Urinary Metabolites Research Articles

Urinary Metabolite Diagnostic and Prognostic Liquid Biopsy Biomarkers of Lung Cancer in Non-smokers and Tobacco Smokers.

Non-smokers account for 10-13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose computed tomography (LDCT). Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort). The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA) were analyzed and quantified using liquid chromatography-mass spectrometry to determine if non-smoker cases can be distinguished from sex and age-matched controls in comparison to tobacco smoker cases and controls, potentially leading to more precise eligibility criteria for LDCT screening. Urinary levels of CR and NANA were significantly higher and comparable in non-smokers and tobacco smoker cases as compared to population controls in both cohorts. Receiver Operating Characteristics (ROC) analysis for combined CR and NANA levels in non-smokers of the exploratory cohort resulted in better predictive performance with the area under the curve (AUC) of 0.94, whereas the validation cohort non-smokers had an AUC of 0.80. Kaplan-Meier survival curves showed that high levels of CR and NANA were associated with increased cancer-specific death in non-smokers as well as tobacco smoker cases in both cohorts. Measuring CR and NANA in urine liquid biopsies could identify non-smokers at high risk for lung cancer as candidates for LDCT screening and warrant prospective studies of these biomarkers.

Investigating gut microbiota-blood and urine metabolite correlations in early sepsis-induced acute kidney injury: insights from targeted KEGG analyses.

The interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI. Utilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns. Our study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6, P = 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2, P = 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae, R > 0, P < 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation. Significant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.

Particulate matter, polycyclic aromatic hydrocarbons and metals, platelet parameters and blood pressure alteration: Multi-pollutants study among population

Epidemiological findings have determined the linkage of fine particulate matter (PM2.5) and the morbidity of hypertension. However, the mode of action and specific contribution of PM2.5 component in the blood pressure elevation remain unclear. Platelets are critical for vascular homeostasis and thrombosis, which may be involved in the increase of blood pressure. Among 240 high-PM2.5 exposed, 318 low-PM2.5 exposed workers in a coking plant and 210 workers in the oxygen plant and cold-rolling mill enrolled in present study, both internal and external exposure characteristics were obtained, and we performed linear regression, adaptive elastic net regression, quantile g-computation and mediation analyses to analyze the relationship between urine metabolites of polycyclic aromatic hydrocarbons (PAHs) and metals fractions with platelets indices and blood pressure indicators. We found that PM2.5 exposure leads to increased systolic blood pressure (SBP) and pulse pressure (PP). Specifically, for every 10 μg/m3 increase in PM2.5, there was a 0.09 mmHg rise in PP. Additionally, one IQR increase in urinary 1-hydroxypyrene (1.06 μmol/mol creatinine) was associated with a 3.43 % elevation in PP. Similarly, an IQR increment of urine cobalt (2.31 μmol/mol creatinine) was associated with a separate 1.77 % and 4.71 % elevation of SBP and PP. Notably, platelet-to-lymphocyte ratio (PLR) played a mediating role in the elevation of SBP and PP induced by cobalt. Our multi-pollutants results showed that PAHs and cobalt were deleterious contributors to the elevated blood pressure. These findings deepen our understanding of the cardiovascular effects associated with PM2.5 constituents, highlighting the importance of increased vigilance in monitoring and controlling the harmful components in PM2.5.

Method development with high-throughput enhanced matrix removal followed by UHPLC-QqQ-MS/MS for analysis of grape polyphenol metabolites in human urine

Grape and grape derived products contain many bioactive phenolics which have a variety of impacts on health. Following oral ingestion, the phenolic compounds and their metabolites may be detectable in human urine. However, developing a reliable method for the analysis of phenolic compounds in urine is challenging. In this work, we developed and validated a new high-throughput, sensitive and reproducible analytical method for the simultaneous analysis of 31 grape phenolic compounds and metabolites using Oasis PRiME HLB cleanup for sample preparation combined with ultra-performance liquid chromatography with triple quadrupole tandem mass spectrometry (UHPLC-QqQ-MS/MS). Using this new method, the accuracy achieved was 69.3 % ∼ 134.9 % (except for six compounds), and the recovery achieved was 52.4 % ∼ 134.7 % (except for two very polar compounds). For each of the 31 target analytes, the value of intra-day precision was less than 14.3 %. The value of inter-day precision was slightly higher than intra-day precision, with a range of 0.7 % ∼ 19.1 %. We report for the first time on the effect of gender and BMI on the accuracy and recovery of human urine samples, and results from analysis of variance (ANOVA), and principal component analysis (PCA) indicated there was no difference in the value of accuracy and recovery between different gender or BMI (>30) using our purposed cleanup and UHPLC-QqQ-MS/MS method. Overall, this newly developed method could serve as a powerful tool for analyzing grape phenolic compounds and metabolites in human urine samples.

A 37-Year-Old Man With Intellectual Disability Discovered to Have Aspartylglucosaminuria: Implications for the Diagnosis of Genetic Causes.

The causes of intellectual disability (ID) are varied, with as many as 1,400 causative genes. We attempted to identify the causative gene in a patient with long-standing undiagnosed ID. Although this was an isolated case with no family history, we searched for the causative gene using trio-based whole-exome sequencing (trio-WES), because severe ID is often caused by genetic variations, and inherited metabolic disorders (IMDs) are assumed to be the cause when regression and epilepsy occur. We identified homozygous donor splice-site variants in the AGA gene (aspartylglucosaminidase; NM_000027.4) Chr4(GRCh38):g. 177436275C>A, c.698+1G>T. This gene is implicated in aspartylglucosaminuria (AGU; OMIM #208400) and originated from both of the patient's parents. We confirmed the pathogenicity of the variant by detecting the splicing defect in cDNA from the patient's blood and accumulation of aberrant metabolites in the patient's urine. We discuss how to more readily achieve an accurate diagnosis for patients with undiagnosed intellectual disabilities. Medical practitioners' awareness of the characteristics of the disease leading to clinical suspicion in patients with matching presentations, and the performance of newborn screening when possible, is important for the diagnosis of ID. In addition, the characteristic symptoms and course of the disease give rise to suspicion of IMDs. Given our results, we consider trio-WES to be a powerful method for identifying the causative genes in cases of ID with genetic causes.

Phthalate and phthalate replacement concentrations in relationship to adiposity in a multi-racial cohort of children.

Phthalates and phthalate replacements are used in multiple everyday products, making many of them bioavailable to children. Experimental studies suggest that phthalates and their replacements may be obesogenic, however, epidemiologic studies remain inconsistent. Therefore, our objective was to examine the association between phthalates, phthalate replacements and childhood adiposity/obesity markers in children. A cross-sectional study was conducted in 630 racial/ethnically diverse children ages 4-8 years. Urinary oxidative metabolites of DINCH and DEHTP, three low molecular weight (LMW) phthalates, and eleven high molecular weight (HMW) phthalates were measured. Weight, height, waist circumference and % body fat were measured. Composite molar sum groups (nmol/ml) were natural log-transformed. Linear regression models adjusted for urine specific gravity, sex, age, race-ethnicity, birthweight, breastfeeding, reported activity level, mother's education and pre-pregnancy BMI. All children had LMW and HMW phthalate metabolites and 88% had DINCH levels above the limit of detection. One unit higher in the log of DINCH was associated with 0.106 units lower BMI z-score [β = -0.106 (95% CI: -0.181, -0.031)], 0.119 units lower waist circumference z-score [β = -0.119 (95% CI: -0.189, -0.050)], and 0.012 units lower percent body fat [β = -0.012 (95% CI: -0.019, -0.005)]. LMW and HMW group values were not associated with adiposity/obesity. We report an inverse association between child urinary DINCH levels, a non-phthalate plasticizer that has replaced DEHP in several applications, and BMI z-score, waist circumference z-score and % body fat in children. Few prior studies of phthalates and their replacements in children have been conducted in diverse populations. Moreover, DINCH has not received a great deal of attention or regulation, but it is a common exposure. In summary, understanding the ubiquitous nature of these chemical exposures and ultimately their sources will contribute to our understanding of their relationship with obesity.

Mast cells control lung type 2 inflammation via prostaglandin E2-driven soluble ST2

Severe asthma and sinus disease are consequences of type 2 inflammation (T2I), mediated by interleukin (IL)-33 signaling through its membrane-bound receptor, ST2. Soluble (s)ST2 reduces available IL-33 and limits T2I, but little is known about its regulation. We demonstrate that prostaglandin E2 (PGE2) drives production of sST2 to limit features of lung T2I. PGE2-deficient mice display diminished sST2. In humans with severe respiratory T2I, urinary PGE2 metabolites correlate with serum sST2. In mice, PGE2 enhanced sST2 secretion by mast cells (MCs). Mice lacking MCs, ST2 expression by MCs, or E prostanoid (EP)2 receptors by MCs showed reduced sST2 lung concentrations and strong T2I. Recombinant sST2 reduced T2I in mice lacking PGE2 or ST2 expression by MCs back to control levels. PGE2 deficiency also reversed the hyperinflammatory phenotype in mice lacking ST2 expression by MCs. PGE2 thus suppresses T2I through MC-derived sST2, explaining the severe T2I observed in low PGE2 states.

Development and Application of a Selective Analytical Method for Indole Metabolites in Urine: Dietary Exposure Biomarkers for Broccoli Consumption.

The identification of dietary exposure biomarkers is crucial for advancing our understanding of the health benefits of specific foods. Broccoli, a vegetable with well-known anticancer properties, contains active ingredients, such as isothiocyanates with indole side chains. Hence, indole metabolites related to broccoli consumption have the potential to serve as biomarkers of dietary exposure. In this work, we developed a new analytical method for indole metabolites in urine using a poly(deep eutectic solvents)-molecularly imprinted polymer/vinyl-functionalized graphene oxide (PDESs-MIP/VGO) in miniaturized centrifugal pipet-tip solid-phase extraction (CPT-SPE) coupled with liquid chromatography. This method integrates the strengths of PDESs-MIP/VGO, including rich adsorption interactions, high adsorption capacity, and excellent selectivity, with the simplicity and cost-effectiveness of CPT-SPE. The proposed method demonstrated low limits of quantification (1.2-2.5 ng mL-1), high accuracy (91.7-104.8%), and good precision (relative standard deviation ≤4.4%). By applying this method to analyze indole metabolites in urine, our results suggested that indole-3-carbinol and indole-3-acetonitrile have the potential to emerge as reliable dietary exposure biomarkers for broccoli intake. Furthermore, highly selective analytical methods based on molecular imprinting technology are advantageous for precise screening and analysis of dietary exposure biomarkers associated with food consumption.

Urinary polycyclic aromatic hydrocarbon metabolites and hyperlipidemia: NHANES 2007-2016.

The relationships between urinary polycyclic aromatic hydrocarbon (PAH) metabolites and hyperlipidemia have not been thoroughly studied. The primary goal of this research focused on investigating the linkage between PAH metabolite concentrations in urine and hyperlipidemia prevalence within US adults. A cross-sectional analysis was conducted using data from the 2007-2016 National Health and Nutrition Examination Survey (NHANES). Logistic regression models were used to assess correlations between urinary PAH metabolite levels and the risk of hyperlipidemia, while restricted cubic spline models were used to examine dose‒response relationships. Subgroup and interaction analyses were performed to further elucidate these associations. Weighted quantile sum (WQS) regression analyzed the cumulative impact of various urinary PAH metabolites on hyperlipidemia risk. This study included 7,030 participants. Notably, individuals in the highest quintile of urinary PAH metabolite concentrations exhibited a significantly elevated prevalence of hyperlipidemia, even after comprehensive adjustments (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.01-1.75). Moreover, elevated levels of 1-hydroxyphenanthrene and 2-hydroxynaphthalene in the fourth quintile and 2-hydroxyfluorene in the third, fourth, and fifth quintiles demonstrated positive correlations with the prevalence of hyperlipidemia. These associations persisted across subgroup analyses. Additionally, a positive correlation between the urinary PAH metabolite mixture and hyperlipidemia (positive model: OR = 1.04, 95% CI: 1.00-1.09) was observed in the WQS model, and 2-hydroxynaphthalene showed the most substantial contribution. The cross-sectional analysis identified a significant correlation between urinary PAH metabolite and hyperlipidemia prevalence within the US demographic, with 2-hydroxynaphthalene being the predominant influencer. These findings underscore the need to mitigate PAH exposure as a preventive measure for hyperlipidemia.

Comparative profiling of serum, urine, and feces bile acids in humans, rats, and mice.

Bile acids (BAs) play important pathophysiological roles in both humans and mammalian animals. Laboratory rats and mice are widely used animal models for assessing pharmacological effects and their underlying molecular mechanisms. However, substantial physiological differences exist in BA composition between humans and murine rodents. Here, we comprehensively compare BA profiles, including primary and secondary BAs, along with their amino acid conjugates, and sulfated metabolites in serum, urine, and feces between humans and two murine rodents. We further analyze the capabilities in gut microbial transform BAs among three species and compare sex-dependent variations within each species. As a result, BAs undergo amidation predominately with glycine in humans and taurine in mice but are primarily unamidated in rats. BA sulfation is a unique characteristic in humans, whereas rats and mice primarily perform multiple hydroxylations during BA synthesis and metabolism. For gut microbial transformed BA capabilities, humans are comparable to those of rats, stronger than those of mice in deconjugation and 7α-dehydroxylation, while humans are weak than those of rats or mice in oxidation and epimerization. Such differences enhance our understanding of the divergent experimental outcomes observed in humans and murine rodents, necessitating caution when translating findings from these rodent species to humans.

Sleep characteristics in underweight young females across their menstrual cycles: A sleep-monitoring survey study with preliminary results.

This study investigated the association between underweight and sleep in young females across their menstrual cycles. A lifestyle-monitoring survey was conducted among 38 female university students aged 18-24 years in Japan from January to December 2023. Sleep data from 28 participants were analysed. Participants were categorized into underweight (n = 10) and control (n = 18) groups based on a baseline body mass index cut-off of 18.5 kg m-2. Sleep parameters were assessed using a daily sleep questionnaire, sleep sensor mats, and urinary melatonin metabolites across their menstrual cycles. The results indicated no significant differences in sleep patterns between the underweight and control groups or menstrual cycle phases, as assessed using both the daily sleep questionnaire and the sleep sensor mats. However, underweight participants experienced more difficulty maintaining sleep during the follicular phase. Body mass index significantly correlated with sleep efficiency (rs = 0.52) and wake after sleep onset (rs = -0.56). While urinary melatonin metabolite levels did not differ significantly between the groups or menstrual cycle phases, decreased levels during the luteal phase were more prevalent in the underweight group (7 of 10 participants) than in the control group (3 of 13 participants). This study suggests an association between underweight and sleep quality, especially nocturnal awakening, in young females. These findings underscore the importance of considering sleep quality in the management of underweight young females to improve their overall health outcomes.

Prenatal arsenic metabolite exposure is associated with increased newborn mitochondrial DNA copy number: evidence from a birth cohort study.

While mitochondria are susceptible to environmental detriments, little is known about potential associations between arsenic metabolites and mitochondria DNA copy number (mtDNAcn). We attempted to examine whether maternal urinary arsenic metabolite levels in different trimesters were related to neonatal cord blood mtDNAcn. We included 819 mother-newborn pairs embedded in an in-progress birth cohort survey performed from April 2014 to October 2016 in Wuhan, China. We determined maternal urinary arsenic species concentrations in different trimesters. We determined cord blood mtDNAcn using quantitative real-time polymerase chain reaction. In covariate-adjusted models, each one-unit increment of dimethylated arsenic (DMA) and total arsenic (TAs) in the third trimester was related to 8.43% (95% CI 1.13%, 16.26%) and 12.15% (95% CI 4.35%, 20.53%) increases in mtDNAcn, respectively. The dose-response trend with statistical significance was observed across tertiles of DMA and TAs in the third trimester with mtDNAcn (DMA percent changes (%Δ) = 25.60 (95% CI 6.73, 47.82), for the highest vs the lowest tertile (P = 0.02); TAs %Δ = 40.31 (95% CI 19.25, 65.10), for the highest vs the lowest tertile (P = 0.0002)). These findings may prove the relationships between prenatalarsenic species levelsand neonatalmitochondrial dysfunction.

Ameliorative effect of rare ginsenosides on reproductive injury induced by cyclophosphamide in female rats: based on metabonomics

Objective: To investigate the effect of rare ginsenosides (RGS) on reproductive injury induced by cyclophosphamide (CP) in female rats. Methods: Twenty-four female rats were divided into four groups [normal control (NC), RGS, CP, and CP+RGS group] with 6 rats in each group. CP group (the model group) and CP+RGS group (the treatment group) were intraperitoneally injected with CP 30 mg/kg for 5 days for modeling, and CP+RGS group was given RGS intragastric intervention. General growth status of rats in each group was observed, the organ index was calculated, and the pathological changes of ovary, uterus, liver and kidney were observed by hematoxylin-eosin staining. Serum levels of estradiol, follicle stimulating hormone (FSH), luteinizing hormone (LH), pro-inflammatory factors interleukin (IL) 6, IL-1β, tumor necrosis factor-α were detected. The urine samples were collected after RGS treatment for metabonomics analysis. Metabolomic profiling based on ultra performance liquid chromatography (UPLC) coupled with mass spectrometry (MS) was used to analyze and determine the urine metabolites of rats in each group. Results: Compared with NC group, the ovary index of CP group [(0.054±0.015) %] was significantly decreased (P<0.05), the uterus index [(0.293±0.036) %] and estradiol level [(62.9±6.4) pmol/L] were significantly decreased (all P<0.01), serum levels of FSH, LH, IL-6 and IL-1β [(20.4±1.0) U/L, (29.0±3.0) U/L, (185.4±28.6) ng/L, (72.9±2.0) ng/L, respectively] were significantly increased (all P<0.01). Compared with CP group, the ovary index in CP+RGS group [(0.075±0.010) %] was significantly increased (P<0.05), serum estradiol level [(122.1±16.2) pmol/L] was significantly increased (P<0.01), serum FSH, IL-1β and IL-6 levels [(16.7±1.0) U/L, (111.8±17.4) ng/L, (60.1±2.2) ng/L, respectively] were significantly decreased (all P<0.01). Metabonomics analysis results showed that, a total of 352 metabolites were detected in urine, of which 12 were found to be potential markers associated with reproductive injury according to the screening standard. After treatment with RGS, differential metabolites were improved in the direction of NC group. Pathway enrichment suggests that the therapeutic effect of RGS was related to multiple metabolic pathways, including purine metabolism and taurine and hypotaurine metabolism. Conclusion: RGS might reduce inflammation and thus ameliorate the damage caused by CP to the reproductive system of female rats by affecting purine metabolism and other pathways.

Closing the gap: an urgent need for newborn screening of organic acid disorders in developing countries

Organic acid disorders are rare inherited metabolic disorders of key metabolic pathways. For the identification of specific organic acids, investigation of urinary metabolites and genetic testing are required through newborn screening programmes. Delayed diagnosis leads to complications, such as cardiac attacks, respiratory problems, neuro-developmental disorders, intellectual disability, and even premature death. The burden of such inherited disorders is quite high in developing countries of South Asia due to high rate of consanguinity in the region. Unfortunately, such disorders are left untreated due to the lack of screening facilities in such countries. The current narrative review was planned to highlight the urgent need for closing this gap and implementing effective newborn screening programmes for organic acid disorders in developing countries. ---Continue

#1554 The association between gut-derived metabolites and biomarkers of renal and cerebro-vascular damage in type 2 diabetes mellitus patients

Abstract Background and Aims Due to its numerous complications, type 2 diabetes mellitus (T2DM) has a major impact on the global economic burden and overall mortality. This condition modifies the metabolic microenvironment in targeted organs, such as the kidney and the brain, by its hyperglycemic nature. Gut microbiota seems to have significant interference with the renal-cerebral axis, especially in a dysbiosis state. The aim of the study was to quantify gut derived metabolites by metabolomic techniques and to evaluate their association with markers of endothelial, podocyte and proximal tubule damage and with cerebro-vascular hemodynamic indices. Method The metabolomic profiling was realized on serum and urine samples originated from 90 T2DM patients, divided into three subgroups, such as the following: 30 normal to mildly-, 30 moderately-, and 30 severely increased albuminuria, respectively, and 20 healthy subjects. The samples were examined by using untargeted and targeted ultra-high performance liquid chromatography coupled with electrospray-ionization quadroupole time-of-flight mass spectrometry (UHPLC-QTOF-ESI+-MS), in order to obtain the metabolic profile. The markers of renal damage such as synaptopodin (SP), podocalyxin (PD), N-acetyl-β-D-glucosaminidase (NAG), kidney injury molecule 1 (KIM-1), monocyte chemotactic protein 1 (MCP-1), and intercellular adhesion molecule 1 (ICAM-1) were assessed by ELISA technique. The hemodynamic cerebro-vascular indices were obtained by high resolution Doppler ultrasound of common carotid arteries (CCAs), internal carotid arteries (ICAs), and middle cerebral arteries (MCAs), bilaterally. The correlations between the metabolites, the markers of renal damage, and neurosonological indices were realized by univariable and multivariable linear regression analyses. Results UHPLC-QTOF-ESI+-MS targeted analysis and subsequent statistical assessments revealed a subset of metabolites with a specific pattern for the normal to mildly increased albuminuria subgroup. The metabolites identified as significant were, in serum: arginine (sArg), hippuric acid (sHA), indoxyl sulfate (sIS), butenoylcarnitine (sBCA), sorbitol (sSorb); and in urine, arginine (uArg), butenoylcarnitine (uBCA), indoxyl sulfate (uIS) and p-cresyl sulfate (uPCS). The univariable linear regression analysis revealed that sArg correlated positively with the breath-holding index (BHI) and negatively with intima media thickness (IMT) in ACI, MCP-1 and ICAM-1; sIS, sSorb, and sBCA correlated inversely with these parametes. The multivariable linear regression analysis displayed the specific correlations between metabolites, markers of endothelial dysfunction, and neurosonological indices, such as follows: sArg correlated with IMT and ICAM-1; sIS followed a predictive pattern along with resistance index (RI) in ACIs and ICAM-1; sBCA correlated with IMT and MCP-1 and sSorb correlated with ICAM-1 and BHI. The urine metabolites were correlated with markers of podocyte and proximal tubule dysfunction: uIS and uBCA were correlated with PD and urinary albumin to-creatinin ratio (uACR), and uPCR correlated with KIM-1 and uACR. Conclusion This study revealed a set of metabolites potentially derived from the intestinal microflora which may act as biomarkers for the early detection of both CMA and DKD in T2DM patients. SArg, sIS and, sBCA are indicators of renal endothelial dysfunction. Moreover, sArg and sIS reflect incipient common and internal carotid artery atherosclerosis, suggesting vascular remodeling at these levels. SSorb correlated with BHI, indicating blood-brain barrier dysfunction and CMA development. In urine, uBCA and uIS are indicators of podocytopathy, whereas uPCS is associated with proximal tubule damage in incipient DKD.

Associations between specific volatile organic chemical exposures and cardiovascular disease risks: insights from NHANES

IntroductionAn increasing body of research has demonstrated a correlation between pollutants from the environment and the development of cardiovascular diseases (CVD). However, the impact of volatile organic chemicals (VOC) on CVD remains unknown and needs further investigation.ObjectivesThis study assessed whether exposure to VOC was associated with CVD in the general population.MethodsA cross-sectional analysis was conducted utilizing data from five survey cycles (2005–2006, 2011–2012, 2013–2014, 2015–2016, and 2017–2018) of the National Health and Nutrition Examination Survey (NHANES) program. We analyzed the association between urinary VOC metabolites (VOCs) and participants by multiple logistic regression models, further Bayesian Kernel Machine Regression (BKMR) models and Weighted Quantile Sum (WQS) regression were performed for mixture exposure analysis.ResultsTotal VOCs were found to be positively linked with CVD in multivariable-adjusted models (p for trend = 0.025), independent of established CVD risk variables, such as hypertension, diabetes, drinking and smoking, and total cholesterol levels. Compared with the reference quartile of total VOCs levels, the multivariable-adjusted odds ratios in increasing quartiles were 1.01 [95% confidence interval (CI): 0.78–1.31], 1.26 (95% CI: 1.05–1.21) and 1.75 (95% CI: 1.36–1.64) for total CVD. Similar positive associations were found when considering individual VOCs, including AAMA, CEMA, CYMA, 2HPMA, 3HPMA, IPM3 and MHBMA3 (acrolein, acrylamide, acrylonitrile, propylene oxide, isoprene, and 1,3-butadiene). In BKMR analysis, the overall effect of a mixture is significantly related to VOCs when all chemicals reach or exceed the 75th percentile. Moreover, in the WQS models, the most influential VOCs were found to be CEMA (40.30%), DHBMA (21.00%), and AMCC (19.70%).ConclusionThe results of our study indicated that VOC was all found to have a significant association with CVD when comparing results from different models. These findings hold significant potential for public health implications and offer valuable insights for future research directions.

Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children

Prenatal exposure to ubiquitous endocrine-disrupting chemicals (EDCs) may increase the risk of metabolic syndrome (MetS) in children, but few studies have studied chemical mixtures or explored underlying protein and metabolic signatures. To investigate associations of prenatal exposure to EDC mixtures with MetS risk score in children and identify associated proteins and metabolites. This population-based, birth cohort study used data collected between April 1, 2003, and February 26, 2016, from the Human Early Life Exposome cohort based in France, Greece, Lithuania, Norway, Spain, and the UK. Eligible participants included mother-child pairs with measured prenatal EDC exposures and complete data on childhood MetS risk factors, proteins, and metabolites. Data were analyzed between October 2022 and July 2023. Nine metals, 3 organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 5 perfluoroalkyl substances (PFAS), 10 phthalate metabolites, 3 phenols, 4 parabens, and 4 organophosphate pesticide metabolites measured in urine and blood samples collected during pregnancy. At 6 to 11 years of age, a composite MetS risk score was constructed using z scores of waist circumference, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and insulin levels. Childhood levels of 44 urinary metabolites, 177 serum metabolites, and 35 plasma proteins were quantified using targeted methods. Associations were assessed using bayesian weighted quantile sum regressions applied to mixtures for each chemical group. The study included 1134 mothers (mean [SD] age at birth, 30.7 [4.9] years) and their children (mean [SD] age, 7.8 [1.5] years; 617 male children [54.4%] and 517 female children [45.6%]; mean [SD] MetS risk score, -0.1 [2.3]). MetS score increased per 1-quartile increase of the mixture for metals (β = 0.44; 95% credible interval [CrI], 0.30 to 0.59), organochlorine pesticides (β = 0.22; 95% CrI, 0.15 to 0.29), PBDEs (β = 0.17; 95% CrI, 0.06 to 0.27), and PFAS (β = 0.19; 95% CrI, 0.14 to 0.24). High-molecular weight phthalate mixtures (β = -0.07; 95% CrI, -0.10 to -0.04) and low-molecular weight phthalate mixtures (β = -0.13; 95% CrI, -0.18 to -0.08) were associated with a decreased MetS score. Most EDC mixtures were associated with elevated proinflammatory proteins, amino acids, and altered glycerophospholipids, which in turn were associated with increased MetS score. This cohort study suggests that prenatal exposure to EDC mixtures may be associated with adverse metabolic health in children. Given the pervasive nature of EDCs and the increase in MetS, these findings hold substantial public health implications.

#2194 Targeted metabolomics analysis identifies a specific metabolomic profile in patients with early chronic kidney disease

Abstract Background and Aims The complex interconnections between various metabolites and the kidney play a major role in the pathogenesis of chronic kidney disease (CKD). Hence, by the assessment of the relationship between metabolites and the kidney, more accurate biomarkers could be discovered to prevent and detect CKD at an early stage. The primary goal of this study was to find new serum and urine biomarkers for the diagnosis of early CKD by conducting a metabolomic profiling through targeted metabolomics of both blood and urine in patients with CKD. Method This cross-sectional study comprised 80 patients with CKD who were categorized into six subgroups (G1-G6) based on their eGFR according to the KDIGO Guidelines. Additionally, 20 healthy individuals were included as healthy control participants (group C). Ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry was used to perform serum and urine metabolomic profiling. The 6 metabolites evaluated by this study were selected based on the results of a previous untargeted analysis research. Both blood and urine samples underwent multivariate analysis, which was subsequently followed by univariate analysis and quantitative analysis. Initially, the PLSDA score plot and VIP score were utilized. The application of the cross-validation procedure to the initial set of 6 molecules provided outstanding results, including high accuracy, high R² values, and a significant Q2 value. Hence, the model might be deemed as predictive. Random Forest analysis was utilized to conduct biomarker analysis and prediction. The specificity and sensitivity of the compounds identified as possible biomarkers were assessed using the Receiver Operating Characteristic (ROC) curve and the area under the curve (AUC). Results There were strong positive correlations between eGFR and serum levels of Arginine (p &amp;lt; 0.05) and L-Acetylcarnitine (p &amp;lt; 0.05). Of note, the amounts of L-Methionine, L-Phenylalanine, Kynurenic acid, and Indoxyl sulfate in serum showed a progressive increase from group C to subgroups G1-G5. Furthermore, L-Methionine, L-Phenylalanine, Kynurenic acid, and Indoxyl sulfate exhibited a negative correlation with eGFR (p &amp;lt; 0.05). In addition, there was a positive correlation between the levels of urine Arginine, L-Methionine, and L-Phenylalanine and eGFR (p &amp;lt; 0.05). Urine levels of Kynurenic acid, Indoxyl sulfate, and L-Acetylcarnitine were higher in groups G4 and G5, as compared to groups G1-G3b and C, respectively. The urinary concentrations of Indoxyl sulfate, Kynurenic acid, Indoxyl sulfate, and L-Acetylcarnitine exhibited a negative correlation with eGFR (p &amp;lt; 0.05). Conclusion The current study shows that serum and urinary metabolites levels in patients with CKD display an alteration in production, secretion, and excretion in all CKD stages. There was demonstrated a distinct metabolomic profile in the course of CKD which points to novel biomarkers useful for the diagnosis and progression evaluation of CKD from its early stages.

Machine learning-based health environmental-clinical risk scores in European children

BackgroundEarly life environmental stressors play an important role in the development of multiple chronic disorders. Previous studies that used environmental risk scores (ERS) to assess the cumulative impact of environmental exposures on health are limited by the diversity of exposures included, especially for early life determinants. We used machine learning methods to build early life exposome risk scores for three health outcomes using environmental, molecular, and clinical data.MethodsIn this study, we analyzed data from 1622 mother-child pairs from the HELIX European birth cohorts, using over 300 environmental, 100 child peripheral, and 18 mother-child clinical markers to compute environmental-clinical risk scores (ECRS) for child behavioral difficulties, metabolic syndrome, and lung function. ECRS were computed using LASSO, Random Forest and XGBoost. XGBoost ECRS were selected to extract local feature contributions using Shapley values and derive feature importance and interactions.ResultsECRS captured 13%, 50% and 4% of the variance in mental, cardiometabolic, and respiratory health, respectively. We observed no significant differences in predictive performances between the above-mentioned methods.The most important predictive features were maternal stress, noise, and lifestyle exposures for mental health; proteome (mainly IL1B) and metabolome features for cardiometabolic health; child BMI and urine metabolites for respiratory health.ConclusionsBesides their usefulness for epidemiological research, our risk scores show great potential to capture holistic individual level non-hereditary risk associations that can inform practitioners about actionable factors of high-risk children. As in the post-genetic era personalized prevention medicine will focus more and more on modifiable factors, we believe that such integrative approaches will be instrumental in shaping future healthcare paradigms.

Estimated daily intake and cumulative risk assessment of organophosphate esters and associations with DNA damage among e-waste workers in Hong Kong

Organophosphate esters (OPEs) are extensively used as additives in various products, including electronic equipment, which becomes e-waste when obsolete. Nevertheless, no study has evaluated OPEs exposure levels and the related health risks among e-waste workers in Hong Kong. Therefore, 201 first-spot morning urine samples were collected from 101 e-waste workers and 100 office workers to compare eight urinary OPE metabolites (mOPEs) levels in these groups. The concentrations of six mOPEs were similar in e-waste workers and office workers, except for significantly higher levels of diphenyl phosphate (DPHP) in e-waste workers and bis(1-chloro-2propyl) phosphate (BCIPP) in office workers. Spearman correlation analysis showed that most non-chlorinated mOPEs were correlated with each other in e-waste workers (i.e., nine out of ten pairs, including di-p-cresyl phosphate (DpCP) and di-o-cresyl phosphate (DoCP), DpCP and bis(2-butoxyethyl) phosphate (BBOEP), DpCP and DPHP, DpCP and dibutyl phosphate (DBP), DoCP and BBOEP, DoCP and DPHP, DoCP and DBP, BBOEP and DPHP, DPHP and DBP), indicating that handling e-waste could be the exposure source of specific OPEs. The median values of estimated daily intake (EDI) and hazard quotient (HQ) suggested that the health risks from OPEs exposures were under the recommended thresholds. However, linear regression models, Quantile g-computation, and Bayesian kernel machine regression found that urinary mOPEs elevated 8-hydroxy-2-deoxyguanosine (8-OhdG) levels individually or as a mixture, in which DPHP contributed prominently. In conclusion, although e-waste might not elevate the internal OPEs levels among the participating Hong Kong e-waste workers, attention should be paid to the potential DNA damage stimulated by OPEs under the currently recommended thresholds.