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.

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.

3,3′-Dichlorobiphenyl (PCB 11) is a byproduct of industrial processes and detected in environmental samples. PCB 11 and its metabolites are present in human serum, and emerging evidence demonstrates that PCB 11 is a developmental neurotoxicant. However, little is known about the metabolism of PCB 11 in humans. Here, we investigated the metabolism of PCB 11 and the associated metabolomics changes in HepG2 cells using untargeted high-resolution mass spectrometry. HepG2 cells were exposed for 24 h to PCB 11 in DMSO or DMSO alone. Cell culture media were analyzed with ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. Thirty different metabolites were formed by HepG2 cells exposed to 10 μM PCB 11, including monohydroxylated, dihydroxylated, methoxylated-hydroxylated, and methoxylated-dihydroxylated metabolites and the corresponding sulfo and glucuronide conjugates. The methoxylated PCB metabolites were observed for the first time in a human-relevant model. 4-OH-PCB 11 (3,3′-dichlorobiphenyl-4-ol) and the corresponding catechol metabolite, 4,5-di-OH-PCB 11 (3′,5-dichloro-3,4-dihydroxybiphenyl), were unambiguously identified based on liquid and gas chromatographic analyses. PCB 11 also altered several metabolic pathways, in particular vitamin B6 metabolism. These results demonstrate that complex PCB 11 metabolite profiles are formed in HepG2 cells that warrant further toxicological investigation, particularly since catechol metabolites are likely reactive and toxic.

BACKGROUND: Exposure to per-and polyfluoroalkyl substances (PFAS), a prevalent class of persistent pollutants, may increase the risk of type 2 diabetes. OBJECTIVE: We examined associations between PFAS exposure and glucose metabolism in youth. METHODS: Overweight/obese adolescents from the Study of Latino Adolescents at Risk of Type 2 Diabetes (SOLAR; n = 310) participated in annual visits for an average of 3:3 ± 2:9 y. Generalizability of findings were tested in young adults from the Southern California Children’s Health Study (CHS; n = 135) who participated in a clinical visit with a similar protocol. At each visit, oral glucose tolerance tests were performed to estimate glucose metabolism and b-cell function via the insulinogenic index. Four PFAS were measured at baseline using liquid chromatography–high-resolution mass spectrometry; high levels were defined as concentrations >66th percentile. RESULTS: In females from the SOLAR, high perfluorohexane sulfonate (PFHxS) levels (≥2:0 ng=mL) were associated with the development of dysre-gulated glucose metabolism beginning in late puberty. The magnitude of these associations increased postpuberty and persisted through 18 years of age. For example, postpuberty, females with high PFHxS levels had 25-mg=dL higher 60-min glucose (95% CI: 12, 39 mg=dL; p < 0:0001), 15-mg=dL higher 2-h glucose (95% CI: 1, 28 mg=dL; p = 0:04), and 25% lower b-cell function (p = 0:02) compared with females with low levels. Results were largely consistent in the CHS, where females with elevated PFHxS levels had 26-mg=dL higher 60-min glucose (95% CI: 6:0, 46 mg=dL; p = 0:01) and 19-mg=dL higher 2-h glucose, which did not meet statistical significance (95% CI: –1, 39 mg=dL; p = 0:08). In males, no consistent associations between PFHxS and glucose metabolism were observed. No consistent associations were observed for other PFAS and glucose metabolism. DISCUSSION: Youth exposure to PFHxS was associated with dysregulated glucose metabolism in females, which may be due to changes in b-cell func-tion. These associations appeared during puberty and were most pronounced postpuberty. https://doi.org/10.1289/EHP9200.

BACKGROUND: Exposure to per-and polyfluoroalkyl substances (PFAS) is ubiquitous and has been associated with an increased risk of several cardio-metabolic diseases. However, the metabolic pathways linking PFAS exposure and human disease are unclear. OBJECTIVE: We examined associations of PFAS mixtures with alterations in metabolic pathways in independent cohorts of adolescents and young adults. METHODS: Three hundred twelve overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) and 137 young adults from the Southern California Children’s Health Study (CHS) were included in the analysis. Plasma PFAS and the metabolome were determined using liquid-chromatography/high-resolution mass spectrometry. A metabolome-wide association study was performed on log-transformed metabolites using Bayesian regression with a g-prior specification and g-computation for modeling exposure mixtures to estimate the impact of exposure to a mixture of six ubiquitous PFAS (PFOS, PFHxS, PFHpS, PFOA, PFNA, and PFDA). Pathway enrichment analysis was performed using Mummichog and Gene Set Enrichment Analysis. Significance across cohorts was determined using weighted Z-tests. RESULTS: In the SOLAR and CHS cohorts, PFAS exposure was associated with alterations in tyrosine metabolism (meta-analysis p = 0:00002) and de novo fatty acid biosynthesis (p = 0:03), among others. For example, when increasing all PFAS in the mixture from low (∼ 30th percentile) to high (∼ 70th percentile), thyroxine (T4), a thyroid hormone related to tyrosine metabolism, increased by 0.72 standard deviations (SDs; equivalent to a standardized mean difference) in the SOLAR cohort (95% Bayesian credible interval (BCI): 0.00, 1.20) and 1.60 SD in the CHS cohort (95% BCI: 0.39, 2.80). Similarly, when going from low to high PFAS exposure, arachidonic acid increased by 0.81 SD in the SOLAR cohort (95% BCI: 0.37, 1.30) and 0.67 SD in the CHS cohort (95% BCI: 0.00, 1.50). In general, no individual PFAS appeared to drive the observed associations. DISCUSSION: Exposure to PFAS is associated with alterations in amino acid metabolism and lipid metabolism in adolescents and young adults. https:// doi.org/10.1289/EHP11372.

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.

Obesity and obesity-related metabolic disorders are linked to the intestinal microbiome. However, the causality of changes in the microbiome–host interaction affecting energy metabolism remains controversial. Here, we show the microbiome-derived metabolite δ-valerobetaine (VB) is a diet-dependent obesogen that is increased with phenotypic obesity and is correlated with visceral adipose tissue mass in humans. VB is absent in germ-free mice and their mitochondria but present in ex-germ-free conventionalized mice and their mitochondria. Mechanistic studies in vivo and in vitro show VB is produced by diverse bacterial species and inhibits mitochondrial fatty acid oxidation through decreasing cellular carnitine and mitochondrial long-chain acyl-coenzyme As. VB administration to germ-free and conventional mice increases visceral fat mass and exacerbates hepatic steatosis with a western diet but not control diet. Thus, VB provides a molecular target to understand and potentially manage microbiome–host symbiosis or dysbiosis in diet-dependent obesity.

Few studies have investigated host-bacterial interactions at sites of infection in humans using transcriptomics and metabolomics. Haemophilus ducreyi causes cutaneous ulcers in children and the genital ulcer disease chancroid in adults. We developed a human challenge model in which healthy adult volunteers are infected with H. ducreyi on the upper arm until they develop pustules. Here, we characterized host-pathogen interactions in pustules using transcriptomics and metabolomics and examined interactions between the host transcriptome and metabolome using integrated omics. In a previous pilot study, we determined the human and H. ducreyi transcriptomes and the metabolome of pustule and wounded sites of 4 volunteers (B. Griesenauer, T. M. Tran, K. R. Fortney, D. M. Janowicz, et al., mBio 10:e01193-19, 2019, https://doi.org/10.1128/mBio.01193-19). While we could form provisional transcriptional networks between the host and H. ducreyi, the study was underpowered to integrate the metabolome with the host transcriptome. To better define and integrate the transcriptomes and metabolome, we used samples from both the pilot study (n = 4) and new volunteers (n = 8) to identify 5,495 human differentially expressed genes (DEGs), 123 H. ducreyi DEGs, 205 differentially abundant positive ions, and 198 differentially abundant negative ions. We identified 42 positively correlated and 29 negatively correlated human-H. ducreyi transcriptome clusters. In addition, we defined human transcriptome-metabolome networks consisting of 9 total clusters, which highlighted changes in fatty acid metabolism and mitigation of oxidative damage. Taken together, the data suggest a mixed pro- and anti-inflammatory environment and rewired central metabolism in the host that provides a hostile, nutrient-limited environment for H. ducreyi. IMPORTANCE Interactions between the host and bacteria at sites of infection in humans are poorly understood. We inoculated human volunteers on the upper arm with the skin pathogen H. ducreyi or a buffer control and biopsied the resulting infected and sham-inoculated sites. We performed dual transcriptome sequencing (RNA-seq) and metabolic analysis on the biopsy samples. Network analyses between the host and bacterial transcriptomes and the host transcriptome-metabolome network were used to identify molecules that may be important for the virulence of H. ducreyi in the human host. Our results suggest that the pustule is highly oxidative, contains both pro- and anti-inflammatory components, and causes metabolic shifts in the host, to which H. ducreyi adapts to survive. To our knowledge, this is the first study to integrate transcriptomic and metabolomic responses to a single bacterial pathogen in the human host.

Background: The incidence of primary hyperparathyroidism has increased 300% in the United States in the past 30 years, and secondary hyperparathyroidism is almost universal in patients with end-stage renal disease. We assessed the presence of environmental chemicals in human hyperplastic parathyroid tumors as possible contributing factors to this increase. Methods: Cryopreserved hyperplastic parathyroid tumors and normal human parathyroids were analyzed by gas chromatography and liquid chromatography coupled to ultra-high-resolution mass spectrometry, bioinformatics, and biostatistics. Results: Detected environmental chemicals included polychlorinated biphenyls, polybrominated diphenyl ethers, dichloro-diphenyl-trichloroethane derivatives, and other insecticides. A total of 99% had p,p’-dichlorodiphenyldichloroethylene. More than 50% contained other environmental chemicals, and many classified as endocrine disruptors. Polychlorinated biphenyl-28 and polychlorinated biphenyl-49 levels correlated positively with parathyroid tumor mass. Polybrominated diphenyl ether-47 concentrations in tumors were inversely correlated with patients’ serum calcium levels. Cellular metabolites in pathways of purine and pyrimidine synthesis and mitochondrial energy production were associated with tumor growth and with p,p’-dichlorodiphenyldichloroethylene in primary hyperparathyroidism tumors. In normal parathyroids, p,p'-dichlorodiphenyldichloroethylene, polychlorinated biphenyl-28, polychlorinated biphenyl-74, and polychlorinated biphenyl-153, but not p,p'-dichlorodiphenyldichloroethylene or polychlorinated biphenyl-49, were detected. Conclusion: Environmental chemicals are present in human parathyroid tumors and warrant detailed epidemiologic and mechanistic studies to test for causal links to the growth of human parathyroid tumors.

Introduction: Integrating 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. Methods: In 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. Results: The 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). Conclusion: By 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.