A comprehensive multiplatform metabolomic analysis reveals alterations of 2-hydroxybutyric acid among women with deep endometriosis related to the pesticide trans-nonachlor.

BACKGROUND: Exposure to persistent organic pollutants (POPs) has been related to the risk of endometriosis however the mechanisms remain unclear. The objective of the present study was to characterize the metabolic profiles underpinning the associations between POPs and endometriosis risk. METHODOLOGY: A hospital-based case-control study was conducted in France to recruit women with and without surgically confirmed deep endometriosis. Women's serum was analyzed using gas and liquid chromatography coupled to high-resolution mass spectrometry (HRMS) to measure the levels of polychlorinated biphenyls (PCBs), organochlorinated pesticides (OCPs) and per-/polyfluoroalkyl substances (PFAS). A comprehensive metabolomic profiling was conducted using targeted HRMS and 1H nuclear magnetic resonance (1H NMR) to cover polar and non-polar fractions. A "meet-in-the-middle" statistical framework was applied to identify the metabolites related to endometriosis and POP levels, using multivariate linear and logistic regressions adjusting for confounding variables. RESULTS: Fourteen PCBs, six OCPs and six PFAS were widely found in almost all serum samples. The pesticide trans-nonachlor was the POP most strongly and positively associated with deep endometriosis risk, with odds ratio (95 % confidence interval) of 2.42 (1.49; 4.12), followed by PCB180 and 167. Women with endometriosis exhibited a distinctive metabolic profile, with elevated serum levels of lactate, ketone bodies and multiple amino acids and lower levels of bile acids, phosphatidylcholines (PCs), cortisol and hippuric acid. The metabolite 2-hydroxybutyrate was simultaneously associated to endometriosis risk and exposure to trans-nonachlor. CONCLUSIONS: To the best of our knowledge, this is the first comprehensive metabolome-wide association study of endometriosis, integrating ultra-trace profiling of POPs. The results confirmed a metabolic alteration among women with deep endometriosis that could be also associated to the exposure to POPs. Further observational and experimental studies will be required to delineate the causal ordering of those associations and gain insight on the underlying mechanisms.

Despite similar clinical features metabolomics reveals distinct signatures in insulin resistant and progressively obese minipigs.

Obesity is a major contributor to the silent and progressive development of type 2 diabetes (T2D) whose prevention could be improved if individuals at risk were identified earlier. Our aim is to identify early phenotypes that precede T2D in diet-induced obese minipigs. We fed four groups of minipigs (n = 5-10) either normal-fat or high-fat high-sugar diet during 2, 4, or 6 months. Morphometric features were recorded, and metabolomics and clinical parameters were assessed on fasting plasma samples. Multivariate statistical analysis on 46 morphometrical and clinical parameters allowed to differentiate 4 distinct phenotypes: NFC (control group) and three others (HF2M, HF4M, HF6M) corresponding to the different stages of the obesity progression. Compared to NFC, we observed a rapid progression of body weight and fat mass (4-, 7-, and tenfold) in obese phenotypes. Insulin resistance (IR; 2.5-fold increase of HOMA-IR) and mild dyslipidemia (1.2- and twofold increase in total cholesterol and HDL) were already present in the HF2M and remained stable in HF4M and HF6M. Plasma metabolome revealed subtle changes of 23 metabolites among the obese groups, including a progressive switch in energy metabolism from amino acids to lipids, and a transient increase in de novo lipogenesis and TCA-related metabolites in HF2M. Low anti-oxidative capacities and anti-inflammatory response metabolites were found in the HF4M, and a perturbed hexose metabolism was observed in HF6M. Overall, we show that IR and progressively obese minipigs reveal phenotype-specific metabolomic signatures for which some of the identified metabolites could be considered as potential biomarkers of early progression to TD2.

Metabolomics and lipidomics to identify biomarkers of effect related to exposure to non-dioxin-like polychlorinated biphenyls in pigs.

Recent epidemiological studies show that current levels of exposure to polychlorinated biphenyls (PCBs) remain of great concern, as there is still a link between such exposures and the development of chronic environmental diseases. In this sense, most studies have focused on the health effects caused by exposure to dioxin-like PCBs (DL-PCBs), although chemical exposure to non-dioxin-like PCB (NDL-PCB) congeners is more significant. In addition, adverse effects of PCBs have been documented in humans after accidental and massive exposure, but little is known about the effect of chronic exposure to low-dose PCB mixtures. In this work, exposure to Aroclor 1260 (i.e. a commercially available mixture of PCBs consisting primarily of NDL-PCB congeners) in pigs is investigated as new evidence in the risk assessment of NDL-PCBs. This animal model has been selected due to the similarities with human metabolism and to support previous toxicological studies carried out with more frequently used animal models. Dietary exposure doses in the order of few ng/kg body weight (b.w.) per day were applied. As expected, exposure to Aroclor 1260 led to the bioaccumulation of NDL-PCBs in perirenal fat of pigs. Metabolomics and lipidomics have been applied to reveal biomarkers of effect related to Aroclor 1260 exposure, and by extension to NDL-PCB exposure, for 21 days. In the metabolomics analysis, 33 metabolites have been identified (level 1 and 2) as significantly altered by the Aroclor 1260 administration, while in the lipidomics analysis, 39 metabolites were putatively annotated (level 3) and associated with NDL-PCB exposure. These biomarkers are mainly related to the alteration of fatty acid metabolism, glycerophospholipid metabolism and tryptophan-kynurenine pathway.

Evidence for the systemic diffusion of (2-chloroethyl)-ethyl-sulfide, a sulfur mustard analog, and its deleterious effects in brain.

Sulfur mustard, a chemical warfare agent known to be a vesicant of skin, readily diffuses in the blood stream and reaches internal organs. In the present study, we used the analog (2-chloroethyl)-ethyl-sulfide (CEES) to provide novel data on the systemic diffusion of vesicants and on their ability to induce brain damage, which result in neurological disorders. SKH-1 hairless mice were topically exposed to CEES and sacrificed at different time until 14 days after exposure. A plasma metabolomics study showed a strong systemic impact following a self-protection mechanism to alleviate the injury of CEES exposure. This result was confirmed by the quantification of specific biomarkers in plasma. Those were the conjugates of CEES with glutathione (GSH-CEES), cysteine (Cys-CEES) and N-acetyl-cysteine (NAC-CEES), as well as the guanine adduct (N7Gua-CEES). In brain, N7Gua-CEES could be detected both in DNA and in organ extracts. Similarly, GSH-CEES, Cys-CEES and NAC-CEES were present in the extracts until day14. Altogether, these results, based on novel exposure markers, confirm the ability of vesicants to induce internal damage following dermal exposure. The observation of alkylation damage to glutathione and DNA in brain provides an additional mechanism to the neurological insult of SM.

ProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis.

Genes are pleiotropic and getting a better knowledge of their function requires a comprehensive characterization of their mutants. Here, we generated multi-level data combining phenomic, proteomic and metabolomic acquisitions from plasma and liver tissues of two C57BL/6 N mouse models lacking the Lat (linker for activation of T cells) and the Mx2 (MX dynamin-like GTPase 2) genes, respectively. Our dataset consists of 9 assays (1 preclinical, 2 proteomics and 6 metabolomics) generated with a fully non-targeted and standardized approach. The data and processing code are publicly available in the ProMetIS R package to ensure accessibility, interoperability, and reusability. The dataset thus provides unique molecular information about the physiological role of the Lat and Mx2 genes. Furthermore, the protocols described herein can be easily extended to a larger number of individuals and tissues. Finally, this resource will be of great interest to develop new bioinformatic and biostatistic methods for multi-omics data integration.

Despite similar clinical features metabolomics reveals distinct signatures in insulin resistant and progressively obese minipigs

Obesity is a major contributor to the silent and progressive development of type 2 diabetes (T2D) whose prevention could be improved if individuals at risk were identified earlier. Our aim is to identify early phenotypes that precede T2D in diet-induced obese minipigs. We fed four groups of minipigs (n = 5–10) either normal-fat or high-fat high-sugar diet during 2, 4, or 6 months. Morphometric features were recorded, and metabolomics and clinical parameters were assessed on fasting plasma samples. Multivariate statistical analysis on 46 morphometrical and clinical parameters allowed to differentiate 4 distinct phenotypes: NFC (control group) and three others (HF2M, HF4M, HF6M) corresponding to the different stages of the obesity progression. Compared to NFC, we observed a rapid progression of body weight and fat mass (4-, 7-, and tenfold) in obese phenotypes. Insulin resistance (IR; 2.5-fold increase of HOMA-IR) and mild dyslipidemia (1.2- and twofold increase in total cholesterol and HDL) were already present in the HF2M and remained stable in HF4M and HF6M. Plasma metabolome revealed subtle changes of 23 metabolites among the obese groups, including a progressive switch in energy metabolism from amino acids to lipids, and a transient increase in de novo lipogenesis and TCA-related metabolites in HF2M. Low anti-oxidative capacities and anti-inflammatory response metabolites were found in the HF4M, and a perturbed hexose metabolism was observed in HF6M. Overall, we show that IR and progressively obese minipigs reveal phenotype-specific metabolomic signatures for which some of the identified metabolites could be considered as potential biomarkers of early progression to TD2. (AU)