Using an accurate and sensitive method, we found significantly higher levels of estrogens as well as androgen metabolites in prepubertal girls compared with age-matched boys. The higher prepubertal sex steroid levels in girls may contribute to their earlier onset of puberty including pubic hair development.

We provide the first evidence that DEHP and MEHP can inhibit testosterone production in the adult human testis. This is consistent with recent epidemiological findings of an inverse correlation between exposure to MEHP and testosterone concentrations.

The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own in-house protocols. Test #1 examined urine samples from adult volunteers either spiked or not spiked with 32 metabolite standards. Test #2 involved a low biological contrast situation comparing the plasma of rats fed a diet either supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. Correlations between blocks (e.g., instruments) were examined (RV coefficients) along with the structure of the common spectral information (common components and specific weights analysis). In addition, in Test #1, an outlier individual was blindly introduced, and its identification by the various platforms was evaluated. Despite large differences in the number of spectral features produced after post-processing and the heterogeneity of the analytical conditions and the data treatment, the spectral information both within (NMR and LCMS) and across methods (NMR vs. LCMS) was highly convergent (from 64 to 91 % on average). No effect of the LCMS instrumentation (TOF, QTOF, LTQ-Orbitrap) was noted. The outlier individual was best detected and characterised by LCMS instruments. In conclusion, untargeted metabolomics analyses report consistent information within and across instruments of various technologies, even without prior standardisation.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-014-0740-0) contains supplementary material, which is available to authorized users.

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18). Keywords:Challenges / Future directions / Mass spectrometry / Metabolomics / Systems biology / Workflow Additional supporting information may be found in the online version of this article at the publisher's web-site Historical backgroundThe high complexity of living organisms and biological systems imposes new more integrated and global (namely untargeted) characterization approaches that would allow addressing, in a comprehensive manner, complex situations that are currently dealt in a piecemeal manner. Indeed, the efficiency of conventional targeted approaches is well established even if some limitations are acknowledged. Targeted methods are then sensitive and specific but they do focus only on particular compounds or activities. With such meth- The concept of biological phenotyping has then emerged and comprehensive "omics" approaches have become for the last years a new way for addressing life complexity. There are three main characterization levels of biological systems, namely genomics-transcriptomics that have emerged in the 80s [1], proteomics in the 90s [2], and the most recent one, metabolomics, introduced about 15 years ago and in constant evolution since [3] (Fig.

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The occurrence of the main steroid hormones (oestrone, 17alpha-oestradiol, 17beta-oestradiol, 17alpha-testosterone, 17beta-testosterone, dehydroepiandrosterone, 4-androstenedione), especially in milk and eggs, was investigated. An analytical method based on GC-MS/MS was developed for steroid measurement at an ultra-trace level in food products. The limits of detection for oestrogens were about 5 and 30 ng kg(-1) in milk and eggs, respectively. For androgens, the limits of detection were around 10 and 50 ng kg(-1) in milk and eggs, respectively. The method was applied to milk and egg samples collected in a French supermarket. In milk, oestrone was found at levels between 100 and 300 ng l(-1), while 17beta-oestradiol levels were estimated to be near 20 ng l(-1). 17alpha-testosterone was found to be from 50 ng l(-1) in skimmed milk to 85 ng l(-1) in whole milk. In egg samples, oestrone and 17beta-oestradiol were found at 1.5 and 0.9 microg kg(-1), respectively, while 17alpha-oestradiol was found to be in lower concentrations (i.e. around 0.55 microg kg(-1)). Regarding androgens, 17alpha- and 17beta-testosterone were estimated at 1.9 and 1.3 microg kg(-1), respectively. These results represent a first attempt to estimate the food exposure to steroid hormones. In the future, the collection of additional data should permit the comparison between this exogenous dietary intake and the daily endogenous production in pre-pubertal children as a basis of risk assessment regarding endocrine disruption linked to these molecules for this critical population.

In the present study, the occurrence of the main sex steroid hormones in milk, egg, and meat was evaluated on the basis of a highly specific gas chromatography-tandem mass spectrometry measurement method. Globally, the results indicated that targeted estrogens and androgens occurred at similar levels (concentration levels in the 10-100 ng kg (-1) range) in the analyzed muscle and milk samples. The same compounds occurred at about 10-fold higher concentrations (i.e., in the 100-1000 ng kg (-1) range) in eggs and kidney samples. More precisely, egg and milk appeared as a non-negligible sources of estradiol (i.e., 2.2 +/- 0.8 and 3.1 +/- 2.0 ng day (-1), respectively), whereas testosterone exposure is caused by ingestion of meat and/or egg (i.e., 12.2 +/- 48.2 and 5.2 +/- 2.3 ng day (-1), respectively). The provided exposure data will be further exploited in the scope of a risk assessment study regarding endocrine disruption associated with these molecules.