Can Small Molecules Provide Clues on Disease Progression in Cerebrospinal Fluid from Mild Cognitive Impairment and Alzheimer's Disease Patients?

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease, which is currently diagnosed via clinical symptoms and nonspecific biomarkers (such as Aß1-42, t-Tau, and p-Tau) measured in cerebrospinal fluid (CSF), which alone do not provide sufficient insights into disease progression. In this pilot study, these biomarkers were complemented with small-molecule analysis using non-target high-resolution mass spectrometry coupled with liquid chromatography (LC) on the CSF of three groups: AD, mild cognitive impairment (MCI) due to AD, and a non-demented (ND) control group. An open-source cheminformatics pipeline based on MS-DIAL and patRoon was enhanced using CSF- and AD-specific suspect lists to assist in data interpretation. Chemical Similarity Enrichment Analysis revealed a significant increase of hydroxybutyrates in AD, including 3-hydroxybutanoic acid, which was found at higher levels in AD compared to MCI and ND. Furthermore, a highly sensitive target LC-MS method was used to quantify 35 bile acids (BAs) in the CSF, revealing several statistically significant differences including higher dehydrolithocholic acid levels and decreased conjugated BA levels in AD. This work provides several promising small-molecule hypotheses that could be used to help track the progression of AD in CSF samples.

The exposome and liver disease - how environmental factors affect liver health.

Since the initial development of the exposome concept, much effort has been devoted to the characterisation of the exposome through analytical, epidemiological, and toxicological/mechanistic studies. There is now an urgent need to link the exposome to human diseases and to include exposomics in the characterisation of environment-linked pathologies together with genomics and other omics. Liver diseases are particularly well suited for such studies since major functions of the liver include the detection, detoxification, and elimination of xenobiotics, as well as inflammatory responses. It is well known that several liver diseases are associated with i) addictive behaviours such as alcohol consumption, smoking, and to a certain extent dietary imbalance and obesity, ii) viral and parasitic infections, and iii) exposure to toxins and occupational chemicals. Recent studies indicate that environmental exposures are also significantly associated with liver diseases, and these include air pollution (particulate matter and volatile chemicals), contaminants such as polyaromatic hydrocarbons, bisphenol A and per-and poly-fluorinated substances, and physical stressors such as radiation. Furthermore, microbial metabolites and the "gut-liver" axis play a major role in liver diseases. Exposomics is poised to play a major role in the field of liver pathology. Methodological advances such as the exposomics-metabolomics framework, the determination of risk factors' genomic and epigenomic signatures, and cross-species biological pathway analysis should further delineate the impact of the exposome on the liver, opening the way for improved prevention, as well as the identification of new biomarkers of exposure and effects, and additional therapeutic targets.

Exploring Single-Cell Exposomics by Mass Spectrometry.

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.

A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome.

Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.

Coking-Produced Aromatic Compounds in Urine of Exposed and Nonexposed Populations: Exposure Levels, Source Identification, and Model-Based Health Implications.

Coking contamination in China is complex and poses potential health risks to humans. In this study, we collected urine samples from coking plant workers, nearby residents, and control individuals to analyze 25 coking-produced aromatic compounds (ACs), including metabolites of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, chlorophenols, and nitrophenols. The median concentration of total ACs in urine of workers was 102 µg·g-1 creatinine, significantly higher than that in the other two groups. Hydroxy-PAHs and hydroxy hetero-PAHs were the dominant ACs. Workers directly exposed from coking industrial processes, i.e., coking, coal preparation, and chemical production processes, showed higher concentrations of hydroxy-PAHs and hydroxy hetero-PAHs (excluding 5-hydroxyisoquinoline), while those from indirect exposure workshops had higher levels of other ACs, indicating different sources in the coking plant. The AC mixture in workers demonstrated positive effects on DNA damage and lipid peroxidation with 5-hydroxyisoquinoline and 3-hydroxycarbazole playing a significant role using a quantile g-computation model. Monte Carlo simulation revealed that coking contamination elevated the carcinogenic risk for exposed workers by 5-fold compared to controls with pyrene, pentachlorophenol, and carbazole contributing the most, and workers from coking process are at the highest risk. This study enhances understanding of coking-produced AC levels and provides valuable insights into coking contamination control.

Global Profiling of Urinary Mercapturic Acids Using Integrated Library-Guided Analysis.

Urinary mercapturic acids (MAs) are often used as biomarkers for monitoring human exposures to occupational and environmental xenobiotics. In this study, we developed an integrated library-guided analysis workflow using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. This method includes expanded assignment criteria and a curated library of 220 MAs and addresses the shortcomings of previous untargeted approaches. We employed this workflow to profile MAs in the urine of 70 participants─40 nonsmokers and 30 smokers. We found approximately 500 MA candidates in each urine sample, and 116 MAs from 63 precursors were putatively annotated. These include 25 previously unreported MAs derived mostly from alkenals and hydroxyalkenals. Levels of 68 MAs were comparable in nonsmokers and smokers, 2 MAs were higher in nonsmokers, and 46 MAs were elevated in smokers. These included MAs of polycyclic aromatic hydrocarbons and hydroxyalkenals and those derived from toxicants present in cigarette smoke (e.g., acrolein, 1,3-butadiene, isoprene, acrylamide, benzene, and toluene). Our workflow allowed profiling of known and unreported MAs from endogenous and environmental sources, and the levels of several MAs were increased in smokers. Our method can also be expanded and applied to other exposure-wide association studies.

Scannotation: A Suspect Screening Tool for the Rapid Pre-Annotation of the Human LC-HRMS-Based Chemical Exposome.

In an increasingly chemically polluted environment, rapidly characterizing the human chemical exposome (i.e., chemical mixtures accumulating in humans) at the population scale is critical to understand its impact on health. High-resolution mass spectrometry (HRMS) profiling of complex biological matrices can theoretically provide a comprehensive picture of chemical exposures. However, annotating the detected chemical features, particularly low-abundant ones, remains a significant obstacle to implementing such approaches at a large scale. We present Scannotation (https://github.com/scannotation/Scannotation_software), an automated and user-friendly suspect screening tool for the rapid pre-annotation of HRMS preprocessed data sets. This software tool combines several MS1 chemical predictors, i.e., m/z, experimental and predicted retention times, isotopic patterns, and neutral loss patterns, to score the proximity between features and suspects, thus efficiently prioritizing tentative annotations to verify. Scannotation and MS-DIAL4 were used to annotate blood serum samples of 75 Breton adolescents. Scannotation's combination of MS1-based chemical predictors allowed us to annotate 89 chemically diverse environmental compounds with high confidence (confirmed by MS2 when available). These compounds included 62% of emerging molecules, for which no toxicological or human biomonitoring data are reported in the literature. The complementarity observed with MS-DIAL4 results demonstrates the relevance of Scannotation for the efficient pre-annotation of large-scale exposomics data sets.

Exposure to persistent organic pollutants alters the serum metabolome in non-obese diabetic mice.

INTRODUCTION: Autoimmune disorders such as type 1 diabetes (T1D) are believed to be caused by the interplay between several genetic and environmental factors. Elucidation of the role of environmental factors in metabolic and immune dysfunction leading to autoimmune disease is not yet well characterized. OBJECTIVES: Here we investigated the impact of exposure to a mixture of persistent organic pollutants (POPs) on the metabolome in non-obese diabetic (NOD) mice, an experimental model of T1D. The mixture contained organochlorides, organobromides, and per- and polyfluoroalkyl substances (PFAS). METHODS: Analysis of molecular lipids (lipidomics) and bile acids in serum samples was performed by UPLC-Q-TOF/MS, while polar metabolites were analyzed by GC-Q-TOF/MS. RESULTS: Experimental exposure to the POP mixture in these mice led to several metabolic changes, which were similar to those previously reported as associated with PFAS exposure, as well as risk of T1D in human studies. This included an increase in the levels of sugar derivatives, triacylglycerols and lithocholic acid, and a decrease in long chain fatty acids and several lipid classes, including phosphatidylcholines, lysophosphatidylcholines and sphingomyelins. CONCLUSION: Taken together, our study demonstrates that exposure to POPs results in an altered metabolic signature previously associated with autoimmunity.

Studying the Parkinson's disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high-resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics, and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development.

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy.

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

Organic Components of Personal PM2.5 Exposure Associated with Inflammation: Evidence from an Untargeted Exposomic Approach.

Fine particulate matter (PM2.5) can promote chronic diseases through the fundamental mechanism of inflammation; however, systemic information is lacking on the inflammatory PM2.5 components. To decipher organic components from personal PM2.5 exposure that were associated with respiratory and circulatory inflammatory responses in older adults, we developed an exposomic approach using trace amounts of particles and applied it on 424 personal PM2.5 samples collected in a panel study in Beijing. Applying an integrated multivariate and univariate untargeted strategy, a total of 267 organic compounds were filtered and then chemically identified according to their association with exhaled nitric oxide (eNO)/interleukin (IL)-6 or serum IL-1ß/IL-6, with monocyclic and polycyclic aromatic compounds (i.e., MACs and PACs) as the representatives. Indoor-derived species with medium volatility including MACs were mainly associated with systemic inflammation, while low-volatile ambient components that originate from combustion sources, such as PACs, were mostly associated with airway inflammation. Following ambient component exposure, we found an inverted U-shaped relationship on change of eNO with insulin resistance, suggesting a higher risk of cardiopulmonary dysfunction for individuals with homeostatic model assessment for insulin resistance (HOMA-IR) levels > 2.3. Overall, this study provided a practical untargeted strategy for the systemic investigation of PM2.5 components and proposed source-specific inflammatory effects.

Analysis of neurotransmitters in rat placenta exposed to flame retardants using IR-MALDESI mass spectrometry imaging.

Chemical exposures can adversely impact fetal development. For many compounds, including common flame retardants, the mechanisms by which this occurs remain unclear, but emerging evidence suggests that disruption at the level of the placenta may play a role. Understanding how the placenta might be vulnerable to chemical exposures is challenging due to its complex structure. The primary objective of this study was to develop a method for detecting placental neurotransmitters and related metabolites without chemical derivatization so changes in the abundance and spatial distribution of neurotransmitters in rat placenta following chemical exposure could be determined using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging. Without chemical derivatization, 49 neurotransmitters and their related metabolites were putatively identified in untreated rat placenta sections using mass measurement accuracy and spectral accuracy. A few neurotransmitters were less abundant in placentas that were exposed to various flame retardants and were further investigated by KEGG metabolic pathway analysis. Many of these downregulated neurotransmitters shared the same enzyme responsible for metabolism, aromaticl-amino acid decarboxylase, suggesting a mechanistic role. These data constitute a new approach that could help identify novel mechanisms of toxicity in complex tissues. Graphical abstract.

Examining NTA performance and potential using fortified and reference house dust as part of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT).

Non-targeted analysis (NTA) methods are being increasingly used to aid in the identification of unknown compounds in the environment, a problem that has challenged environmental chemists for decades. Despite its increased use, quality assurance practices for NTA have not been well established. Furthermore, capabilities and limitations of certain NTA methods have not been thoroughly evaluated. Standard reference material dust (SRM 2585) was used here to evaluate the ability of NTA to identify previously reported compounds, as well as a suite of 365 chemicals that were spiked at various stages of the analytical procedure. Analysis of the unaltered SRM 2585 extracts revealed that several previously reported compounds can be identified by NTA, and that correct identification was dependent on concentration. A manual inspection of unknown features in SRM 2585 revealed the presence of two chlorinated and fluorinated compounds in high abundance, likely precursors to perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS). A retrospective analysis of data from the American Healthy Homes Survey revealed that these compounds were present in 42% of sampled homes. Spiking the dust at various stages of sample preparation revealed losses from extraction, cleanup, and instrumental analysis; the log Kow for individual compounds influenced the overall recovery levels but no pattern could be discerned from the various degrees of interference that the matrix had on the ionization efficiency of the spiked chemicals. Analysis of the matrix-free chemical mixture at low, medium, and high concentrations led to more correct identifications than analysis at one, very high concentration. Varying the spiked amount and identifying reported compounds at known concentrations allowed an estimation of the lower limits of identification (LOIs) for NTA, analogous to limits of detection in targeted analysis. The LOIs were much lower than levels in dust that would be likely to cause bioactivity in humans, indicating that NTA is useful for identifying and monitoring compounds that may be of toxicological concern. Graphical abstract.

Association between prenatal immune phenotyping and cord blood leukocyte telomere length in the PRISM pregnancy cohort.

BACKGROUND: Environmental exposures including air pollutants, toxic metals, and psychosocial stress have been associated with shorter telomere length (TL) in newborns. These exposures have in turn been linked to an enhanced inflammatory immune response. Increased inflammation during pregnancy may be a central biological pathway linking environmental factors with reduced TL at birth. Approaches that more comprehensively characterize the prenatal inflammatory milieu rather than targeting specific individual cytokines in relation to newborn TL may better elucidate inflammatory mechanisms. METHODS: Analyses included 129 mother-child dyads enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) pregnancy cohort. We measured 92 inflammation related proteins during pregnancy in maternal serum using the Olink protein array and quantified cord blood relative leukocyte TL (rLTL) via qPCR. We leveraged a tree-based machine learning algorithm to select the most important inflammatory related proteins jointly associated with rLTL. We then evaluated the combined association between the selected proteins with rLTL using Bayesian Weighted Quantile Sum (BWQS) Regression. Analyses were adjusted for gestational week of serum collection, maternal race/ethnicity, age, and education, and fetal sex. We evaluated major biological function of the identified proteins by using the UniProtKB, a centralized repository of curated functional information. RESULTS: Three proteins were negatively and linearly associated with rLTL (CASP8 ß: -0.22 p = 0.008, BNGF ß: -0.43 p = 0.033, TRANCE ß: 0.38 p = 0.004). Results from BWQS regression showed a significant overall decrease in rLTL (ß: -0.26 95%CrI: -0.43, -0.07) per quartile increase of the mixture, with CASP8 contributing the greatest weight (CASP8 50%; BNGF 27%, and TRANCE 23%). The identified proteins were involved in the regulation of apoptotic processes and cell proliferation. CONCLUSIONS: This proteomics approach identifies novel maternal prenatal inflammatory protein biomarkers associated with shortened rLTL in newborns.

Toxicity testing in the 21st century: progress in the past decade and future perspectives.

Advances in the biological sciences have led to an ongoing paradigm shift in toxicity testing based on expanded application of high-throughput in vitro screening and in silico methods to assess potential health risks of environmental agents. This review examines progress on the vision for toxicity testing elaborated by the US National Research Council (NRC) during the decade that has passed since the 2007 NRC report on Toxicity Testing in the 21st Century (TT21C). Concomitant advances in exposure assessment, including computational approaches and high-throughput exposomics, are also documented. A vision for the next generation of risk science, incorporating risk assessment methodologies suitable for the analysis of new toxicological and exposure data, resulting in human exposure guidelines is described. Case study prototypes indicating how these new approaches to toxicity testing, exposure measurement, and risk assessment are beginning to be applied in practice are presented. Overall, progress on the 20-year transition plan laid out by the US NRC in 2007 has been substantial. Importantly, government agencies within the United States and internationally are beginning to incorporate the new approach methodologies envisaged in the original TT21C vision into regulatory practice. Future perspectives on the continued evolution of toxicity testing to strengthen regulatory risk assessment are provided.

[Progress in the application of exposomics in risk assessment of environmental chemicals].

With the increasing number of environmental chemicals, the risk assessment system based on animal toxicity testing is difficult to satisfy the current demands and needs to be reformed urgently. With the wide application of high-throughput screening technology, the advantage of exposomics in risk assessment is gradually emerging. Exposomics aims to study the health effects of mixed environmental exposure at different stages of life (especially in the early stage of life) through the dynamic monitoring of external and internal exposure levels. Exposomics is introduced into risk assessment to systematically study gene-environment interaction so as to provide a reliable basis for the construction of exposure-biomarker-disease network. This review summarized the importance and application prospect of exposomics in risk assessment of environmental chemicals in terms of the research progress, application in risk assessment and existing problems, opportunities and challenges.

Ion Mobility Spectrometry and the Omics: Distinguishing Isomers, Molecular Classes and Contaminant Ions in Complex Samples.

Ion mobility spectrometry (IMS) is a widely used analytical technique providing rapid gas phase separations. IMS alone is useful, but its coupling with mass spectrometry (IMS-MS) and various front-end separation techniques has greatly increased the molecular information achievable from different omic analyses. IMS-MS analyses are specifically gaining attention for improving metabolomic, lipidomic, glycomic, proteomic and exposomic analyses by increasing measurement sensitivity (e.g. S/N ratio), reducing the detection limit, and amplifying peak capacity. Numerous studies including national security-related analyses, disease screenings and environmental evaluations are illustrating that IMS-MS is able to extract information not possible with MS alone. Furthermore, IMS-MS has shown great utility in salvaging molecular information for low abundance molecules of interest when high concentration contaminant ions are present in the sample by reducing detector suppression. This review highlights how IMS-MS is currently being used in omic analyses to distinguish structurally similar molecules, isomers, molecular classes and contaminant ions.

Food allergy and omics.

Food allergy (FA) prevalence has been increasing over the last few decades and is now a global health concern. Current diagnostic methods for FA result in a high number of false-positive results, and the standard of care is either allergen avoidance or use of epinephrine on accidental exposure, although currently with no other approved treatments. The increasing prevalence of FA, lack of robust biomarkers, and inadequate treatments warrants further research into the mechanism underlying food allergies. Recent technological advances have made it possible to move beyond traditional biological techniques to more sophisticated high-throughput approaches. These technologies have created the burgeoning field of omics sciences, which permit a more systematic investigation of biological problems. Omics sciences, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, have enabled the construction of regulatory networks and biological pathway models. Parallel advances in bioinformatics and computational techniques have enabled the integration, analysis, and interpretation of these exponentially growing data sets and opens the possibility of personalized or precision medicine for FA.

Quantitative characterization of the urine and serum metabolomes of children is essential for 'omics' studies.

Understanding the long-term health impacts of the early-life exposome requires the characterization and assimilation of multi 'omics' data to ultimately link molecular changes to exposures. In this way, markers associated with negative health outcomes, such as increased disease risk, can be ascertained. However, determining the extent and direction of metabolic perturbations relies on comparisons to existing metabolomic reference profiles. While such resources are increasingly available for adult populations, analogous tools for children are decidedly lacking. Lau et al. have compiled robust, translatable quantitative metabolomics data on urine and serum samples for European children across six study locations. Metabolites were associated with body mass index, diet and demographics, and correlated within and between biofluids. As a result, a novel association between urinary 4-deoxyerythronic acid and body mass index was uncovered. This work serves as a crucial reference for future studies in exposomics, and - more broadly - represents a significant step forward for metabolomics by creating the foundation for a comprehensive reference metabolome for children.Please see related article: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-018-1190-8.

IR-MALDESI mass spectrometry imaging of underivatized neurotransmitters in brain tissue of rats exposed to tetrabromobisphenol A.

There is a pressing need to develop tools for assessing possible neurotoxicity, particularly for chemicals where the mode of action is poorly understood. Tetrabromobisphenol A (TBBPA), a highly abundant brominated flame retardant, has lately been targeted for neurotoxicity analysis by concerned public health entities in the EU and USA because it is a suspected thyroid disruptor and neurotoxicant. In this study, infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) coupled to a Q Exactive Plus mass spectrometer was used for the analysis of neurotransmitters in the brains of rats exposed to TBBPA in gestation and lactation through their mothers. Three neurotransmitters of interest were studied in three selected regions of the brain: caudate putamen, substantia nigra (SN), and dorsal raphe. Stable isotope labeled (SIL) standards were used as internal standards and a means to achieve relative quantification. This study serves as a demonstration of a new application of IR-MALDESI, namely that neurotransmitter distributions can be confidently and rapidly imaged without derivatization.