Metabolic profiling of human plasma and urine in chronic kidney disease by hydrophilic interaction liquid chromatography coupled with time-of-flight mass spectrometry: a pilot study

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine

BACKGROUND

Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed.

RESULTS

Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices).

SIGNIFICANCE

This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

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.

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

Metabolomic profiling to identify early urinary biomarkers and metabolic pathway alterations in autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of numerous fluid-filled cysts that lead to progressive loss of functional nephrons. Currently, there is an unmet need for diagnostic and prognostic indicators of early stages of the disease. Metabolites were extracted from the urine of patients with early-stage ADPKD (n = 48 study participants) and age- and sex-matched normal controls (n = 47) and analyzed by liquid chromatography-mass spectrometry. Orthogonal partial least squares-discriminant analysis was used to generate a global metabolomic profile of early ADPKD for the identification of metabolic pathway alterations and discriminatory metabolites as candidates of diagnostic and prognostic biomarkers. The global metabolomic profile exhibited alterations in steroid hormone biosynthesis and metabolism, fatty acid metabolism, pyruvate metabolism, amino acid metabolism, and the urea cycle. A panel of 46 metabolite features was identified as candidate diagnostic biomarkers. Notable putative identities of candidate diagnostic biomarkers for early detection include creatinine, cAMP, deoxycytidine monophosphate, various androgens (testosterone; 5-α-androstane-3,17,dione; trans-dehydroandrosterone), betaine aldehyde, phosphoric acid, choline, 18-hydroxycorticosterone, and cortisol. Metabolic pathways associated with variable rates of disease progression included steroid hormone biosynthesis and metabolism, vitamin D3 metabolism, fatty acid metabolism, the pentose phosphate pathway, tricarboxylic acid cycle, amino acid metabolism, sialic acid metabolism, and chondroitin sulfate and heparin sulfate degradation. A panel of 41 metabolite features was identified as candidate prognostic biomarkers. Notable putative identities of candidate prognostic biomarkers include ethanolamine, C20:4 anandamide phosphate, progesterone, various androgens (5-α-dihydrotestosterone, androsterone, etiocholanolone, and epiandrosterone), betaine aldehyde, inflammatory lipids (eicosapentaenoic acid, linoleic acid, and stearolic acid), and choline. Our exploratory data support metabolic reprogramming in early ADPKD and demonstrate the ability of liquid chromatography-mass spectrometry-based global metabolomic profiling to detect metabolic pathway alterations as new therapeutic targets and biomarkers for early diagnosis and tracking disease progression of ADPKD.NEW & NOTEWORTHY To our knowledge, this study is the first to generate urinary global metabolomic profiles from individuals with early-stage ADPKD with preserved renal function for biomarker discovery. The exploratory dataset reveals metabolic pathway alterations that may be responsible for early cystogenesis and rapid disease progression and may be potential therapeutic targets and pathway sources for candidate biomarkers. From these results, we generated a panel of candidate diagnostic and prognostic biomarkers of early-stage ADPKD for future validation.

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.

Changes in glomerular filtration rate and metabolomic differences in severely ill coronavirus disease survivors 3 months after discharge

To explore the recovery of renal function in severely ill coronavirus disease (COVID-19) survivors and determine the plasma metabolomic profile of patients with different renal outcomes 3 months after discharge, we included 89 severe COVID-19 survivors who had been discharged from Wuhan Union Hospital for 3 months. All patients had no underlying kidney disease before admission. At patient recruitment, renal function assessment, laboratory examination, chest computed tomography (CT) were performed. Liquid chromatography-mass spectrometry was used to detect metabolites in the plasma. We analyzed the longitudinally change in the estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin-c levels using the CKD-EPI equation and explored the metabolomic differences in patients with different eGFR change patterns from hospitalization to 3 months after discharge. Lung CT showed good recovery; however, the median eGFR significantly decreased at the 3-month follow-up. Among the 89 severely ill COVID-19 patients, 69 (77.5%) showed abnormal eGFR (<90 mL/min per 1.73 m²) at 3 months after discharge. Age (odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.08-1.47, p = 0.003), body mass index (OR = 1.97, 95% CI = 1.20-3.22, p = 0.007), and cystatin-c level (OR = 1.22, 95% CI = 1.07-1.39, p = 0.003) at discharge were independent risk factors for post-discharge abnormal eGFR. Plasma metabolomics at the 3-months follow-up revealed that β-pseudouridine, uridine, and 2-(dimethylamino) guanosine levels gradually increased with an abnormal degree of eGFR. Moreover, the kynurenine pathway in tryptophan metabolism, vitamin B6 metabolism, cysteine and methionine metabolism, and arginine biosynthesis were also perturbed in survivors with abnormal eGFR.

Metabolic profiling in children and young adults with autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is the most commonly inherited kidney disease. Although children with ADPKD show normal renal function, cyst development is already occurring. In this study, we aimed to identify markers and associated molecular pathways of disease progression in children and young adults with ADPKD. Plasma samples were collected during a 3-year randomized, double-blind, placebo-controlled, phase III clinical trial that was designed to test the efficacy of pravastatin on slowing down ADPKD progression in pediatric patients. Samples from 58 patients were available at baseline and at the 3-year endpoint of the study, respectively. Furthermore, plasma samples from 98 healthy children were used as controls. Metabolomic analysis was performed using liquid chromatography-tandem mass spectrometry and differences in metabolic profiles over time and within study groups were evaluated. While pravastatin therapy led to a decrease in a percent change of total kidney volume (HtTKV) in ADPKD patients, it had minimal effects on metabolite changes. Oxidative stress, endothelial dysfunction, inflammation and immune response were the most affected signaling pathways that distinguished healthy from diseased children. Pathway analysis revealed that metabolites in the arginine metabolism (urea and nitric oxide cycles), asparagine and glutamine metabolism, in the methylation cycle and kynurenine pathway were significantly changed between healthy and children with ADPDK and continued to diverge from the control levels while the disease progressed. Detected metabolite changes were primarily governed by disease progression, and less by pravastatin treatment. Identified metabolic pathways, from arginine and asparagine to kynurenine metabolism could present therapeutic targets and should be further investigated for potential to treat ADPKD progression at an early stage.

Impairment of renal steroidogenesis at the onset of diabetes

Accumulating evidence indicates the association between changes in circulating sex steroid hormone levels and the development of diabetic nephropathy. However, the renal synthesis of steroid hormones during diabetes is essentially unknown. Male Wistar rats were injected with streptozotocin (STZ) or vehicle. After one week, no changes in functional or structural parameters related to kidney damage were observed in STZ group; however, a higher renal expression of proinflammatory cytokines and HSP70 was found. Expression of Steroidogenic Acute Regulatory protein (StAR) and P450scc (CYP11A1) was decreased in STZ kidneys. Incubation of isolated mitochondria with 22R-hydroxycholesterol revealed a marked inhibition in CYP11A1 function at the medullary level in STZ group. The inhibition of these first steps of renal steroidogenesis in early STZ-induced diabetes led to a decreased local synthesis of pregnenolone and progesterone. These findings stimulate investigation of the probable role of nephrosteroids in kidney damage associated with diabetes.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

New Potential Biomarkers for Chronic Kidney Disease Management-A Review of the Literature

The prevalence of chronic kidney disease (CKD) is increasing worldwide, and the mortality rate continues to be unacceptably high. The biomarkers currently used in clinical practice are considered relevant when there is already significant renal impairment compromising the early use of potentially successful therapeutic interventions. More sensitive and specific biomarkers to detect CKD earlier on and improve patients' prognoses are an important unmet medical need. The aim of this review is to summarize the recent literature on new promising early CKD biomarkers of renal function, tubular lesions, endothelial dysfunction and inflammation, and on the auspicious findings from metabolomic studies in this field. Most of the studied biomarkers require further validation in large studies and in a broad range of populations in order to be implemented into routine CKD management. A panel of biomarkers, including earlier biomarkers of renal damage, seems to be a reasonable approach to be applied in clinical practice to allow earlier diagnosis and better disease characterization based on the underlying etiologic process.

Exploring blood alterations in chronic kidney disease and haemodialysis using metabolomics

Chronic kidney disease (CKD) is characterized by retention of uremic solutes. Compared to patients with non-dialysis dependent CKD, those requiring haemodialysis (HD) have increased morbidity and mortality. We wished to characterise metabolic patterns in CKD compared to HD patients using metabolomics. Prevalent non-HD CKD KDIGO stage 3b-4 and stage 5 HD outpatients were screened at a single tertiary hospital. Various liquid chromatography approaches hyphenated with mass spectrometry were used to identify 278 metabolites. Unsupervised and supervised data analyses were conducted to characterize metabolic patterns. 69 patients were included in the CKD group and 35 in the HD group. Unsupervised data analysis showed clear clustering of CKD, pre-dialysis (preHD) and post-dialysis (postHD) patients. Supervised data analysis revealed qualitative as well as quantitative differences in individual metabolites profiles between CKD, preHD and postHD states. An original metabolomics framework could discriminate between CKD stages and highlight HD effect based on 278 identified metabolites. Significant differences in metabolic patterns between CKD and HD patients were found overall as well as for specific metabolites. Those findings could explain clinical discrepancies between patients requiring HD and those with earlier stage of CKD.

Identification of biomarkers for early diagnosis of diabetic nephropathy disease using direct flow through mass spectrometry

BACKGROUND AND AIMS

Albuminuria is not an effective marker for early diagnosis of diabetic renal complication with several subjects progressing to chronic kidney disease without any albuminuria. A biomarker that can predict early changes of the diabetic kidney will be useful in effective management of type 2 diabetes. Mass spectrometry based metabolomics approach offers tremendous promise for the identification of novel metabolite biomarkers.

METHODS

A case-control approach was carried out to identify renal biomarkers among Asian Indian subjects in a hospital setting. A total of 29 subjects were included in the study that included groups of diabetic controls, diabetic subjects with eGFR >90 ml/min/1.72 m² and diabetic subjects with eGFR between 60 and 89 ml/min/1.72 m² and eGFR between 15 and 30 ml/min/1.72 m². We employed an un-targeted mass spectrometry method for the identification of plasma metabolites.

RESULTS

A total of 1414 and 975 metabolites were identified in the positive and negative ion mode respectively. 19 metabolites were up regulated and 18 metabolites were down regulated in CKD2 and CKD4 groups when compared to control. Correlation analysis of the differential metabolites revealed Pregnenolone sulfate, creatinine and ganglioside GA1 to be negatively correlated and hexyl glucoside, all-trans-carophyll yellow and PG to be positively correlated with eGFR.

CONCLUSION

We have identified Pregnenolone sulfate, GA1, PG and all-trans-Carophyll yellow as biomarkers for early identification of diabetic nephropathy. These markers could aid in better management of diabetic nephropathy that may result delaying the progression of the disease.

How do Uremic Toxins Affect the Endothelium?

Uremic toxins can induce endothelial dysfunction in patients with chronic kidney disease (CKD). Indeed, the structure of the endothelial monolayer is damaged in CKD, and studies have shown that the uremic toxins contribute to the loss of cell–cell junctions, increasing permeability. Membrane proteins, such as transporters and receptors, can mediate the interaction between uremic toxins and endothelial cells. In these cells, uremic toxins induce oxidative stress and activation of signaling pathways, including the aryl hydrocarbon receptor (AhR), nuclear factor kappa B (NF-κB), and mitogen-activated protein kinase (MAPK) pathways. The activation of these pathways leads to overexpression of proinflammatory (e.g., monocyte chemoattractant protein-1, E-selectin) and prothrombotic (e.g., tissue factor) proteins. Uremic toxins also induce the formation of endothelial microparticles (EMPs), which can lead to the activation and dysfunction of other cells, and modulate the expression of microRNAs that have an important role in the regulation of cellular processes. The resulting endothelial dysfunction contributes to the pathogenesis of cardiovascular diseases, such as atherosclerosis and thrombotic events. Therefore, uremic toxins as well as the pathways they modulated may be potential targets for therapies in order to improve treatment for patients with CKD.

Metabolic profiling for water-soluble metabolites in patients with schizophrenia and healthy controls in a Chinese population: A case-control study

Objectives: Objective measures integrated with clinical symptoms may improve early prevention and detection of schizophrenia. Herein we aim to evaluate potential water-soluble metabolic biomarkers in schizophrenia.Methods: We recruited adults with schizophrenia (n = 113) who had not received pharmacological treatment for at least 1 month prior to enrollment and 111 age- and sex-matched healthy subjects from Weifang, Shandong province, China. All serum samples were analysed using liquid chromatography-tandem mass spectrometry coupled with a hydrophilic interaction liquid chromatography column.Results: Eleven metabolites, namely carnitines (oleoylcarnitine, l-palmitoylcarnitine, 9-decenoylcarnitine and 2-trans,4-cis-decadienoylcarnitine), polar lipids (lysophosphatidylcholine (LPC)(P-16:0), LPC (16:0), LPC (15:0) and LPC(14:0)), amino acids (taurine and l-arginine), and organic acid (2,5-dichloro-4-oxohex-2-enedioate), separated the patients and healthy controls. Compared with healthy controls, taurine, l-palmitoylcarnitine and oleoylcarnitine levels were higher, whereas the remaining eight metabolites were lower in patients with schizophrenia. A combination of four metabolites, i.e., oleoylcarnitine, 9-decenoylcarnitine, LPC (15:0) and LPC (14:0), provided the most robust between-group separation.Conclusions: This study appears to distinguish between groups of patients and controls, which should be considered as a contribution to putative potential biomarkers. The water-soluble metabolites were determined to be significantly different between the groups in the current study, and were primarily related to cellular bioenergetics, notably oxidative stress.

Chronic kidney disease: Biomarker diagnosis to therapeutic targets

Chronic kidney disease (CKD), characterized as renal dysfunction, is recognized as a major public health problem with high morbidity and mortality worldwide. Unfortunately, there are no obvious clinical symptoms in early stage disease until severe damage has occurred. Further complicating early diagnosis and treatment is the lack of sensitive and specific biomarkers. As such, novel biomarkers are urgently needed. Metabolomics has shown an increasing potential for identifying underlying disease mechanisms, facilitating clinical diagnosis and developing pharmaceutical treatments for CKD. Recent advances in metabolomics revealed that CKD was closely associated with the dysregulation of numerous metabolites, such as amino acids, lipids, nucleotides and glycoses, that might be exploited as potential biomarkers. In this review, we summarize recent metabolomic applications based on animal model studies and in patients with CKD and highlight several biomarkers that may play important roles in diagnosis, intervention and development of new therapeutic strategies.

An update of urine and blood metabolomics in chronic kidney disease

Chronic kidney disease is considered as a serious obstacle in global health, with increasing incidence and prevalence. In spite of numerous attempts by using recent omics technologies, specially metabolomics, for understanding pathophysiology, molecular mechanism and identification reliable consensus biomarkers for diagnosis and prognosis of this complex disease, the current biomarkers are still insensitive and many questions about its pathomechanism are still to be unanswered. This review is focused on recent findings about urine and serum/plasma metabolite biomarkers and changes in the pathways that occurs in the disease conditions. The urine and blood metabolome content in the normal and disease state is investigated based on the current metabolomics studies and well known metabolite candidate biomarkers for chronic kidney disease are discussed.

Toward a better understanding of chronic kidney disease with complementary chromatographic methods hyphenated with mass spectrometry for improved polar metabolome coverage

The prevalence of chronic kidney disease (CKD) is increasing worldwide. New technical approaches are needed to improve early diagnosis, disease understanding and patient monitoring, and to evaluate new therapies. Metabolomics, as a prime candidate in the field of CKD research, aims to comprehensively analyze the metabolic complexity of biological systems. An extensive analysis of the metabolites contained in biofluids is therefore needed, and the combination of data obtained from multiple analytical platforms constitutes a promising methodological approach. This study presents an original workflow based on complementary chromatographic conditions, reversed-phase and hydrophilic interaction chromatography hyphenated to mass spectrometry to improve the polar metabolome coverage coupled with a univocal metabolite annotation strategy enabling a rapid access to the biological interpretation. This multiplatform workflow was applied in a CKD cohort study to assess plasma metabolic profile modifications related to renal disease. Multivariate analysis of 278 endogenous annotated metabolites enabled patient stratification with respect to CKD stages and helped to generate new biological insights, while also confirming the relevance of tryptophan metabolism pathway in this condition.

Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage

Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.

Neutral Loss Scan - Based Strategy for Integrated Identification of Amorfrutin Derivatives, New Peroxisome Proliferator-Activated Receptor Gamma Agonists, from Amorpha Fruticosa by UPLC-QqQ-MS/MS and UPLC-Q-TOF-MS

Amorfrutins with a 2-hydroxybenzoic acid core structure are promising natural PPARγ agonists with potent antidiabetic activity. Owing to the complex matrix and low concentration in botanical material, the identification of unknown amorfrutins remains a challenge. In the present study, a combined application of UPLC-Q-TOF-MS and UPLC-QqQ-MS was developed to discover unknown amorfrutins from fruits of Amorpha fruticosa. First, reference compounds of amorfrutin A (AA), amorfrutin B (AB), and 2-carboxy-3,5-dihydroxy-4-geranylbibenzyl (AC) were analyzed using UPLC-Q-TOF-MS to reveal the characteristic fragment ions and the possible neutral loss. Second, the extract of A. fruticosa was separated and screened by UPLC-QqQ-MS using neutral loss scan to find out suspect compounds associated with the specified neutral fragment Δm/z 44. Third, the extract was re-analyzed by UPLC-Q-TOF-MS to obtain the exact mass of quasi-molecular ion and fragment ions of each suspect compound, and to subsequently calculate their corresponding molecular formulas. Finally, according to the molecular formula of suspect compound and its fragment ions and comparing with literature data, structure elucidation of four unidentified amorfrutins was achieved. The results indicated that the combination of QqQ-MS neutral loss scan and Q-TOF-MS molecular formula calculation was proven to be a powerful tool for unknown natural product identification, and this strategy provides an effective solution to discover natural products or metabolites of trace content. Graphical Abstract ᅟ.

Targeting human urinary metabolome by LC-MS/MS: a review

Urine is a biological matrix that contains hundreds of metabolic end products which constitute the urinary metabolome. The development and advances on LC-MS/MS have revolutionized the analytical study of biomolecules by enabling their accurate identification and quantification in an unprecedented manner. Nowadays, LC-MS/MS is helping to unveil the complexity of urine metabolome, and the results obtained have multiple biomedical applications. This review focuses on the targeted LC-MS/MS analysis of the urine metabolome. In the first part, we describe general considerations (from sample collection to quantitation) required for a proper targeted metabolic analysis. In the second part, we address the urinary analysis and recent applications of four relevant families: amino acids, catecholamines, lipids and steroids.

Identification of serum metabolites associated with obesity and traditional risk factors for metabolic disease in Chinese adults

BACKGROUND AND AIMS

Obesity is a major worldwide health problem and is often associated with many metabolic diseases. Levels of several serum-specific metabolites may be altered in patients with these metabolic diseases. We aimed to investigate the associations of serum metabolite levels with obesity and traditional risk factors for metabolic disease in Chinese individuals.

METHODS AND RESULTS

Six-hundred Chinese individuals undergoing annual physical exams were recruited and categorized into overweight/obese and control groups (1:1 ratio). We simultaneously quantified the serum lysophosphatidylcholine (LPC), branched-chain amino acids (BCAA), aromatic amino acids (AAA), 25-hydroxyvitamin D, glutamine (Gln), glutamic acid (Glu), and Gln/Glu ratio levels using our previously established targeted serum metabolomic method. The overweight/obesity group had significantly higher levels of BCAA, AAA, and Glu, as well as lower levels of unsaturated LPC, Gln, and Gln/Glu, than the control group. Correlation analyses revealed significant and positive relationships of saturated LPC, BCAA, AAA, and Glu with blood pressure, glucose, triglycerides, apolipoprotein B, and high-sensitivity C-reactive protein, while unsaturated LPC, Gln, Gln/Glu, and 25-hydroxyvitamin D exhibited an opposite trend. In the multifactor logistic regression model, low unsaturated LPC and Gln/Glu, as well as high BCAA and AAA levels, were found to be independent risk factors for obesity; the odds ratios (95% confidence interval) of the highest quartile compared to the lowest quartile were 0.241 (0.139-0.417), 0.436 (0.252-0.755), 3.944 (2.094-7.430), and 2.357 (1.274-4.361) (P < 0.01), respectively.

CONCLUSION

LPC, BCAA, AAA, and Gln/Glu are significantly related to obesity development and risk factors of some metabolic diseases.

Biochemical and Clinical Impact of Organic Uremic Retention Solutes: A Comprehensive Update

In this narrative review, the biological/biochemical impact (toxicity) of a large array of known individual uremic retention solutes and groups of solutes is summarized. We classified these compounds along their physico-chemical characteristics as small water-soluble compounds or groups, protein bound compounds and middle molecules. All but one solute (glomerulopressin) affected at least one mechanism with the potential to contribute to the uremic syndrome. In general, several mechanisms were influenced for each individual solute or group of solutes, with some impacting up to 7 different biological systems of the 11 considered. The inflammatory, cardio-vascular and fibrogenic systems were those most frequently affected and they are one by one major actors in the high morbidity and mortality of CKD but also the mechanisms that have most frequently been studied. A scoring system was built with the intention to classify the reviewed compounds according to the experimental evidence of their toxicity (number of systems affected) and overall experimental and clinical evidence. Among the highest globally scoring solutes were 3 small water-soluble compounds [asymmetric dimethylarginine (ADMA); trimethylamine-N-oxide (TMAO); uric acid], 6 protein bound compounds or groups of protein bound compounds [advanced glycation end products (AGEs); p-cresyl sulfate; indoxyl sulfate; indole acetic acid; the kynurenines; phenyl acetic acid;] and 3 middle molecules [β₂-microglobulin; ghrelin; parathyroid hormone). In general, more experimental data were provided for the protein bound molecules but for almost half of them clinical evidence was missing in spite of robust experimental data. The picture emanating is one of a complex disorder, where multiple factors contribute to a multisystem complication profile, so that it seems of not much use to pursue a decrease of concentration of a single compound.

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.

Simultaneous quantitative analysis of uremic toxins by LC-MS/MS with a reversed-phase/cation-exchange/anion-exchange tri-modal mixed-mode column

Column choice is crucial to the development of liquid chromatography/tandem mass spectrometry (LC-MS/MS) methods because analyte selectivity is dependent on the nature of the stationary phase. Recently, mixed-mode chromatography, which employs a combination of two or more stationary phases and solvent systems, has emerged as an alternative to multiple, complementary, single-column systems. This report describes the development and validation of a novel analytical method based on LC-MS/MS employing a reversed-phase/cation-exchange/anion-exchange tri-modal column (Scherzo SS-C18; Imtakt) for the simultaneous quantification of various uremic toxins (UTx), including creatinine, 1-methyladenosine, trimethylamine-N-oxide, indoxyl sulfate, p-cresyl sulfate, phenyl sulfate and 4-ethylphenyl sulfate. Stable isotope-labeled compounds were prepared as internal standards (ISs) for each analyte. Mobile phase optimization and appropriate gradient conditions resulted in satisfactory retention and peak resolution that could not have been attained with a single stationary phase LC system. The essential validation parameters, including intra- and inter-assay precision and accuracy, were adequate. The validated method was applied to measure serum levels of the aforementioned compounds in 19 patients with chronic kidney disease. This is the first report detailing the simultaneous quantification of these analytes using stable isotopes as ISs. Our results suggest that Scherzo SS-C18 columns will be considered breakthrough tools in the development of analytical methods for compounds that are difficult to quantify simultaneously in traditional LC systems.

Elucidating the Structure of N1-Acetylisoputreanine: A Novel Polyamine Catabolite in Human Urine

An untargeted metabolomics approach was utilized to determine urinary metabolites that could serve as small-molecule biomarkers for treatment response to standard tuberculosis treatment. However, the majority of metabolites that most accurately distinguished patient samples at the time of diagnosis from those at 1 month after the start of therapy lacked structural identification. The detection of unknown metabolite structures is a well-known limitation of untargeted metabolomics and underscores a need for continued elucidation of novel metabolite structures. In this study, we sought to define the structure of a urine metabolite with an experimentally determined mass of 202.1326 Da, classified as molecular feature (MF) 202.1326. A hypothesized structure of N¹-acetylisoputreanine was developed for MF 202.1326 using in silico tools and liquid chromatography-tandem mass spectrometry (LC-MS/MS). In the absence of a commercial standard, synthetic N¹-acetylisoputreanine was generated using enzymatic and chemical syntheses, and LC-MS/MS was used to confirm the structure of MF 202.1326 as N¹-acetylisoputreanine, a proposed terminal polyamine catabolite that had not been previously detected in biological samples. Further analysis demonstrated that N¹-acetylisoputreanine and an alternative form of this metabolite, N¹-acetylisoputreanine-γ-lactam, are both present in human urine and are likely end-products of polyamine metabolism.