Drug-Exposome Interactions: The Next Frontier in Precision Medicine

Interdisciplinary fetal-neonatal neurology training applies neural exposome perspectives to neurology principles and practice

An interdisciplinary fetal-neonatal neurology (FNN) program over the first 1,000 days teaches perspectives of the neural exposome that are applicable across the life span. This curriculum strengthens neonatal neurocritical care, pediatric, and adult neurology training objectives. Teaching at maternal-pediatric hospital centers optimally merges reproductive, pregnancy, and pediatric approaches to healthcare. Phenotype-genotype expressions of health or disease pathways represent a dynamic neural exposome over developmental time. The science of uncertainty applied to FNN training re-enforces the importance of shared clinical decisions that minimize bias and reduce cognitive errors. Trainees select mentoring committee participants that will maximize their learning experiences. Standardized questions and oral presentations monitor educational progress. Master or doctoral defense preparation and competitive research funding can be goals for specific individuals. FNN principles applied to practice offer an understanding of gene-environment interactions that recognizes the effects of reproductive health on the maternal-placental-fetal triad, neonate, child, and adult. Pre-conception and prenatal adversities potentially diminish life-course brain health. Endogenous and exogenous toxic stressor interplay (TSI) alters the neural exposome through maladaptive developmental neuroplasticity. Developmental disorders and epilepsy are primarily expressed during the first 1,000 days. Communicable and noncommunicable illnesses continue to interact with the neural exposome to express diverse neurologic disorders across the lifespan, particularly during the critical/sensitive time periods of adolescence and reproductive senescence. Anomalous or destructive fetal neuropathologic lesions change clinical expressions across this developmental-aging continuum. An integrated understanding of reproductive, pregnancy, placental, neonatal, childhood, and adult exposome effects offers a life-course perspective of the neural exposome. Exosome research promises improved disease monitoring and drug delivery starting during pregnancy. Developmental origins of health and disease principles applied to FNN practice anticipate neurologic diagnoses with interventions that can benefit successive generations. Addressing health care disparities in the Global South and high-income country medical deserts require constructive dialogue among stakeholders to achieve medical equity. Population health policies require a brain capital strategy that reduces the global burden of neurologic diseases by applying FNN principles and practice. This integrative neurologic care approach will prolong survival with an improved quality of life for persons across the lifespan confronted with neurological disorders.

The Austrian children's biomonitoring survey 2020 Part B: Mycotoxins, phytotoxins, phytoestrogens and food processing contaminants

This study assessed the levels of environment and food-related exposures in urine of Austrian school children aged six to ten (n = 85) focusing on mycotoxins, phytoestrogens, and food processing by-products using two multi-analyte LC-MS/MS methods. Out of the 55 biomarkers of exposure reported in this study, 22 were quantified in the first void urine samples. Mycotoxins frequently quantified included zearalenone (detection rate 100%; median 0.11 ng/mL), deoxynivalenol (99%; 15 ng/mL), alternariol monomethyl ether (75%; 0.04 ng/mL), and ochratoxin A (19%; 0.03 ng/mL). Several phytoestrogens, including genistein, daidzein, and its metabolite equol, were detected in all samples at median concentrations of 22 ng/mL, 43 ng/mL, and 14 ng/mL, respectively. The food processing by-product 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), was detected in 4% of the samples (median 0.016 ng/mL). None of the investigated samples contained the tested phytotoxins that were rarely considered for human biomonitoring previously (pyrrolizidine alkaloids, tropane alkaloids, aristolochic acids). When relating estimated exposure to current health-based guidance values, 22% of the children exceeded the tolerable daily intake for deoxynivalenol, and the estimated MOE for OTA indicates possible health risks for some children. The results clearly demonstrate frequent low-level (co-)exposure and warrant further exposome-scale exposure assessments, especially in susceptible sub-populations and longitudinal settings.

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

Human Carboxylesterase 1A Plays a Predominant Role in Hydrolysis of the Anti-Dyslipidemia Agent Fenofibrate in Humans

Fenofibrate, a marketed peroxisome proliferator-activated receptor-α (PPARα) agonist, has been widely used for treating severe hypertriglyceridemia and mixed dyslipidemia. As a canonical prodrug, fenofibrate can be rapidly hydrolyzed to release the active metabolite (fenofibric acid) in vivo, but the crucial enzyme(s) responsible for fenofibrate hydrolysis and the related hydrolytic kinetics have not been well-investigated. This study aimed to assign the key organs and crucial enzymes involved in fenofibrate hydrolysis in humans, as well as reveal the impact of fenofibrate hydrolysis on its non-PPAR-mediated biologic activities. Our results demonstrated that fenofibrate could be rapidly hydrolyzed in the preparations from both human liver and lung to release fenofibric acid. Reaction phenotyping assays coupling with chemical inhibition assays showed that human carboxylesterase 1A (hCES1A) played a predominant role in fenofibrate hydrolysis in human liver and lung, while human carboxylesterase 2A (hCES2A) and human monoacylglycerol esterase (hMAGL) contributed to a very lesser extent. Kinetic analyses showed that fenofibrate could be rapidly hydrolyzed by hCES1A in human liver preparations, while the inherent clearance of hCES1A-catalyzed fenofibrate hydrolysis is much higher (>200-fold) than than that of hCES2A or hMAGL. Biologic assays demonstrated that both fenofibrate and fenofibric acid showed very closed Nrf2 agonist effects, but fenofibrate hydrolysis strongly weakens its inhibitory effects against both hCES2A and hNtoum. Collectively, our findings reveal that the liver is the major organ and hCES1A is the predominant enzyme-catalyzing fenofibrate hydrolysis in humans, while fenofibrate hydrolysis significantly reduces inhibitory effects of fenofibrate against serine hydrolases. SIGNIFICANCE STATEMENT: Fenofibrate can be completely converted to fenofibric acid in humans and subsequently exert its pharmacological effects, but the hydrolytic pathways of fenofibrate in humans have not been well-investigated. This study reported that the liver was the predominant organ and human carboxylesterase 1A was the crucial enzyme involved in fenofibrate hydrolysis in humans.

High-resolution mass spectrometry identifies delayed biomarkers for improved precision in acetaminophen/paracetamol human biomonitoring

Paracetamol/acetaminophen (N-acetyl-p-aminophenol, APAP) is a top selling analgesic used in more than 600 prescription and non-prescription pharmaceuticals. To study efficiently some of the potential undesirable effects associated with increasing APAP consumption (e.g., developmental disorders, drug-induced liver injury), there is a need to improve current APAP biomonitoring methods that are limited by APAP short half-life. Here, we demonstrate using high-resolution mass spectrometry (HRMS) in several human studies that APAP thiomethyl metabolite conjugates (S-methyl-3-thioacetaminophen sulfate and S-methyl-3-thioacetaminophen sulphoxide sulfate) are stable biomarkers with delayed excretion rates compared to conventional APAP metabolites, that could provide a more reliable history of APAP ingestion in epidemiological studies. We also show that these biomarkers could serve as relevant clinical markers to diagnose APAP acute intoxication in overdosed patients, when free APAP have nearly disappeared from blood. Using in vitro liver models (HepaRG cells and primary human hepatocytes), we then confirm that these thiomethyl metabolites are directly linked to the toxic N-acetyl-p-benzoquinone imine (NAPQI) elimination, and produced via an overlooked pathway called the thiomethyl shunt pathway. Further studies will be needed to determine whether the production of the reactive hepatotoxic NAPQI metabolites is currently underestimated in human. Nevertheless, these biomarkers could already serve to improve APAP human biomonitoring, and investigate, for instance, inter-individual variability in NAPQI production to study underlying causes involved in APAP-induced hepatotoxicity. Overall, our findings demonstrate the potential of exposomics-based HRMS approach to advance towards a better precision for human biomonitoring.

Understanding the Chemical Exposome During Fetal Development and Early Childhood: A Review

Early human life is considered a critical window of susceptibility to external exposures. Infants are exposed to a multitude of environmental factors, collectively referred to as the exposome. The chemical exposome can be summarized as the sum of all xenobiotics that humans are exposed to throughout a lifetime. We review different exposure classes and routes that impact fetal and infant metabolism and the potential toxicological role of mixture effects. We also discuss the progress in human biomonitoring and present possiblemodels for studying maternal-fetal transfer. Data gaps on prenatal and infant exposure to xenobiotic mixtures are identified and include natural biotoxins, in addition to commonly reported synthetic toxicants, to obtain a more holistic assessment of the chemical exposome. We highlight the lack of large-scale studies covering a broad range of xenobiotics. Several recommendations to advance our understanding of the early-life chemical exposome and the subsequent impact on health outcomes are proposed.

Pesticides and the Microbiome-Gut-Brain Axis: Convergent Pathways in the Pathogenesis of Parkinson's Disease

The increasing global burden of Parkinson's disease (PD), termed the PD pandemic, is exceeding expectations related purely to population aging and is likely driven in part by lifestyle changes and environmental factors. Pesticides are well recognized risk factors for PD, supported by both epidemiological and experimental evidence, with multiple detrimental effects beyond dopaminergic neuron damage alone. The microbiome-gut-brain axis has gained much attention in recent years and is considered to be a significant contributor and driver of PD pathogenesis. In this narrative review, we first focus on how both pesticides and the microbiome may influence PD initiation and progression independently, describing pesticide-related central and peripheral neurotoxicity and microbiome-related local and systemic effects due to dysbiosis and microbial metabolites. We then depict the bidirectional interplay between pesticides and the microbiome in the context of PD, synthesizing current knowledge about pesticide-induced dysbiosis, microbiome-mediated alterations in pesticide availability, metabolism and toxicity, and complex systemic pesticide-microbiome-host interactions related to inflammatory and metabolic pathways, insulin resistance and other mechanisms. An overview of the unknowns follows, and the role of pesticide-microbiome interactions in the proposed body-/brain-first phenotypes of PD, the complexity of environmental exposures and gene-environment interactions is discussed. The final part deals with possible further steps for translation, consisting of recommendations on future pesticide use and research as well as an outline of promising preventive/therapeutic approaches targeted on strengthening or restoring a healthy gut microbiome, closing with a summary of current gaps and future perspectives in the field.

Charting the landscape of the environmental exposome

The exposome depicts the total exposures in the lifetime of an organism. Human exposome comprises exposures from environmental and humanistic sources. Biological, chemical, and physical environmental exposures pose potential health threats, especially to susceptible populations. Although still in its nascent stage, we are beginning to recognize the vast and dynamic nature of the exposome. In this review, we systematically summarize the biological and chemical environmental exposomes in three broad environmental matrices-air, soil, and water; each contains several distinct subcategories, along with a brief introduction to the physical exposome. Disease-related environmental exposures are highlighted, and humans are also a major source of disease-related biological exposures. We further discuss the interactions between biological, chemical, and physical exposomes. Finally, we propose a list of outstanding challenges under the exposome research framework that need to be addressed to move the field forward. Taken together, we present a detailed landscape of environmental exposome to prime researchers to join this exciting new field.

Studying the Impact of Persistent Organic Pollutants Exposure on Human Health by Proteomic Analysis: A Systematic Review

Persistent organic pollutants (POPs) are organic chemical substances that are widely distributed in environments around the globe. POPs accumulate in living organisms and are found at high concentrations in the food chain. Humans are thus continuously exposed to these chemical substances, in which they exert hepatic, reproductive, developmental, behavioral, neurologic, endocrine, cardiovascular, and immunologic adverse health effects. However, considerable information is unknown regarding the mechanism by which POPs exert their adverse effects in humans, as well as the molecular and cellular responses involved. Data are notably lacking concerning the consequences of acute and chronic POP exposure on changes in gene expression, protein profile, and metabolic pathways. We conducted a systematic review to provide a synthesis of knowledge of POPs arising from proteomics-based research. The data source used for this review was PubMed. This study was carried out following the PRISMA guidelines. Of the 742 items originally identified, 89 were considered in the review. This review presents a comprehensive overview of the most recent research and available solutions to explore proteomics datasets to identify new features relevant to human health. Future perspectives in proteomics studies are discussed.

Early-life chemical exposome and gut microbiome development: African research perspectives within a global environmental health context

The gut microbiome of neonates, infants, and toddlers (NITs) is very dynamic, and only begins to stabilize towards the third year of life. Within this period, exposure to xenobiotics may perturb the gut environment, thereby driving or contributing to microbial dysbiosis, which may negatively impact health into adulthood. Despite exposure of NITs globally, but especially in Africa, to copious amounts and types of xenobiotics - such as mycotoxins, pesticide residues, and heavy metals - little is known about their influence on the early-life microbiome or their effects on acute or long-term health. Within the African context, the influence of fermented foods, herbal mixtures, and the delivery environment on the early-life microbiome are often neglected, despite being potentially important factors that influence the microbiome. Consequently, data on in-depth understanding of the microbiome-exposome interactions is lacking in African cohorts. Collecting and evaluating such data is important because exposome-induced gut dysbiosis could potentially favor disease progression.

Multimodal interactions of drugs, natural compounds and pollutants with the gut microbiota

The gut microbiota contributes to diverse aspects of host physiology, ranging from immunomodulation to drug metabolism. Changes in the gut microbiota composition are associated with various diseases as well as with the response to medications. It is therefore important to understand how different lifestyle and environmental factors shape gut microbiota composition. Beyond the commonly considered factor of diet, small-molecule drugs have recently been identified as major effectors of the microbiota composition. Other xenobiotics, such as environmental or chemical pollutants, can also impact gut bacterial communities. Here, we review the mechanisms of interactions between gut bacteria and antibiotics, host-targeted drugs, natural food compounds, food additives and environmental pollutants. While xenobiotics can impact bacterial growth and metabolism, bacteria in turn can bioaccumulate or chemically modify these compounds. These reciprocal interactions can manifest in complex xenobiotic-microbiota-host relationships. Our Review highlights the need to study mechanisms underlying interactions with pollutants and food additives towards deciphering the dynamics and evolution of the gut microbiota.

Next-generation biomonitoring of the early-life chemical exposome in neonatal and infant development

Exposure to synthetic and natural chemicals is a major environmental risk factor in the etiology of many chronic diseases. Investigating complex co-exposures is necessary for a holistic assessment in exposome-wide association studies. In this work, a sensitive liquid chromatography-tandem mass spectrometry approach was developed and validated. The assay enables the analysis of more than 80 highly-diverse xenobiotics in urine, serum/plasma, and breast milk; with detection limits generally in the pg-ng mL-1 range. In plasma of extremely-premature infants, 27 xenobiotics are identified; including contamination with plasticizers, perfluorinated alkylated substances and parabens. In breast milk samples collected longitudinally over the first 211 days post-partum, 29 analytes are detected, including pyrrolizidine- and tropane alkaloids which have not been identified in this matrix before. A preliminary estimation of daily toxicant intake via breast milk is conducted. In conclusion, we observe significant early-life co-exposure to multiple toxicants, and demonstrate the method's applicability for large-scale exposomics-type cohort studies.

Gut microbial metabolite p-cresol alters biotransformation of bisphenol A: Enzyme competition or gene induction?

Recent studies on pharmaceuticals have revealed the direct and indirect mechanisms that link human gut microbiome to xenobiotic biotransformation. Though environmental contaminants compose a vital portion of xenobiotics and share overlapping biotransformation pathways with gut microbial metabolites, the possible interplay between gut microbiome and biotransformation of environmental contaminants remains obscure. This study utilized bisphenol A (BPA) and p-cresol as model compounds to explore whether gut microbial metabolites could affect environmental phenol metabolism on both in vitro and in vivo models. We have observed some distinct biotransformation behavior, where in vivo mouse examination using 171 & 1972 μg/kg bw p-cresol injection exhibited enhancing effect on BPA metabolism, but p-cresol was found as a strong inhibitor from 10/5 μM in a non-competitive pattern for BPA biotransformation in in vitro models of liver S9 fractions and HepG2 cell line, respectively. A further investigation revealed that the expression of biotransformation enzyme genes including Ugt1a1, Ugt2b1, or Sult1a1 of p-cresol treated mice were dynamically induced. In silico docking approach was also utilized to explore the non-competitive inhibition mechanism by estimating the binding affinity of key enzyme SULT 1A1. Overall, our results provided a novel insight into the biotransformation interaction between gut microbiome and environmental contaminants.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Metabolic Impact of Anticancer Drugs Pd2Spermine and Cisplatin on the Brain of Healthy Mice

The new palladium agent Pd2Spermine (Spm) has been reported to exhibit promising cytotoxic properties, while potentially circumventing the known disadvantages associated to cisplatin therapeutics, namely acquired resistance and high toxicity. This work presents a nuclear magnetic resonance (NMR) metabolomics study of brain extracts obtained from healthy mice, to assess the metabolic impacts of the new Pd2Spm complex in comparison to that of cisplatin. The proton NMR spectra of both polar and nonpolar brain extracts were analyzed by multivariate and univariate statistics, unveiling several metabolite variations during the time course of exposition to each drug (1–48 h). The distinct time-course dependence of such changes revealed useful information on the drug-induced dynamics of metabolic disturbances and recovery periods, namely regarding amino acids, nucleotides, fatty acids, and membrane precursors and phospholipids. Putative biochemical explanations were proposed, based on existing pharmacokinetics data and previously reported metabolic responses elicited by the same metal complexes in the liver of the same animals. Generally, results suggest a more effective response of brain metabolism towards the possible detrimental effects of Pd2Spm, with more rapid recovery back to metabolites’ control levels and, thus, indicating that the palladium drug may exert a more beneficial role than cDDP in relation to brain toxicity.

An overview of machine learning methods for monotherapy drug response prediction

For an increasing number of preclinical samples, both detailed molecular profiles and their responses to various drugs are becoming available. Efforts to understand, and predict, drug responses in a data-driven manner have led to a proliferation of machine learning (ML) methods, with the longer term ambition of predicting clinical drug responses. Here, we provide a uniquely wide and deep systematic review of the rapidly evolving literature on monotherapy drug response prediction, with a systematic characterization and classification that comprises more than 70 ML methods in 13 subclasses, their input and output data types, modes of evaluation, and code and software availability. ML experts are provided with a fundamental understanding of the biological problem, and how ML methods are configured for it. Biologists and biomedical researchers are introduced to the basic principles of applicable ML methods, and their application to the problem of drug response prediction. We also provide systematic overviews of commonly used data sources used for training and evaluation methods.

Elucidation of xenoestrogen metabolism by non-targeted, stable isotope-assisted mass spectrometry in breast cancer cells

Environmental exposure to xenoestrogens, i.e., chemicals that imitate the hormone 17β-estradiol, has the potential to influence hormone homeostasis and action. Detailed knowledge of xenobiotic biotransformation processes in cell models is key when transferring knowledge learned from in vitro models to in vivo relevance. This study elucidated the metabolism of two naturally-occurring phyto- and mycoestrogens; namely genistein and zearalenone, in an estrogen receptor positive breast cancer cell line (MCF-7) with the aid of stable isotope-assisted metabolomics and the bioinformatic tool MetExtract II. Metabolism was studied in a time course experiment after 2 h, 6 h and 24 h incubation. Twelve and six biotransformation products of zearalenone and genistein were detected, respectively, clearly demonstrating the abundant xenobiotic biotransformation capability of the cells. Zearalenone underwent extensive phase-I metabolism resulting in α-zearalenol (α-ZEL), a molecule known to possess a significantly higher estrogenicity, and several phase-II metabolites (sulfo- and glycoconjugates) of the native compound and the major phase I metabolite α-ZEL. Moreover, potential adducts of zearalenone with a vitamin and several hydroxylated metabolites were annotated. Genistein metabolism resulted in sulfation, combined sulfation and hydroxylation, acetylation, glucuronidation and unexpectedly adduct formation with pentose- and hexose sugars. Kinetics of metabolite formation and subsequent excretion into the extracellular medium revealed a time-dependent increase in most biotransformation products. The untargeted elucidation of biotransformation products formed during cell culture experiments enables an improved and more meaningful interpretation of toxicological assays and has the potential to identify unexpected or unknown metabolites.

Capturing a Comprehensive Picture of Biological Events From Adverse Outcome Pathways in the Drug Exposome

Background: The chemical part of the exposome, including drugs, may explain the increase of health effects with outcomes such as infertility, allergies, metabolic disorders, which cannot be only explained by the genetic changes. To better understand how drug exposure can impact human health, the concepts of adverse outcome pathways (AOPs) and AOP networks (AONs), which are representations of causally linked events at different biological levels leading to adverse health, could be used for drug safety assessment.

Methods: To explore the action of drugs across multiple scales of the biological organization, we investigated the use of a network-based approach in the known AOP space. Considering the drugs and their associations to biological events, such as molecular initiating event and key event, a bipartite network was developed. This bipartite network was projected into a monopartite network capturing the event–event linkages. Nevertheless, such transformation of a bipartite network to a monopartite network had a huge risk of information loss. A way to solve this problem is to quantify the network reduction. We calculated two scoring systems, one measuring the uncertainty and a second one describing the loss of coverage on the developed event–event network to better investigate events from AOPs linked to drugs.

Results: This AON analysis allowed us to identify biological events that are highly connected to drugs, such as events involving nuclear receptors (ER, AR, and PXR/SXR). Furthermore, we observed that the number of events involved in a linkage pattern with drugs is a key factor that influences information loss during monopartite network projection. Such scores have the potential to quantify the uncertainty of an event involved in an AON, and could be valuable for the weight of evidence assessment of AOPs. A case study related to infertility, more specifically to “decrease, male agenital distance” is presented.

Conclusion: This study highlights that computational approaches based on network science may help to understand the complexity of drug health effects, with the aim to support drug safety assessment.

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

Pharmaco-metabolomics opportunities in drug development and clinical research

Pharmaco-metabolomics uses metabolic phenotypes for the prediction of inter-individual variations in drug response and helps in understanding the mechanisms of drug action. The field has made significant progress over the last 14 years with numerous studies providing clinical evidence for personalised medicine. However, discovered pharmaco-metabolomic biomarkers are not yet translated into clinics due to a lack of large-scale validation. Integration of targeted and untargeted metabolomics workflows into pharmacokinetic analysis and drug development can advance the field from bench to bedside. Also, Indian pharmaceutical research and its bioanalytical infrastructure are in a position to take on these opportunities by addressing challenges such as appropriate training and regulatory compliance.

Metabolome-wide association study of occupational exposure to benzene

Benzene is a recognized hematotoxin and leukemogen; however, its mechanism of action in humans remain unclear. To provide insight into the processes underlying benzene hematotoxicity, we performed high-resolution metabolomic profiling of plasma collected from a cross-sectional study of 33 healthy workers exposed to benzene (median 8-h time-weighted average exposure; 20 ppma), and 25 unexposed controls in Shanghai, China. Metabolic features associated with benzene were identified using a metabolome-wide association study (MWAS) that tested for the relationship between feature intensity and benzene exposure. MWAS identified 478 mass spectral features associated with benzene exposure at false discovery rate < 20%. Comparison to a list of 13 known benzene metabolites and metabolites predicted using a multi-component biotransformation algorithm showed five metabolites were detected, which included the known metabolites phenol and benzene diolepoxide. Metabolic pathway enrichment identified 41 pathways associated with benzene exposure, with altered pathways including carnitine shuttle, fatty acid metabolism, sulfur amino acid metabolism, glycolysis, gluconeogenesis and branched chain amino acid metabolism. These results suggest disruption to fatty acid uptake, energy metabolism and increased oxidative stress, and point towards pathways related to mitochondrial dysfunction, which has previously been linked to benzene exposure in animal models and human studies. Taken together, these results suggest benzene exposure is associated with disruption of mitochondrial pathways, and provide promising, systems biology biomarkers for risk assessment of benzene-induced hematotoxicity in humans.

Preventing Parkinson's Disease: An Environmental Agenda

Fueled by aging populations and continued environmental contamination, the global burden of Parkinson's disease (PD) is increasing. The disease, or more appropriately diseases, have multiple environmental and genetic influences but no approved disease modifying therapy. Additionally, efforts to prevent this debilitating disease have been limited. As numerous environmental contaminants (e.g., pesticides, metals, industrial chemicals) are implicated in PD, disease prevention is possible. To reduce the burden of PD, we have compiled preclinical and clinical research priorities that highlight both disease prediction and primary prevention. Though not exhaustive, the "PD prevention agenda" builds upon many years of research by our colleagues and proposes next steps through the lens of modifiable risk factors. The agenda identifies ten specific areas of further inquiry and considers the funding and policy changes that will be necessary to help prevent the world's fastest growing brain disease.

Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Combining targeted metabolite analyses and transcriptomics to reveal the specific chemical composition and associated genes in the incompatible soybean variety PI437654 infected with soybean cyst nematode HG1.2.3.5.7

BACKGROUND

Soybean cyst nematode, Heterodera glycines, is one of the most devastating pathogens of soybean and causes severe annual yield losses worldwide. Different soybean varieties exhibit different responses to H. glycines infection at various levels, such as the genomic, transcriptional, proteomic and metabolomic levels. However, there have not yet been any reports of the differential responses of incompatible and compatible soybean varieties infected with H. glycines based on combined metabolomic and transcriptomic analyses.

RESULTS

In this study, the incompatible soybean variety PI437654 and three compatible soybean varieties, Williams 82, Zhonghuang 13 and Hefeng 47, were used to clarify the differences in metabolites and transcriptomics before and after the infection with HG1.2.3.5.7. A local metabolite-calibrated database was used to identify potentially differential metabolites, and the differences in metabolites and metabolic pathways were compared between the incompatible and compatible soybean varieties after inoculation with HG1.2.3.5.7. In total, 37 differential metabolites and 20 KEGG metabolic pathways were identified, which were divided into three categories: metabolites/pathways overlapped in the incompatible and compatible soybeans, and metabolites/pathways specific to either the incompatible or compatible soybean varieties. Twelve differential metabolites were found to be involved in predicted KEGG metabolite pathways. Moreover, 14 specific differential metabolites (such as significantly up-regulated nicotine and down-regulated D-aspartic acid) and their associated KEGG pathways (such as the tropane, piperidine and pyridine alkaloid biosynthesis, alanine, aspartate and glutamate metabolism, sphingolipid metabolism and arginine biosynthesis) were significantly altered and abundantly enriched in the incompatible soybean variety PI437654, and likely played pivotal roles in defending against HG1.2.3.5.7 infection. Three key metabolites (N-acetyltranexamic acid, nicotine and D,L-tryptophan) found to be significantly up-regulated in the incompatible soybean variety PI437654 infected by HG1.2.3.5.7 were classified into two types and used for combined analyses with the transcriptomic expression profiling. Associated genes were predicted, along with the likely corresponding biological processes, cellular components, molecular functions and pathways.

CONCLUSIONS

Our results not only identified potential novel metabolites and associated genes involved in the incompatible response of PI437654 to soybean cyst nematode HG1.2.3.5.7, but also provided new insights into the interactions between soybeans and soybean cyst nematodes.

In Silico Exploration of the Potential Role of Acetaminophen and Pesticides in the Etiology of Autism Spectrum Disorder

Recent epidemiological studies suggest that prenatal exposure to acetaminophen (APAP) is associated with increased risk of Autism Spectrum Disorder (ASD), a neurodevelopmental disorder affecting 1 in 59 children in the US. Maternal and prenatal exposure to pesticides from food and environmental sources have also been implicated to affect fetal neurodevelopment. However, the underlying mechanisms for ASD are so far unknown, likely with complex and multifactorial etiology. The aim of this study was to explore the potential effects of APAP and pesticide exposure on development with regards to the etiology of ASD by highlighting common genes and biological pathways. Genes associated with APAP, pesticides, and ASD through human research were retrieved from molecular and biomedical literature databases. The interaction network of overlapping genetic associations was subjected to network topology analysis and functional annotation of the resulting clusters. These genes were over-represented in pathways and biological processes (FDR p < 0.05) related to apoptosis, metabolism of reactive oxygen species (ROS), and carbohydrate metabolism. Since these three biological processes are frequently implicated in ASD, our findings support the hypothesis that cell death processes and specific metabolic pathways, both of which appear to be targeted by APAP and pesticide exposure, may be involved in the etiology of ASD. This novel exposures-gene-disease database mining might inspire future work on understanding the biological underpinnings of various ASD risk factors.

Immuno-Hormonal, Genetic and Metabolic Profiling of Newborns as a Basis for the Life-Long OneHealth Medical Record: A Scoping Review

Holistic and life-long medical surveillance is the core of personalised medicine and supports an optimal implementation of both preventive and curative healthcare. Personal medical records are only partially unified by hospital or general practitioner informatics systems, but only for citizens with long-term permanent residence. Otherwise, insight into the medical history of patients greatly depends on their medical archive and memory. Additionally, occupational exposure records are not combined with clinical or general practitioner records. Environmental exposure starts preconceptionally and continues during pregnancy by transplacental exposure. Antenatal exposure is partially dependent on parental lifestyle, residence and occupation. Newborn screening (NBS) is currently being performed in developed countries and includes testing for rare genetic, hormone-related, and metabolic conditions. Transplacental exposure to substances such as endocrine disruptors, air pollutants and drugs may have life-long health consequences. However, despite the recognised impact of transplacental exposure on the increased risk of metabolic syndrome, neurobehavioral disorders as well as immunodisturbances including allergy and infertility, not a single test within NBS is geared toward detecting biomarkers of exposure (xenobiotics or their metabolites, nutrients) or effect such as oestradiol, testosterone and cytokines, known for being associated with various health risks and disturbed by transplacental xenobiotic exposures. The outcomes of ongoing exposome projects might be exploited to this purpose. Developing and using a OneHealth Medical Record (OneHealthMR) may allow the incorporated chip to harvest information from different sources, with high integration added value for health prevention and care: environmental exposures, occupational health records as well as diagnostics of chronic diseases, allergies and medication usages, from birth and throughout life. Such a concept may present legal and ethical issues pertaining to personal data protection, requiring no significant investments and exploits available technologies and algorithms, putting emphasis on the prevention and integration of environmental exposure and health data.