Metabolomic Analysis Reveals a Unique Urinary Pattern in Normozoospermic Infertile Men

Insight into the complexity of male infertility: a multi-omics review

Male infertility is a reproductive disorder, accounting for 40-50% of infertility. Currently, in about 70% of infertile men, the cause remains unknown. With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging. The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, non-coding RNA, proteins, and metabolites worth further exploring. Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping. A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics. A GO enrichment analysis was performed using the Enrichr tool. We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies. Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent. With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.

Metabolomics of male infertility

This review explores the use of metabolomics in male infertility. Metabolomics, an evolving omics technology that targets the products of cellular metabolism, is valuable for elucidating underlying pathophysiology of many disorders including male infertility. The identification of reliable biomarkers is essential for accurate diagnosis and for developing precision therapeutics for those afflicted by reproductive dysfunction. Unfortunately, despite significant progress to date, the intricate relationships between these metabolic pathways and male infertility remain elusive. It is clear, however, that additional research is required to more fully characterize the role of metabolomics in this disorder and in the potential development of targeted therapies for precision medicine.

Trichinella spiralis -induced immunomodulation signatures on gut microbiota and metabolic pathways in mice

The hygiene hypothesis proposes that decreased exposure to infectious agents in developed countries may contribute to the development of allergic and autoimmune diseases. Trichinella spiralis, a parasitic roundworm, causes trichinellosis, also known as trichinosis, in humans. T. spiralis had many hosts, and almost any mammal could become infected. Adult worms lived in the small intestine, while the larvae lived in muscle cells of the same mammal. T. spiralis was a significant public health threat because it could cause severe illness and even death in humans who eat undercooked or raw meat containing the parasite. The complex interactions between gastrointestinal helminths, gut microbiota, and the host immune system present a challenge for researchers. Two groups of mice were infected with T. spiralis vs uninfected control, and the experiment was conducted over 60 days. The 16S rRNA gene sequences and untargeted LC/MS-based metabolomics of fecal and serum samples, respectively, from different stages of development of the Trichinella spiralis-mouse model, were examined in this study. Gut microbiota alterations and metabolic activity accompanied by parasite-induced immunomodulation were detected. The inflammation parameters of the duodenum (villus/crypt ratio, goblet cell number and size, and histological score) were involved in active inflammation and oxidative metabolite profiles. These profiles included increased biosynthesis of phenylalanine, tyrosine, and tryptophan while decreasing cholesterol metabolism and primary and secondary bile acid biosynthesis. These disrupted metabolisms adapted to infection stress during the enteral and parenteral phases and then return to homeostasis during the encapsulated phase. There was a shift from an abundance of Bacteroides in the parenteral phase to an abundance of probiotic Lactobacillus and Treg-associated-Clostridia in the encapsulated phase. Th2 immune response (IL-4/IL-5/IL-13), lamina propria Treg, and immune hyporesponsiveness metabolic pathways (decreased tropane, piperidine and pyridine alkaloid biosynthesis and biosynthesis of alkaloids derived from ornithine, lysine, and nicotinic acid) were all altered. These findings enhanced our understanding of gut microbiota and metabolic profiles of Trichinella -infected mice, which could be a driving force in parasite-shaping immune system maintenance.

Exploring the internal exposome of seminal plasma with semen quality and live birth: A Pilot Study

Infertility is clinically defined as the inability to achieve pregnancy within 12 months of regular unprotected sexual intercourse and affects 15% of couples worldwide. Therefore, the identification of novel biomarkers that can accurately predict male reproductive health and couples' reproductive success is of major public health significance. The objective of this pilot study is to test whether untargeted metabolomics is capable of discriminating reproductive outcomes and understand associations between the internal exposome of seminal plasma and the reproductive outcomes of semen quality and live birth among ten participants undergoing assisted reproductive technology (ART) in Springfield, MA. We hypothesize that seminal plasma offers a novel biological matrix by which untargeted metabolomics is able to discern male reproductive status and predict reproductive success. The internal exposome data was acquired using UHPLC-HR-MS on randomized seminal plasma samples at UNC at Chapel Hill. Unsupervised and supervised multivariate analyses were used to visualize the differentiation of phenotypic groups classified by men with normal or low semen quality based on World Health Organization guidelines as well as by successful ART: live birth or no live birth. Over 100 exogenous metabolites, including environmentally relevant metabolites, ingested food components, drugs and medications, and metabolites relevant to microbiome-xenobiotic interaction, were identified and annotated from the seminal plasma samples, through matching against the NC HHEAR hub in-house experimental standard library. Pathway enrichment analysis indicated that fatty acid biosynthesis and metabolism, vitamin A metabolism, and histidine metabolism were associated sperm quality; while pathways involving vitamin A metabolism, C21-steroid hormone biosynthesis and metabolism, arachidonic acid metabolism, and Omega-3 fatty acid metabolism distinguished live birth groups. Taken together, these pilot results suggest that seminal plasma is a novel matrix to study the influence of the internal exposome on reproductive health outcomes. Future research aims to increase the sample size to validate these findings.

Metabolomic investigation of urinary extracellular vesicles for early detection and screening of lung cancer

Lung cancer is a prevalent cancer type worldwide that often remains asymptomatic in its early stages and is frequently diagnosed at an advanced stage with a poor prognosis due to the lack of effective diagnostic techniques and molecular biomarkers. However, emerging evidence suggests that extracellular vesicles (EVs) may promote lung cancer cell proliferation and metastasis, and modulate the anti-tumor immune response in lung cancer carcinogenesis, making them potential biomarkers for early cancer detection. To investigate the potential of urinary EVs for non-invasive detection and screening of patients at early stages, we studied metabolomic signatures of lung cancer. Specifically, we conducted metabolomic analysis of 102 EV samples and identified metabolome profiles of urinary EVs, including organic acids and derivatives, lipids and lipid-like molecules, organheterocyclic compounds, and benzenoids. Using machine learning with a random forest model, we screened for potential markers of lung cancer and identified a marker panel consisting of Kanzonol Z, Xanthosine, Nervonyl carnitine, and 3,4-Dihydroxybenzaldehyde, which exhibited a diagnostic potency of 96% for the testing cohort (AUC value). Importantly, this marker panel also demonstrated effective prediction for the validation set, with an AUC value of 84%, indicating the reliability of the marker screening process. Our findings suggest that the metabolomic analysis of urinary EVs provides a promising source of non-invasive markers for lung cancer diagnostics. We believe that the EV metabolic signatures could be used to develop clinical applications for the early detection and screening of lung cancer, potentially improving patient outcomes.

Germ cell-specific proteins AKAP4 and ASPX facilitate identification of rare spermatozoa in non-obstructive azoospermia

Non-obstructive azoospermia (NOA), the most severe form of male infertility, could be treated with intra-cytoplasmic sperm injection, providing spermatozoa were retrieved with the microdissection testicular sperm extraction (mTESE). We hypothesized that testis- and germ cell-specific proteins would facilitate flow cytometry-assisted identification of rare spermatozoa in semen cell pellets of NOA patients, thus enabling non-invasive diagnostics prior to mTESE. Data mining, targeted proteomics, and immunofluorescent microscopy identified and verified a panel of highly testis-specific proteins expressed at the continuum of germ cell differentiation. Late germ cell-specific proteins AKAP4_HUMAN and ASPX_HUMAN (ACRV1 gene) revealed exclusive localization in spermatozoa tails and acrosomes, respectively. A multiplex imaging flow cytometry assay facilitated fast and unambiguous identification of rare but morphologically intact AKAP4⁺/ASPX⁺/Hoechst⁺ spermatozoa within debris-laden semen pellets of NOA patients. While the previously suggested markers for spermatozoa retrieval suffered from low diagnostic specificity, the multi-step gating strategy and visualization of AKAP4⁺/ASPX⁺/Hoechst⁺ cells with elongated tails and acrosome-capped nuclei facilitated fast and unambiguous identification of the mature intact spermatozoa. AKAP4⁺/ASPX⁺/Hoechst⁺ assay may emerge as a non-invasive test to predict retrieval of morphologically intact spermatozoa by mTESE, thus improving diagnostics and treatment of severe forms of male infertility.

Maternal exposure to ambient PM2.5 perturbs the metabolic homeostasis of maternal serum and placenta in mice

Epidemiological and animal studies have shown that maternal fine particulate matters (PM_2.5) exposure correlates with various adverse pregnancy outcomes such as low birth weight (LBW) of offspring. However, the underlying biological mechanisms have not been fully understood. In this study, female C57Bl/6 J mice were exposed to filtered air (FA) or concentrated ambient PM_2.5 (CAP) during pregestational and gestational periods, and metabolomics was performed to analyze the metabolic features in maternal serum and placenta by liquid chromatography-mass spectrometry (LC-MS). The partial least squares discriminate analysis (PLS-DA) displayed evident clustering of FA- and CAP-exposed samples for both maternal serum and placenta. In addition, pathway analysis identified that vitamin digestion and absorption was perturbed in maternal serum, while metabolic pathways including arachidonic acid metabolism, serotonergic synapse, 2-oxocarboxylic acid metabolism and cAMP signaling pathway were perturbed in placenta. Further analysis indicated that CAP exposure influenced the nutrient transportation capacity of placenta, by not only changing the ratios of some critical metabolites in placenta to maternal serum but also significantly altering the expressions of nutrition transporters in placenta. These findings reaffirm the importance of protecting women from PM_2.5 exposure, and also advance our understanding of the toxic actions of ambient PM_2.5.

Environmental metal exposure, seminal plasma metabolome and semen quality: Evidence from Chinese reproductive-aged men

Environmental metal exposure has been associated with decreasing semen quality, but the effects of multiple metal exposure on seminal plasma metabolome remain obscure. In this study, semen and repeated urine samples from 551 volunteers were collected in Wuhan City. Heavy metals and trace elements were measured using inductively coupled plasma mass spectrometer, and seminal plasma metabolomes were acquired using liquid chromatography coupled with high-resolution mass spectrometry. Weighted gene co-expression network analysis showed more than half of the seminal plasma metals were associated with specific metabolite modules, whereas only a few urine metals presented weak associations, indicating that seminal plasma may be an ideal biological sample for male reproductive biomarker discovery and exposure risk assessment. Seminal plasma zinc (Zn) and selenium (Se) concentrations were significantly associated with 22 metabolites (e.g., glycerophospholipids, acyl-carnitines and amino acid derivatives). Among these metabolites, acyl-carnitines were positively associated with semen quality and sperm concentration. Moreover, acyl-carnitines were associated with both Zn and Se exposure, indicating the potential role of carnitine pathway in their toxicity mechanism. Our findings suggest that seminal plasma metabolome connects Zn and Se exposure and sperm concentrations in Chinese men of reproductive age.

Ultra-Performance Liquid Chromatography-Mass Spectrometry-Based Untargeted Metabolomics Reveals the Key Potential Biomarkers for Castor Meal-Induced Enteritis in Juvenile Hybrid Grouper (Epinephelus fuscoguttatus♀ × E. lanceolatus♂)

The intensification of aquaculture to help kerb global food security issues has led to the quest for more economical new protein-rich ingredients for the feed-based aquaculture since fishmeal (FM, the ingredient with the finest protein and lipid profile) is losing its acceptability due to high cost and demand. Although very high in protein, castor meal (CM), a by-product after oil-extraction, is disposed-off due to the high presence of toxins. Concurrently, the agro-industrial wastes’ consistent production and disposal are of utmost concern; however, having better nutritional profiles of these wastes can lead to their adoption. This study was conducted to identify potential biomarkers of CM-induced enteritis in juvenile hybrid-grouper (Epinephelus fuscoguttatus♀ × Epinephelus lanceolatus♂) using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) alongside their growth and distal intestinal (DI) health evaluation. A total of 360 fish (initial weight = 9.13 ± 0.01g) were randomly assigned into three groups, namely, fish-meal (FM) (control), 4% CM (CM4), and 20% CM (CM20). After the 56-days feeding-trial, the DI tissues of FM, CM4, and CM20 groups were collected for metabolomics analysis. Principal components analysis and partial least-squares discriminant-analysis (PLS-DA, used to differentiate the CM20 and CM4, from the FM group with satisfactory explanation and predictive ability) were used to analyze the UPLC-MS data. The results revealed a significant improvement in the growth, DI immune responses and digestive enzyme activities, and DI histological examinations in the CM4 group than the others. Nonetheless, CM20 replacement caused DI physiological damage and enteritis in grouper as shown by AB-PAS staining and scanning electron microscopy examinations, respectively. The most influential metabolites in DI contents identified as the potential biomarkers in the positive and negative modes using the metabolomics UPLC-MS profiles were 28 which included five organoheterocyclic compounds, seven lipids, and lipid-like molecules, seven organic oxygen compounds, two benzenoids, five organic acids and derivatives, one phenylpropanoids and polyketides, and one from nucleosides, nucleotides, and analogues superclass. The present study identified a broad array of DI tissue metabolites that differed between FM and CM diets, which provides a valuable reference for further managing fish intestinal health issues. A replacement level of 4% is recommended based on the growth and immunity of fish.

Non-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review

OBJECTIVE

To summarize the application of non-targeted metabolomics in epidemiological studies that assessed metabolite and metabolic pathway alterations associated with per- and polyfluoroalkyl substances (PFAS) exposure.

RECENT FINDINGS

Eleven human studies published before April 1st, 2021 were identified through database searches (PubMed, Dimensions, Web of Science Core Collection, Embase, Scopus), and citation chaining (Citationchaser). The sample sizes of these studies ranged from 40 to 965, involving children and adolescents (n = 3), non-pregnant adults (n = 5), or pregnant women (n = 3). High-resolution liquid chromatography-mass spectrometry was the primary analytical platform to measure both PFAS and metabolome. PFAS were measured in either plasma (n = 6) or serum (n = 5), while metabolomic profiles were assessed using plasma (n = 6), serum (n = 4), or urine (n = 1). Four types of PFAS (perfluorooctane sulfonate(n = 11), perfluorooctanoic acid (n = 10), perfluorohexane sulfonate (n = 9), perfluorononanoic acid (n = 5)) and PFAS mixtures (n = 7) were the most studied. We found that alterations to tryptophan metabolism and the urea cycle were most reported PFAS-associated metabolomic signatures. Numerous lipid metabolites were also suggested to be associated with PFAS exposure, especially key metabolites in glycerophospholipid metabolism which is critical for biological membrane functions, and fatty acids and carnitines which are relevant to the energy supply pathway of fatty acid oxidation. Other important metabolome changes reported included the tricarboxylic acid (TCA) cycle regarding energy generation, and purine and pyrimidine metabolism in cellular energy systems.

CONCLUSIONS

There is growing interest in using non-targeted metabolomics to study the human physiological changes associated with PFAS exposure. Multiple PFAS were reported to be associated with alterations in amino acid and lipid metabolism, but these results are driven by one predominant type of pathway analysis thus require further confirmation. Standardizing research methods and reporting are recommended to facilitate result comparison. Future studies should consider potential differences in study methodology, use of prospective design, and influence from confounding bias and measurement errors.

Effects of varicocele and microsurgical varicocelectomy on the metabolites in semen

The influence of varicocele and microsurgical varicocelectomy on semen quality remains unclear. Few studies have investigated the relationship between semen metabolism and the abnormalities in reproductive function caused by varicocele, however, there is no study on the changes of semen metabolism after microsurgical varicocelectomy. Here, we used the non-targeted and targeted metabolic analysis to investigate the different metabolites in seminal plasma within normal, varicocele, and varicocelectomy groups. We clearly showed that varicocele significantly affects semen metabolism, and microsurgical varicocelectomy can reverse this metabolic abnormality. Moreover, we characterized the landscape of three dipeptides in the seminal plasma of patients with varicocele that have not been identified previously in human tissues or biofluids. Interestingly, the levels of these three dipeptides decreased after microsurgical varicocelectomy coincident with an improvement in semen quality. Western blotting confirmed the downregulation of DPEP3 (dipeptidase 3) in the varicocele group and the upregulation of DPEP3 in the varicocelectomy group. Furthermore, we found that eight metabolites may be helpful to distinguish varicocele patients from normal subjects. Our results may be applied to earlier diagnosis or to predict the outcome of microsurgery for varicocele.

Biomarkers of Mycoplasma pneumoniae pneumonia in children by urine metabolomics based on Q Exactive liquid chromatography/tandem mass spectrometry

RATIONALE

Mycoplasma pneumoniae has become one of the common pathogens causing pediatric respiratory infections. In clinical diagnosis, throat swabs are very difficult to obtain from children, and there is a possibility of false positive results; hence, there are few clinically available diagnostic methods.

METHODS

In this study, Q Exactive liquid chromatography/tandem mass spectrometry was used to analyze the metabolites in the urine of healthy children (HC) and M. pneumoniae pneumonia in children (MPPC) patients. A multivariate statistical analysis was performed to screen the differential metabolites. Based on the HMDB and KEGG, the possible metabolic pathways subject to biological alteration were identified.

RESULTS

Compared with HC, 73 different metabolites in MPPC patients disrupted nine metabolic pathways through different change trends; after integrating various parameters, 20 significantly different metabolites were identified as MPPC potential biomarkers. Through the above two analysis modes, acetylphosphate and 2,5-dioxopentanoate were both screened out and used as potential biomarkers for the early diagnosis of MPPC for the first time.

CONCLUSIONS

The characterization of 20 potential biomarkers provides a scientific basis for predicting and diagnosing MPPC. This article further indicates that urine metabolic profiling has great potential in diagnosing MPPC and can effectively prevent the disease from causing further deterioration.

Comprehensive Targeted Metabolomic Study in the Lung, Plasma, and Urine of PPE/LPS-Induced COPD Mice Model

(1) Background: Progression of chronic obstructive pulmonary disease (COPD) leads to irreversible lung damage and inflammatory responses; however, biomarker discovery for monitoring of COPD progression remains challenging. (2) Methods: This study evaluated the metabolic mechanisms and potential biomarkers of COPD through the integrated analysis and receiver operating characteristic (ROC) analysis of metabolic changes in lung, plasma, and urine, and changes in morphological characteristics and pulmonary function in a model of PPE/LPS-induced COPD exacerbation. (3) Results: Metabolic changes in the lungs were evaluated as metabolic reprogramming to counteract the changes caused by the onset of COPD. In plasma, several combinations of phenylalanine, 3-methylhistidine, and polyunsaturated fatty acids have been proposed as potential biomarkers; the α-aminobutyric acid/histidine ratio has also been reported, which is a novel candidate biomarker for COPD. In urine, a combination of succinic acid, isocitric acid, and pyruvic acid has been proposed as a potential biomarker. (4) Conclusions: This study proposed potential biomarkers in plasma and urine that reflect altered lung metabolism in COPD, concurrently with the evaluation of the COPD exacerbation model induced by PPE plus LPS administration. Therefore, understanding these integrative mechanisms provides new insights into the diagnosis, treatment, and severity assessment of COPD.

Glucose metabolism enhancement by 10-hydroxy-2-decenoic acid via the PI3K/AKT signaling pathway in high-fat-diet/streptozotocin induced type 2 diabetic mice

Here, we used high fat diet (HFD) combined with streptozotocin (STZ) injection to establish a diabetes model, with the aim of exploring the hypoglycemic effects of 10-hydroxy-2-decenoic acid (10-HDA), and...

Analytical aspects of meet-in-metabolite analysis for molecular pathway reconstitution from exposure to adverse outcome

To explore the etiology of diseases is one of the major goals in epidemiological study. Meet-in-metabolite analysis reconstitutes biomonitoring-based adverse outcome (AO) pathways from environmental exposure to a disease, in which the chemical exposome-related metabolism responses are transmitted to incur the AO-related metabolism phenotypes. However, the ongoing data-dependent acquisition of non-targeted biomonitoring by high-resolution mass spectrometry (HRMS) is biased against the low abundance molecules, which forms the major of molecular internal exposome, i.e., the totality of trace levels of environmental pollutants and/or their metabolites in human samples. The recent development of data-independent acquisition protocols for HRMS screening has opened new opportunities to enhance unbiased measurement of the extremely low abundance molecules, which can encompass a wide range of analytes and has been applied in metabolomics, DNA, and protein adductomics. In addition, computational MS for small molecules is urgently required for the top-down exposome databases. Although a holistic analysis of the exposome and endogenous metabolites is plausible, multiple and flexible strategies, instead of "putting one thing above all" are proposed.

Cardiorespiratory Effects of Indoor Ozone Exposure Associated with Changes in Metabolic Profiles among Children: A Repeated-Measure Panel Study

Ozone is one of the major gaseous pollutants associated with short-term adverse cardiopulmonary effects, even at concentrations below the current indoor air quality limits. However, the underlying biological mechanisms of cardiorespiratory changes with exposure to ozone remain unclear. To further explore molecular linkages between indoor ozone exposure and relevant cardiorespiratory effects, a repeated-measure panel study including 46 schoolchildren was conducted and real-time exposure measurements including ozone were performed inside classrooms every weekday during the study period. Repeated health measurements and urine sample collection were conducted in each participant. Ultra-high-performance liquid chromatography/tandem mass spectrometry and meet-in-metabolite approach were used in metabolomics analysis. Methods including mixed-effect models were adopted to identify metabolites associated with ozone exposure or health indices. Nine metabolites were found to be associated with ozone after mixed-effect model analysis, which are mainly involved in amino acid and bile acid metabolism. Boys may have a greater decrease in bile acid and RNA related metabolites. Four of the nine ozone-related metabolites were also associated with cardiorespiratory function indices. Furthermore, 26.67% of the positive association between ozone and heart rate was mediated by cholestane-3,7,12,25-tetrol-3-glucuronide. Exposure to ozone below the current indoor standards was associated with the deteriorated cardiovascular function by disturbing bile acid and endogenous nitric oxide-related oxidation and inflammation, and associated with the exacerbated airway inflammation by reducing GPx-related anti-oxidation. The results provide metabolic evidence of the cardiorespiratory effects of indoor ozone exposure. Indoor ozone pollution should be controlled further, and more attention should be paid to preventing its adverse health effects, especially in children.

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Indoor O₃ exposure far below the indoor air quality limits disturbed amino acid and bile acid metabolism of children

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Exposure to indoor O₃ at low concentrations was associated with the deteriorated HRV, BP by affecting bile acid- and endogenous NO-related oxidation and inflammation

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Exposure to indoor O₃ at low concentrations was associated with the aggravated airway inflammation by reducing GPx-related anti-oxidation

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The cardiorespiratory effects of low-level ozone exposure indoors in children require additional attention

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Indoor ozone pollution should be controlled further and the current indoor ozone standards should be revised

Meet-in-metabolite analysis: A novel strategy to identify connections between arsenic exposure and male infertility

BACKGROUND

Despite a trend in the use of systems epidemiology to fill the knowledge gap between risk-factor exposure and adverse outcomes in the OMICS data, such as the metabolome, seriously hindrances need to be overcome for identifying molecular connections.

OBJECTIVES

Using male infertility phenotypes and arsenic exposure, we aimed to identify intermediate biomarkers that reflect both arsenic exposure and male infertility with a meet-in-metabolite analysis (MIMA).

METHODS

Urinary arsenic levels and metabolome were measured by using inductively coupled plasma-mass spectrometry (ICP-MS) and HPLC-quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS), respectively. To identify arsenic-related metabolic markers (A-MIMA), the intermediate markers were profiled by orthogonal projections to latent structures (OPLS-DA). To detect infertility-related metabolic markers (I-MIMA), the intermediate markers were investigated by weighted gene co-expression network analysis. The key node markers, related to both A-MIMA and I-MIMA, were determined by O2PLS and defined as MIMA markers. Finally, network analysis was used to construct the MIMA-related metabolic network.

RESULTS

Twelve markers each were defined through the significant associations with arsenic exposure (A-MIMA) and/or infertility (I-MIMA), respectively. Seven of them, including acetyl-N-formyl-5-methoxykynurenamine, carnitine, estrone, 2-oxo-4-methylthiobutanoic acid, malonic acid, valine, and LysoPC (10:0), were defined through the associations with both arsenic exposure and male infertility (MIMA markers). These intermediate markers were involved majorly in oxidative stress, one-carbon metabolism, steroid hormone homeostasis, and lipid metabolism pathways. The core correlation network analysis further highlighted that testosterone is a vital link between the effect of arsenic and male infertility.

CONCLUSIONS

From arsenic exposure to male infertility, the arsenic methylation that coupled one-carbon metabolism disruption with oxidation stress may have extended its effect to fatty acid oxidation and steroidogenesis dysfunction. Testosterone is at the hub between arsenic exposure and male infertility modules and, along with the related metabolic pathways, may service as a potential surrogate marker in risk assessment for male dysfunction due to arsenic exposure.

Proteomics and metabolomics - Current and future perspectives in clinical andrology

Proteomics and metabolomics are emerging as promising tools to investigate the molecular mechanisms associated with male infertility. Proteins and metabolites play a pivotal role in regulating the molecular pathways associated with physiological functions of spermatozoa. Semen analysis, physical examination and laboratory work up cannot identify the etiology of infertility in 30%-40% of cases, which are classified as idiopathic. Therefore, the application of proteomics and metabolomics in the field of andrology will aid to overcome the limitations of the standard semen analysis. Understanding the molecular pathways associated with male infertility will help in planning ad hoc treatments, contributing to the clinical management of infertile patients. In this review, proteomics and metabolomics studies on spermatozoa and seminal plasma are discussed with a focus on molecular biomarkers associated with male infertility-related conditions.

Seminal plasma metabolites mediate the associations of multiple environmental pollutants with semen quality in Chinese men

Environmental exposure to arsenic, phthalate esters (PAEs) and perfluorinated compounds (PFCs) has been associated with human semen quality. However, the epidemiological "black-box" of these associations remains poorly uncovered. In this study, based on the association analysis between arsenic, PAE and PFC exposure and semen quality parameters (i.e., semen volume, sperm concentration, sperm count, progressive motility, total motility and normal morphology) in a Chinese male population, we explored the seminal plasma metabolic signatures that may mediate the exposure-outcome relations by using the meet-in-metabolite-analysis (MIMA) approach. As a result, a negative association was found between DMA and sperm concentration, whereas MEHP and PFHxS were positively associated with sperm count and concentration, respectively. Metabolomics analysis revealed that sixteen and twenty-two seminal plasma metabolites were related to sperm concentration and count, respectively, and they are mainly involved in fatty acid, lipid and amino acid metabolism. Moreover, it was further indicated that eicosatetraenoate, carnitines and DHA may impact the inverse association between DMA and sperm concentration, while eicosatetraenoate, carnitines, DHA, PGB2 and tocotrienol are possible mediators of the positive association between PFHxS and sperm concentration. As these metabolic biomarkers are relevant to antioxidation and fatty acid β-oxidation, we suggest that redox balance and energy generation shifts in seminal plasma are involved in the association of human semen quality with environmental DMA and PFHxS exposure.

Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics

Semen abnormality (SA) male infertility has become a worldwide reproductive health problem. The invasive tests (e.g., testicular biopsy) and labor-intensive methods of semen collection severely inhibit diagnosis of male infertility. In addition, the pathogenesis and biological interpretation of male infertility are still obscure. In this report, a total of 84 semen abnormality (SA) patients, diagnosed as teratozoospermia (TE, n = 21), asthenozoospermia (AS, n = 23), oligozoospermia (OL, n = 20), azoospermia (AZ, n = 20), and age-matched healthy controls (HC, n = 29) were analyzed by GC-MS for discrimination analysis and discovery of potential biomarkers. Twenty-three biomarkers were obtained by multivariate statistical method (partial least squares-discriminant analysis, PLS-DA) and univariate statistical method (analysis of variance, ANOVA) with comparisons of TE versus HC, AS versus HC, OL versus HC and AZ versus HC. Based on those biomarkers, the most relevant pathways were mainly associated with the metabolism of carbohydrates, amino acids, and lipids. The principal metabolic alternations in SA male infertility included increased levels of energy-related metabolisms, such as tricarboxylic acid cycle, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, glycine, serine, threonine metabolism and saturated fatty acid metabolism. Furthermore, increased levels of glutathione metabolism were related to oxidative stress. Finally, decreased levels of arginine and proline metabolism and inositol phosphate metabolism were observed. In conclusion, blood plasma metabolomics is powerful for characterizing metabolic disturbances in SA male infertility. From metabolic pathway analysis, energy production, oxidation stress and the released enzyme during spermatogenesis take the primary responsibilities for SA male infertility.

The modification of indoor PM2.5 exposure to chronic obstructive pulmonary disease in Chinese elderly people: A meet-in-metabolite analysis

BACKGROUND

Exposure to airborne fine particulate matter (PM_2.5) has been associated with a variety of adverse health outcomes including chronic obstructive pulmonary disease (COPD). However, the linkages between PM_2.5 exposure, PM_2.5-related biomarkers, COPD-related biomarkers and COPD remain poorly elucidated.

OBJECTIVES

To investigate the linkages between PM_2.5 exposure and COPD outcome by using the meet-in-middle strategy based on urinary metabolic biomarkers.

METHODS

A cross-sectional study was designed to illustrate the mentioned quadripartite linkages. Indoor PM_2.5 and its element components were assessed in 41 Chinese elderly participants including COPD patients and their healthy spouses. Metabolic biomarkers involved in PM_2.5 exposure and COPD were identified by using urinary metabolomics. The associations between PM_2.5- and COPD-related biomarkers were investigated by statistics and metabolic pathway analysis.

RESULTS

Seven metabolites were screened and identified with significant correlations to PM_2.5 exposure, which were majorly involved in purine and amino acid metabolism as well as glycolysis. Ten COPD-related metabolic biomarkers were identified, which suggested that amino acid metabolism, lipid and fatty acid metabolism, and glucose metabolism were disturbed in the patients. Also, PM_2.5 and its many elemental components were significantly associated with COPD-related biomarkers. We observed that the two kinds of biomarkers (PM_2.5- and COPD-related) integrated in a locally connected network and the alterations of these metabolic biomarkers can biologically link PM_2.5 exposure to COPD outcome.

CONCLUSIONS

Our study indicated the modification of PM_2.5 to COPD via both modes of action of lowering participants' antioxidation capacity and decreasing their lung energy generation; this information would be valuable for the prevention strategy of COPD.

Tests for comparison of multiple endpoints with application to omics data

In biomedical research, multiple endpoints are commonly analyzed in "omics" fields like genomics, proteomics and metabolomics. Traditional methods designed for low-dimensional data either perform poorly or are not applicable when analyzing high-dimensional data whose dimension is generally similar to, or even much larger than, the number of subjects. The complex biochemical interplay between hundreds (or thousands) of endpoints is reflected by complex dependence relations. The aim of the paper is to propose tests that are very suitable for analyzing omics data because they do not require the normality assumption, are powerful also for small sample sizes, in the presence of complex dependence relations among endpoints, and when the number of endpoints is much larger than the number of subjects. Unbiasedness and consistency of the tests are proved and their size and power are assessed numerically. It is shown that the proposed approach based on the nonparametric combination of dependent interpoint distance tests is very effective. Applications to genomics and metabolomics are discussed.

Metabolic profiling putatively identifies plasma biomarkers of male infertility using UPLC-ESI-IT-TOFMS

Male infertility has become a global health problem. Currently, the diagnosis of male infertility depends on the results of semen quality or requires invasive surgical intervention. The process is complex and time-consuming. Metabolomics is an emerging platform with unique advantages in disease diagnosis and pathological mechanism research. In this study, ultra-performance liquid chromatography-electrospray ionization-ion trap-time of flight mass spectrometry (UPLC-ESI-IT-TOFMS) combined with chemometrics methods was used to discover potential biomarkers of male infertility based on non-targeted plasma metabolomics. Plasma samples from healthy controls (HC, n = 43) and various types of infertile patients, i.e., patients having oligozoospermia (OS, n = 36), asthenospermia (AS, n = 56) and erectile dysfunction (ED, n = 45) were analyzed by UPLC-ESI-IT-TOFMS. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed. The results of OPLS-DA showed that HCs could be discriminated from infertile patients including OS (R² = 0.903, Q² = 0.617, AUC = 0.992), AS (R² = 0.985, Q² = 0.658, AUC = 0.999) or ED (R² = 0.942, Q² = 0.500, AUC = 0.998). Some potential biomarkers were successfully discovered by variable selection methods and variable important in the projection (VIP) in combination with the T-test. Statistical significance was set at p < 0.05; the Benjamini–Hochberg false discovery rate was used to reduce type 1 errors resulting from multiple comparisons. The identified biomarkers were associated with energy consumption, hormone regulation and antioxidant defenses in spermatogenesis. To elucidate the pathophysiology of male infertility, relative metabolic pathways were studied. It was found that male infertility is closely related to disturbed phospholipid metabolism, amino acid metabolism, steroid hormone biosynthesis metabolism, metabolism of fatty acids and products of carnitine acylation, and purine and pyrimidine metabolisms. Plasma metabolomics provides a novel strategy for the diagnosis of male infertility and offers a new insight to study pathogenesis mechanism.

Ultra-performance liquid chromatography-electrospray ionization-ion trap-time of flight mass spectrometry combined with chemometrics methods was used to discover potential biomarkers of male infertility based on untargeted plasma metabolomics.

Phthalate metabolites related to infertile biomarkers and infertility in Chinese men

Although in vitro and in vivo laboratory studies have demonstrated androgen and anti-androgen effects on male reproduction from phthalate exposures, human studies still remain inconsistent. Therefore, a case-control study (n = 289) was conducted to evaluate the associations between phthalate exposures, male infertility risks, and changes in metabolomic biomarkers. Regional participants consisted of fertile (n = 150) and infertile (n = 139) males were recruited from Nanjing Medical University' affiliated hospitals. Seven urinary phthalate metabolites were measured using HPLC-MS/MS. Associations between levels of phthalate metabolites, infertility risks, and infertility-related biomarkers were statistically evaluated. MEHHP, one of the most abundant DEHP oxidative metabolites was significantly lower in cases than in controls (p = 0.039). When using the 1st quartile range as a reference, although statistically insignificant for odds ratios (ORs) of the 2nd, 3rd, and 4th quartiles (OR (95% CI) = 1.50 (0.34-6.48), 0.70 (0.14-3.52) and 0.42 (0.09-2.00), respectively), the MEHHP dose-dependent trend of infertility risk expressed as OR decreased significantly (p = 0.034). More interestingly, most of the phthalate metabolites, including MEHHP, were either positively associated with fertile prevention metabolic biomarkers or negatively associated with fertile hazard ones. Phthalate metabolism, along with their activated infertility-related biomarkers, may contribute to a decreased risk of male infertility at the subjects' ongoing exposure levels. Our results may be illustrated by the low-dose related androgen effect of phthalates and can improve our understanding of the controversial epidemiological results on this issue.

Serum metabolome biomarkers associate low-level environmental perfluorinated compound exposure with oxidative /nitrosative stress in humans

Previous in vivo and in vitro studies have linked perfluorinated compound (PFC) exposure with metabolic interruption, but the inter-species difference and high treatment doses usually make the results difficult to be extrapolated to humans directly. The best strategy for identifying the metabolic interruption may be to establish the direct correlations between monitored PFCs data and metabolic data on human samples. In this study, serum metabolome data and PFC concentrations were acquired for a Chinese adult male cohort. The most abundant PFCs are PFOA and PFOS with concentration medians 7.56 and 12.78 nM, respectively; in together they count around 81.6% of the total PFCs. PFC concentration-related serum metabolic profile changes and the related metabolic biomarkers were explored by using partial least squares-discriminant analysis (PLS-DA). Respectively taking PFOS, PFOA and total PFC as the classifiers, serum metabolome can be differentiated between the lowest dose group (1st quartile PFCs) and the highest PFC dose group (4th quartile PFCs). Ten potential PFC biomarkers were identified, mainly involving in pollutant detoxification, antioxidation and nitric oxide (NO) signal pathways. These suggested that low-level environmental PFC exposure has significantly adverse impacts on glutathione (GSH) cycle, Krebs cycle, nitric oxide (NO) generation and purine oxidation in humans. To the best of our knowledge, this is the first report investigating the association of environmental PFC exposure with human serum metabolome alteration. Given the important biological functions of the identified biomarkers, we suggest that PFC could increase the metabolism syndromes risk including diabetes and cardiovascular diseases.

Obesity aggravates toxic effect of BPA on spermatogenesis

Both bisphenol A (BPA) and obesity affect male reproductive system. However, whether there is an interaction between them remains poorly understood. The aim of the present study was to evaluate the interaction between BPA exposure and obesity on semen quality and elucidate the mechanism in humans and animals. We firstly analyzed the interaction on semen volume, sperm count per ejaculate, sperm concentration and sperm motility in 357 men, and found that urinary BPA concentration was significantly correlated with sperm count per ejaculate in obese men (β=-34.62; 95% CI: -60.75, -8.48; P=0.01). Then we validated the interaction using lean and obese mice with administration of BPA. Significant interactions between BPA exposure and obesity on sperm count and sperm concentration was observed in mice. Finally, we conducted metabolomics analyses to identify metabolites related to the interaction. Metabolites related to the interaction, including capric acid, dodecanoic acid, l-palmitoylcarnitine, niacinamide, etc., are known to play critical roles in fatty acid oxidation and tricarboxylic acid cycle indicating increased oxidative stress associated with male reproductive dysfunction. Thus, our study finds an interaction between BPA exposure and obesity on sperm count and reveals potential metabolic mechanisms. It emphasizes the importance to study interactions between endocrine disrupting chemicals and obesity, and opens avenues for the possible use of animal models in identifying the interactions.

Serum Metabolomic Profiling Identifies Characterization of Non-Obstructive Azoospermic Men

Male infertility is considered a common health problem, and non-obstructive azoospermia with unclear pathogenesis is one of the most challenging tasks for clinicians. The objective of this study was to investigate the differential serum metabolic pattern in non-obstructive azoospermic men and to determine potential biomarkers related to spermatogenic dysfunction. Serum samples from patients with non-obstructive azoospermia (n = 22) and healthy controls (n = 31) were examined using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Serum metabolomic profiling could differentiate non-obstructive azoospermic patients from healthy control subjects. A total of 24 metabolites were screened and identified as potential markers, many of which are involved in energy production, oxidative stress and cell apoptosis in spermatogenesis. Moreover, the results showed that various metabolic pathways, including d-glutamine and d-glutamate metabolism, taurine and hypotaurine metabolism, pyruvate metabolism, the citrate cycle and alanine, aspartate and glutamate metabolism, were disrupted in patients with non-obstructive azoospermia. Our results indicated that the serum metabolic disorders may contribute to the etiology of non-obstructive azoospermia. This study suggested that serum metabolomics could identify unique metabolic patterns of non-obstructive azoospermia and provide novel insights into the pathogenesis underlying male infertility.

Gene-gene and gene-environment interactions on risk of male infertility: Focus on the metabolites

Infertility affects about 17% couples, and males contribute to half of the cases. Compared with independent effects of genetic and environmental factors, interactions between them help in the understanding of the susceptibility to male infertility. Thus, we genotyped 25 polymorphisms, measured 16 urinary chemical concentrations and explored interactions between gene-gene and gene-environment in 1039 Han Chinese using metabolomic analysis. We first observed that GSTT1 might interact with GSTM1 (Pinter=6.33×10(-8)). Furthermore, an interaction between GSTM1 and 4-n-octylphenol (4-n-OP) was identified (Pinter=7.00×10(-3)), as well as a 2-order interaction among GSTT1, GSTM1 and 4-n-OP (Pinter=0.04). Subjects with GSTT1-present and GSTM1-null genotypes were susceptible to male infertility when exposed to 4-n-OP (OR=14.05, 95% CI=4.78-60.20, P=2.34×10(-5)). Most metabolites identified were involved in the tricarboxylic acid cycle. In conclusion, it is a novel study of the interaction on male infertility from the aspect of metabolomics.

Serum metabolomics reveals that arsenic exposure disrupted lipid and amino acid metabolism in rats: a step forward in understanding chronic arsenic toxicity

Chronic arsenic exposure through drinking water threatens public health worldwide. Although its multiorgan toxicity has been reported, the impact of chronic arsenic exposure on the metabolic network remains obscure. In this study, male Sprague Dawley rats were exposed to 0.5, 2 or 10 ppm sodium arsenite for three months. An ultra-high performance liquid chromatography/mass spectrometry based metabolomics approach was utilized to unveil the global metabolic response to chronic arsenic exposure in rats. Distinct serum metabolome profiles were found to be associated with the doses. Eighteen differential metabolites were identified, and most of them showed dose-dependent responses to arsenic exposure. Metabolic abnormalities mainly involved lipid metabolism and amino acid metabolism. The metabolic alterations were further confirmed by hepatic gene expression. Expressions of cpt2, lcat, cact, crot and mtr were significantly elevated in high dose groups. This study provides novel evidence to support the association between arsenic exposure and metabolic disruption, and it contributes to understanding the mechanism of chronic arsenic toxicity.

A potential tool for diagnosis of male infertility: Plasma metabolomics based on GC-MS

Male infertility has become an important public health problem worldwide. Nowadays the diagnosis of male infertility frequently depends on the results of semen quality or requires more invasive surgical intervention. Therefore, it is necessary to develop a novel approach for early diagnosis of male infertility. According to the presence or absence of normal sexual function, the male infertility is classified into two phenotypes, erectile dysfunction (ED) and semen abnormalities (SA). The aim of this study was to investigate the GC-MS plasma profiles of infertile male having erectile dysfunction (ED) and having semen abnormalities (SA) and discover the potential biomarkers. The plasma samples from healthy controls (HC) (n=61) and infertility patients with ED (n=26) or with SA (n=44) were analyzed by gas chromatography-mass spectrometry (GC-MS) for discrimination and screening potential biomarkers. The partial least squares-discriminant analysis (PLS-DA) was performed on GC-MS dataset. The results showed that HC could be discriminated from infertile cases having SA (AUC=86.96%, sensitivity=78.69%, specificity=84.09%, accuracy=80.95%) and infertile cases having ED (AUC=94.33%, sensitivity=80.33%, specificity=100%, accuracy=87.36%). Some potential biomarkers were successfully discovered by two commonly used variable selection methods, variable importance on projection (VIP) and original coefficients of PLS-DA (β). 1,5-Anhydro-sorbitol and α-hydroxyisovaleric acid were identified as the potential biomarkers for distinguishing HC from the male infertility patients. Meanwhile, lactate, glutamate and cholesterol were the found to be the important variables to distinguish between patients with erectile dysfunction from those with semen abnormalities. The plasma metabolomics may be developed as a novel approach for fast, noninvasive, and acceptable diagnosis and characterization of male infertility.

Metabolomics reveals disturbed metabolic pathways in human lung epithelial cells exposed to airborne fine particulate matter

Airborne PM2.5 exposure disturbs citrate cycle, amino acid biosynthesis and metabolism, and glutathione metabolism in A549 cells.

Urinary metabolomics revealed arsenic internal dose-related metabolic alterations: a proof-of-concept study in a Chinese male cohort

Urinary biomonitoring provides the most accurate arsenic exposure assessment; however, to improve the risk assessment, arsenic-related metabolic biomarkers are required to understand the internal processes that may be perturbed, which may, in turn, link the exposure to a specific health outcome. This study aimed to investigate arsenic-related urinary metabolome changes and identify dose-dependent metabolic biomarkers as a proof-of-concept of the information that could be obtained by combining metabolomics and targeted analyses. Urinary arsenic species such as inorganic arsenic, methylarsonic acid, dimethylarsinic acid and arsenobetaine were quantified using high performance liquid chromatography (HPLC)-inductively coupled plasma-mass spectrometry in a Chinese adult male cohort. Urinary metabolomics was conducted using HPLC-quadrupole time-of-flight mass spectrometry. Arsenic-related metabolic biomarkers were investigated by comparing the samples of the first and fifth quintiles of arsenic exposure classifications using a partial least-squares discriminant model. After the adjustments for age, body mass index, smoking, and alcohol consumption, five potential biomarkers related to arsenic exposure (i.e., testosterone, guanine, hippurate, acetyl-N-formyl-5-methoxykynurenamine, and serine) were identified from 61 candidate metabolites; these biomarkers suggested that endocrine disruption and oxidative stress were associated with urinary arsenic levels. Testosterone, guanine, and hippurate showed a high or moderate ability to discriminate the first and fifth quintiles of arsenic exposure with area-under-curve (AUC) values of 0.89, 0.87, and 0.83, respectively; their combination pattern showed an AUC value of 0.91 with a sensitivity of 88% and a specificity of 80%. Arsenic dose-dependent AUC value changes were also observed. This study demonstrated that metabolomics can be used to investigate arsenic-related biomarkers of metabolic changes; the dose-dependent trends of arsenic exposure to these biomarkers may translate into the potential use of metabolic biomarkers in arsenic risk assessment. Since this was a proof-of-concept study, more research is needed to confirm the relationships we observed between arsenic exposure and biochemical changes.