Predicting and monitoring treatment response via 1-H NMR metabolomics of plasma, serum, and urine

AB1313 NMR SPECTROSCOPY REVEALS ALTERATIONS OF URINARY ACETATE AND CITRATE LEVELS FOLLOWING CYCLOPHOSPHAMIDE THERAPY IN PATIENTS WITH LUPUS NEPHRITIS

BackgroundSystemic inflammation in rheumatoid arthritis (RA) is associated with metabolic changes. We used nuclear magnetic resonance (NMR) spectroscopy–based metabolomics to assess the relationship between an objective measure of systemic inflammation [C-reactive protein (CRP)] and both the serum and urinary metabolome in patients with newly presenting RA.MethodsSerum (n=126) and urine (n=83) samples were collected at initial presentation from disease modifying anti-rheumatic drug naïve RA patients for metabolomic profile assessment using 1-dimensional 1H-NMR spectroscopy. Metabolomics data were analysed using partial least square regression (PLS-R) and orthogonal projections to latent structure discriminant analysis (OPLS-DA) with cross validation.ResultsUsing PLS-R analysis, a relationship between the level of inflammation, as assessed by CRP, and the serum (p=0.001) and urinary (p<0.001) metabolome was detectable. Likewise, following categorisation of CRP into tertiles, patients in the lowest CRP tertile and the highest CRP tertile were statistically discriminated using OPLS-DA analysis of both serum (p=0.033) and urinary (p<0.001) metabolome. The most highly weighted metabolites for these models included glucose, amino acids, lactate, and citrate. These findings suggest increased glycolysis, perturbation in the citrate cycle, oxidative stress, protein catabolism and increased urea cycle activity are key characteristics of newly presenting RA patients with elevated CRP.ConclusionsThis study consolidates our understanding of a previously identified relationship between serum metabolite profile and inflammation and provides novel evidence that there is a relationship between urinary metabolite profile and inflammation as measured by CRP. Identification of these metabolic perturbations provides insights into the pathogenesis of RA and may help in the identification of therapeutic targets.

Predicting and monitoring treatment response via 1-H NMR metabolomics of plasma, serum, and urine

High-resolution metabolomics has enhanced our understanding of pollutants' adverse effects on humans, particularly in multipollutant exposure scenarios. However, whether metabolic profiles differ across biological matrices in response to contaminants remains unclear. In this study, we analyzed urinary concentrations of 38 legacy and emerging contaminants, including 15 metal(loid)s and 23 metabolites of polycyclic aromatic hydrocarbons, phthalates, and alternative plasticizers in 74 general residents from southern China using inductively coupled plasma mass spectrometry and high-performance liquid chromatography-tandem mass spectrometry. High-resolution metabolomics of paired serum and urine samples identified 186 serum and 774 urine metabolites significantly associated with measured contaminant, enriching 12 serum and 22 urine metabolic pathways. Cross-validation across serum and urine metabolomes revealed 37 overlapping metabolites (mainly as 12 lipids and 9 organic acids) and 8 metabolic pathways (7 amino acid-related and 1 sphingolipid pathway) as primary metabolic perturbations. Notwithstanding shared signatures, organic nitrogen and organ heterocyclic compounds comprise a significantly higher proportion in serum and urine. Only serum phenylalanine and leucine were associated with globulin. These findings first characterize metabolic responses to pollutant mixtures and highlight the complementary value of serum (for biomarker screening) and urine (for exposure assessment) metabolomics in environmental health research.

The maturation of ultra-high-field magnetic resonance imaging (MRI) [≥7 Tesla (7T)] has improved our capability to depict and characterise brain structures efficiently, with better signal-to-noise ratio (SNR) and spatial resolution. We evaluated whether these improvements benefit the clinical detection and management of Parkinson's disease (PD). We performed a literature search in March 2023 in PubMed (MEDLINE), EMBASE and Google Scholar for articles on "7T MRI" AND "Parkinson*", written in English, published between inception and 1st March, 2023, which we synthesised in narrative form. In deep-brain stimulation (DBS) surgical planning, early studies show that 7T MRI can distinguish anatomical substructures, and that this results in reduced adverse effects. In other areas, while there is strong evidence for improved accuracy and precision of 7T MRI-based measurements for PD, there is limited evidence for meaningful clinical translation. In particular, neuromelanin-iron complex quantification and visualisation in midbrain nuclei is enhanced, enabling depiction of nigrosomes 1-5, improved morphometry and vastly improved radiological assessments; however, studies on the related clinical outcomes, diagnosis, subtyping, differentiation of atypical parkinsonisms, and monitoring of treatment response using 7T MRI are lacking. Moreover, improvements in clinical utility must be great enough to justify the additional costs. Together, current evidence supports feasible future clinical implementation of 7T MRI for PD. Future impacts to clinical decision making for diagnosis, differentiation, and monitoring of progression or treatment response are likely; however, to achieve this, further longitudinal studies using 7T MRI are needed in prodromal, early-stage PD and parkinsonism cohorts focusing on clinical translational potential.

L-ornithine L-aspartate (LOLA) is administered as a therapeutic and/or preventive strategy against hepatic encephalopathy either intravenously or orally in patients with liver cirrhosis. Here, we analyzed how LOLA influences the microbiome and metabolome of patients with liver cirrhosis. We retrospectively analyzed the stool microbiome, stool, urine and serum metabolome as well as markers for gut permeability, inflammation and muscle metabolism of 15 cirrhosis patients treated orally with LOLA for at least one month and 15 propensity-score-matched cirrhosis patients without LOLA. Results were validated by comparing the LOLA-treated patients to a second set of controls. Patients with and without LOLA were comparable in age, sex, etiology and severity of cirrhosis as well as PPI and laxative use. In the microbiome, Flavonifractor and Oscillospira were more abundant in patients treated with LOLA compared to the control group, while alpha and beta diversity were comparable between groups. Differences in stool and serum metabolomes reflected the pathophysiology of hepatic encephalopathy and confirmed LOLA intake. In the urine metabolome, ethanol to acetic acid ratio was lower in patients treated with LOLA compared to controls. LOLA-treated patients also showed lower serum levels of insulin-like growth factor (IGF) 1 than patients without LOLA. No differences in gut permeability or inflammation markers were found. A higher abundance of Flavonifractor and Oscillospira in LOLA-treated patients could indicate LOLA as a potential microbiome modulating strategy in patients with liver disease. The lower levels of IGF1 in patients treated with LOLA suggest a possible link between the pathophysiology of hepatic encephalopathy and muscle health.

Patients with a spleen-qi deficiency often exhibit dysfunction in the metabolic system. Metabolites are considered the most direct reflection of individual physiological and pathological conditions and represent attractive candidates to provide deep insights into disease phenotypes. This study examines the potential therapeutic mechanism of wild ginseng on spleen-qi deficiency through the analysis of serum and urine metabolomics using rapid-resolution liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry. The reasons for the superiority of wild ginseng treatment over cultivated ginseng were also analyzed in depth. After wild ginseng intervention, anandamide, urobilinogen, aldosterone, and testosterone glucuronide were significantly reduced in serum. Meanwhile, argininosuccinic acid, L-cysteine, and seven other metabolites were significantly elevated in serum. Nine metabolites, including L-acetylcarnitine, and citrulline were elevated in the urine, and trimethylamine N-oxide, adrenic acid, and 10 other metabolites were reduced. Arginine biosynthesis, pantothenate and CoA biosynthesis, thiamin metabolism, taurine, and tryptophan metabolism pathways were mainly improved. Further analysis was conducted on the relationship between Lactobacillus and Akkermansia bacteria with metabolites, and it was found that they are mainly related to amino acid metabolites. This study provides strong theoretical support and direction for further explanation of the immune mechanism of wild ginseng and lays the foundation for future studies.

The multi-omic basis for hepatic encephalopathy recurrence: Analysis of the THEMATIC trial

Gout is the most common inflammatory arthritis and the worldwide incidence is increasing. By revealing the metabolic alterations in serum and urine of gout patients, the first aim of our study was to discover novel molecular biomarkers allowing for early diagnosis. We also aimed to investigate the underlying pathogenic pathways. Serum and urine samples from gout patients (n = 30) and age-matched healthy controls (n = 30) were analysed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to screen the differential metabolites and construct a diagnostic model. Next, the model was verified and optimized in the second validation cohort (n = 100). The pathways were illustrated to understand the underlying pathogenesis of gout. In general, serum metabolomics demonstrated a clearer distinction than urine metabolomics. In the discovery cohort, 40 differential serum metabolites were identified that could distinguish gout patients from healthy controls. Among them, eight serum metabolites were verified in the validation cohort. Through regression analysis, the final model consisted of three serum metabolites-pyroglutamic acid, 2-methylbutyryl carnitine and Phe-Phe-that presented optimal diagnostic power. The three proposed metabolites produced an area under the curve of 0.956 (95% CI 0.911, 1.000). Additionally, the proposed metabolic pathways were primarily involved in purine metabolism, branched-chain amino acids (BCAAs) metabolism, the tricarboxylic acid cycle, synthesis and degradation of ketone bodies, bile secretion and arachidonic acid metabolism. The metabolomics signatures could serve as an efficient tool for early diagnosis and provide novel insights into the pathogenesis of gout.

Metabolic profiling of serum and urine in preeclampsia and gestational diabetes in early pregnancy

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.

Background: Abelmoschus manihot (L.) Medik (“Huangkui” in Chinese, HK) has been widely used for the treatment of kidney diseases. Nephrotoxicity is the side effect of cisplatin (CDDP), which greatly limits its clinical application. Therefore, CDDP could be used to establish the chronic kidney disease (CKD) model. However, the protective effects of HK on CDDP-induced CKD have not been investigated.Purpose: To explore the protective effect and underlying mechanisms of HK on multiple low-dose CDDP-induced CKD in rats by the integrated analysis of serum, kidney, and urine metabolomics and network pharmacology.Methods: The CKD model was induced by multiple low-dose CDDP. Body weight, organ index, serum biochemical, and kidney histology were examined to evaluate the effect of HK. Serum, kidney, and urine were collected and profiled by HILIC/RPLC-Q-TOF/MS-based metabolomics. Potential biomarkers (PBs) were screened according to the criteria of VIP >1, p < 0.01, and FC > 2, and then identified or assigned. The pathway analysis and PBs enrichment were conducted by MetaboAnalyst and ChemRICH. Furthermore, network pharmacology was adopted to dig out the active components and targets. Finally, the results from metabolomics and network pharmacology were integrated to confirm each other.Results: HK could recover the CDDP-induced abnormal pharmacological and metabolic profile changes. A total of 187 PBs were screened and identified from the serum, kidney, and urine metabolomics. Pathway analysis showed that multiple metabolic pathways, mainly related to amino acid and lipid metabolisms, were involved in the nephroprotective effect of HK, and especially, HK could significantly alleviate the disorder of tryptophan metabolism pathway in serum, kidney, and urine. Meanwhile, network pharmacology analysis revealed that 5 components in HK and 4 key genes could be responsible for the nephroprotection of HK, which also indicated that the metabolism of tryptophan played an important role in HK against CKD.Conclusion: HK has a nephroprotection on CDDP-induced CKD, mainly by restoring the dysregulation of tryptophan metabolism. Integrated analysis of serum, kidney, and urine metabolomics and network pharmacology was a powerful method for exploring pharmacological mechanisms and screening active components and targets of traditional Chinese medicine.

The present study aimed to investigate overall metabolic changes caused by cranberry juice or apple juice consumption using a global 1H NMR‐based metabolomics approach. Eighteen female college students, between 21‐29 years old, were given either cranberry juice or apple juice for three days using a cross‐over design. Plasma and urine samples were collected before and after juice consumption. Metabolome in urine and plasma were analyzed using 1H NMR‐based metabolomics followed by multivariate analyses. No metabolic difference was observed in human plasma before and after juice consumption for either cranberry or apple juices. However, metabolome in plasma and urine after cranberry juice consumption were different from those after apple juice consumption. Cranberry juice consumption caused a greater increase in urinary excretion of hippuric acid and a higher level of citric acid in the plasma. On the other hand, cranberry juice decreased the plasma level of lactate, D‐glucose, and two unidentified metabolites compared to apple juice consumption. The metabolomic changes caused by cranberry juice consumption may help to explain its reported health benefits.This research is supported in part by Ocean Spray Cranberries, Inc.

Background: The utility of single-pulse TMS (transcranial magnetic stimulation)-evoked EEG (electroencephalograph) potentials (TEPs) has been extensively studied in the past three decades. TEPs have been shown to provide insights into features of cortical excitability and connectivity, reflecting mechanisms of excitatory/inhibitory balance, in various neurological and psychiatric conditions. In the present study, we sought to review and summarize the most studied neurological and psychiatric clinical indications utilizing single-pulse TEP and describe its promise as an informative novel tool for the evaluation of brain physiology. Methods: A thorough search of PubMed, Embase, and Google Scholar for original research utilizing single-pulse TMS-EEG and the measurement of TEP was conducted. Our review focused on the indications and outcomes most clinically relevant, commonly studied, and well-supported scientifically. Results: We included a total of 55 publications and summarized them by clinical application. We categorized these publications into seven sub-sections: healthy aging, Alzheimer's disease (AD), disorders of consciousness (DOCs), stroke rehabilitation and recovery, major depressive disorder (MDD), Parkinson's disease (PD), as well as prediction and monitoring of treatment response. Conclusions: TEP is a useful measurement of mechanisms underlying neuronal networks. It may be utilized in several clinical applications. Its most prominent uses include monitoring of consciousness levels in DOCs, monitoring and prediction of treatment response in MDD, and diagnosis of AD. Additional applications including the monitoring of stroke rehabilitation and recovery, as well as a diagnostic aid for PD, have also shown encouraging results but require further evidence from randomized controlled trials (RCTs).

Objectives: The molecular landscape of non-muscle-invasive (NMIBC) and muscle-invasive (MIBC) bladder cancer based on molecular characteristics is essential but poorly understood. In this pilot study we aimed to identify a multi-omics signature that can distinguish MIBC from NMIBC. Such a signature can assist in finding potential mechanistic biomarkers and druggable targets. Methods: Patients diagnosed with NMIBC (n = 15) and MIBC (n = 11) were recruited at a tertiary-care hospital in Nanjing from 1 April 2021, and 31 July 2021. Blood, urine and stool samples per participant were collected, in which the serum metabolome, urine metabolome, gut microbiome, and serum extracellular vesicles (EV) proteome were quantified. The differences of the global profiles and individual omics measure between NMIBC vs. MIBC were assessed by permutational multivariate analysis and the Mann–Whitney test, respectively. Logistic regression analysis was used to assess the association of each identified analyte with NMIBC vs. MIBC, and the Spearman correlation was used to investigate the correlations between identified analytes, where both were adjusted for age, sex and smoking status. Results: Among 3168 multi-omics measures that passed the quality control, 159 were identified to be differentiated in NMIBC vs. MIBC. Of these, 46 analytes were associated with bladder cancer progression. In addition, the global profiles showed significantly different urine metabolome (p = 0.029), gut microbiome (p = 0.036), and serum EV (extracellular vesicles) proteome (p = 0.039) but not serum metabolome (p = 0.059). We also observed 17 (35%) analytes that had been developed as drug targets. Multiple interactions were obtained between the identified analytes, whereas for the majority (61%), the number of interactions was at 11–20. Moreover, unconjugated bilirubin (p = 0.009) and white blood cell count (p = 0.006) were also shown to be different in NMIBC and MIBC, and associated with 11 identified omics analytes. Conclusions: The pilot study has shown promising to monitor the progression of bladder cancer by integrating multi-omics data and deserves further investigations.