites.

Amino acids, post-translational modifications, nitric oxide, and oxidative stress in serum and urine of long COVID and ex COVID human subjects

In this study, we investigated the status of amino acids, their post-translational modifications (PTM), major nitric oxide (NO) metabolites and of malondialdehyde (MDA) as a biomarker of oxidative stress in serum and urine samples of long COVID (LoCo, n = 124) and ex COVID (ExCo, n = 24) human subjects collected in 2022. Amino acids and metabolites were measured by gas chromatography-mass spectrometry (GC-MS) methods using stable-isotope labelled analogs as internal standards. There were no differences with respect to circulating and excretory arginine and asymmetric dimethylarginine (ADMA). LoCo participants excreted higher amounts of guanidino acetate than ExCo participants (17.8 ± 10.4 µM/mM vs. 12.6 ± 8.86 µM/mM, P = 0.005). By contrast, LoCo participants excreted lower amounts of the advanced glycation end-product (AGE) NG-carboxyethylarginine (CEA) than ExCo participants did (0.675 ± 0.781 µM/mM vs. 1.16 ± 2.04 µM/mM, P = 0.0326). The serum concentrations of MDA did not differ between the groups, indicating no elevated oxidative stress in LoCo or ExCo. The serum concentration of nitrite was lower in LoCo compared to ExCo (1.96 ± 0.92 µM vs. 2.56 ± 1.08 µM; AUC, 0.718), suggesting altered NO synthesis in the endothelium. The serum concentration of nitrite correlated inversely with the symptom anxiety (r = - 0.293, P = 0.0003). The creatinine-corrected urinary excretion of Lys and its metabolite L-5-hydroxy-Lys correlated positively with COVID toes (r = 0.306, P = 0.00027) and sore throat (r = 0.302, P = 0.0003). Our results suggest that amino acid metabolism, PTM and oxidative stress are not severely affected in long COVID. LoCo participants may have a lower circulating NO reservoir than ExCo.

Metabolomic Profile and Its Correlation with the Plasmatic Levels of Losartan, EXP3174 and Blood Pressure Control in Hypertensive and Chronic Kidney Disease Patients

Systemic arterial hypertension (SAH) is one of the most prevalent chronic diseases worldwide and, when dysregulated, may cause serious complications. Losartan (LOS) blocks relevant physiological aspects of hypertension, acting mainly on the reduction of peripheral vascular resistance. Complications of hypertension include nephropathy, in which diagnosis is based on the observation of functional or structural renal dysfunction. Therefore, blood pressure control is essential to attenuate the progression of chronic kidney disease (CKD). In this study, 1H NMR metabolomics were used to differentiate hypertensive and chronic renal patients. Plasmatic levels of LOS and EXP3174, obtained by liquid chromatography coupled with mass-mass spectroscopy, were correlated with blood pressure control, biochemical markers and the metabolomic fingerprint of the groups. Some biomarkers have been correlated with key aspects of hypertension and CKD progression. For instance, higher levels of trigonelline, urea and fumaric acid were found as characteristic markers of kidney failure. In the hypertensive group, the urea levels found could indicate the onset of kidney damage when associated with uncontrolled blood pressure. In this sense, the results point to a new approach to identify CKD in early stages and may contribute to improving pharmacotherapy and reducing morbidity and mortality associated with hypertension and CKD.

The Effects of Two Kinds of Dietary Interventions on Serum Metabolic Profiles in Haemodialysis Patients

The goal of this study was to evaluate the effects of two kinds of 24-week dietary interventions in haemodialysis patients, a traditional nutritional intervention without a meal before dialysis (HG1) and implementation of a nutritional intervention with a meal served just before dialysis (HG2), in terms of analysing the differences in the serum metabolic profiles and finding biomarkers of dietary efficacy. These studies were performed in two homogenous groups of patients (n = 35 in both groups). Among the metabolites with the highest statistical significance between HG1 and HG2 after the end of the study, 21 substances were putatively annotated, which had potential significance in both of the most relevant metabolic pathways and those related to diet. After the 24 weeks of the dietary intervention, the main differences between the metabolomic profiles in the HG2 vs. HG1 groups were related to the higher signal intensities from amino acid metabolites: indole-3-carboxaldehyde, 5-(hydroxymethyl-2-furoyl)glycine, homocitrulline, 4-(glutamylamino)butanoate, tryptophol, gamma-glutamylthreonine, and isovalerylglycine. These metabolites are intermediates in the metabolic pathways of the necessary amino acids (Trp, Tyr, Phe, Leu, Ile, Val, Liz, and amino acids of the urea cycle) and are also diet-related intermediates (4-guanidinobutanoic acid, indole-3-carboxyaldehyde, homocitrulline, and isovalerylglycine).

Identifying disease progression in chronic kidney disease using proton magnetic resonance spectroscopy

Chronic kidney disease (CKD) affects approximately 10% of the world population, higher still in some developing countries, and can cause irreversible kidney damage eventually leading to kidney failure requiring dialysis or kidney transplantation. However, not all patients with CKD will progress to this stage, and it is difficult to distinguish between progressors and non-progressors at the time of diagnosis. Current clinical practice involves monitoring estimated glomerular filtration rate and proteinuria to assess CKD trajectory over time; however, there remains a need for novel, validated methods that differentiate CKD progressors and non-progressors. Nuclear magnetic resonance techniques, including magnetic resonance spectroscopy and magnetic resonance imaging, have the potential to improve our understanding of CKD progression. Herein, we review the application of magnetic resonance spectroscopy both in preclinical and clinical settings to improve the diagnosis and surveillance of patients with CKD.

Determination of creatinine in urine and blood serum human samples by CZE-UV using on-column internal standard injection

Creatinine is a well-stablished biomarker for kidney malfunctions and for normalization parameter of urinary quantitative information. Recently, metabolic studies have been discovering other functionalities for creatinine tests in human urine and blood serum. In this work we present an enhanced capillary electrophoresis (CE) based protocol for determination of creatinine. CE is a high-throughput separation technique that have been getting attention through the last decades and might be considered to be adopted as an analytical instrumentation for clinical purposes. In the proposed method, we performed a short injection program with on-column addition of internal standard. Additionally, the method allows a simultaneous screening of non-proteinogenic amino acids that could be considered for metabolomics purposes. We design a pilot study that successfully estimated the creatinine value in 100 urine samples with (2.85 ± 1.78) mg dL^-1 LOD; (8.24 ± 5.93) mg dL^-1 LOQ and 82.4% accuracy. Considering that serum creatinine is also included in the clinical laboratory routines for estimated Glomerular Filtration Rate dosage, the method was complementary applied to 10 blood serum samples, which resulted in a model with (0.4 ± 0.2) mg dL^-1 LOD; (2.0 ± 0.6) mg dL^-1 LOQ and 83.8% of accuracy. All results were in agreement with reference values. The proposed method promotes a great analytical frequency and reproducibility with enhanced specificity compared with the ongoing protocol by Jaffe's reaction, thereby proving to be useful as an alternative for creatinine exams that might help complete a diagnosis of a series of health-related issues.

Associations of Biopterins and ADMA with Vascular Function in Peripheral Microcirculation from Patients with Chronic Kidney Disease

We hypothesized that patients with chronic kidney disease (CKD) display an altered plasma amino acid (AA) metabolomic profile that could contribute to abnormal vascular maintenance of peripheral circulation in uremia. The relationships between plasma AAs and endothelial and vascular smooth muscle function in the microcirculation of CKD patients are not well understood. The objective of this study is to investigate to what extent the levels of AAs and its metabolites are changed in CKD patients and to test their relationship with endothelial and vascular smooth muscle function. Patients with CKD stages 3 and 5 and non-CKD controls are included in this study. We report that there was a significant reduction of the biopterin (BH4/BH2) ratio, which was accompanied by increased plasma levels of BH2, asymmetric dimethylarginine (ADMA) and citrulline in patients with CKD-5 vs. CKD-3 vs. controls. In vivo augmentation index measurement showed a positive association with ADMA in all participants. The contribution of nitric oxide, assessed by ex vivo assay, showed a negative association with creatinine, ADMA and citrulline in all participants. In CKD-5, BH4 negatively correlated with ADMA and ornithine levels, and the ex vivo endothelium-mediated dilatation positively correlated with phenylalanine levels. In conclusion, uremia is associated with alterations in AA metabolism that may affect endothelium-dependent dilatation and vascular stiffness in microcirculation. Interventional strategies aiming to normalize the AA metabolism could be of interest as treatment options.

Effect of Severe Renal Dysfunction on the Plasma Levels of DNA-Reactive Platinum after Oxaliplatin Administration

Higher amounts of circulating ultrafilterable platinum (fPt) are found in patients with renal dysfunction receiving a constant dose of oxaliplatin. However, the increased systemic fPt levels do not increase oxaliplatin-induced toxicities. We hypothesized that renal dysfunction has minimal effect on the elimination rate of reactive fPt, and that the DNA-binding capacity is one of the properties of reactive Pt species. This study aimed to quantify DNA-reactive fPt in plasma and to evaluate the impact of severe renal dysfunction on its pharmacokinetics. The pharmacokinetics of oxaliplatin was assessed in rats with bilateral nephrectomy (BNx) and in a hemodialysis patient who received mFOLFOX7 therapy for advanced metastatic gastric cancer. The platinum concentrations were determined using inductively coupled plasma-mass spectrometry. The amount of DNA-reactive fPt in the plasma was evaluated by the reaction between plasma and calf thymus DNA. Compared to the sham group in rats, the BNx group had significantly higher plasma total fPt concentrations at 24 h after drug administration. However, there was no significant difference in the plasma levels of DNA-reactive fPt between the two groups. In a hemodialysis patient, the plasma levels of total fPt decreased to 35.9 and 7.3% at 2 and 14 d after treatment, respectively. The plasma level of DNA-reactive fPt also decreased to 1.9 and 0.6%, respectively, on these days. This study showed that severe renal dysfunction has a limited effect on the plasma levels of DNA-reactive fPt after oxaliplatin administration.

Associations of serum amino acids related to urea cycle with risk of chronic kidney disease in Chinese with type 2 diabetes

OBJECTIVE

Serum levels of amino acids related to urea cycle are associated with risk of type 2 diabetes mellitus (T2DM). Our study aimed to explore whether serum levels of amino acids related to urea cycle, i.e., arginine, citrulline, and ornithine, are also associated with increased risk of chronic kidney disease (CKD) in T2DM.

METHODS

We extracted medical records of 1032 consecutive patients with T2DM from the Electronic Administrative System of Liaoning Medical University First Affiliated Hospital (LMUFAH) system from May 2015 to August 2016. Of them, 855 patients with completed data available were used in the analysis. CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m². Serum amino acids were measured by mass spectrometry (MS) technology. Binary logistic regression was performed to obtain odds ratios (ORs) and their 95% confidence intervals (CIs).

RESULTS

52.3% of the 855 T2DM patients were male, and 143 had CKD. In univariable analysis, high serum citrulline, high ratio of arginine to ornithine, and low ratio of ornithine to citrulline were associated with markedly increased risk of CKD (OR of top vs. bottom tertile: 2.87, 95%CI, 1.79-4.62 & 1.98, 95%CI,1.25-3.14 & 2.56, 95%CI, 1.61-4.07, respectively). In multivariable analysis, the ORs of citrulline and ornithine/citrulline ratio for CKD remained significant (OR of top vs. bottom tertile: 2.22, 95%CI, 1.29-3.82 & 2.24, 1.29-3.87, respectively).

CONCLUSIONS

In Chinese patients with T2DM, high citrulline and low ornithine/citrulline ratio were associated with increased risk of CKD.

Identification of Serum Metabolites for Predicting Chronic Kidney Disease Progression according to Chronic Kidney Disease Cause

Early detection and proper management of chronic kidney disease (CKD) can delay progression to end-stage kidney disease. We applied metabolomics to discover novel biomarkers to predict the risk of deterioration in patients with different causes of CKD. We enrolled non-dialytic diabetic nephropathy (DMN, n = 124), hypertensive nephropathy (HTN, n = 118), and polycystic kidney disease (PKD, n = 124) patients from the KNOW-CKD cohort. Within each disease subgroup, subjects were categorized as progressors (P) or non-progressors (NP) based on the median eGFR slope. P and NP pairs were randomly selected after matching for age, sex, and baseline eGFR. Targeted metabolomics was performed to quantify 188 metabolites in the baseline serum samples. We selected ten progression-related biomarkers for DMN and nine biomarkers each for HTN and PKD. Clinical parameters showed good ability to predict DMN (AUC 0.734); however, this tendency was not evident for HTN (AUC 0.659) or PKD (AUC 0.560). Models constructed with selected metabolites and clinical parameters had better ability to predict CKD progression than clinical parameters only. When selected metabolites were used in combination with clinical indicators, random forest prediction models for CKD progression were constructed with AUCs of 0.826, 0.872, and 0.834 for DMN, HTN, and PKD, respectively. Select novel metabolites identified in this study can help identify high-risk CKD patients who may benefit from more aggressive medical treatment.

The metabolomic differential plasma profile between dialysates. Pursuing to understand the mechanisms of citrate dialysate clinical benefits

Background: Currently, bicarbonate-based dialysate needs a buffer to prevent precipitation of bicarbonate salts with the bivalent cations, and acetate at 3-4 mmol/L is the most used. However, citrate is being postulated as a preferred option because of its association with better clinical results by poorly understood mechanisms. In that sense, this hypothesis-generating study aims to identify potential metabolites that could biologically explain these improvements found in patients using citrate dialysate. Methods: A unicentric, cross-over, prospective untargeted metabolomics study was designed to analyze the differences between two dialysates only differing in their buffer, one containing 4 mmol/L of acetate (AD) and the other 1 mmol/L of citrate (CD). Blood samples were collected in four moments (i.e., pre-, mid-, post-, and 30-min-post-dialysis) and analyzed in an untargeted metabolomics approach based on UPLC-Q-ToF mass spectrometry. Results: The 31 most discriminant metabolomic variables from the plasma samples of the 21 participants screened by their potential clinical implications show that, after dialysis with CD, some uremic toxins appear to be better cleared, the lysine degradation pathway is affected, and branched-chain amino acids post-dialysis levels are 9-10 times higher than with AD; and, on its part, dialysis with AD affects acylcarnitine clearance. Conclusion: Although most metabolic changes seen in this study could be attributable to the dialysis treatment itself, this study successfully identifies some metabolic variables that differ between CD and AD, which raise new hypotheses that may unveil the mechanisms involved in the clinical improvements observed with citrate in future research.

FuZhengHuaYuJiangZhuTongLuoFang Prescription Modulates Gut Microbiota and Gut-Derived Metabolites in UUO Rats

Background

Alteration of intestinal flora and metabolites is closely related to chronic kidney disease (CKD) across early to advanced stages. FuZhengHuaYuJiangZhuTongLuoFang prescription (FZHY) is a Chinese herb that has been proven to effectively treat CKD, but the underlying mechanism is not clear.

Methods

Rats were subjected to intragastric treatment with FZHY 7, 14, and 21 days after unilateral ureteral obstruction (UUO) surgery, and kidney tissue, colon tissue, serum, and stool samples were collected.

Results

FZHY treatment effectively ameliorated UUO-induced renal function loss, renal injury and renal fibrosis, and colon tissue damage and fibrosis on day 7. The results of 16S flora analysis (day 7) showed that, compared with the UUO group, both the FZHY group and the sham group showed decreased levels of g_Monoglobus, g_Papillibacter, g_Eubacterium_nodatum, and g_Family_XIII_AD3011. Additionally, FZHY obviously induced the reduction of serum citrulline, glycoursodeoxycholic acid, 23-nordeoxycholic acid, 7-ketodeoxycholic acid, kahweol, lipoid B4, 4-(3,4-dihydro-2H-1,5-benzodioxepin-7-yl)-2-methyl-1,3-thiazole, taurolithocholic acid sodium salt, indoline-2-carboxylic acid, 5(S),15(S)-diHETE, and others and the increase of bilirubin, asparagine, and others, which were positively associated with the above four candidate bacteria. Moreover, FZHY increased the levels of ZO-1, occludin, and claudin-1 in the colonic mucosa and reduced the levels of CRP, TNF-α, IL-6, and IL-1 in the serum and LN, FN, Col-I, and Col-III in the tubulointerstitium of UUO rats on day 7.

Conclusion

Our study revealed that FZHY reduced kidney damage at the early stage of CKD by regulating the above four candidate bacteria biomarkers and gut-derived harmful metabolites, inhibiting the inflammation response and tubulointerstitial fibrosis, providing deep insight into CKD therapeutic strategy.

Guanidine acetic acid supplementation altered plasma and tissue free amino acid profiles in finishing pigs

Background

As a nutritive feed additive, guanidine acetic acid (GAA) participates in the metabolism of energy and proteins. This study aimed to investigate the effects of GAA on growth performance, organ index, plasma and tissue free amino acid profiles, and related metabolites in finishing pigs. A total of 72 crossbred pigs (body weight 86.59 ± 1.16 kg) were randomly assigned to 1 of 4 dietary treatments (GAA0, GAA500, GAA1000, and GAA1500). They were fed the basal diets supplemented with 0, 500, 1000, or 1500 mg/kg GAA for 42 days, respectively. The growth performance and organ weight were evaluated, and the contents of crude protein, free amino acids, and metabolites in plasma and tissues were determined. Spearman correlation between plasma and tissue free amino acids and related metabolites was also analyzed.

Results

Growth performance in pigs was not altered by GAA (P > 0.05). The absolute and relative weight of kidneys increased (quadratic, P < 0.05). As dietary GAA concentration was increased, the contents of plasma glycine, serine, leucine, ornithine, and ratio of ornithine/arginine decreased (linear or quadratic, P < 0.05), but the contents of plasma isoleucine and taurine and the ratios of alanine/branched-chain amino acids and proline/ornithine increased quadratically (P < 0.05). The hepatic γ-amino-n-butyric acid content increased linearly and quadratically (P < 0.001), while the carnosine content decreased (quadratic, P = 0.004). The contents of renal arginine, proline, cystine, glutamate, and total amino acids (TAA) decreased quadratically (P < 0.05), but the contents of glycine (quadratic, P = 0.015) and γ-amino-n-butyric acid (linear, P = 0.008) increased. The pancreatic tryptophan content (quadratic, P = 0.024) increased, while the contents of pancreatic proline (linear, P = 0.005) and hydroxyproline (quadratic, P = 0.032) decreased in response to GAA supplementation. The contents of cardiac essential amino acids (EAA), nonessential amino acids (NEAA), and TAA in GAA1000 were higher than those in GAA1500 (P < 0.05). Supplementing with GAA linearly increased the contents of methionine, threonine, valine, isoleucine, leucine, phenylalanine, tryptophan, lysine, histidine, arginine, serine, alanine, glutamine, asparagine, tyrosine, proline, taurine, cystathionine, α-aminoadipic acid, β-aminoisobutyric acid, EAA, NEAA, and TAA in the spleen (P < 0.05). A strong Spearman correlation existed between plasma and tissue free amino acids and related metabolites.

Conclusion

GAA supplementation did not altered pig growth performance, but it altered plasma and tissue free amino acid profiles and the contents of related metabolites in pigs in a tissue-dependent manner.

Health Risks of Chronic Exposure to Small Doses of Microcystins: An Integrative Metabolomic and Biochemical Study of Human Serum

Health risks of chronic exposure to microcystins (MCs), a family of aquatic contaminants produced mainly by cyanobacteria, are critical yet unsolved problems. Despite a few epidemiological studies, the metabolic profiles of humans exposed to MCs remain unknown, hindering the deep understanding of the molecular toxicity mechanisms. Here, sensitive nuclear magnetic resonance (NMR)- and liquid chromatography-mass spectrometry (LC-MS)-based metabolomics were applied to investigate the serum metabolic profiles of humans living near Lake Chao, where toxic cyanobacterial blooms occur annually. MCs were positively detected in 92 of 144 sera by ultra-high-pressure liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) with a median concentration of 0.016 μg/L. The estimated daily intake (0.15-0.27 μg MC-LReq/day) was less than the tolerable daily intake (TDI, 2.4 μg MC-LR for 60 kg adults) recommended by the World Health Organization (WHO). Obvious disruptions of the amino acid metabolism were confirmed and played important roles in renal impairments associated with serum MC burdens. Chronic oral exposure of mice to 30 μg MC-LR/kg body mass, which is less than the no observed adverse effect level, also led to obvious renal lesions and metabolic dysfunction. These observations provide the first evidence of metabolic disturbance of humans exposed to MCs and indicate that the WHO's TDI value determined traditionally should be lessened to protect human health effectively.

Toxicometabolomics and Biotransformation Product Elucidation in Single Zebrafish Embryos Exposed to Carbamazepine from Environmentally-Relevant to Morphologically Altering Doses

Toxicometabolomics and biotransformation product (bioTP) elucidation were carried out in single zebrafish (ZF) embryos exposed to carbamazepine (CBZ). Exposures were conducted in 96-well plates containing six CBZ concentrations ranging from 0.5 μg/L to 50 mg/L (n = 12 embryos per dose). In the 50 mg/L dose group, 33% of embryos developed edema during the exposure (120 hpf), while hatching was significantly delayed in three of the lower-dose groups (0.46, 3.85, and 445 μg/L) compared to the control at 48 hpf. Toxicometabolomic analysis together with random forest modeling revealed a total of 80 significantly affected metabolites (22 identified via targeted lipidomics and 58 via nontarget analysis). The wide range of doses enabled the observation of both monotonic and nonmonotonic dose responses in the metabolome, which ultimately produced a unique and comprehensive biochemical picture that aligns with existing knowledge on the mode of action of CBZ. The combination of high dose exposures and apical endpoint assessment in single embryos also enabled hypothesis generation regarding the target organ for the morphologically altering insult. In addition, two CBZ bioTPs were identified without additional exposure experiments. Overall, this work showcases the potential of toxicometabolomics and bioTP determination in single ZF embryos for rapid and comprehensive chemical hazard assessment.

In-depth characterisation of the urine metabolome in cats with and without urinary tract diseases

INTRODUCTION

Our understanding of the urine metabolome and its association with urinary tract disease is limited in cats.

OBJECTIVES

We conducted a case-control study to characterise the feline urine metabolome, investigate its association with chronic kidney disease (CKD) and feline idiopathic cystitis (FIC), and assess its compositional relationship with the urine microbiome.

METHODS

The urine metabolome of 45 owned cats, including 23 controls, 16 CKD, and 6 FIC cases, was characterised by an untargeted metabolomics approach using high-performance chemical isotope labelling liquid chromatography-mass spectrometry.

RESULTS

We detected 9411 unique compounds in the urine of controls and cases and identified 1037 metabolites with high confidence. Amino acids, peptides, and analogues dominated these metabolites (32.2%), followed by carbonyl compounds (7.1%) and carbohydrates (6.5%). Seven controls from one household showed a significant level of metabolome clustering, with a distinct separation from controls from other households (p value < 0.001). Owner surveys revealed that this cluster of cats was fed dry food only, whereas all but one other control had wet food in their diet. Accordingly, the diet type was significantly associated with the urine metabolome composition in our multivariate model (p value = 0.001). Metabolites significantly altered in this cluster included taurine, an essential amino acid in cats. Urine metabolome profiles were not significantly different in CKD and FIC cases compared with controls, and no significant compositional relationship was detected between the urine metabolome and microbiome.

CONCLUSION

Our study reveals in-depth diversity of the feline urine metabolome composition, and suggests that it can vary considerably depending on environmental factors.

Urinary metabolomic profiling from spontaneous tolerant kidney transplanted recipients shows enrichment in tryptophan-derived metabolites

Background

Operational tolerance is the holy grail in solid organ transplantation. Previous reports showed that the urinary compartment of operationally tolerant recipients harbor a specific and unique profile. We hypothesized that spontaneous tolerant kidney transplanted recipients (KTR) would have a specific urinary metabolomic profile associated to operational tolerance.

Methods

We performed metabolomic profiling on urine samples from healthy volunteers, stable KTR under standard and minimal immunosuppression and spontaneous tolerant KTR using liquid chromatography in tandem with mass spectrometry. Supervised and unsupervised multivariate computational analyses were used to highlight urinary metabolomic profile and metabolite identification thanks to workflow4metabolomic platform.

Findings

The urinary metabolome was composed of approximately 2700 metabolites. Raw unsupervised clustering allowed us to separate healthy volunteers and tolerant KTR from others. We confirmed by two methods a specific urinary metabolomic signature in tolerant KTR mainly driven by kynurenic acid independent of immunosuppressive drugs, serum creatinine and gender.

Interpretation

Kynurenic acid and tryptamine enrichment allowed the identification of putative pathways and metabolites associated with operational tolerance like IDO, GRP35 and AhR and indole alkaloids.

Funding

This study was supported by the ANR, IRSRPL and CHU de Nantes.

Avenues for post-translational protein modification prevention and therapy

Non-enzymatic post-translational modifications (nPTMs) of proteins have emerged as novel risk factors for the genesis and progression of various diseases. We now have a variety of experimental and established therapeutic strategies to target harmful nPTMs and potentially improve clinical outcomes. Protein carbamylation and glycation are two common and representative nPTMs that have gained considerable attention lately as favorable therapeutic targets with emerging clinical evidence. Protein carbamylation is associated with the occurrence of cardiovascular disease (CVD) and mortality in patients with chronic kidney disease (CKD); and advanced glycation end products (AGEs), a heterogeneous group of molecules produced in a series of glycation reactions, have been linked to various diabetic complications. Therefore, reducing the burden of protein carbamylation and AGEs is an appealing and promising therapeutic approach. This review chapter summarizes potential anti-nPTM therapy options in CKD, CVD, and diabetes along with clinical implications. Using two prime examples-protein carbamylation and AGEs-we discuss the varied preventative and therapeutic options to mitigate these pathologic nPTMs in detail. We provide in-depth case studies on carbamylation in the setting of kidney disease and AGEs in metabolic disorders, with an emphasis on the relevance to reducing adverse clinical outcomes such as CKD progression, cardiovascular events, and mortality. Overall, whether specific efforts to lower carbamylation and AGE burden will yield definitive clinical improvement in humans remains largely to be seen. However, the scientific rationale for such pursuits is demonstrated herein.

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.

Relationship between amino acid ratios and decline in estimated glomerular filtration rate in diabetic and non-diabetic patients in South Africa

Background

Diabetic kidney disease is a major complication resulting from type 1 and type 2 diabetes. Currently, the microalbuminuria test is used to monitor renal function; however, it does not detect albumin until progressive loss of renal function has occurred.

Objective

This study analysed the relationship between changes in amino acid ratios and estimated glomerular filtration rate (eGFR) decline in diabetic and non-diabetic patients.

Methods

Urine samples were collected from participants between February 2019 to April 2019 and analysed from November 2020 to January 2021. Diabetic (glycated haemoglobin > 6.4%) and non-diabetic patients (glycated haemoglobin ≤ 6.4%) from Chris Hani Baragwanath Hospital, South Africa, were further categorised based on the degree of renal function predicted by the eGFRs. Amino acids were quantified using tandem mass spectrometry to determine the concentrations and ratios of tyrosine/phenylalanine, ornithine/arginine, arginine/citrulline and citrulline/ornithine at different stages of the chronic kidney disease.

Results

Among diabetic patients, the tyrosine/phenylalanine ratio showed a statistically significant increase (p = 0.04) as the eGFR declined from stage 1 to stage 4; the ornithine/arginine ratio showed a strong negative correlation with eGFR. The citrulline/ornithine ratio differed between the diabetic and non-diabetic patients in stage 1 of chronic kidney disease.

Conclusion

Amino acid ratios (ornithine/arginine and tyrosine/phenylalanine) are affected by the progression of diabetes and can be correlated to renal function. The citrulline/ornithine ratios differ between the studied groups in stage 1 of the disease and may be utilised to predict the onset of chronic kidney disease.

Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived 'metabolite constellation' (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (-1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. -6.0 (-7.0; -5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.

Lipidomic and Metabolomic Signature of Progression of Chronic Kidney Disease in Patients with Severe Obesity

Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the assessment of clinical parameters. To explore whether distinct lipid and metabolic signatures in obesity may signify early stages of pathogenesis toward CKD, liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) analyses were performed in the serum and the urine of severely obese patients with and without CKD. Moreover, the impact of bariatric surgery (BS) in lipid and metabolic signature was also studied, through LC-MS and GC-HRAM-MS analyses in the serum and urine of patients with severe obesity and CKD before and after undergoing BS. Regarding patients with severe obesity and CKD compared to severely obese patients without CKD, serum lipidome analysis revealed significant differences in lipid signature. Furthermore, serum metabolomics profile revealed significant changes in specific amino acids, with isoleucine and tyrosine, increased in CKD patients compared with patients without CKD. LC-MS and GC-HRAM-MS analysis in serum of patients with severe obesity and CKD after BS showed downregulation of levels of triglycerides (TGs) and diglycerides (DGs) as well as a decrease in branched-chain amino acid (BCAA), lysine, threonine, proline, and serine. In addition, BS removed most of the correlations in CKD patients against biochemical parameters related to kidney dysfunction. Concerning urine analysis, hippuric acid, valine and glutamine were significantly decreased in urine from CKD patients after surgery. Interestingly, bariatric surgery did not restore all the lipid species, some of them decreased, hence drawing attention to them as potential targets for early diagnosis or therapeutic intervention. Results obtained in this study would justify the use of comprehensive mass spectrometry-based lipidomics to measure other lipids aside from conventional lipid profiles and to validate possible early markers of risk of CKD in patients with severe obesity.

A knock-in rat model unravels acute and chronic renal toxicity in glutaric aciduria type I

Glutaric aciduria type I (GA-I, OMIM # 231670) is an autosomal recessive inborn error of metabolism caused by deficiency of the mitochondrial enzyme glutaryl-CoA dehydrogenase (GCDH). The principal clinical manifestation in GA-I patients is striatal injury most often triggered by catabolic stress. Early diagnosis by newborn screening programs improved survival and reduced striatal damage in GA-I patients. However, the clinical phenotype is still evolving in the aging patient population. Evaluation of long-term outcome in GA-I patients recently identified glomerular filtration rate (GFR) decline with increasing age. We recently created the first knock-in rat model for GA-I harboring the mutation p.R411W (c.1231 C>T), corresponding to the most frequent GCDH human mutation p.R402W. In this study, we evaluated the effect of an acute metabolic stress in form of high lysine diet (HLD) on young Gcdh^ki/ki rats. We further studied the chronic effect of GCDH deficiency on kidney function in a longitudinal study on a cohort of Gcdh^ki/ki rats by repetitive ⁶⁸Ga-EDTA positron emission tomography (PET) renography, biochemical and histological analyses. In young Gcdh^ki/ki rats exposed to HLD, we observed a GFR decline and biochemical signs of a tubulopathy. Histological analyses revealed lipophilic vacuoles, thinning of apical brush border membranes and increased numbers of mitochondria in proximal tubular (PT) cells. HLD also altered OXPHOS activities and proteome in kidneys of Gcdh^ki/ki rats. In the longitudinal cohort, we showed a progressive GFR decline in Gcdh^ki/ki rats starting at young adult age and a decline of renal clearance. Histopathological analyses in aged Gcdh^ki/ki rats revealed tubular dilatation, protein accumulation in PT cells and mononuclear infiltrations. These observations confirm that GA-I leads to acute and chronic renal damage. This raises questions on indication for follow-up on kidney function in GA-I patients and possible therapeutic interventions to avoid renal damage.

Metabolomic Profiling of Amino Acids in Human Plasma Distinguishes Diabetic Kidney Disease From Type 2 Diabetes Mellitus

Background: Diabetic kidney disease (DKD) is a highly prevalent complication in patients with type 2 diabetes mellitus (T2DM). Patients with DKD exhibit changes in plasma levels of amino acids (AAs) due to insulin resistance, reduced protein intake, and impaired renal transport of AAs. The role of AAs in distinguishing DKD from T2DM and healthy controls has yet to be elucidated. This study aimed to investigate the metabolomic profiling of AAs in the plasma of patients with DKD. Methods: We established an ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method to detect the plasma levels of the 20 AAs in healthy controls (n = 112), patients with T2DM (n = 101), and patients with DKD (n = 101). The key AAs associated with DKD were identified by orthogonal partial least-squares discriminant analysis (OPLS-DA) models with loading plots, shared and unique structures (SUS) plots, and variable importance in projection (VIP) values. The discrimination accuracies of these key AAs were then determined by analyses of receiver-operating characteristic (ROC) curves. Results: Metabolomic profiling of plasma revealed significant alterations in levels of the 20 AAs in patients with DKD when compared to those in either patients with T2DM or healthy controls. Metabolomic profiling of the 20 AAs showed a visual separation of patients with DKD from patients with T2DM and healthy controls in OPLS-DA models. Based on loading plots, SUS plots, and VIP values in the OPLS-DA models, we identified valine and cysteine as potential contributors to the progression of DKD from patients with T2DM. Histidine was identified as a key mediator that could distinguish patients with DKD from healthy controls. Plasma levels of histidine and valine were decreased significantly in patients with DKD with a decline in kidney function, and had excellent performance in distinguishing patients with DKD from patients with T2DM and healthy controls according to ROC curves. Conclusion: Plasma levels of histidine and valine were identified as the main AAs that can distinguish patients with DKD. Our findings provide new options for the prevention, treatment, and management of DKD.

Musk Tongxin Dripping Pills for treating Ticagrelor in Patients After Percutaneous Coronary Intervention: Echocardiography Combined with Untargeted Metabolomics

Objectives: As current clinical practice guidelines, ticagrelor is the suggested therapeutic scheme to prevent adverse cardiovascular events in acute myocardial infarction (AMI) patients undergoing percutaneous coronary intervention (PCI) treatment. However, this therapeutic strategy still fails, and around 30% patients display inadequate antiplatelet responses. Musk Tongxin Dripping Pill (MTDP) in Chinese hospital was usually considered as the combination with ticagrelor to improve the treatment effect. Unfortunately, the mechanism has not been elucidated.

Methods: The untargeted metabolomic method was introduced based on liquid chromatography–high-resolution mass spectrometry (HPLC-HRMS) coupled with STI for the research of the drug combination mechanism between ticagrelor and MTDP. 28 patients with a confirmed diagnosis of AMI were selectively collected, who were then divided into two different dosage regimen groups, and the serum samples were collected for the untargeted metabolomics assay. Then the differential metabolites were associated with blood biochemical indicators.

Results: The GLS values in both groups increased after treatment and those in the ticagrelor and MTDP combination group after treatment were higher than those in the ticagrelor group (p < 0.05), suggesting that the combination medication has better therapeutic effect on patients with myocardial infarction. From metabolomics analysis, the species of metabolites changed in two groups before and after treatment. Moreover, 93 differential metabolites changed in the drug combination group compared with the ticagrelor group after treatment (p < 0.05), which mainly related to changes in fatty acid metabolism pathways. Then the differential metabolites were found to be related with blood biochemical indicators, such as lipid, high-density lipoprotein (HDL), and low-density lipoprotein (LDL).

Conclusion: This work will provide a possible mechanism of the drug combination interaction between ticagrelor and MTDP from two angles of echocardiography and metabonomics. Several potential metabolic pathways were also found to have a relationship with MTDP, which will provide a new perspective in clinical medication.

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.

Uremic encephalopathy

Uremic encephalopathy encompasses a wide range of central nervous system abnormalities associated with poor kidney function occurring with either progressive chronic kidney disease or acute kidney injury. The syndrome is likely caused by retention of uremic solutes, alterations in hormonal metabolism, changes in electrolyte and acid-base homeostasis, as well as changes in vascular reactivity, blood-brain barrier transport, and inflammation. There are no defining clinical, laboratory, or imaging findings, and the diagnosis is often made retrospectively when symptoms improve after dialysis or transplantation. The diagnosis is also made difficult because of the many confounding and overlapping conditions seen in patients with chronic kidney disease and acute kidney injury. Thus, institution of kidney replacement therapy should be considered as a trial to improve symptoms in the right clinical context. Neurological symptoms that do not improve after improvement in clearance should prompt a search for other explanations. Further knowledge linking possible uremic retention solutes with neurological symptoms is needed to better understand this syndrome as well as to develop more tailored treatments that aim to improve cognitive function.

Nutritional Adequacy of Animal-Based and Plant-Based Asian Diets for Chronic Kidney Disease Patients: A Modeling Study

Plant-based low protein diets (LPDs) have gained popularity for managing chronic kidney disease (CKD) patients. The nutritional adequacy of these and other LPDs prescribed for CKD patients have not been carefully examined. This study assessed the nutrient composition of such LPDs and moderately high protein diets (MHPDs) that might be prescribed for patients in the Asia Pacific region with CKD who are not dialyzed or undergoing maintenance dialysis. Conventional diets containing at least 50% animal-based proteins and plant-based diets were also planned with protein prescriptions of 0.5 to 0.8 g/kg/day and MHPDs with protein prescriptions of 1.0 to 1.2 g/kg/day. Plant-based, lacto-, ovo-, and lacto-ovo-vegetarian and vegan LPDs and MHPDs were planned by replacing some or all of the animal proteins from the conventional diet. With 0.5 g protein/kg/day, all diets were below the Recommended Dietary Allowances (RDA) for at least one essential amino acid (EAA). At a protein prescription of 0.6 g/kg/day, only the conventional LPD met the RDA for all EAAs. This deficiency with the plant-based LPDs persisted even with several plant food substitutions. With a protein prescription ≥0.7 g/kg/day, all the plant-based and vegetarian LPDs provided the RDA for all EAA. The plant-based and vegetarian diets also contained relatively greater potassium, phosphorus, and calcium content but lower long-chain n-3 polyunsaturated fatty acids and vitamin B-12 than the conventional diet. Other essential micronutrients were commonly below the RDA even at higher protein intakes. The low contents of some essential micronutrients were found in both animal-based and plant-based diets. Prescription of all LPDs for CKD patients, especially plant-based and vegetarian LPDs, requires careful planning to ensure the adequacy of all nutrients, particularly essential amino acids. Consideration should be given to supplementing all animal-based and plant-based LPDs and MHPDs with multivitamins and certain trace elements.

Fisetin Improves Hyperuricemia-Induced Chronic Kidney Disease via Regulating Gut Microbiota-Mediated Tryptophan Metabolism and Aryl Hydrocarbon Receptor Activation

The intestinal flora serves a critical role in the development of hyperuricemia-induced chronic kidney disease (CKD). We previously found that natural flavonol fisetin exhibited nephroprotective effects in hyperuricemic mice. However, the mechanism remains largely unknown. To investigate the underlying mechanism of fisetin, mice were fed with potassium oxonate and adenine to introduce hyperuricemia-induced CKD. Fisetin improved kidney function, ameliorated renal fibrosis, and restored enteric dysbacteriosis in hyperuricemia-induced CKD mice. Meanwhile, gut microbiota-derived tryptophan metabolites, especially l-kynurenine, showed correlations with nephroprotective profiles of fisetin. Additionally, the kidney expression of the aryl hydrocarbon receptor (AHR), an endogenous receptor of l-kynurenine, was enhanced in hyperuricemic mice and further reduced in fisetin-treated mice. Finally, in vitro results showed that inhibition of AHR activation attenuated l-kynurenine-induced fibrosis. These results highlighted that fisetin protected against hyperuricemia-induced CKD via modulating gut microbiota-mediated tryptophan metabolism and AHR activation.

High salt diet-induced proximal tubular phenotypic changes and sodium-glucose cotransporter-2 expression are coordinated by cold shock Y-box binding protein-1

High salt diet (HSD) is a hallmark of blood pressure elevations, weight gain and diabetes onset in the metabolic syndrome. In kidney, compensatory mechanisms are activated to balance salt turnover and maintain homeostasis. Data on the long-term effects of HSD with respect to tubular cell functions and kidney architecture that exclude confounding indirect blood pressure effects are scarce. Additionally we focus on cold shock Y-box binding protein-1 as a tubular cell protective factor. A HSD model (4% NaCl in chow; 1% NaCl in water) was compared to normal salt diet (NSD, standard chow) over 16 months using wild type mice and an inducible conditional whole body knockout for cold shock Y-box binding protein-1 (BL6J/N, Ybx1). HSD induced no difference in blood pressure over 16 months, comparing NSD/HSD and Ybx1 wild type/knockout. Nevertheless, marked phenotypic changes were detected. Glucosuria and subnephrotic albuminuria ensued in wild type animals under HSD, which subsided in Ybx1-deficient animals. At the same time megalin receptors were upregulated. The sodium-glucose cotransporter-2 (SGLT2) was completely downregulated in wild type HSD animals that developed glucosuria. In Ybx1 knockouts, expression of AQP1 and SGLT2 was maintained under HSD; proximal tubular widening and glomerular tubularization developed. Concurrently, amino aciduria of neutral and hydrophobic amino acids was seen. In vitro translation confirmed that YB-1 translationally represses Sglt2 transcripts. Our data reveal profound effects of HSD primarily within glomeruli and proximal tubular segments. YB-1 is regulated by HSD and orchestrates HSD-dependent changes; notably, sets reabsorption thresholds for amino acids, proteins and glucose.

Combined Untargeted and Targeted Metabolomics Approaches Reveal Urinary Changes of Amino Acids and Energy Metabolism in Canine Babesiosis With Different Levels of Kidney Function

Canine babesiosis is a tick-borne disease with a worldwide distribution, caused by the haemoprotozoan parasites of the genus Babesia. One of the most prevalent complication is acute kidney injury, and an early diagnosis of altered kidney function remains a challenge for veterinary practice. The aim of this study was to assess the urine metabolic profile from dogs with babesiosis and different degree of kidney function using untargeted and targeted MS-based metabolomics approaches. In this study, 22 dogs naturally infected with Babesia canis and 12 healthy dogs were included. Untargeted metabolomics approach identified 601 features with a differential abundance between the healthy group and groups of dogs with babesiosis and different level of kidney function, with 27 of them identified as a match to known standards; while targeted approach identified 17 metabolites with significantly different concentrations between the groups. A pattern of significantly altered metabolites referring to the inflammatory host response, oxidative stress, and energy metabolism modulation in babesiosis was presented. Our findings have demonstrated that kidney dysfunction accompanying canine babesiosis was associated with changes in amino acid metabolism, energy metabolism, fatty acid metabolism, and biochemical pathways such as urea cycle and ammonia detoxication. These findings will enable the inclusion of urinary markers for the detection and monitoring of renal damage in babesiosis, as well as in other similar diseases.

Comprehensive analysis of diabetic nephropathy expression profile based on weighted gene co-expression network analysis algorithm

BACKGROUND

Diabetic nephropathy (DN) is the major complication of diabetes mellitus, and leading cause of end-stage renal disease. The underlying molecular mechanism of DN is not yet completely clear. The aim of this study was to analyze a DN microarray dataset using weighted gene co-expression network analysis (WGCNA) algorithm for better understanding of DN pathogenesis and exploring key genes in the disease progression.

METHODS

The identified differentially expressed genes (DEGs) in DN dataset GSE47183 were introduced to WGCNA algorithm to construct co-expression modules. STRING database was used for construction of Protein-protein interaction (PPI) networks of the genes in all modules and the hub genes were identified considering both the degree centrality in the PPI networks and the ranked lists of weighted networks. Gene ontology and Reactome pathway enrichment analyses were performed on each module to understand their involvement in the biological processes and pathways. Following validation of the hub genes in another DN dataset (GSE96804), their up-stream regulators, including microRNAs and transcription factors were predicted and a regulatory network comprising of all these molecules was constructed.

RESULTS

After normalization and analysis of the dataset, 2475 significant DEGs were identified and clustered into six different co-expression modules by WGCNA algorithm. Then, DEGs of each module were subjected to functional enrichment analyses and PPI network constructions. Metabolic processes, cell cycle control, and apoptosis were among the top enriched terms. In the next step, 23 hub genes were identified among the modules in genes and five of them, including FN1, SLC2A2, FABP1, EHHADH and PIPOX were validated in another DN dataset. In the regulatory network, FN1 was the most affected hub gene and mir-27a and REAL were recognized as two main upstream-regulators of the hub genes.

CONCLUSIONS

The identified hub genes from the hearts of co-expression modules could widen our understanding of the DN development and might be of targets of future investigations, exploring their therapeutic potentials for treatment of this complicated disease.