Circulating endogenous sex steroids and risk of differentiated thyroid carcinoma in men and women.

Thyroid cancer (TC) is substantially more common in women than in men, pointing to a possible role of sex steroid hormones. We investigated the association between circulating sex steroid hormones, sex hormone binding globulin (SHBG) and the risk of differentiated TC in men and women within the European Prospective Investigation into Cancer and nutrition (EPIC) cohort. During follow-up, we identified 333 first primary incident cases of differentiated TC (152 in pre/peri-menopausal women, 111 in post-menopausal women, and 70 in men) and 706 cancer-free controls. Women taking exogenous hormones at blood donation were excluded. Plasma concentrations of testosterone, androstenedione, dehydroepiandrosterone, estradiol, estrone and progesterone (in pre-menopausal women only) were performed using liquid chromatography/mass spectrometry method. SHBG concentrations were measured by immunoassay. Odds ratios (ORs) were estimated using conditional logistic regression models adjusted for possible confounders. No significant associations were observed in men and postmenopausal women, while a borderline significant increase in differentiated TC risk was observed with increasing testosterone (adjusted OR T3 vs T1: 1.68, 95% CI: 0.96-2.92, ptrend = .06) and androstenedione concentrations in pre/perimenopausal women (adjusted OR T3 vs T1: 1.78, 95% CI: 0.96-3.30, ptrend = .06, respectively). A borderline decrease in risk was observed for the highest progesterone/estradiol ratio (adjusted OR T3 vs T1: 0.54, 95% CI: 0.28-1.05, ptrend = .07). Overall, our results do not support a major role of circulating sex steroids in the etiology of differentiated TC in post-menopausal women and men but may suggest an involvement of altered sex steroid production in pre-menopausal women.

The IbeA protein from adherent invasive Escherichia coli is a flavoprotein sharing structural homology with FAD-dependent oxidoreductases.

Invasion of brain endothelium protein A (IbeA) is a virulence factor specific to pathogenic Escherichia coli. Originally identified in the K1 strain causing neonatal meningitis, it was more recently found in avian pathogenic Escherichia coli (APEC) and adherent invasive Escherichia coli (AIEC). In these bacteria, IbeA facilitates host cell invasion and intracellular survival, in particular, under harsh conditions like oxidative stress. Furthermore, IbeA from AIEC contributes to intramacrophage survival and replication, thus enhancing the inflammatory response within the intestine. Therefore, this factor is a promising drug target for anti-AIEC strategies in the context of Crohn's disease. Despite such an important role, the biological function of IbeA remains largely unknown. In particular, its exact nature and cellular localization, i.e., membrane-bound invasin versus cytosolic factor, are still of debate. Here, we developed an efficient protocol for recombinant expression of IbeA under native conditions and demonstrated that IbeA from AIEC is a soluble, homodimeric flavoprotein. Using mass spectrometry and tryptophan fluorescence measurements, we further showed that IbeA preferentially binds flavin adenine dinucleotide (FAD), with an affinity in the one-hundred nanomolar range and optimal binding under reducing conditions. 3D-modeling with AlphaFold revealed that IbeA shares strong structural homology with FAD-dependent oxidoreductases. Finally, we used ligand docking, mutational analyses, and molecular dynamics simulations to identify the FAD binding pocket within IbeA and characterize possible conformational changes occurring upon ligand binding. Overall, we suggest that the role of IbeA in the survival of AIEC within host cells, notably macrophages, is linked to modulation of redox processes.

Circulating hormones and risk of gastric cancer by subsite in three cohort studies.

BACKGROUND: Obesity has been positively associated with gastric cancer. Excess fat impacts hormones, which have been implicated in carcinogenesis. We investigated obesity-related hormones and cardia gastric cancer (CGC) and non-cardia gastric cancer (NCGC) risk. METHODS: Nested case-control studies were conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (61 CGCs, and 172 NCGCs and matched controls) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) study (100 CGCs and 65 NCGCs and matched controls); serum hormones were measured. In UK-Biobank (n = 458,713), we included 137 CGCs and 92 NCGCs. Sex-specific analyses were conducted. For EPIC and ATBC, odds ratios (ORs), and for UK-Biobank hazard ratios (HRs), were estimated using conditional logistic regression and Cox regression, respectively. RESULTS: Insulin-like growth-factor-1 was positively associated with CGC and NCGC in EPIC men (ORper 1-SD increase 1.94, 95% CI 1.03-3.63; ORper 1-SD increase 1.63, 95% CI 1.05-2.53, respectively), with similar findings for CGC in UK-Biobank women (HRper 1-SD increase 1.76, 95% CI 1.08-2.88). Leptin in EPIC men and C-peptide in EPIC women were positively associated with NCGC (ORT3 vs. T1 2.72, 95% CI 1.01-7.34 and ORper 1-SD increase 2.17, 95% CI 1.19-3.97, respectively). Sex hormone-binding globulin was positively associated with CGC in UK-Biobank men (HRper 1-SD increase 1.29, 95% CI 1.02-1.64). Conversely, ghrelin was inversely associated with NCGC among EPIC and ATBC men (ORper 1-SD increase 0.53, 95% CI 0.34-0.84; ORper 1-SD increase 0.22, 95% CI 0.10-0.50, respectively). In addition, dehydroepiandrosterone was inversely associated with CGC in EPIC and ATBC men combined. CONCLUSIONS: Some obesity-related hormones influence CGC and NCGC risk.

Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study.

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

A metabolomic study of red and processed meat intake and acylcarnitine concentrations in human urine and blood.

BACKGROUND: Acylcarnitines (ACs) play a major role in fatty acid metabolism and are potential markers of metabolic dysfunction with higher blood concentrations reported in obese and diabetic individuals. Diet, and in particular red and processed meat intake, has been shown to influence AC concentrations but data on the effect of meat consumption on AC concentrations is limited. OBJECTIVES: To investigate the effect of red and processed meat intake on AC concentrations in plasma and urine using a randomized controlled trial with replication in an observational cohort. METHODS: In the randomized crossover trial, 12 volunteers successively consumed 2 different diets containing either pork or tofu for 3 d each. A panel of 44 ACs including several oxidized ACs was analyzed by LC-MS in plasma and urine samples collected after the 3-d period. ACs that were associated with pork intake were then measured in urine (n = 474) and serum samples (n = 451) from the European Prospective Investigation into Cancer and nutrition (EPIC) study and tested for associations with habitual red and processed meat intake derived from dietary questionnaires. RESULTS: In urine samples from the intervention study, pork intake was positively associated with concentrations of 18 short- and medium-chain ACs. Eleven of these were also positively associated with habitual red and processed meat intake in the EPIC cross-sectional study. In blood, C18:0 was positively associated with red meat intake in both the intervention study (q = 0.004, Student's t-test) and the cross-sectional study (q = 0.033, linear regression). CONCLUSIONS: AC concentrations in urine and blood were associated with red meat intake in both a highly controlled intervention study and in subjects of a cross-sectional study. Our data on the role of meat intake on this important pathway of fatty acid and energy metabolism may help understanding the role of red meat consumption in the etiology of some chronic diseases. This trial was registered at Clinicaltrials.gov as NCT03354130.

Impact of short-term traffic-related air pollution on the metabolome - Results from two metabolome-wide experimental studies.

Exposure to traffic-related air pollution (TRAP) has been associated with adverse health outcomes but underlying biological mechanisms remain poorly understood. Two randomized crossover trials were used here, the Oxford Street II (London) and the TAPAS II (Barcelona) studies, where volunteers were allocated to high or low air pollution exposures. The two locations represent different exposure scenarios, with Oxford Street characterized by diesel vehicles and Barcelona by normal mixed urban traffic. Levels of five and four pollutants were measured, respectively, using personal exposure monitoring devices. Serum samples were used for metabolomic profiling. The association between TRAP and levels of each metabolic feature was assessed. All pollutant levels were significantly higher at the high pollution sites. 29 and 77 metabolic features were associated with at least one pollutant in the Oxford Street II and TAPAS II studies, respectively, which related to 17 and 30 metabolic compounds. Little overlap was observed across pollutants for metabolic features, suggesting that different pollutants may affect levels of different metabolic features. After observing the annotated compounds, the main pathway suggested in Oxford Street II in association with NO2 was the acyl-carnitine pathway, previously found to be associated with cardio-respiratory disease. No overlap was found between the metabolic features identified in the two studies.

Perturbation of metabolic pathways mediates the association of air pollutants with asthma and cardiovascular diseases.

BACKGROUND: Epidemiologic evidence indicates common risk factors, including air pollution exposure, for respiratory and cardiovascular diseases, suggesting the involvement of common altered molecular pathways. OBJECTIVES: The goal was to find intermediate metabolites or metabolic pathways that could be associated with both air pollutants and health outcomes ("meeting-in-the-middle"), thus shedding light on mechanisms and reinforcing causality. METHODS: We applied a statistical approach named 'meet-in-the-middle' to untargeted metabolomics in two independent case-control studies nested in cohorts on adult-onset asthma (AOA) and cardio-cerebrovascular diseases (CCVD). We compared the results to identify both common and disease-specific altered metabolic pathways. RESULTS: A novel finding was a strong association of AOA with ultrafine particles (UFP; odds ratio 1.80 [1.26, 2.55] per increase by 5000 particles/cm3). Further, we have identified several metabolic pathways that potentially mediate the effect of air pollution on health outcomes. Among those, perturbation of Linoleate metabolism pathway was associated with air pollution exposure, AOA and CCVD. CONCLUSIONS: Our results suggest common pathway perturbations may occur as a consequence of chronic exposure to air pollution leading to increased risk for both AOA and CCVD.

Chemometric and high-resolution mass spectrometry tools for the characterization and comparison of raw and treated wastewater samples of a pilot plant on the SIPIBEL site.

Due to its key role in the contamination of natural resources, the assessment of raw and treated wastewater effluents is a current major concern and urges comprehensive analytical methods capable of selectively capturing the chemodiversity of these samples. In this context, the overall objective of this work can be summarized as (i) the assessment of the performance of secondary and tertiary (advanced oxidation) wastewater treatments through multivariate analysis followed by (ii) the comprehensive characterization of wastewater samples based on their spectral fingerprints and a combination of suspect and non-target screening approaches. Several compounds, belonging to different sources of contamination were annotated and/or partially identified: pharmaceuticals, metabolites and transformation compounds, human activity markers, surfactants, and polyethoxy compounds. These results highlight the contribution of filtering and screening tools such as monoisotopic exact mass, mass defect, MS/MS data-dependent acquisitions, isotopic pattern and retention time to the selection, and the identification of environmental contaminants and their metabolites/degradation products. This paper completes the target study conducted in the SIPIBEL site and offers an alternative for the assessment of treatment processes by broadening the spectrum to a larger number of compounds and the correlations between them.

Human exposure assessment to a large set of polymer additives through the analysis of urine by solid phase extraction followed by ultra high performance liquid chromatography coupled to tandem mass spectrometry.

Polymer items are extensively present in the human environment. Humans may be consequently exposed to some compounds, such as additives, incorporated in these items. The objective of this work is to assess the human exposure to the main additives such as those authorized in the packaging for pharmaceutical products. The urinary matrix was selected to optimally answer this challenge because it has already been proven that the exposure to chemicals can be revealed by the analysis of this biological matrix. A multi-residue analytical method for the trace analysis at ng/mL in human urine was developed, and consisted of an extraction of analytes from urine by solid phase extraction (SPE) and an analysis by ultra-high performance liquid chromatography coupled to a tandem mass spectrometer (UHPLC-MS/MS). Even if the quantification of these compounds was an analytical challenge because of (i) the presence of these substances in the analytical process, (ii) the diversity of their physicochemical properties, and (iii) the complexity of the matrix, the optimized method exhibited quantification limits lower than 25ng/mL and recoveries between 51% and 120% for all compounds. The method was validated and applied to 52 human urines. To the best of our knowledge, this work presents the first study allowing the assessment of the occurrence of more than twenty polymer additives at ng/mL in human urine.

Survey regarding the occurrence of selected organic micropollutants in the groundwaters of overseas departments.

To collect a complete dataset regarding the occurrence of organic substances in groundwater, this study presents the examination of 66 organic contaminants in the groundwater of overseas departments, including pesticides, pharmaceutical compounds, hormones and some industrial substances. The selective and sensitive analytical methods are described. These techniques begin with solid-phase extraction (SPE) followed by analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-ToF-MS). The paper summarises the analytical results from 40 sampling points collected during two campaigns in Guadeloupe, Martinique, Reunion, Mayotte and Guiana, representing 80 samples. Of the 66 target substances, 36 were determined at least once. Among the most frequently detected are bisphenol A (frequency, 96%; max., 7,400 ng/L), caffeine (frequency, 91%; max., 1,240 ng/L), pentachlorophenol (frequency, 55%; max., 418 ng/L), and carbamazepine (frequency, 56%; max., 22 ng/L). The results do not put in evidence that the origin of the sample or climatic characteristics of these regions influence the dilution and release of micropollutants.

Data-handling strategies for metabonomic studies: example of the UHPLC-ESI/ToF urinary signature of tetrahydrocannabinol in humans.

Metabonomics has become a very valuable tool and many research fields rely on results coming out from this combination of analytical techniques, chemometric strategies, and biological interpretation. Moreover, the matrices are more and more complex and the implications of the results are often of major importance. In this context, the need for pertinent validation strategies comes naturally. The choice of the appropriate chemometric method remains nevertheless a difficult task due to particularities such as: the number of measured variables, the complexity of the matrix and the purposes of the study. Consequently, this paper presents a detailed metabonomic study on human urine with a special emphasis on the importance of assessing the data's quality. It also describes, step by step, the statistical tools currently used and offers a critical view on some of their limits. In this work, 29 urine samples among which 15 samples obtained from tetrahydrocannabinol (delta-9-tetrahydrocannabinol)-consuming athletes, 5 samples provided by volunteers, and 9 samples obtained from athletes were submitted to untargeted analysis by means of ultra high-pressure liquid chromatography-electrospray ionization-time-of-flight mass spectrometry. Next, the quality of the obtained data was assessed and the results were compared to those found in databases. Then, unsupervised (principal component analysis (PCA)) and supervised (ANOVA/PCA, partial least-square-discriminant analysis (PLS-DA), orthogonal PLS-DA) univariate and multivariate statistical methods were applied.

Doping control using high and ultra-high resolution mass spectrometry based non-targeted metabolomics-a case study of salbutamol and budesonide abuse.

We have detected differences in metabolite levels between doped athletes, clean athletes, and volunteers (non athletes). This outcome is obtained by comparing results of measurements from two analytical platforms: UHPLC-QTOF/MS and FT-ICR/MS. Twenty-seven urine samples tested positive for glucocorticoids or beta-2-agonists and twenty samples coming from volunteers and clean athletes were analyzed with the two different mass spectrometry approaches using both positive and negative electrospray ionization modes. Urine is a highly complex matrix containing thousands of metabolites having different chemical properties and a high dynamic range. We used multivariate analysis techniques to unravel this huge data set. Thus, the several groups we created were studied by Principal Components Analysis (PCA) and Partial Least Square regression (PLS-DA and OPLS) in the search of discriminating m/z values. The selected variables were annotated and placed on pathway by using MassTRIX.

Multi-residue analysis of free and conjugated hormones and endocrine disruptors in rat testis by QuEChERS-based extraction and LC-MS/MS.

Endocrine disrupting compounds (EDCs) are suspected to be responsible for many disorders of the human reproductive system. To establish a causality relationship between exposure to endocrine disruptors and disease, experiments on animals must be performed with improved or new analytical tools. Therefore, a simple, rapid, and effective multi-residue method was developed for the determination of four steroid hormones (i.e., testosterone, androstenedione, estrone, and estradiol), glucuronide and sulfate conjugates of estrone and estradiol and four endocrine disruptors in rat testis (i.e., bisphenol A, atrazine, and active metabolites of methoxychlor and vinclozolin). The sample preparation procedure was based on the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) approach. An analytical method was then developed to quantify these compounds at ultra-trace levels by liquid chromatography coupled to tandem mass spectrometry. The QuEChERS extraction was optimized with regard to the acetonitrile/water ratio used in the extraction step, the choice of the cleanup method and the acetonitrile/hexane ratio used in the cleanup step. The optimized extraction method exhibited recoveries between 89% and 108% for all tested compounds except the conjugates (31% to 58%). The detection limits of all compounds were below 20 ng g(-1) of wet weight of testis. The method was subsequently applied to determine the levels of hormones and EDCs in seven rat testis samples.

Urinary signature of anabolic steroids and glucocorticoids in humans by LC-MS.

A metabonomic strategy based on LC-MS was employed to investigate the metabolic profile of urine samples from 20 athletes who had been tested positive for corticoids and anabolic steroids and 29 controls. In this aim, different sample preparations and chromatographic conditions were compared. The acquired LC-MS data of doped athletes and controls were subjected to analysis of variance (ANOVA) and principal component analysis (PCA). Using this approach, molecular signature of human urine was obtained showing that metabonomics could be a complementary tool to discriminate different urinary profiles and to track down metabolic changes in humans.

Water-soluble BODIPY derivatives.

New, water-soluble BODIPY dyes have been readily obtained from various BODIPY cores by reactions involving the introduction of novel sulfonated peptide chains by either coupling or substitution to give dimethylpropargylamine derivatives subsequently quaternized by reaction with propanesultone.