Urine volatile organic compounds as biomarkers for minimal change type nephrotic syndrome

Exposure to volatile organic compounds and growth indicators in adolescents: Unveiling the association and potential intervention strategies

Environmental pollutant is considered to be one of the important factors affecting adolescent growth. However, the effects of volatile organic compounds (VOCs) exposure on adolescent growth have not been assessed. Data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 was used to examine the associations between VOCs exposure and adolescent growth indicators through three statistical models. The mediating effect of bone mineral density (BMD) on these associations was examined. The potential pathways and key targets were identified by the network pharmacology analysis methods. This study included 746 adolescents. Three statistical methods consistently showed a negative correlation between VOCs exposure and adolescent growth indicators. Furthermore, BMD mediated the relationship between VOCs exposure and adolescent growth indicators, with mediated proportion ranging from 4.3 % to 53.4 %. Network pharmacology analysis found a significant enrichment in IL-17 signaling pathway. Moreover, the adverse effects of VOCs exposure on adolescent growth were observed to significantly attenuate in adolescents with high serum vitamin D levels. Our results suggested that VOCs exposure was an adverse factor affecting adolescent growth, with BMD playing a significant regulatory role, and IL-17 signaling pathway was the underlying mechanism. Vitamin D supplementation may be a viable strategy to prevent VOCs exposure from affecting adolescent growth.

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

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

Association between urinary metabolites of volatile organic compounds and cardiovascular disease in the general population from NHANES 2011-2018

BACKGROUND

Volatile organic compounds (VOCs) contain hundreds of chemicals and human exposure to VOCs is pervasive. However, most studies have considered only a single chemical or a class of similar chemicals.

OBJECTIVE

We aimed to investigate the association between urinary volatile organic compound metabolites (mVOCs) and the risk of cardiovascular disease (CVD) in the general population.

METHODS

The data in this study were collected from the National Health and Nutrition Examination Survey in 2011-2018. Eligible patients were aged ≥20 years for whom complete data for 20 types of urinary mVOCs and CVD outcomes were available. Multivariate logistic regression models were used to elucidate the association between mVOCs and CVD. Generalized additive models were used to examine the nonlinear relationships between mVOCs and CVD.

RESULTS

6814 indiviuals were included in the final analysis, of whom 508 had CVD. Higher urinary concentrations of N-acetyl-S-(2-carboxyethyl)-L-cysteine (CEMA) and N-Acetyl-S-(2-cyanoethyl)-l-cysteine (CYMA) and a lower urinary concentration of 2-aminothiazoline-4-carboxylic acid (ATCA) were associated with CVD outcomes after the adjustment for potential confounding factors. A nonlinear relationship and a threshold effect were only observed between N-acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) and CVD among 20 types of mVOCs. There was a significantly positive correlation between AMCC and CVD when AMCC concentration was >2.32 g/mL.

CONCLUSION

The findings of this study suggested a significant correlation between urinary VOC metabolites and CVD. Urinary mVOCs may indicate hazardous exposure or distinct metabolic traits in patients with CVD.

The untargeted urine volatilome for biomedical applications: methodology and volatilome database

Chemically diverse in compounds, urine can give us an insight into metabolic breakdown products from foods, drinks, drugs, environmental contaminants, endogenous waste metabolites, and bacterial by-products. Hundreds of them are volatile compounds; however, their composition has never been provided in detail, nor has the methodology used for urine volatilome untargeted analysis. Here, we summarize key elements for the untargeted analysis of urine volatilome from a comprehensive compilation of literature, including the latest reports published. Current achievements and limitations on each process step are discussed and compared. 34 studies were found retrieving all information from the urine treatment to the final results obtained. In this report, we provide the first specific urine volatilome database, consisting of 841 compounds from 80 different chemical classes.

Utility of volatile organic compounds as a diagnostic tool in preterm infants

BACKGROUND

Volatile organic compounds (VOCs) are hydrocarbons that originate within different healthy and diseased tissues. VOCs can be secreted into the circulation and then excreted in the urine and faeces. In the lungs, VOCs are locally produced and can be detected in exhaled breath. VOCs can be identified using non-invasive techniques, which make their use in preterm infants safe and desirable.

METHODS

A systematic search of the literature in PubMed, Embase and Web of Science was conducted looking for VOCs techniques and diagnostic performance in preterm infants. A total of 50 articles identified with only seven papers were included in the final analysis in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

RESULTS

VOCs could diagnose necrotising enterocolitis up to 4 days before a clinical diagnosis; for late onset sepsis, up to 3 days before; and for bronchopulmonary dysplasia, up to 2 weeks before. In addition to these diagnostic uses, VOCs analysis could also distinguish breastfed from formula-fed preterm neonates in the first month of life.

CONCLUSION

VOCs analysis is a non-invasive tool that makes the use in preterm infants of preference. VOCs analytic techniques require more research and consensus between researchers to overcome their limitations.

IMPACT

Volatile organic compounds are hydrocarbons that can separate between healthy and diseased states in preterm infants. Biomarker panels developed from volatile organic compounds are potential diagnostic tools. The non-invasive nature of acquiring volatile organic compounds markers make it desirable in the paediatric patients. Research into exact chemical components of the volatile organic compounds can inform about the pathophysiology of disease in preterm infants. More robust longitudinal studies with repeated experiments are required before volatile organic compounds can be applied in clinical practice.

Optimisation of Urine Sample Preparation for Headspace-Solid Phase Microextraction Gas Chromatography-Mass Spectrometry: Altering Sample pH, Sulphuric Acid Concentration and Phase Ratio

Headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) can be used to measure volatile organic compounds (VOCs) in human urine. However, there is no widely adopted standardised protocol for the preparation of urine samples for analysis resulting in an inability to compare studies reliably between laboratories. This paper investigated the effect of altering urine sample pH, volume, and vial size for optimising detection of VOCs when using HS-SPME-GC-MS. This is the first, direct comparison of H₂SO₄, HCl, and NaOH as treatment techniques prior to HS-SPME-GC-MS analysis. Altering urine sample pH indicates that H₂SO₄ is more effective at optimising detection of VOCs than HCl or NaOH. H₂SO₄ resulted in a significantly larger mean number of VOCs being identified per sample (on average, 33.5 VOCs to 24.3 in HCl or 12.2 in NaOH treated urine) and more unique VOCs, produced a more diverse range of classes of VOCs, and led to less HS-SPME-GC-MS degradation. We propose that adding 0.2 mL of 2.5 M H₂SO₄ to 1 mL of urine within a 10 mL headspace vial is the optimal sample preparation prior to HS-SPME-GC-MS analysis. We hope the use of our optimised method for urinary HS-SPME-GC-MS analysis will enhance our understanding of human disease and bolster metabolic biomarker identification.

Application of RRLC-QTOF-MS-based metabonomics and UPE for investigating Spleen-Qi deficiency syndrome with Panax ginseng treatment

ETHNOPHARMACOLOGICAL RELEVANCE

Spleen-Qi deficiency is a syndrome of traditional Chinese medicine. Panax ginseng (ginseng) is well known as the key herb for replenishing Qi and tonifying Spleen. However, the pathogenesis of Spleen-Qi deficiency syndrome and therapeutic mechanism of ginseng on Spleen-Qi deficiency constitution have not yet been entirely elucidated.

AIM OF THE STUDY

The aim of this work was to investigate the pathogenesis of Spleen-Qi deficiency syndrome and therapeutic mechanism of ginseng on Spleen-Qi deficiency constitution.

MATERIALS AND METHODS

The urinary metabonomics was investigated before and after ginseng treatment in Spleen-Qi deficiency subjects by rapid resolution liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (RRLC-QTOF-MS). The spectra of metabolites were analyzed by principal component analysis (PCA) and the score showed significant difference among the three different groups. The serum biochemical parameters creatine kinases (CK), lactate dehydrogenase (LDH), interferon-γ (INF-γ), Interleukin-4 (IL-4), superoxide dismutase (SOD) and malondialdehyde (MDA) were determined by assay kits. In addition, ultraweak photon emission (UPE) intensity was measured at dazhui point in each subject.

RESULTS

According to the orthogonal partial least-squares discriminant analysis (OPLS-DA) results and biochemistry databases searching, 15 potential biomarkers were identified to be involved in Spleen-Qi deficiency syndrome and ginseng influenced Spleen-Qi deficiency. The metabonomics and biological experiment data indicated that metabolism pathways were corresponding to energy metabolism, amino acid, carbohydrate, lipid and pyrimidine metabolisms, oxidative stress urea cycle, and intestinal flora metabolism. And the UPE intensity decreased significantly after the treatment.

CONCLUSIONS

Ginseng could promote the related metabolisms in Spleen-Qi deficiency constitution and the metabolites and UPE intensity may be useful as potential biomarkers for diagnosing and monitoring for Spleen-Qi deficiency syndrome.

Fecal Volatile Organic Compound Profiles are Not Influenced by Gestational Age and Mode of Delivery: A Longitudinal Multicenter Cohort Study

Fecal volatile organic compounds (VOC) reflect human and gut microbiota metabolic pathways and their interaction. VOC behold potential as non-invasive preclinical diagnostic biomarkers in various diseases, e.g., necrotizing enterocolitis and late onset sepsis. There is a need for standardization and assessment of the influence of clinical and environmental factors on the VOC outcome before this technique can be applied in clinical practice. The aim of this study was to investigate the influence of gestational age (GA) and mode of delivery on the fecal VOC pattern in preterm infants born below 30 weeks of gestation. Longitudinal fecal samples, collected on days 7, 14, and 21 postnatally, were analyzed by an electronic nose device (Cyranose 320^®). In total, 58 preterm infants were included (29 infants born at GA 24–26 weeks vs. 29 at 27–29 completed weeks, 24 vaginally born vs. 34 via C-section). No differences were identified at any predefined time point in terms of GA and delivery mode (p > 0.05). We, therefore, concluded that correction for these factors in this population is not warranted when performing fecal VOC analysis in the first three weeks of life.

The smell of longevity: a combination of Volatile Organic Compounds (VOCs) can discriminate centenarians and their offspring from age-matched subjects and young controls

Aging is characterized by dynamic changes at metabolic level that lead to modifications in the composition of the metabolome. Since the identification of biomarkers that can discriminate people of different age and health status has recently attracted a great interest, we wondered whether age-specific changes in the metabolome could be identified and serve as new and informative biomarkers of aging and longevity. In the last few years, a specific branch of metabonomics devoted to the study of volatile organic compounds (VOCs) has been developed. To date, little is known about the profile of specific VOCs in healthy aging and longevity in humans; therefore, we investigated the profile of VOCs in both urine and feces samples from 73 volunteers of different age including centenarians that represent useful "super-controls" to identify potential biomarkers of successful aging and footprints of longevity. To this purpose, we performed a discriminant analysis by which we were able to identify specific profiles of urinary and fecal VOCs. Such profiles can discriminate different age groups, from young to centenarians, and, even more interesting, centenarians' offspring from age-matched controls. Moreover, we were able to identify VOCs that are specific for the couples "centenarians - offspring" or the trios "centenarians - offspring - spouse," suggesting the possible existence of a familiar component also for VOCs profile.

Solid-phase microextraction: An appealing alternative for the determination of endogenous substances - A review

The determination of endogenous substances is of great significance for obtaining important biotic information such as biological components, metabolic pathways and disease biomarkers in different living organisms (e.g. plants, insects, animals and humans). However, due to the complex matrix and the trace concentrations of target analytes, the sample preparation procedure is an essential step before the analytes of interest are introduced into a detection instrument. Solid-phase microextraction (SPME), an emerging sample preparation technique that integrates sampling, extraction, concentration, and sample introduction into one step, has gained wide acceptance in various research fields, including in the determination of endogenous compounds. In this review, recent developments and applications of SPME for the determination of endogenous substances over the past five years are summarized. Several aspects, including the design of SPME devices (sampling configuration and coating), applications (in vitro and in vivo sampling), and coupling with emerging instruments (comprehensive two-dimensional gas chromatography (GC × GC), ambient mass spectrometry (AMS) and surface enhanced Raman scattering (SERS)) are involved. Finally, the challenges and opportunities of SPME methods in endogenous substances analysis are also discussed.

Machine Learning in Human Olfactory Research

The complexity of the human sense of smell is increasingly reflected in complex and high-dimensional data, which opens opportunities for data-driven approaches that complement hypothesis-driven research. Contemporary developments in computational and data science, with its currently most popular implementation as machine learning, facilitate complex data-driven research approaches. The use of machine learning in human olfactory research included major approaches comprising 1) the study of the physiology of pattern-based odor detection and recognition processes, 2) pattern recognition in olfactory phenotypes, 3) the development of complex disease biomarkers including olfactory features, 4) odor prediction from physico-chemical properties of volatile molecules, and 5) knowledge discovery in publicly available big databases. A limited set of unsupervised and supervised machine-learned methods has been used in these projects, however, the increasing use of contemporary methods of computational science is reflected in a growing number of reports employing machine learning for human olfactory research. This review provides key concepts of machine learning and summarizes current applications on human olfactory data.

Urinary excretion of heptanones, heptanoles and 2,5-heptanedione after controlled acute exposure of volunteers to n-heptane

A lack of well-established parameters and assessment values currently impairs biomonitoring of n-heptane exposure. Using controlled inhalation experiments, we collected information on urinary n-heptane metabolite concentrations and the time course of metabolite excretion. Relationships between external and internal exposure were analysed to investigate the suitability of selected metabolites to reflect n-heptane uptake. Twenty healthy, non-smoking males (aged 19-38 years, median 25.5) were exposed for 3 h to 167, 333 and 500 ppm n-heptane, each. Spot urine samples of the volunteers, collected before exposure and during the following 24 h, were analysed for heptane-2-one, 3-one, 4-one, 2,5-dione, 1-ol, 2-ol, 3-ol, and 4-ol using headspace solid phase dynamic extraction gas chromatography/mass spectrometry (HS-SPDE-GC/MS). Starting from median pre-exposure concentrations between <0.5 (3-one) and 82.9 μg/L (4-one), exposure increased the concentrations for all parameters except for 4-one. Median post-exposure concentrations ranged up to 840.4 μg/L (2-ol) and decreased with half-lifes <3 h after exposure. Non-parametric correlation analyses (n = 47, p < 0.05) revealed weak to moderate associations of volume related metabolite excretion with external exposure for 2-one, 3-one and 2,5-dione (R = 0.332-0.753). Heptanol excretion was moderately associated with exposure (R ≥ 0.509) only after creatinine adjustment. Lacking association with external exposure impedes the use of 4-one as heptane biomarker, whereas 2-ol and 3-ol turned out to be sensitive indicators of exposure if creatinine correction is applied. By providing fundamental data on a panel of eight potential heptane metabolites, our study can help to promote biological monitoring of n-heptane exposure.