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Abstract Interstitial lung diseases (ILDs) include a variety of inflammatory and fibrotic pulmonary conditions. This study employs high‐resolution metabolomics (HRM) to explore plasma metabolites and pathways across ILD phenotypes, including non‐fibrotic ILD, idiopathic pulmonary fibrosis (IPF), and non‐IPF fibrotic ILD. The study used 80 plasma samples for HRM, and involved linear trend and group‐wise analyses of metabolites altered in ILD phenotypes. We utilized limma one‐way ANOVA and mummichog algorithms to identify differences in metabolites and pathways across ILD groups. Then, we focused on metabolites within critical pathways, indicated by high pathway overlap sizes and low p‐values, for further analysis. Targeted HRM identified putrescine, hydroxyproline, prolyl‐hydroxyproline, aspartate, and glutamate with significant linear increases in more fibrotic ILD phenotypes, suggesting their role in ILD fibrogenesis. Untargeted HRM highlighted pathway alterations in lysine, vitamin D3, tyrosine, and urea cycle metabolism, all associated with pulmonary fibrosis. In addition, methylparaben level had a significantly increasing linear trend and was higher in the IPF than fibrotic and non‐ILD groups. This study highlights the importance of specific amino acids, metabolic pathways, and xenobiotics in the progression of pulmonary fibrosis.

Abstract Plasma metabolomics profiling is an emerging methodology to identify metabolic pathways underlying cardiovascular health (CVH). The objective of this study was to define metabolomic profiles underlying CVH in a cohort of Black adults, a population that is understudied but suffers from disparate levels of CVD risk factors. The Morehouse-Emory Cardiovascular (MECA) Center for Health Equity study cohort consisted of 375 Black adults (age 53 ± 10, 39% male) without known CVD. CVH was determined by the AHA Life’s Simple 7 (LS7) score, calculated from measured blood pressure, body mass index (BMI), fasting blood glucose and total cholesterol, and self-reported physical activity, diet, and smoking. Plasma metabolites were assessed using untargeted high-resolution metabolomics profiling. A metabolome wide association study (MWAS) identified metabolites associated with LS7 score after adjusting for age and sex. Using Mummichog software, metabolic pathways that were significantly enriched in metabolites associated with LS7 score were identified. Metabolites representative of these pathways were compared across clinical domains of LS7 score and then developed into a metabolomics risk score for prediction of CVH. We identified novel metabolomic signatures and pathways associated with CVH in a cohort of Black adults without known CVD. Representative and highly prevalent metabolites from these pathways included glutamine, glutamate, urate, tyrosine and alanine, the concentrations of which varied with BMI, fasting glucose, and blood pressure levels. When assessed in conjunction, these metabolites were independent predictors of CVH. One SD increase in the novel metabolomics risk score was associated with a 0.88 higher LS7 score, which translates to a 10.4% lower incident CVD risk. We identified novel metabolomic signatures of ideal CVH in a cohort of Black Americans, showing that a core group of metabolites central to nitrogen balance, bioenergetics, gluconeogenesis, and nucleotide synthesis were associated with CVH in this population.

Abstract Background Untargeted high-resolution metabolomic profiling provides simultaneous measurement of thousands of metabolites. Metabolic networks based on these data can help uncover disease-related perturbations across interconnected pathways. Objective Identify metabolic disturbances associated with Parkinson’s disease (PD) in two population-based studies using untargeted metabolomics. Methods We performed a metabolome-wide association study (MWAS) of PD using serum-based untargeted metabolomics data derived from liquid chromatography with high-resolution mass spectrometry (LC-HRMS) using two distinct population-based case-control populations. We also combined our results with a previous publication of 34 metabolites linked to PD in a large-scale, untargeted MWAS to assess external validation. Results LC-HRMS detected 4,762 metabolites for analysis (HILIC: 2716 metabolites; C18: 2046 metabolites). We identified 296 features associated with PD at FDR

Background: Strong epidemiological evidence shows positive associations between exposure to per- and polyfluoroalkyl substances (PFAS) and adverse cardiometabolic outcomes (e.g., diabetes, hypertension, and dyslipidemia). However, the underlying cardiometabolic-relevant biological activities of PFAS in humans remain largely unclear. Aim: We evaluated the associations of PFAS exposure with high-throughput proteomics in Hispanic youth. Material and Methods: We included 312 overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) between 2001 and 2012, along with 137 young adults from the Metabolic and Asthma Incidence Research (Meta-AIR) between 2014 and 2018. Plasma PFAS (i.e., PFOS, PFOA, PFHxS, PFHpS, PFNA) were quantified using liquid-chromatography high-resolution mass spectrometry. Plasma proteins (n = 334) were measured utilizing the proximity extension assay using an Olink Explore Cardiometabolic Panel I. We conducted linear regression with covariate adjustment to identify PFAS-associated proteins. Ingenuity Pathway Analysis, protein-protein interaction network analysis, and protein annotation were used to investigate alterations in biological functions and protein clusters. Results: Results after adjusting for multiple comparisons showed 13 significant PFAS-associated proteins in SOLAR and six in Meta-AIR, sharing similar functions in inflammation, immunity, and oxidative stress. In SOLAR, PFNA demonstrated significant positive associations with the largest number of proteins, including ACP5, CLEC1A, HMOX1, LRP11, MCAM, SPARCL1, and SSC5D. After considering the mixture effect of PFAS, only SSC5D remained significant. In Meta-AIR, PFAS mixtures showed positive associations with GDF15 and IL6. Exploratory analysis showed similar findings. Specifically, pathway analysis in SOLAR showed PFOA- and PFNA-associated activation of immune-related pathways, and PFNA-associated activation of inflammatory response. In Meta-AIR, PFHxS-associated activation of dendric cell maturation was found. Moreover, PFAS was associated with common protein clusters of immunoregulatory interactions and JAK-STAT signaling in both cohorts. Conclusion: PFAS was associated with broad alterations of the proteomic profiles linked to pro-inflammation and immunoregulation. The biological functions of these proteins provide insight into potential molecular mechanisms of PFAS toxicity.

Background: Per- and polyfluoroalkyl substances (PFAS) are pollutants linked to adverse health effects. Diet is an important source of PFAS exposure, yet it is unknown how diet impacts longitudinal PFAS levels. Objective: To determine if dietary intake and food sources were associated with changes in blood PFAS concentrations among Hispanic young adults at risk of metabolic diseases. Methods: Predominantly Hispanic young adults from the Children’s Health Study who underwent two visits (CHS; n = 123) and young adults from NHANES 2013–2018 who underwent one visit (n = 604) were included. Dietary data at baseline was collected using two 24-hour dietary recalls to measure individual foods and where foods were prepared/consumed (home/restaurant/fast-food). PFAS were measured in blood at both visits in CHS and cross-sectionally in NHANES. In CHS, multiple linear regression assessed associations of baseline diet with longitudinal PFAS; in NHANES, linear regression was used. Results: In CHS, all PFAS except PFDA decreased across visits (all p

Abstract Background Cardiac pathological outcome of metabolic remodeling is difficult to model using cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CMs) due to low metabolic maturation. Methods hiPSC-CM spheres were treated with AMP-activated protein kinase (AMPK) activators and examined for hiPSC-CM maturation features, molecular changes and the response to pathological stimuli. Results Treatment of hiPSC-CMs with AMPK activators increased ATP content, mitochondrial membrane potential and content, mitochondrial DNA, mitochondrial function and fatty acid uptake, indicating increased metabolic maturation. Conversely, the knockdown of AMPK inhibited mitochondrial maturation of hiPSC-CMs. In addition, AMPK activator-treated hiPSC-CMs had improved structural development and functional features—including enhanced Ca2+ transient kinetics and increased contraction. Transcriptomic, proteomic and metabolomic profiling identified differential levels of expression of genes, proteins and metabolites associated with a molecular signature of mature cardiomyocytes in AMPK activator-treated hiPSC-CMs. In response to pathological stimuli, AMPK activator-treated hiPSC-CMs had increased glycolysis, and other pathological outcomes compared to untreated cells. Conclusion AMPK activator-treated cardiac spheres could serve as a valuable model to gain novel insights into cardiac diseases.

Abstract This report identifies, for the first time, a phytochelatin compound, phytochelatin 2 [γ‐E‐C‐γ‐E‐C‐G], and related metabolites in human urine. Phytochelatins are metal‐binding peptides produced by plants. They are present in nearly all human diets, due to their ubiquity in plants. The urinary concentration of phytochelatin 2 among 143 adults was in the low micromolar range, and phytochelatin 2 and its metabolites had differential correlations with urinary selenium and toxic metals. Activities of ingested phytochelatins are largely undescribed. Observed urinary metal interactions were investigated further in cell and animal models. Selenite reacted with phytochelatin to form a phytochelatin selenotrisulfide, and the preformed selenotrisulfide showed increased selenium uptake by renal proximal tubule cells. In vivo studies further showed that oral phytochelatin increased renal selenium content and decreased lung cadmium in mice. Presence of phytochelatin in human urine combined with its function in selenium and heavy metal distribution present a new route by which diet may influence metal disposition and bioavailability.

Background: Retinoblastoma is rare but nevertheless the most common pediatric eye cancer that occurs in children under age 5. High-resolution metabolomics (HRM) is a powerful analytical approach to profile metabolic features and pathways or identify metabolite biomarkers. To date, no studies have used pre-diagnosis blood samples from retinoblastoma cases and compared them to healthy controls to elucidate early perturbations in tumor pathways. Objectives: Here, we report on metabolic profiles of neonatal blood comparing cases later in childhood diagnosed with retinoblastoma and controls. Methods: We employed untargeted metabolomics analysis using neonatal dried blood spots for 1327 children (474 retinoblastoma cases and 853 healthy controls) born in California from 1983 to 2011. Cases were selected from the California Cancer Registry and controls, frequency matched to cases by birth year, from California birth rolls. We performed high-resolution metabolomics to extract metabolic features, partial least squares discriminant analysis (PLS-DA) and logistic regression to identify features associated with disease, and Mummichog pathway analysis to characterize enriched biological pathways. Results: PLS-DA identified 1917 discriminative features associated with retinoblastoma and Mummichog identified 14 retinoblastoma-related enriched pathways including linoleate metabolism, pentose phosphate pathway, pyrimidine metabolism, fructose and mannose metabolism, vitamin A metabolism, as well as fatty acid and lipid metabolism. Interpretation: Our findings linked a retinoblastoma diagnosis in early life to newborn blood metabolome perturbations indicating alterations in inflammatory pathways and energy metabolism. Neonatal blood spots may provide a venue for early detection for this or potentially other childhood cancers.

Abstract Marginalized populations experience disproportionate rates of preterm birth and early term birth. Exposure to per- and polyfluoroalkyl substances (PFAS) has been reported to reduce length of gestation, but the underlying mechanisms are unknown. In the present study, we characterized the molecular signatures of prenatal PFAS exposure and gestational age at birth outcomes in the newborn dried blood spot metabolome among 267 African American dyads in Atlanta, Georgia between 2016 and 2020. Pregnant people with higher serum perfluorooctanoic acid and perfluorohexane sulfonic acid concentrations had increased odds of an early birth. After false discovery rate correction, the effect of prenatal PFAS exposure on reduced length of gestation was associated with 8 metabolomic pathways and 52 metabolites in newborn dried blood spots, which suggested perturbed tissue neogenesis, neuroendocrine function, and redox homeostasis. These mechanisms explain how prenatal PFAS exposure gives rise to the leading cause of infant death in the United States.

Background: Agricultural workers are consistently exposed to elevated heat exposures and vulnerable to acute kidney injury. The underlying pathophysiology and detailed molecular mechanisms of AKI among agricultural workers, and the disproportionate burden of HRI and heat stress exposure are not well understood, especially at the level of cellular metabolism. Objective: The aim of this study was to examine the impact of heat exposures on renal biomarkers and on the human metabolome via untargeted high-resolution metabolomics among agricultural and non-agricultural workers. Methods: Blood and urine samples were collected pre- and post-work shift from 63 agricultural workers and 27 non– agricultural workers. We evaluated pre- and post-work shift renal biomarkers and completed untargeted metabolomics using high-resolution mass spectrometry with liquid chromatography. Metabolome-wide association studies (MWAS) models identified the metabolic features differentially expressed between agricultural workers and non-agricultural workers. Results: Median values of pre-shift creatinine and osteopontin (p

Summary: Background: Unravelling the relationships between candidate genes and autism spectrum disorder (ASD) phenotypes remains an outstanding challenge. Endophenotypes, defined as inheritable, measurable quantitative traits, might provide intermediary links between genetic risk factors and multifaceted ASD phenotypes. In this study, we sought to determine whether plasma metabolite levels could serve as endophenotypes in individuals with ASD and their family members. Methods: We employed an untargeted, high-resolution metabolomics platform to analyse 14,342 features across 1099 plasma samples. These samples were collected from probands and their family members participating in the Autism Genetic Resource Exchange (AGRE) (N = 658), compared with neurotypical individuals enrolled in the PrecisionLink Health Discovery (PLHD) program at Boston Children's Hospital (N = 441). We conducted a metabolite quantitative trait loci (mQTL) analysis using whole-genome genotyping data from each cohort in AGRE and PLHD, aiming to prioritize significant mQTL and metabolite pairs that were exclusively observed in AGRE. Findings: Within the AGRE group, we identified 54 significant associations between genotypes and metabolite levels (P

Abstract Background Emotional behavior problems (EBP) are the most common and persistent mental health issues in early childhood. Early intervention programs are crucial in helping children with EBP. Parent–child interaction therapy (PCIT) is an evidence-based therapy designed to address personal difficulties of parent–child dyads as well as reduce externalizing behaviors. In clinical practice, parents consistently struggle to provide accurate characterizations of EBP symptoms (number, timing of tantrums, precipitating events) even from the week before in their young children. The main aim of the study is to evaluate feasibility of the use of smartwatches in children aged 3–7 years with EBP. Methods This randomized double-blind controlled study aims to recruit a total of 100 participants, consisting of 50 children aged 3–7 years with an EBP measure rated above the clinically significant range (T-score ≥ 60) (Eyberg Child Behavior Inventory-ECBI; Eyberg & Pincus, 1999) and their parents who are at least 18 years old. Participants are randomly assigned to the artificial intelligence-PCIT group (AI-PCIT) or the PCIT-sham biometric group. Outcome parameters include weekly ECBI and Pediatric Sleep Questionnaire (PSQ) as well as Child Behavior Checklist (CBCL) obtained weeks 1, 6, and 12 of the study. Two smartphone applications (Garmin connect and mEMA) and a wearable Garmin smartwatch are used collect the data to monitor step count, sleep, heart rate, and activity intensity. In the AI-PCIT group, the mEMA application will allow for the ecological momentary assessment (EMA) and will send behavioral alerts to the parent. Discussion Real-time predictive technologies to engage patients rely on daily commitment on behalf of the participant and recurrent frequent smartphone notifications. Ecological momentary assessment (EMA) provides a way to digitally phenotype in-the-moment behavior and functioning of the parent–child dyad. One of the study’s goals is to determine if AI-PCIT outcomes are superior in comparison with standard PCIT. Overall, we believe that the PISTACHIo study will also be able to determine tolerability of smartwatches in children aged 3–7 with EBP and could participate in a fundamental shift from the traditional way of assessing and treating EBP to a more individualized treatment plan based on real-time information about the child’s behavior. Trial registration The ongoing clinical trial study protocol conforms to the international Consolidated Standards of Reporting Trials (CONSORT) guidelines and is registered in clinicaltrials.gov (ID: NCT05077722), an international clinical trial registry.

Abstract During the first 2 years of life, the infant gut microbiome is rapidly developing, and gut bacteria may impact host health through the production of metabolites that can have systemic effects. Thus, the fecal metabolome represents a functional readout of gut bacteria. Despite the important role that fecal metabolites may play in infant health, the development of the infant fecal metabolome has not yet been thoroughly characterized using frequent, repeated sampling during the first 2 years of life. Here, we described the development of the fecal metabolome in a cohort of 101 Latino infants with data collected at 1-, 6-, 12-, 18-, and 24-months of age. We showed that the fecal metabolome is highly conserved across time and highly personalized, with metabolic profiles being largely driven by intra-individual variability. Finally, we also identified several novel metabolites and metabolic pathways that changed significantly with infant age, such as valerobetaine and amino acid metabolism, among others.

Cpt1a-dependent fatty acid beta-oxidation is found to regulate neutrophil trafficking to the site of infection in a mouse model of pneumonia and is found to play a role in pneumonia susceptibility in humans.

Abstract Background The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels, while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype–metabotype associations. However, these associations have not been characterized in children. Results We conducted the largest genome by metabolome-wide association study to date of children (N = 441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h 2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h 2 (> 0.8) for 15.9% of features and low h 2 (

Measurement(s) parasitemia • blood Chemistry • reticulocyte count • platelet activation status • neutrophil and monocyte activation after stimulation • T-cell phenotyping • B-cell phenotyping • monocyte phenotyping • dendritic cell phenotyping • lymphocyte phenotyping • multiplexed cytokine assay • erythropoietin measurement • total IgG concentration • transcriptome • metabolomics • lipidomics • proteomics Technology Type(s) brightfield microscopy • iSTAT machine • immunological flow cytometry • chemokine receptor markers • intracellular staining • ELISA • LC/MS Factor Type(s) Parasitemia Sample Characteristic - Organism Macaca mulatta • Plasmodium cynomolgi B/M strain • Plasmodium cynomolgi Ceylon Sample Characteristic - Environment venous blood • capillary blood

Abstract Pediatric liver transplantation rejection affects 20% of children. Currently, liver biopsy, expensive and invasive, is the best method of diagnosis. Discovery and validation of clinical biomarkers from blood or other biospecimens would improve clinical care. For this study, stored plasma samples were utilized from two cross-sectional cohorts of liver transplant patients at Children’s Healthcare of Atlanta. High resolution metabolic profiling was completed using established methods. Children with (n = 18) or without (n = 25) acute cellular rejection were included in the analysis (n = 43 total). The mean age of these racially diverse cohorts ranged from 12.6 years in the rejection group and 13.6 years in the no rejection group. Linear regression provided 510 significantly differentiating metabolites between groups, and OPLS-DA showed 145 metabolites with VIP > 2. A total of 95 overlapping significant metabolites between OPLS-DA and linear regression analyses were detected. Pathway analysis (p 500 significant metabolites. This result suggests that development of a non-invasive biomarker-based test is possible for rejection screening.

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry of pregnancy cohort biospecimens in the Child Health and Development Studies to test for associations with breast cancer identified via the California Cancer Registry. Second and third trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both second and third trimesters to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol, linked to variations in amino acid and nucleotide pathways in second trimester and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in third trimester. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

Cadmium (Cd) is a toxic environmental metal that interacts with selenium (Se) and contributes to many lung diseases. Humans have widespread exposures to Cd through diet and cigarette smoking, and studies in rodent models show that Se can protect against Cd toxicities. We sought to identify whether an antagonistic relationship existed between Se and Cd burdens and determine whether this relationship may associate with metabolic variation within human lungs. We performed metabolomics of 31 human lungs, including 25 with end-stage lung disease due to idiopathic pulmonary fibrosis, cystic fibrosis, chronic obstructive lung disease (COPD)/emphysema and other causes, and 6 non-diseased lungs. Results showed pathway associations with Cd including amino acid, lipid and energy-related pathways. Metabolic pathways varying with Se had considerable overlap with these pathways. Hierarchical cluster analysis (HCA) of individuals according to metabolites associated with Cd showed partial separation of disease types, with COPD/emphysema in the cluster with highest Cd, and non-diseased lungs in the cluster with the lowest Cd. When compared to HCA of metabolites associated with Se, the results showed that the cluster containing COPD/emphysema had the lowest Se, and the non-diseased lungs had the highest Se. A greater number of pathway associations occurred for Cd to Se ratio than either Cd or Se alone, indicating that metabolic patterns were more dependent on Cd to Se ratio than on either alone. Network analysis of interactions of Cd and Se showed network centrality was associated with pathways linked to polyunsaturated fatty acids involved in inflammatory signaling. Overall, the data show that metabolic pathway responses in human lung vary with Cd and Se in a pattern suggesting that Se is antagonistic to Cd toxicity in humans.

Progress in development of prognostic and therapeutic options for the rare cholestatic liver diseases, primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC), is hampered by limited knowledge of their pathogeneses. In particular, the potential role of hepatotoxic and/or metabolism‐altering environmental chemicals in the pathogenesis of these diseases remains relatively unstudied. Moreover, the extent to which metabolic pathways are altered due to ongoing cholestasis and subsequent liver damage or possibly influenced by hepatotoxic chemicals is poorly understood. In this study, we applied a comprehensive exposomics‐metabolomics approach to uncover potential pathogenic contributors to PSC and PBC. We used untargeted high‐resolution mass spectrometry to characterize a wide range of exogenous chemicals and endogenous metabolites in plasma and tested them for association with disease. Exposome‐wide association studies (EWAS) identified environmental chemicals, including pesticides, additives and persistent pollutants, that were associated with PSC and/or PBC, suggesting potential roles for these compounds in disease pathogenesis. Metabolome‐wide association studies (MWAS) found disease‐associated alterations to amino acid, eicosanoid, lipid, co‐factor, nucleotide, mitochondrial and microbial metabolic pathways, many of which were shared between PSC and PBC. Notably, this analysis implicates a potential role of the 5‐lipoxygenase pathway in the pathogenesis of these diseases. Finally, EWAS × MWAS network analysis uncovered linkages between environmental agents and disrupted metabolic pathways that provide insight into potential mechanisms for PSC and PBC. Conclusion: This study establishes combined exposomics‐metabolomics as a generalizable approach to identify potentially pathogenic environmental agents and enumerate metabolic alterations that may impact PSC and PBC, providing a foundation for diagnostic and therapeutic strategies.

Abstract Background Adiposity and mitochondrial dysfunction are related factors contributing to metabolic disease development. This pilot study examined whether in vivo and ex vivo indices of mitochondrial metabolism were differentially associated with body composition in males and females. Methods Thirty-four participants including 19 females (mean 27 yr) and 15 males (mean 29 yr) had body composition assessed by dual energy x-ray absorptiometry and magnetic resonance (MR) imaging. Monocyte reserve capacity and maximal oxygen consumption rate (OCR) were determined ex vivo using extracellular flux analysis. In vivo quadriceps mitochondrial function was measured using 31P-MR spectroscopy based on post-exercise recovery kinetics (τPCr). The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated from fasting glucose and insulin levels. Variables were log-transformed, and Pearson correlations and partial correlations were used for analyses. Results Mitochondrial metabolism was similar between sexes (p > 0.05). In males only, higher fat mass percent (FM%) was correlated with lower reserve capacity (r = − 0.73; p = 0.002) and reduced muscle mitochondrial function (r = 0.58, p = 0.02). Thigh subcutaneous adipose tissue was inversely related to reserve capacity in males (r = − 0.75, p = 0.001), but in females was correlated to higher maximal OCR (r = 0.48, p = 0.046), independent of FM. In females, lean mass was related to greater reserve capacity (r = 0.47, p = 0.04). In all participants, insulin (r = 0.35; p = 0.04) and HOMA-IR (r = 0.34; p = 0.05) were associated with a higher τPCr. Conclusions These novel findings demonstrate distinct sex-dependent associations between monocyte and skeletal muscle mitochondrial metabolism with body composition. With further study, increased understanding of these relationships may inform sex-specific interventions to improve mitochondrial function and metabolic health.

Abstract Bovine fescue toxicosis (FT) is caused by grazing ergot alkaloid-producing endophyte (Epichloë coenophiala)-infected tall fescue. Endophyte’s effects on the animal’s microbiota and metabolism were investigated recently, but its effects in planta or on the plant–animal interactions have not been considered. We examined multi-compartment microbiota–metabolome perturbations using multi-‘omics (16S and ITS2 sequencing, plus untargeted metabolomics) in Angus steers grazing non-toxic (Max-Q) or toxic (E+) tall fescue for 28 days and in E+ plants. E+ altered the plant/animal microbiota, decreasing most ruminal fungi, with mixed effects on rumen bacteria and fecal microbiota. Metabolic perturbations occurred in all matrices, with some plant-animal overlap (e.g., Vitamin B6 metabolism). Integrative interactomics revealed unique E+ network constituents. Only E+ had ruminal solids OTUs within the network and fecal fungal OTUs in E+ had unique taxa (e.g., Anaeromyces). Three E+-unique urinary metabolites that could be potential biomarkers of FT and targeted therapeutically were identified.

Abstract The 1.6 Mb 3q29 deletion is associated with developmental and psychiatric phenotypes, including a 40-fold increased risk for schizophrenia. Reduced birth weight and a high prevalence of feeding disorders in patients suggest underlying metabolic dysregulation. We investigated 3q29 deletion-induced metabolic changes using our previously generated heterozygous B6.Del16+/Bdh1-Tfrc mouse model. Animals were provided either standard chow (STD) or high-fat diet (HFD). Growth curves were performed on HFD mice to assess weight change (n = 30–50/group). Indirect calorimetry and untargeted metabolomics were performed on STD and HFD mice to evaluate metabolic phenotypes (n = 8–14/group). A behavioral battery was performed on STD and HFD mice to assess behavior change after the HFD challenge (n = 5–13/group). We found that B6.Del16+/Bdh1-Tfrc animals preferentially use dietary lipids as an energy source. Untargeted metabolomics of liver tissue showed a strong sex-dependent effect of the 3q29 deletion on fat metabolism. A HFD partially rescued the 3q29 deletion-associated weight deficit in females, but not males. Untargeted metabolomics of liver tissue after HFD revealed persistent fat metabolism alterations in females. The HFD did not affect B6.Del16+/Bdh1-Tfrc behavioral phenotypes, suggesting that 3q29 deletion-associated metabolic and behavioral outcomes are uncoupled. Our data suggest that dietary interventions to improve weight phenotypes in 3q29 deletion syndrome patients are unlikely to exacerbate behavioral manifestations. Our study also highlights the importance of assessing sex in metabolic studies and suggests that mechanisms underlying 3q29 deletion-associated metabolic phenotypes are sex-specific.

Abstract Pulmonary arterial hypertension (PAH) prevalence is increasing worldwide, and the prognosis is poor with 5‐year survival

Previous studies have suggested that a relationship exists between severity and transmissibility of malaria and variations in the gut microbiome, yet only limited information exists on the temporal dynamics of the gut microbial community during a malarial infection. Here, using a rhesus macaque model of relapsing malaria, we investigate how malaria affects the gut microbiome. In this study, we performed 16S sequencing on DNA isolated from rectal swabs of rhesus macaques over the course of an experimental malarial infection with Plasmodium cynomolgi and analyzed gut bacterial taxa abundance across primary and relapsing infections. We also performed metabolomics on blood plasma from the animals at the same timepoints and investigated changes in metabolic pathways over time. Members of Proteobacteria (family Helicobacteraceae) increased dramatically in relative abundance in the animal’s gut microbiome during peak infection while Firmicutes (family Lactobacillaceae and Ruminococcaceae), Bacteroidetes (family Prevotellaceae) and Spirochaetes amongst others decreased compared to baseline levels. Alpha diversity metrics indicated decreased microbiome diversity at the peak of parasitemia, followed by restoration of diversity post-treatment. Comparison with healthy subjects suggested that the rectal microbiome during acute malaria is enriched with commensal bacteria typically found in the healthy animal’s mucosa. Significant changes in the tryptophan-kynurenine immunomodulatory pathway were detected at peak infection with P. cynomolgi, a finding that has been described previously in the context of P. vivax infections in humans. During relapses, which have been shown to be associated with less inflammation and clinical severity, we observed minimal disruption to the gut microbiome, despite parasites being present. Altogether, these data suggest that the metabolic shift occurring during acute infection is associated with a concomitant shift in the gut microbiome, which is reversed post-treatment.

Humans are exposed to millions of chemicals but mass spectrometry (MS)-based targeted biomonitoring assays are usually limited to a few hundred known hazards. Here, the authors develop a workflow for MS-based untargeted exposome profiling of known and unidentified environmental chemicals.

Humans are exposed to many xenobiotic chemicals, but identification of low abundance xenobiotic exposures is limited by a lack of authentic standards for xenobiotic metabolites. Here the authors develop methods for enzymatic generation of diverse xenobiotic metabolites for use with high-resolution mass spectrometry for biology-based chemical identification.

Background: Human and animal exposure to bisphenol A (BPA) has been associated with adverse developmental and reproductive effects. The molecular mechanisms by which BPA exposure exerts its effects are not well-understood, even less known about its analogues bisphenol F (BPF). To address these knowledge gaps, we conducted an untargeted metabolome-wide association study (MWAS) to identify metabolic perturbations associated with BPA/BPF exposures in a pregnant African American cohort. Methods: From a subset of study participants enrolled in the Atlanta African American Maternal-Child cohort, we collected both urine samples, for targeted exposure assessment of BPA (N = 230) and BPF (N = 48), and serum samples, for high-resolution metabolomics (HRM) profiling (N = 230), during early pregnancy (8–14 weeks’ gestation). Using an established untargeted HRM workflow consisting of MWAS modeling, pathway enrichment analysis, and chemical annotation and confirmation, we investigated the potential metabolic pathways and features associated with BPA/BPF exposures. Results: The geometric mean creatinine-adjusted concentrations of urinary BPA and BPF were 0.85 ± 2.58 and 0.70 ± 4.71 µg/g creatinine, respectively. After false positive discovery rate correction at 20 % level, 264 and 733 unique metabolic features were significantly associated with urinary BPA and BPF concentrations, representing 10 and 12 metabolic pathways, respectively. Three metabolic pathways, including steroid hormones biosynthesis, lysine and lipoate metabolism, were significantly associated with both BPA and BPF exposure. Using chemical standards, we have confirmed the chemical identity of 16 metabolites significantly associated with BPA or BPF exposure. Conclusions: Our findings support that exposure to BPA and BPF in pregnant women is associated with the perturbation of aromatic amino acid metabolism, xenobiotics metabolism, steroid biosynthesis, and other amino acid metabolism closely linked to stress responses, inflammation, neural development, reproduction, and weight regulation.

Both environmental exposure to vanadium pentoxide (V2O5, V+5 for its ionic counterparts) and fibroblast senescence are associated with pulmonary fibrosis, but whether V+5 causes fibroblast senescence remains unknown. We found in a dose-response study that 2–40 μM V+5 caused human lung fibroblasts (HLF) senescence with increased senescence-associated β-galactosidase activity and p16 expression, while cell death occurred at higher concentration (LC50, 82 μM V+5). Notably, measures of reactive oxygen species (ROS) production with fluorescence probes showed no association of ROS with V+5-dependent senescence. Preloading catalase (polyethylene-conjugated), a H2O2 scavenger, did not alleviate the cellular senescence induced by V+5. Analyses of the cellular glutathione (GSH) system showed that V+5 oxidized GSH, increased GSH biosynthesis, stimulated cellular GSH efflux and increased protein S-glutathionylation, and addition of N-acetyl cysteine inhibited V+5-elevated p16 expression, suggesting that thiol oxidation mediates V+5-caused senescence. Moreover, strong correlations between GSSG/GSH redox potential (Eh), protein S-glutathionylation, and cellular senescence (R2 > 0.99, p

Plasmodium knowlesi poses a health threat throughout Southeast Asian communities and currently causes most cases of malaria in Malaysia. This zoonotic parasite species has been studied in Macaca mulatta (rhesus monkeys) as a model for severe malarial infections, chronicity, and antigenic variation. The phenomenon of Plasmodium antigenic variation was first recognized during rhesus monkey infections. Plasmodium-encoded variant proteins were first discovered in this species and found to be expressed at the surface of infected erythrocytes, and then named the Schizont-Infected Cell Agglutination (SICA) antigens. SICA expression was shown to be spleen dependent, as SICA expression is lost after P. knowlesi is passaged in splenectomized rhesus. Here we present data from longitudinal P. knowlesi infections in rhesus with the most comprehensive analysis to date of clinical parameters and infected red blood cell sequestration in the vasculature of tissues from 22 organs. Based on the histopathological analysis of 22 tissue types from 11 rhesus monkeys, we show a comparative distribution of parasitized erythrocytes and the degree of margination of the infected erythrocytes with the endothelium. Interestingly, there was a significantly higher burden of parasites in the gastrointestinal tissues, and extensive margination of the parasites along the endothelium, which may help explain gastrointestinal symptoms frequently reported by patients with P. knowlesi malarial infections. Moreover, this margination was not observed in splenectomized rhesus that were infected with parasites not expressing the SICA proteins. This work provides data that directly supports the view that a subpopulation of P. knowlesi parasites cytoadheres and sequesters, likely via SICA variant antigens acting as ligands. This process is akin to the cytoadhesive function of the related variant antigen proteins, namely Erythrocyte Membrane Protein-1, expressed by Plasmodium falciparum.

Nuclear factor erythroid 2-related factor 2 (NRF2), a redox sensor, is vital for cellular redox homeostasis. We reported that transgenic mice expressing constitutively active Nrf2 (CaNrf2-TG) exhibit reductive stress (RS). In this study, we identified novel protein signature for RS-induced cardiomyopathy using Tandem Mass Tag (TMT) proteomic analysis in heart tissues of TG (CaNrf2-TG) mice at 6–7 months of age. A total of 1,105 proteins were extracted from 22,544 spectra. About 560 proteins were differentially expressed in TG vs. NTg hearts, indicating a global impact of RS on the myocardial proteome. Over 32 proteins were significantly altered in response to RS -20 were upregulated and 12 were downregulated in the hearts of TG vs. NTg mice, suggesting that these proteins could be putative signatures of RS. Scaffold analysis revealed a clear distinction between TG vs. NTg hearts. The majority of the differentially expressed proteins (DEPs) that were significantly altered in RS mice were found to be involved in stress related pathways such as antioxidants, NADPH, protein quality control, etc. Interestingly, proteins that were involved in mitochondrial respiration, lipophagy and cardiac rhythm were dramatically decreased in TG hearts. Of note, we identified the glutathione family of proteins as the significantly changed subset of the proteome in TG heart. Surprisingly, our comparative analysis of NGS based transcriptome and TMT-proteome indicated that ~50% of the altered proteins in TG myocardium was found to be negatively correlated with their transcript levels. In association with the altered proteome the TG mice displayed pathological cardiac remodeling.

Leigh syndrome (LS) is a severe neurometabolic disorder which lacks effective models. Here, the authors developed human neuronal models of LS carrying mutations in SURF1 which show impaired neuronal morphogenesis due to metabolic deficiencies.

Antagonistic interaction refers to opposing beneficial and adverse signaling by a single agent. Understanding opposing signaling is important because pathologic outcomes can result from adverse causative agents or the failure of beneficial mechanisms. To test for opposing responses at a systems level, we used a transcriptome–metabolome-wide association study (TMWAS) with the rationale that metabolite changes provide a phenotypic readout of gene expression, and gene expression provides a phenotypic readout of signaling metabolites. We incorporated measures of mitochondrial oxidative stress (mtOx) and oxygen consumption rate (mtOCR) with TMWAS of cells with varied manganese (Mn) concentration and found that adverse neuroinflammatory signaling and fatty acid metabolism were connected to mtOx, while beneficial ion transport and neurotransmitter metabolism were connected to mtOCR. Each community contained opposing transcriptome–metabolome interactions, which were linked to biologic functions. The results show that antagonistic interaction is a generalized cell systems response to mitochondrial ROS signaling.

Dietary sugar reduction is one therapeutic strategy for improving nonalcoholic fatty liver disease (NAFLD), and the underlying mechanisms for this effect warrant further investigation. Here, we employed metabolomics and metagenomics to examine systemic biological adaptations associated with dietary sugar restriction and (subsequent) hepatic fat reductions in youth with NAFLD. Data/samples were from a randomized controlled trial in adolescent boys (11–16 years, mean ± SD: 13.0 ± 1.9 years) with biopsy-proven NAFLD who were either provided a low free-sugar diet (LFSD) (n = 20) or consumed their usual diet (n = 20) for 8 weeks. Plasma metabolomics was performed on samples from all 40 participants by coupling hydrophilic interaction liquid chromatography (HILIC) and C18 chromatography with mass spectrometry. In a sub-sample (n = 8 LFSD group and n = 10 usual diet group), 16S ribosomal RNA (rRNA) sequencing was performed on stool to examine changes in microbial composition/diversity. The diet treatment was associated with differential expression of 419 HILIC and 205 C18 metabolite features (p < 0.05), which were enriched in amino acid pathways, including methionine/cysteine and serine/glycine/alanine metabolism (p < 0.05), and lipid pathways, including omega-3 and linoleate metabolism (p < 0.05). Quantified metabolites that were differentially changed in the LFSD group, compared to usual diet group, and representative of these enriched metabolic pathways included increased serine (p = 0.001), glycine (p = 0.004), 2-aminobutyric acid (p = 0.012), and 3-hydroxybutyric acid (p = 0.005), and decreased linolenic acid (p = 0.006). Microbiome changes included an increase in richness at the phylum level and changes in a few genera within Firmicutes. In conclusion, the LFSD treatment, compared to usual diet, was associated with metabolome and microbiome changes that may reflect biological mechanisms linking dietary sugar restriction to a therapeutic decrease in hepatic fat. Studies are needed to validate our findings and test the utility of these “omics” changes as response biomarkers.

People living with HIV (PLWH) who are immune nonresponders (INRs) are at greater risk of comorbidity and mortality than are immune responders (IRs) who restore their CD4+ T cell count after antiretroviral therapy (ART). INRs have low CD4+ T cell counts (

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.

Abstract With the growth of metabolomics research, more and more studies are conducted on large numbers of samples. Due to technical limitations of the Liquid Chromatography–Mass Spectrometry (LC/MS) platform, samples often need to be processed in multiple batches. Across different batches, we often observe differences in data characteristics. In this work, we specifically focus on data generated in multiple batches on the same LC/MS machinery. Traditional preprocessing methods treat all samples as a single group. Such practice can result in errors in the alignment of peaks, which cannot be corrected by post hoc application of batch effect correction methods. In this work, we developed a new approach that address the batch effect issue in the preprocessing stage, resulting in better peak detection, alignment and quantification. It can be combined with down-stream batch effect correction methods to further correct for between-batch intensity differences. The method is implemented in the existing workflow of the apLCMS platform. Analyzing data with multiple batches, both generated from standardized quality control (QC) plasma samples and from real biological studies, the new method resulted in feature tables with better consistency, as well as better down-stream analysis results. The method can be a useful addition to the tools available for large studies involving multiple batches. The method is available as part of the apLCMS package. Download link and instructions are at https://mypage.cuhk.edu.cn/academics/yutianwei/apLCMS/ .

Abstract Background Alzheimer’s disease (AD) is a complex neurological disorder with contributions from genetic and environmental factors. High‐resolution metabolomics (HRM) has the potential to identify novel endogenous and environmental factors involved in AD. Previous metabolomics studies have identified circulating metabolites linked to AD, but lack of replication and inconsistent diagnostic algorithms have hindered the generalizability of these findings. Here we applied HRM to identify plasma metabolic and environmental factors associated with AD in two study samples, with cerebrospinal fluid (CSF) biomarkers of AD incorporated to achieve high diagnostic accuracy. Methods Liquid chromatography‐mass spectrometry (LC–MS)‐based HRM was used to identify plasma and CSF metabolites associated with AD diagnosis and CSF AD biomarkers in two studies of prevalent AD (Study 1: 43 AD cases, 45 mild cognitive impairment [MCI] cases, 41 controls; Study 2: 50 AD cases, 18 controls). AD‐associated metabolites were identified using a metabolome‐wide association study (MWAS) framework. Results An MWAS meta‐analysis identified three non‐medication AD‐associated metabolites in plasma, including elevated levels of glutamine and an unknown halogenated compound and lower levels of piperine, a dietary alkaloid. The non‐medication metabolites were correlated with CSF AD biomarkers, and glutamine and the unknown halogenated compound were also detected in CSF. Furthermore, in Study 1, the unknown compound and piperine were altered in MCI patients in the same direction as AD dementia. Conclusions In plasma, AD was reproducibly associated with elevated levels of glutamine and a halogen‐containing compound and reduced levels of piperine. These findings provide further evidence that exposures and behavior may modify AD risks.

Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010, and analyzed using untargeted high-resolution metabolomics to characterize metabolite associations with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Metabolic associations with EC, OC and PM2.5 were evaluated for biochemical processes known to be associated with disease risk. Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and transcriptomic changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution.

Background: Prenatal exposures to per- and polyfluoroalkyl substances (PFAS) have been linked to reduced fetal growth. However, the detailed molecular mechanisms remain largely unknown. This study aims to investigate biological pathways and intermediate biomarkers underlying the association between serum PFAS and fetal growth using high-resolution metabolomics in a cohort of pregnant African American women in the Atlanta area, Georgia. Methods: Serum perfluorohexane sulfonic acid (PFHxS), perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorononanoic acid (PFNA) measurements and untargeted serum metabolomics profiling were conducted in 313 pregnant African American women at 8–14 weeks gestation. Multiple linear regression models were applied to assess the associations of PFAS with birth weight and small-for-gestational age (SGA) birth. A high-resolution metabolomics workflow including metabolome-wide association study, pathway enrichment analysis, and chemical annotation and confirmation with a meet-in-the-middle approach was performed to characterize the biological pathways and intermediate biomarkers of the PFAS-fetal growth relationship. Results: Each log2-unit increase in serum PFNA concentration was significantly associated with higher odds of SGA birth (OR = 1.32, 95% CI 1.07, 1.63); similar but borderline significant associations were found in PFOA (OR = 1.20, 95% CI 0.94, 1.49) with SGA. Among 25,516 metabolic features extracted from the serum samples, we successfully annotated and confirmed 10 overlapping metabolites associated with both PFAS and fetal growth endpoints, including glycine, taurine, uric acid, ferulic acid, 2-hexyl-3-phenyl-2-propenal, unsaturated fatty acid C18:1, androgenic hormone conjugate, parent bile acid, and bile acid-glycine conjugate. Also, we identified 21 overlapping metabolic pathways from pathway enrichment analyses. These overlapping metabolites and pathways were closely related to amino acid, lipid and fatty acid, bile acid, and androgenic hormone metabolism perturbations. Conclusion: In this cohort of pregnant African American women, higher serum concentrations of PFOA and PFNA were associated with reduced fetal growth. Perturbations of biological pathways involved in amino acid, lipid and fatty acid, bile acid, and androgenic hormone metabolism were associated with PFAS exposures and reduced fetal growth, and uric acid was shown to be a potential intermediate biomarker. Our results provide opportunities for future studies to develop early detection and intervention for PFAS-induced fetal growth restriction.

IntroductionIntegrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a “metabolic map” of the brain in prodromal AD.MethodsIn 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort.ResultsThe multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05).ConclusionBy integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches.

Abstract Background Insulin impairment and inflammation are two features common to type 2 diabetes and Alzheimer’s disease; however, the molecular and signaling interactions underlying this relationship are not well understood. Mounting evidence point to the associations between the disruption of metabolite processing in insulin impairment and neurodegenerative conditions such as Alzheimer’s. Although the brain depends partially on metabolites processed in the periphery, to date, little is known about how soluble tumor necrosis factor signaling (solTNF) impacts integrated peripheral immune and metabolic feedback signals in states of energy overload and insulin insensitivity. Methods C57Bl/6J mice were fed a high-fat high-carbohydrate diet (HFHC) for 14 weeks. The brain-permeant biologic XPro1595® was used to block solTNF-dependent pathways. Metabolic and immune alterations were evaluated in the gut, liver, and brain. Behavioral tests were performed. Untargeted metabolomics was carried out in the plasma and liver. Results HFHC diet promotes central insulin impairment and dysregulation of immune-modulatory gene expressed in the brain. Alteration of metabolites associated with type 2 diabetes and Alzheimer’s such as butanoate, glutamate, biopterin, branched-chain amino acids, purines, and proteoglycan metabolism was observed in HFHC-fed mice. solTNF inhibition ameliorates hepatic metabolic disturbances and hepatic and intestinal lipocalin-2 levels, and decreases insulin impairment in the brain and behavioral deficits associated with HFHC diet. Conclusions Our novel findings suggest that HFHC diet impacts central insulin signaling and immune-metabolic interactions in a solTNF-dependent manner to increase the risk for neurodegenerative conditions. Our novel findings indicate that selective solTNF neutralization can ameliorate peripheral and central diet-induced insulin impairment and identify lipocalin-2 as a potential target for therapeutic intervention to target inflammation and insulin disturbances in obesogenic environments. Collectively, our findings identify solTNF as a potential target for therapeutic intervention in inflammatory states and insulin disturbances in obesogenic environments to lower risk for AD.

Background: Chronic exposure to certain metals plays a role in disease development. Integrating untargeted metabolomics with urinary metallome data may contribute to better understanding the pathophysiology of diseases and complex molecular interactions related to environmental metal exposures. To discover novel associations between urinary metal biomarkers and metabolism networks, we conducted an integrative metallome-metabolome analysis using a panel of urinary metals and untargeted blood metabolomic data from the Strong Heart Family Study (SHFS). Methods: The SHFS is a prospective family-based cohort study comprised of American Indian men and women recruited in 2001–2003. This nested case-control analysis of 145 participants of which 50 developed incident diabetes at follow up in 2006–2009, included participants with urinary metal and untargeted metabolomic data. Concentrations of 8 creatinine-adjusted urine metals/metalloids [antimony (Sb), cadmium (Cd), lead (Pb), molybdenum (Mo), selenium (Se), tungsten (W), uranium (U) and zinc (Zn)], and 4 arsenic species [inorganic arsenic (iAs), monomethylarsonate (MMA), dimethylarsinate (DMA), and arsenobetaine (AsB)] were measured. Global metabolomics was performed on plasma samples using high-resolution Orbitrap mass spectrometry. We performed an integrative network analysis using xMWAS and a metabolic pathway analysis using Mummichog. Results: 8,810 metabolic features and 12 metal species were included in the integrative network analysis. Most metal species were associated with distinct subsets of metabolites, forming single-metal-multiple-metabolite clusters (|r|>0.28, p-value 0.17, p-value

Background: Air pollution exposure has been linked with diminished fertility. Identifying the metabolic changes induced by periconception air pollution exposure among women could enhance our understanding of the potential biological pathways underlying air pollution’s reproductive toxicity. Objective: To identify serum metabolites associated with periconception air pollution exposure and evaluate the extent to which these metabolites mediate the association between air pollution and live birth. Methods: We included 200 women undergoing a fresh assisted reproductive technology (ART) cycle at Massachusetts General Hospital Fertility Center (2005–2015). A serum sample was collected during stimulation, and untargeted metabolic profiling was conducted using liquid chromatography with ultra-high-resolution mass spectrometry. Exposure to nitrogen dioxide (NO2), ozone (O3), fine particulate matter

Omics analyses are commonly used for identifying pathways and genes responsible for physiologic and pathologic processes. Though sex is considered a biological variable in rigorous assessments of pulmonary responses to oxidant exposures, the contribution of the murine strain is largely ignored. This study utilized an unbiased integrated assessment of high-resolution metabolomic profiling and RNA-sequencing to explore sex- and strain-dependent pathways in adult mouse lungs. The results indicated that strain exhibited a greater influence than sex on pathways associated with inflammatory and oxidant/antioxidant responses and that interaction metabolites more closely resembled those identified as differentially expressed by strain. Metabolite analyses revealed that the components of the glutathione antioxidant pathway were different between strains, specifically in the formation of mixed disulfides. Additionally, selenium metabolites such as selenohomocystiene and selenocystathionine were similarly differentially expressed. Transcriptomic analysis revealed similar findings, as evidenced by differences in glutathione peroxidase, peroxiredoxin, and the inflammatory transcription factors RelA and Jun. In summary, an multi-omics integrated approach identified that murine strain disproportionately impacts baseline expression of antioxidant systems in lung tissues. We speculate that strain-dependent differences contribute to discrepant pulmonary responses in preclincal mouse models, with deleterious effects on clinical translation.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children, but diagnosis is challenging due to limited availability of noninvasive biomarkers. Machine learning applied to high‐resolution metabolomics and clinical phenotype data offers a novel framework for developing a NAFLD screening panel in youth. Here, untargeted metabolomics by liquid chromatography–mass spectrometry was performed on plasma samples from a combined cross‐sectional sample of children and adolescents ages 2‐25 years old with NAFLD (n = 222) and without NAFLD (n = 337), confirmed by liver biopsy or magnetic resonance imaging. Anthropometrics, blood lipids, liver enzymes, and glucose and insulin metabolism were also assessed. A machine learning approach was applied to the metabolomics and clinical phenotype data sets, which were split into training and test sets, and included dimension reduction, feature selection, and classification model development. The selected metabolite features were the amino acids serine, leucine/isoleucine, and tryptophan; three putatively annotated compounds (dihydrothymine and two phospholipids); and two unknowns. The selected clinical phenotype variables were waist circumference, whole‐body insulin sensitivity index (WBISI) based on the oral glucose tolerance test, and blood triglycerides. The highest performing classification model was random forest, which had an area under the receiver operating characteristic curve (AUROC) of 0.94, sensitivity of 73%, and specificity of 97% for detecting NAFLD cases. A second classification model was developed using the homeostasis model assessment of insulin resistance substituted for the WBISI. Similarly, the highest performing classification model was random forest, which had an AUROC of 0.92, sensitivity of 73%, and specificity of 94%. Conclusion: The identified screening panel consisting of both metabolomics and clinical features has promising potential for screening for NAFLD in youth. Further development of this panel and independent validation testing in other cohorts are warranted.

Abstract Background Given the central importance of anti-malarial drugs in the treatment of malaria, there is a need to understand the effect of Plasmodium infection on the broad spectrum of drug metabolizing enzymes. Previous studies have shown reduced clearance of quinine, a treatment for Plasmodium infection, in individuals with malaria. Methods The hepatic expression of a large panel of drug metabolizing enzymes was studied in the livers of mice infected with the AS strain of Plasmodium chabaudi chabaudi, a nonlethal parasite in most strains of mice with several features that model human Plasmodium infections. C57BL/6J mice were infected with P. chabaudi by intraperitoneal injection of infected erythrocytes and sacrificed at different times after infection. Relative hepatic mRNA levels of various drug metabolizing enzymes, cytokines and acute phase proteins were measured by reverse transcriptase-real time PCR. Relative levels of cytochrome P450 proteins were measured by Western blotting with IR-dye labelled antibodies. Pharmacokinetics of 5 prototypic cytochrome P450 substrate drugs were measured by cassette dosing and high-resolution liquid chromatography-mass spectrometry. The results were analysed by MANOVA and post hoc univariate analysis of variance. Results The great majority of enzyme mRNAs were down-regulated, with the greatest effects occurring at the peak of parasitaemia 8 days post infection. Protein levels of cytochrome P450 enzymes in the Cyp 2b, 2c, 2d, 2e, 3a and 4a subfamilies were also down-regulated. Several distinct groups differing in their temporal patterns of regulation were identified. The cassette dosing study revealed that at the peak of parasitaemia, the clearances of caffeine, bupropion, tolbutamide and midazolam were markedly reduced by 60–70%. Conclusions These findings in a model of uncomplicated human malaria suggest that changes in drug clearance in this condition may be of sufficient magnitude to cause significant alterations in exposure and response of anti-malarial drugs and co-medications.

Cadmium (Cd) is a toxic, pro-inflammatory metal ubiquitous in the diet that accumulates in body organs due to inefficient elimination. Responses to influenza virus infection are variable, particularly severity of pneumonia. We used a murine model of chronic low-dose oral exposure to Cd to test if increased lung tissue Cd worsened inflammation in response to sub-lethal H1N1 infection. The results show that Cd-treated mice had increased lung tissue inflammatory cells, including neutrophils, monocytes, T lymphocytes and dendritic cells, following H1N1 infection. Lung genetic responses to infection (increasing TNF-α, interferon and complement, and decreasing myogenesis) were also exacerbated. To reveal the organization of a network structure, pinpointing molecules critical to Cd-altered lung function, global correlations were made for immune cell counts, leading edge gene transcripts and metabolites. This revealed that Cd increased correlation of myeloid immune cells with pro-inflammatory genes, particularly interferon-γ and metabolites. Together, the results show that Cd burden in mice increased inflammation in response to sub-lethal H1N1 challenge, which was coordinated by genetic and metabolic responses, and could provide new targets for intervention against lethal inflammatory pathology of clinical H1N1 infection. Keywords: Environmental safety, Exposome, Heavy metals, Influenza A virus, Public health

Background: Mechanisms underlying the effects of traffic-related air pollution on people with asthma remain largely unknown, despite the abundance of observational and controlled studies reporting associations between traffic sources and asthma exacerbation and hospitalizations. Objectives: To identify molecular pathways perturbed following traffic pollution exposures, we analyzed data as part of the Atlanta Commuters Exposure (ACE-2) study, a crossover panel of commuters with and without asthma. Methods: We measured 27 air pollutants and conducted high-resolution metabolomics profiling on blood samples from 45 commuters before and after each exposure session. We evaluated metabolite and metabolic pathway perturbations using an untargeted metabolome-wide association study framework with pathway analyses and chemical annotation. Results: Most of the measured pollutants were elevated in highway commutes (p

Objective: To examine the prospective associations between exposure to perfluoroalkyl substances (PFASs) and longitudinal measurements of glucose metabolism in high-risk overweight and obese Hispanic children. Methods: Forty overweight and obese Hispanic children (8–14 years) from urban Los Angeles underwent clinical measures and 2-hour oral glucose tolerance tests (OGTT) at baseline and a follow-up visit (range: 1–3 years after enrollment). Baseline plasma perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and the plasma metabolome were measured by liquid-chromatography with high-resolution mass spectrometry. Multiple linear regression models were used to assess the association between baseline PFASs and changes in glucose homeostasis over follow-up. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with plasma PFASs concentrations. We performed a structural integrated analysis aiming to characterize the joint impact of all factors and to identify latent clusters of children with alterations in glucose homeostasis, based on their exposure and metabolomics profile. Results: Each ln (ng/ml) increase in PFOA and PFHxS concentrations was associated with a 30.6 mg/dL (95% CI: 8.8–52.4) and 10.2 mg/dL (95% CI: 2.7–17.7) increase in 2-hour glucose levels, respectively. A ln (ng/ml) increase in PFHxS concentrations was also associated with 17.8 mg/dL increase in the glucose area under the curve (95% CI: 1.5–34.1). Pathway enrichment analysis showed significant alterations of lipids (e.g., glycosphingolipids, linoleic acid, and de novo lipogenesis), and amino acids (e.g., aspartate and asparagine, tyrosine, arginine and proline) in association to PFASs exposure. The integrated analysis identified a cluster of children with increased 2-h glucose levels over follow up, characterized by increased PFAS levels and altered metabolite patterns. Conclusions: This proof-of-concept analysis shows that higher PFAS exposure was associated with dysregulation of several lipid and amino acid pathways and longitudinal alterations in glucose homeostasis in Hispanic youth. Larger studies are needed to confirm these findings and fully elucidate the underlying biological mechanisms. Keywords: Perfluoroalkyl substances, Type 2 diabetes, Glucose metabolism, Metabolomics, Children