Urinary Metabolomic Analysis Research Articles

Nontargeted urine metabolomic analysis of acute intermittent porphyria reveals novel interactions between bile acids and heme metabolism: New promising biomarkers for the long-term management of patients.

Acute intermittent porphyria is an inherited error of heme synthesis. The underlying pathophysiology, involving mainly hepatic heme synthesis, is poorly understood despite its occurrence, and the severity of acute porphyria attack is still difficult to control. A better understanding of the interactions between heme synthesis and global metabolism would improve the management of AIP patients. An untargeted metabolomic analysis was performed on the urine of 114 patients with overt AIP and asymptomatic carriers using liquid chromatography coupled to high-resolution mass spectrometry. The collected data were analyzed by combining univariate and multivariate analyses. A total of 239 metabolites were annotated in urine samples by matching chromatographic and mass spectral characteristics with those from our chemical library. Twenty-six metabolites, including porphyrin precursors, intermediates of tryptophan or glycine metabolism and, unexpectedly, bile acids, showed significant concentration differences between the phenotypic groups. Dysregulation of bile acid metabolism was confirmed by targeted quantitative analysis, which revealed an imbalance in favor of hydrophobic bile acids associated with changes in conjugation, which was more pronounced in the severe phenotype. Using a random forest model, the cholic acid/chenodeoxycholic acid ratio enables the differential classification of severe patients from other patients with a diagnostic accuracy of 84%. The analysis of urine samples revealed significant modifications in the metabolome of AIP patients. Alteration in bile acids provides new insights into the pathophysiology of chronic complications, such as primary liver cancer, while also providing new biomarker candidates for predicting the most severe phenotypes.

Integrated metabolomics and gut microbiota analysis to explore potential mechanism of Qi-Huo-Yi-Fei formula against chronic obstructive pulmonary disease

Metabolic disorders and gut microbiota dysbiosis contribute to the complicated pathology of chronic obstructive pulmonary disease (COPD). Qi-Huo-Yi-Fei formula (QHYFF) is a Chinese medicine prescription for COPD treatment and has showed beneficial clinical effects, but the underlying mechanism remains elusive. This study integrated metabolomics and gut microbiota analysis to explore potential mechanism of QHYFF against COPD. The therapeutic effects of QHYFF were evaluated using a murine model of COPD induced by cigarette smoke and lipopolysaccharide. QHYFF effectively improved pulmonary function, suppressed inflammation, and relieved lung pathological changes. Serum and urine metabolomics analysis identified 19 differential metabolites, such as L-tyrosine, epinephrine, dopamine, hypotaurine, citric acid, L-tryptophan and indoleacrylic acid, involving tyrosine metabolism, taurine and hypotaurine metabolism, citrate cycle and tryptophan metabolism. QHYFF also enriched Bifidobacterium, Blautia, Faecalibaculum and Parasutterella. Moreover, Spearman’s correlation analysis showed that discriminative metabolites and bacteria were closely correlated with efficacy indices. The findings indicated that QHYFF could be an effective therapeutic measure against COPD by regulating metabolism and gut microbiota.

Revealing the links between hair metal(loids) and alterations in blood pressure among children in e-waste recycling areas through urinary metabolomics

Hypertension is prevalent in e-waste recycling areas, and elevated blood pressure in children significantly increases the risk of hypertension in adulthood. However, the associations and toxic pathways between chronic exposure to metal(loids) and elevated blood pressure are rarely investigated. In this study, we measured the levels of 29 hair metal(loids) (chronic exposure biomarkers) and blood pressure in 667 susceptible children from an e-waste recycling area to explore their relationships. Paired urine metabolomics analysis was also performed to interpret potential mechanistic pathways. Results showed that the hypertension prevalence in our recruited children (13.0 %) exceeded the average rate (9.5 %) for Chinese children aged 6–17 years. The top five abundant metal(loids), including lead, strontium, barium, and zinc, demonstrated the most profound associations with elevated systolic blood pressure. Quantile g-computation, weighted quantile sum, and Bayesian kernel machine regression analysis jointly demonstrated a significant association between chronic exposure to metal(loids) mixture and systolic blood pressure. Interestingly, selenium showed significant antagonistic interactions with these four metals, suggesting that supplementing selenium may help children resist the elevated blood pressure induced by metal(loids) exposure. Increased metal(loids) and blood pressure levels were significantly linked to changes in urine metabolomics. Structural equation model indicated that androsterone glucuronide and N-Acetyl-1-aspartylglutamic acid were the significant mediators of the associations between metal(loids) and blood pressure, with mediation effects of 77.4 % and 29.0 %, respectively, suggesting that androsterone glucuronide and N-Acetyl-1-aspartylglutamic acid may be involved in the development of metal-induced blood pressure elevating effect. Girls were more vulnerable to metal(loids)-induced hormonal imbalance, especially androsterone glucuronide, than boys. Chronic exposure to metal(loids) at e-waste recycling sites may contribute to elevated blood pressure in children through disrupting various metabolism pathways, particularly hormonal balance. Our study provides new insights into potential mechanistic pathways of metal(loids)-induced changes in children's blood pressure.

Characterization of squash polysaccharide and the anti-diabetic effect on type 2 diabetic rat revealed by urine metabolomics analysis

The present study reports the structural characteristics of 3 polysaccharide fractions (SPS-F1, SPS-F2 and SPS-F3) isolated and purified from squash. SPS-F1 (molecular weight (Mw) = 12.30 kDa) and SPS-F2 (Mw = 19.40 kDa) were likely to contain HG and RG-I domain of pectic polysaccharide, respectively. SPS-F2 (Mw = 270.4 kDa) was mainly composed of rhamnose, galactose and arabinose. The treatment with SPS decreased body weight gain, glucose and TG levels in type 2 diabetes rats. Besides, 25 differential metabolites were identified based on urinary metabolomics analysis, which are crucial to the anti-diabetic effect of SPS. The regulation of nicotinamide N-oxide, histamine, cis-aconitate, citrate, L-malic acid, 3-(3-hydroxyphenyl) propanoic acid and N-acetyl-L-aspartic acid were mainly associated with energy metabolism, gut microbiota and inflammation. Study of surface plasmon resonance revealed the binding kinetics with galectin-3 (Gal-3) and fibroblast growth factor 2 (FGF2). The KD values of SPS-F2 and SPS-F3 to Gal-3 were 4.97 × 10-3 and 1.48 × 10-3 mol/L, indicating a weak binding affinity. All 3 fractions showed moderate binding to FGF2 and the affinity was SPS-F3 > SPS-F2 > SPS-F1. Thus, the metabolomics and SPR approach were proved to be a promising tool in exploring the anti-diabetes effects of SPS and provided a deep understanding of the mechanisms.

Untargeted Metabolomic Analyses of Body Fluids to Differentiate TBI DOC and NTBI DOC.

To investigate the metabolomic differences between Traumatic brain injury (TBI) disorder of consciousness (DOC) patients and non-traumatic brain injury (NTBI) DOC patients by using cerebrospinal fluid (CSF), serum and urine samples beneficial to understand the pathological mechanism differences between the two etiologies, provide potential clues for the subsequent treatment and prognosis, and investigate the metabolome differences and similarities between TBI and NTBI among three different body fluids. In total, 24 TBI DOC subjects and 29 NTBI DOC subjects were enrolled. CSF, serum and urine samples from TBI DOC and NTBI DOC patients were collected and analyzed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarkers and altered metabolic functions. When comparing TBI DOC and NTBI DOC, 36, 31 and 52 differential metabolites were obtained in CSF, serum and urine, respectively. The functional analysis of differential metabolites obtained in CSF, serum and urine were all related to amino acid metabolism. Except for amino acid metabolism, metabolic biomarkers in CSF, serum and urine mainly focus on central function, cognitive function, necrosis and apoptosis and neurological function, respectively. In CSF, the highest AUC was 0.864 (Isoproturon) and 0.816 (Proline betaine). Then, the AUC of NFurfurylformamide in serum was 0.941, while the AUC of Dihydronepetalactone and Doxepin N-oxide glucuronide were 1.0 in urine. CSF, serum and urine metabolomic analyses could differentiate TBI DOC from NTBI DOC and functional analyses showed a metabolic change difference between TBI DOC and NTBI DOC.

Metabolomic Analysis Reveals the Association of Severe Bronchopulmonary Dysplasia with Gut Microbiota and Oxidative Response in Extremely Preterm Infants.

Bronchopulmonary dysplasia (BPD) is a chronic lung disease mainly affecting premature infants needing ventilation or oxygen for respiratory distress. This study aimed to evaluate the molecular linkages for BPD in very and extremely preterm infants using a metabolomics-based approach. A case-control study of enrolling preterm infants born before 32 weeks gestational age (GA) was prospectively performed. These preterm infants were subsequently stratified into the following two groups for further analysis: no or mild BPD, and moderate or severe BPD based on the 2019 NICHD criteria. Urinary metabolomic profiling was performed using 1H-Nuclear magnetic resonance (NMR) spectroscopy coupled with partial least squares discriminant analysis (PLS-DA) at a corrected age of 6 months. Metabolites significantly differentially related to GA and BPD severity were performed between groups, and their roles in functional metabolic pathways were also assessed. A total of 89 preterm infants born before 32 weeks gestation and 50 infants born at term age (above 37 completed weeks' gestation) served as controls and were enrolled into the study. There were 21 and 24 urinary metabolites identified to be significantly associated with GA and BPD severity, respectively (p < 0.05). Among them, N-phenylacetylglycine, hippurate, acetylsalicylate, gluconate, and indoxyl sulfate were five metabolites that were significantly higher, with the highest importance in both infants with GA < 28 weeks and those with moderate to severe BPD, whereas betaine and N,N-dimethylglycine were significantly lower (p < 0.05). Furthermore, ribose and a gluconate related pentose phosphate pathway were strongly associated with these infants (p < 0.01). In conclusion, urinary metabolomic analysis highlights the crucial role of gut microbiota dysbiosis in the pathogenesis of BPD in preterm infants, accompanied by metabolites related to diminished antioxidative capacity, prompting an aggressive antioxidation response in extremely preterm infants with severe BPD.

Unraveling Metabolic Changes following Stroke: Insights from a Urinary Metabolomics Analysis.

The neuropathological sequelae of stroke and subsequent recovery are incompletely understood. Here, we investigated the metabolic dynamics following stroke to advance the understanding of the pathophysiological mechanisms orchestrating stroke recovery. Using a nuclear magnetic resonance (NMR)-driven metabolomic profiling approach for urine samples obtained from a clinical group, the objective of this research was to (1) identify novel biomarkers indicative of severity and recovery following stroke, and (2) uncover the biochemical pathways underlying repair and functional recovery after stroke. Urine samples and clinical stroke assessments were collected during the acute (2-11 days) and chronic phases (6 months) of stroke. Using a 700 MHz 1H NMR spectrometer, metabolomic profiles were acquired followed by a combination of univariate and multivariate statistical analyses, along with biological pathway analysis and clinical correlations. The results revealed changes in phenylalanine, tyrosine, tryptophan, purine, and glycerophospholipid biosynthesis and metabolism during stroke recovery. Pseudouridine was associated with a change in post-stroke motor recovery. Thus, NMR-based metabolomics is able to provide novel insights into post-stroke cellular functions and establish a foundational framework for future investigations to develop targeted therapeutic interventions, advance stroke diagnosis and management, and enhance overall quality of life for individuals with stroke.

Urine and serum metabolomic analysis of endometrial cancer diagnosis and classification based on ultra-performance liquid chromatography mass spectrometry.

This study aimed to reveal the urinary and serum metabolic pattern of endometrial cancer (EC) and establish diagnostic models to identify EC from controls, high-risk from low-risk EC, and type II from type I EC. This study included 146 EC patients (comprising 79 low-risk and 67 high-risk patients, including 124 type I and 22 type II) and 59 controls. The serum and urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry. Analysis was used to elucidate the distinct metabolites and altered metabolic pathways. Receiver operating characteristic (ROC) analyses were employed to discover and validate the potential biomarker models. Serum and urine metabolomes displayed significant differences between EC and controls, with metabolites related to amino acid and nicotinamide metabolisms. The serum and urine panels distinguished these two groups with Area Under the Curve (AUC) of 0.821 and 0.902, respectively. The panel consisting of serum and urine metabolites demonstrated the best predictive ability (AUC = 0.953 and 0.976 in discovering and validation group). In comparing high-risk and low risk EC, differential metabolites were enriched in purine and glutamine metabolism. The AUC values for serum and urine panels were 0.818, and 0.843, respectively. The combined panel exhibited better predictive accuracy (0.881 in discovering group and 0.936 in external validation). In the comparison between type I and type II group, altered folic acid metabolism was identified. The serum, urine and combined panels discriminated these two groups with the AUC of 0.829, 0.913 and 0.922, respectively. The combined urine and serum metabolome effectively revealed the metabolic patterns in EC patients, offering valuable diagnostic models for EC diagnosis and classification.

Plasma and Urinary Metabolomic Analysis of Gout and Asymptomatic Hyperuricemia and Profiling of Potential Biomarkers: A Pilot Study.

Gout results from monosodium urate deposition caused by hyperuricemia, but most individuals with hyperuricemia remain asymptomatic. The pathogenesis of gout remains uncertain. To identify potential biomarkers distinguishing gout from asymptomatic hyperuricemia, we conducted a genetic analysis of urate transporters and metabolomic analysis as a proof-of-concept study, including 33 patients with gout and 9 individuals with asymptomatic hyperuricemia. The variant allele frequencies of rs72552713, rs2231142, and rs3733591, which are related to serum urate levels (SUA) and gout, did not differ between the gout and asymptomatic hyperuricemia groups. In metabolomic analysis, the levels of citrate cycle intermediates, especially 2-ketoglutarate, were higher in patients with gout than in those with asymptomatic hyperuricemia (fold difference = 1.415, p = 0.039). The impact on the TCA cycle was further emphasized in high-risk gout (SUA ≥ 9.0 mg/dL). Of note, urinary nicotinate was the most prominent biomarker differentiating high-risk gout from asymptomatic hyperuricemia (fold difference = 6.515, p = 0.020). Although urate transporters play critical roles in SUA elevation and promote hyperuricemia, this study suggests that the progression from asymptomatic hyperuricemia to gout might be closely related to other genetic and/or environmental factors affecting carbohydrate metabolism and urinary urate excretion.

Clinical Efficacy and Metabolomics Modifications Induced by Polyphenol Compound Supplementation in the Treatment of Residual Dizziness following Semont Maneuver in Benign Paroxysmal Positional Vertigo (BPPV) of the Posterior Semicircular Canal (PSC): Preliminary Results.

Benign paroxysmal positional vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases, it is successfully treated using the canalith repositioning procedure, but it is often followed by continuous lightheadedness in the absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile of treating these patients with polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV of the posterior semicircular canal (PSC) successfully treated using the Semont maneuver. Supplementation with a polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment using self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and urine metabolomics analysis performed using 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported excellent or good efficacy in the treatment of RD with a significant decrease in VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment, namely 1-methylnicotinamide, anserine, hippurate, lysine, methyl succinate and urea, indicating the inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound could induce some metabolic changes that can help in recovery from RD. However, future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomics evaluation to other problems concerning the different clinical aspects of BPPV, such as the high rate of relapse.

Metabolomics analysis of serum and urine in type 1 diabetes patients with different time in range derived from continuous glucose monitoring

BackgroundTime in range (TIR), as an important glycemic variability (GV) index, is clearly associated with disease complications in type 1 diabetes (T1D). Metabolic dysregulation is also involved in the risks of T1D complications. However, the relationship between metabolites and TIR remains poorly understood. We used metabolomics to investigate metabolic profile changes in T1D patients with different TIR.MethodsThis study included 85 T1D patients and 81 healthy controls. GV indices, including TIR, were collected from continuous glucose monitoring system. The patients were compared within two subgroups: TIR-L (TIR < 50%, n = 21) and TIR-H (TIR > 70%, n = 14). To screen for differentially abundant metabolites and metabolic pathways, serum and urine samples were obtained for untargeted metabolomics by ultra-performance liquid chromatography‒mass spectrometry. Correlation analysis was conducted with GV metrics and screened biomarkers.ResultsMetabolites were significantly altered in T1D and subgroups. Compared with healthy controls, T1D patients had higher serum levels of 5-hydroxy-L-tryptophan, 5-methoxyindoleacetate, 4-(2-aminophenyl)-2,4-dioxobutanoate, and 4-pyridoxic acid and higher urine levels of thromboxane B3 but lower urine levels of hypoxanthine. Compared with TIR-H group, The TIR-L subgroup had lower serum levels of 5-hydroxy-L-tryptophan and mevalonolactone and lower urine levels of thromboxane B3 and phenylbutyrylglutamine. Dysregulation of pathways, such as tryptophan, vitamin B6 and purine metabolism, may be involved in the mechanism of diabetic complications related to glycemic homeostasis. Mevalonolactone, hypoxanthine and phenylbutyrylglutamine showed close correlation with TIR.ConclusionsWe identified altered metabolic profiles in T1D individuals with different TIR. These findings provide new insights and merit further exploration of the underlying molecular pathways relating to diabetic complications.

A comparative urinary proteomic and metabolomic analysis between renal aa amyloidosis and membranous nephropathy with clinicopathologic correlations

Urinary omics has become a powerful tool for elucidating pathophysiology of glomerular diseases. However, no urinary omics analysis has been performed yet on renal AA amyloidosis. Here, we performed a comparative urine proteomic and metabolomic analysis between recently diagnosed renal AA amyloidosis (AA) and membranous nephropathy (MN) patients. Urine samples of 22 (8 AA, 8 MN and 6 healthy control) patients were analyzed with nLC-MS/MS and GC/MS for proteomic and metabolomic studies, respectively. Pathological specimens were scored for glomerulosclerosis and tubulointerstitial fibrosis grades. Functional enrichment analysis between AA and control groups showed enrichment in cell adhesion related sub-domains. Uromodulin (UMOD) was lower, whereas ribonuclease 1 (RNase1) and α-1-microglobulin/bikunin precursor (AMBP) were higher in AA compared to MN group. Correlations were demonstrated between UMOD-proteinuria (r = −0.48, p = 0.03) and AMBP-eGFR (r = −0.69, p = 0.003) variables. Metabolomic analysis showed myo-inositol and urate were higher in AA compared to MN group. A positive correlation was detected between RNase1 and urate independent of eGFR values (r = 0.63, p = 0.01). Enrichment in cell adhesion related domains suggested a possible increased urinary shear stress due to amyloid fibrils. UMOD, AMBP and myo-inositol were related with tubulointerstitial damage, whereas RNase1 and urate were believed to be related with systemic inflammation in AA amyloidosis. SignificanceUrinary omics studies have become a standard tool for biomarker studies. However, no urinary omics analysis has been performed yet on renal AA amyloidosis. Here, we performed a comparative urinary omics analysis between recently diagnosed renal AA amyloidosis (AA), membranous nephropathy (MN) patients and healthy controls. Pathological specimens were scored with glomerulosclerosis (G) and tubulointerstitial fibrosis (IF) grades to consolidate the results of the omics studies and correlation analyzes. Functional enrichment analysis showed enrichment in cell adhesion related sub-domains due to downregulation of cadherins; which could be related with increased urinary shear stress due to amyloid deposition and disruption of tissue micro-architecture. In comparative proteomic analyzes UMOD was lower, whereas RNase1 and AMBP were higher in AA compared to MN group. Whereas in metabolomic analyzes; myo-inositol, urate and maltose were higher in AA compared to MN group. Correlations were demonstrated between UMOD-proteinuria (r = −0.48, p = 0.03), AMBP-eGFR (r = −0.69, p = 0.003) and between RNase1-Urate independent of eGFR values (r = 0.63, p = 0.01). This study is the first comprehensive urinary omics analysis focusing on renal AA Amyloidosis to the best of our knowledge. Based on physiologic roles and clinicopathologic correlations of the molecules; UMOD, AMBP and myo-inositol were related with tubulointerstitial damage, whereas RNase1 and urate were believed to be increased with systemic inflammation and endothelial damage in AA amyloidosis.

Delineating endogenous Cushing’s syndrome by GC-MS urinary steroid metabotyping

BackgroundDiagnosing Cushing’s syndrome (CS) is highly complex. As the diagnostic potential of urinary steroid metabolome analysis by gas chromatography-mass spectrometry (GC-MS) in combination with systems biology has not yet been fully exploited, we studied a large cohort of patients with CS. MethodsWe quantified daily urinary excretion rates of 36 steroid hormone metabolites. Applying cluster analysis, we investigated a control group and 168 patients: 44 with Cushing’s disease (CD) (70% female), 18 with unilateral cortisol-producing adrenal adenoma (83% female), 13 with primary bilateral macronodular adrenal hyperplasia (PBMAH) (77% female), and 93 ruled-out CS (73% female). FindingsCluster-Analysis delineated five urinary steroid metabotypes in CS. Metabotypes 1, 2 and 3 revealing average levels of cortisol and adrenal androgen metabolites included patients with exclusion of CS or and healthy controls. Metabotype 4 reflecting moderately elevated cortisol metabolites but decreased DHEA metabolites characterized the patients with unilateral adrenal CS and PBMAH. Metabotype 5 showing strong increases both in cortisol and DHEA metabolites, as well as overloaded enzymes of cortisol inactivation, was characteristic of CD patients. 11-oxygenated androgens were elevated in all patients with CS. The biomarkers THS, F, THF/THE, and (An + Et)/(11β-OH-An + 11β-OH-Et) correctly classified 97% of patients with CS and 95% of those without CS. An inverse relationship between 11-deoxygenated and 11-oxygenated androgens was typical for the ACTH independent (adrenal) forms of CS with an accuracy of 95%. InterpretationGC-MS based urinary steroid metabotyping allows excellent identification of patients with endogenous CS and differentiation of its subtypes. FundingThe study was funded by the Else-Kröner-Fresenius-Stiftung and the Eva-Luise-und-Horst-Köhler-Stiftung.

Cell and rat serum, urine and tissue metabolomics analysis elucidates the key pathway changes associated with chronic nephropathy and reveals the mechanism of action of rhein

BackgroundRhein can significantly delay the progression of chronic nephropathy. However, its mechanism of action has not been adequately elaborated, which hinders its extensive clinical application. In this work, the effects of rhein on models of TGF-β-induced NRK-49F cellular fibrosis and rat renal ischemia–reperfusion fibrosis were evaluated using metabolomics and western blotting.MethodsThe metabolic profiles of NRK-49F cells and rat urine, serum, and kidney tissues in the control, model, and rhein groups were investigated using UPLC-QTOF-MS. The levels of p-P65, p-IKK, p-AKT, p-P38, p-JNK and AP-1 in NRK-49F cells were measured using western blotting and immunofluorescence methods. Molecular docking and network pharmacology methods were employed to explore the relationship between the potential targets of rhein and key proteins in the NF-κB and MAPK signaling pathways.ResultsVarious potential metabolites, including sphingolipids, ceramides, phosphatidylcholine, and lysophosphatidylcholine,14-hydroxy-E4-neuroprostane E, and 5-HPETE, were present in the cell, tissue, urine, and serum samples; however, few metabolites matches exactly among the four type of biological samples. These differential metabolites can effectively differentiated between the control, model, and rhein groups. Pathway enrichment analysis of differential metabolites unveiled that sphingolipid metabolism, arachidonic acid metabolism, and glycerophospholipid metabolism were closely related to nephropathy. Phosphorylation levels of AKT, IKK, P65 and AP-1 in NRK-49F cells was reduced by rhein treatment. Network pharmacology and molecular docking showed that the potential targets of rhein might regulated the expression of MAPK and AKT in the NF-κB and MAPK signaling pathways.ConclusionIn brief, rhein might delays the progression of chronic nephropathy via the metabolic pathways, NF-κB and MAPKs signaling pathways, which provides the foundation for its development and clinical application.

Urine metabolomics analysis of patients recovered of the Omicron variant of COVID-19 using ultrahigh-performance liquid chromatography with high-resolution mass spectrometry

Urine metabolomics analysis of patients recovered of the Omicron variant of COVID-19 using ultrahigh-performance liquid chromatography with high-resolution mass spectrometry

LC-MS-based urine metabolomics analysis of chronic subdural hematoma for biomarker discovery.

Chronic subdural hematoma (CSDH) is one of the most common neurosurgical diseases with atypical manifestations. The aim of this study was to utilize urine metabolomics to explore potential biomarkers for the diagnosis and prognosis of CSDH. Seventy-seven healthy controls and ninety-two patients with CSDH were enrolled in our study. In total, 261 urine samples divided into the discovery group and validation group were analyzed by LC-MS. The statistical analysis and functional annotation were applied to discover potential biomarker panels and altered metabolic pathways. A total of 53 differential metabolites were identified in this study. And the urinary metabolic profiles showed apparent separation between patients and controls. Further functional annotation showed that the differential metabolites were associated with lipid metabolism, fatty acid metabolism, amino acid metabolism, biotin metabolism, steroid hormone biosynthesis, and pentose and glucuronate interconversions. Moreover, one panel of Capryloylglycine, cis-5-Octenoic acid, Ethisterone, and 5,6-DiHETE showed good predictive performance in the diagnosis of CSDH, with an AUC of 0.89 in discovery group and an AUC of 0.822 in validation group. Another five metabolites (Trilobinol, 3'-Hydroxyropivacaine, Ethisterone, Arginyl-Proline, 5-alpha-Dihydrotestosterone glucuronide) showed the levels of them returned to a healthy state after surgery, showing good possibility to monitor the recovery of CSDH patients. The findings of the study revealed urine metabolomic differences between CSDH and controls. The potentially diagnostic and prognostic biomarker panels of urine metabolites were established, and functional analysis demonstrated deeper metabolic disorders of CSDH, which might conduce to improve early diagnose of CSDH clinically.

Urinary Metabolomic Analysis of Prostate Cancer by UPLC-FTMS and UPLC-Ion Trap MSn.

Accumulative evidence suggests metabolic disorders correlate with prostate cancer. Metabolic profiling of urine allows the measurement of numerous metabolites simultaneously. This study set up a metabolomic platform consisting of UPLC-FTMS and UPLC-ion trap MSn for urine metabolome analysis. The platform improved retention time, mass accuracy, and signal stability. Additionally, the product ion spectrum obtained from ion trap MSn facilitated structure elucidation of candidate metabolites, especially when authentic standards were not available. Urine samples from six hernia patients and six BPH patients were used for the initial establishment of the analytic platform. This platform was further employed to analyze the urine samples of 27 PCa and 49 BPH patients. Choosing the upper and lower 16% of metabolites, 258 metabolite candidates were selected. Twenty-four of them with AUC values larger than 0.65 were further selected. Eighteen of the twenty-four features can be matched in METLIN and HMDB. Eleven of the eighteen features can be interpreted by MSn experiments. They were used for the combination achieving the best differential power. Finally, four metabolites were combined to reach the AUC value of 0.842 (CI 95, 0.7559 to 0.9279). This study demonstrates the urinary metabolomic analysis of prostate cancer and sheds light on future research.

Phenylketonuria (PKU) Urinary Metabolomic Phenotype Is Defined by Genotype and Metabolite Imbalance: Results in 51 Early Treated Patients Using Ex Vivo 1H-NMR Analysis.

Phenylketonuria (PKU) is a rare metabolic disorder caused by mutations in the phenylalanine hydroxylase gene. Depending on the severity of the genetic mutation, medical treatment, and patient dietary management, elevated phenylalanine (Phe) may occur in blood and brain tissues. Research has recently shown that high Phe not only impacts the central nervous system, but also other organ systems (e.g., heart and microbiome). This study used ex vivo proton nuclear magnetic resonance (1H-NMR) analysis of urine samples from PKU patients (mean 14.9 ± 9.2 years, n = 51) to identify the impact of elevated blood Phe and PKU treatment on metabolic profiles. Our results found that 24 out of 98 urinary metabolites showed a significant difference (p < 0.05) for PKU patients compared to age-matched healthy controls (n = 51) based on an analysis of urinary metabolome. These altered urinary metabolites were related to Phe metabolism, dysbiosis, creatine synthesis or intake, the tricarboxylic acid (TCA) cycle, end products of nicotinamide-adenine dinucleotide degradation, and metabolites associated with a low Phe diet. There was an excellent correlation between the metabolome and genotype of PKU patients and healthy controls of 96.7% in a confusion matrix model. Metabolomic investigations may contribute to a better understanding of PKU pathophysiology.

#4952 CLINICOPATHOLOGIC CORRELATIONS OF URINARY PROTEOMIC AND METABOLOMIC ANALYSIS IN PATIENTS WITH RENAL AA AMYLOIDOSIS AND MEMBRANOUS NEPHROPATHY

Abstract Background and Aims AA Amyloidosis is a multisystemic amyloidosis subtype that develops on the background of various chronic inflammatory etiologies. Urinary omics studies have become a promising tool for elucidating pathophysiology and prognosis of glomerular diseases. However, no urinary omics analysis has been performed focusing on renal AA amyloidosis in literature to the best of our knowledge. Our main aim in this study is to perform a comparative urine proteomic and metabolomic analysis of recently diagnosed renal AA amyloidosis and to investigate the correlation of bioinformatic results with clinical and pathological data. Method Urine samples of 8 recently diagnosed AA amyloidosis (AA), 8 membranous nephropathy (MN) and 6 healthy control group patients were collected before kidney biopsy procedure. Proteomic analyzes were performed with nLC/Q-TOF MS/MS and metabolomic analyzes were performed by GC/MS in all patients. Biopsy specimens were scored according to glomerulosclerosis (G), tubular atrophy (TA) and interstitial fibrosis (IF) grades by two pathologists. Raw spectroscopic data was analyzed using MaxQuant and MS-DIAL programs for proteomic and metabolomic studies, respectively. Statistical analysis of the differences in molecules between study groups were performed with ANOVA and HSD-Tukey tests. Principal component (PCA) and heatmap analyzes were made in R language, while gene ontology (GO), network and functional enrichment analysis of bioinformatic results were performed with PANTHER, STRING and MetaboAnalyst databases. Results In comparison between AA and MN groups, median eGFR values tend to be lower in the AA group (67.6 vs 112 ml/min/1.73 m2 respectively, p = 0.08). Median 24-hour urine protein levels did not show statistically significant difference (9499 vs 9512 mg/day respectively, p = 0.9). Percentage of patients with moderate/severe IF/TA was higher and G score was tend to be in AA group compared to MN group (p values 0.02 and 0.07 for IF/TA and G scores, respectively). As a result of proteomic analysis, a total of 859 proteins were determined. Statistical analysis showed 51 proteins that were significantly differ in AA group compared to the control group. GO and functional enrichment analyzes showed that statistically most significant sub-domains were mainly related with cell-cell adhesion (Figure 1 &amp; 2). In comparative analysis between AA and MN patients, uromodulin (UMOD) was lower in the AA group than in the MN group (log2FC -3.37), whereas ribonuclease 1 (RNASE1) and α-1-microglobulin/bikunin precursor protein (AMBP) were higher in the AA group (log2FC 3.41 and 3.07, respectively). In Spearman correlation analyzes, significant negative correlations were demonstrated between UMOD-proteinuria (r = -0.48, p = 0.03) and between AMBP-eGFR (r = -0.69, p = 0.003) variables. Metabolomic analysis showed 9 metabolites that were significantly different between AA and other study groups. Myo-inositol and urate were higher in AA group compared to MN group, while D-mannitol and N-acetylglutamate were higher in AA group compared to the control group. Significant positive correlation independent of GFR was detected between RNASE1 and urate (r = 0.63, p = 0.01). Conclusion Our study is the first urinary comparative omics analysis performed on renal AA amyloidosis patients to the best of our knowledge. We demonstrated specific protein and metabolites that distinguish AA group from the control and MN groups. Enrichment and GO analyzes between AA and the control group showed a negative enrichment in cell-cell adhesion related sub-domains, suggesting a possible increased urinary shear stress resulting in downregulation of cadherins in AA amyloidosis. In comparative analysis between AA and MN groups, UMOD and AMBP proteins and myo-inositol were thought to be associated with high tubulointerstitial damage, whereas RNASE1 and urate were believed to be related with systemic inflammation and endothelial damage [1].

Metabolic biomarkers linking urinary arsenic species to gestational diabetes mellitus: A cross-sectional study in Chinese pregnant women

Environmental arsenic (As) exposure has been associated with gestational diabetes mellitus (GDM) risk. Our recent study found that GDM was positively associated with urinary As3+ level while negatively correlated to As5+. However, the mechanisms underlying the association between arsenic species and GDM remain largely unknown. In the present study, through the measurement of urinary arsenic species and metabolome analysis in 399 pregnant women, we aimed to identify the metabolic biomarkers that may link arsenic exposure to GDM based on a novel systems epidemiology strategy termed meet-in-metabolite-analysis (MIMA). The metabolomics analysis revealed that 20 and 16 urinary metabolites were relevant to arsenic exposure and GDM, respectively. Among them, 12 metabolites were identified to be both arsenic- and GDM-related, which are mainly involved in purine metabolism, one‑carbon metabolism (OCM) and glycometabolism. Moreover, it was further showed that the regulation of thiosulfate (AOR: 2.52; 95 % CI: 1.33, 4.77) and phosphoroselenoic acid (AOR: 2.35; 95 % CI: 1.31, 4.22) could significantly contribute to the negative association between As5+ and GDM. Considering the biological functions of these metabolites, it is suggested that As5+ may reduce GDM risk by disturbing OCM in the pregnant women. These data will provide novel insights into the mechanism of action of environmental arsenic exposure on GDM incidence from the aspect of metabolism disorder.