Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. Aims of this study were to characterize a metabolic signature of ASD, and to evaluate multi-platform analytical methodologies in order to develop predictive tools for diagnosis and disease follow up. Urines were analyzed using: 1H- and 1 H-13C-NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on a HILIC and C18 chromatography column). Data tables obtained from the six analytical modalities on a training set of 46 urines (22 autistic children and 24 controls) were processed by multivariate analysis (OPLS-DA). Prediction of each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and ROC curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLSDA model showed an enhanced performance (R 2Y(cum)=0.88, Q 2 (cum)=0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC=0.91, p-value 0.006). Metabolites that are most significantly different between autistic and control children (p<0.05) are indoxyl sulfate, N-\u2329-Acetyl-L-arginine, methyl guanidine and phenylacetylglutamine. This multi-modality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population

1H-NMR-Based Metabolomic Profiling of CSF in Early Amyotrophic Lateral Sclerosis

Background: Pathophysiological mechanisms involved in amyotrophic lateral sclerosis (ALS) are complex and none has identified reliable markers useful in routine patient evaluation. The aim of this study was to analyze the CSF of patients with ALS by 1 H NMR (Nuclear Magnetic Resonance) spectroscopy in order to identify biomarkers in the early stages of the disease, and to evaluate the biochemical factors involved in ALS. Methodology: CSF samples were collected from patients with ALS at the time of diagnosis and from patients without neurodegenerative diseases. One and two-dimensional 1 H NMR analyses were performed and metabolites were quantified by the ERETIC method. We compared the concentrations of CSF metabolites between both groups. Finally, we performed principal component (PCA) and discriminant analyses. Principal Findings: Fifty CSF samples from ALS patients and 44 from controls were analyzed. We quantified 17 metabolites including amino-acids, organic acids, and ketone bodies. Quantitative analysis revealed significantly lower acetate concentrations (p = 0.0002) in ALS patients compared to controls. Concentration of acetone trended higher (p = 0.015), and those of pyruvate (p = 0.002) and ascorbate (p = 0.003) were higher in the ALS group. PCA demonstrated that the pattern of analyzed metabolites discriminated between groups. Discriminant analysis using an algorithm of 17 metabolites reveale

Relationship between intestinal and blood metabolome and fecal digestive efficiency in chicken

Digestive efficiency (DE) is an essential component of feed efficiency, especially in the context of increasing variety of feedstuffs with variable quality used in poultry diets. However, measuring fecal DE during balance trials is time-consuming nd constraining as birds are placed in individual cages. Moreover, all the mechanisms controlling DE are still not known. The aim of our study was thus to identify biomarkers of DE using intestinal and blood metabolomics.Our study used 60 chickens of an advanced intercross line (8th generation) between two broiler lines divergentlyselected for their fecal DE, based on metabolisable energy corrected to zero nitrogen retention (AMEn). At 3 weeks, fecal AMEn and coefficients of digestive use of lipids, nitrogen and starch were measured during a balance trial, ileal and caecal contents were sampled and blood collected. Metabolome was determinedby proton high resolution NMR. Correlation models (canonical partial least squares) were fitted to assess the links between efficiency and metabolites of the 3 compartments.Metabolites differences between animals with high or low levels of DE were mainly involved in amino-acids metabolism (lysine, isoleucine, methionine) and energetic metabolism (glutamate, glucose) in the 3 compartments. High positive correlations were especially found between glucose in caecal content and AMEnand coefficient of DE of nitrogen (Figure 1), which is consistent with the large divergence found in the divergent lines on these criteria. This result suggests an effect of microbial fermentation on DE.These metabolic profiles give us information on mechanisms implied in feed digestion in chickens. Further analyses will estimate if blood metabolome could be used as an indirect criterion of selection of feed and DE. This study has been supported by the EU H2020 Feeda--Gene project and by the INRA program GISA-GALMIDE

Steroidome and metabolome analysis in gilt saliva to identify potential biomarkers of boar effect receptivity

Optimal management of gilt reproduction requires oestrus synchronization. Hormonal treatments are used for this purpose, but there is a growing demand for non-hormonal alternatives, especially in organic farms. The boar effect is an important alternative opportunity to induce and synchronize oestrus without hormones. Before puberty, gilts exhibit a 'waiting period' during which boar exposure could induce and synchronize the first ovulation. We searched for salivary biomarkers of this period of boar effect receptivity to improve detection of the gilts to stimulate with the perspective of enhancing the efficacy of the boar effect. Saliva samples were collected from 30 Large-White×Landrace crossbred gilts between 140 and 175 days of age. Gilts were exposed twice a day to a boar and subjected to oestrus detection from 150 to 175 days of age. Among the 30 gilts, 10 were detected in oestrus 4 to 7 days after the first introduction of the boar and were considered receptive to the boar effect, 14 were detected in oestrus more than 8 days after first boar contact, and six did not show oestrus and were considered non-receptive. Saliva samples from six receptive and six non-receptive gilts were analyzed for steroidome and for metabolome using gas chromatography coupled to tandem mass spectrometry and 1H nuclear magnetic resonance spectroscopy, respectively. Four saliva samples per gilt were analyzed: 25 days and 11 days before boar introduction, the day of boar introduction, 3 days later for receptive gilts or 7 days later for non-receptive gilts. Twenty-nine steroids and 31 metabolites were detected in gilt saliva. Salivary concentrations of six steroids and three metabolites were significantly different between receptive and non-receptive gilts: progesterone and glycolate 25 days before boar introduction, 3α5β20α- and 3β5α20β-hexahydroprogesterone, dehydroepiandrosterone, androstenediol, succinate, and butyrate 11 days before boar introduction, and 3β5α-tetrahydroprogesterone on the day of boar introduction. Thus, nine potential salivary biomarkers of boar effect receptivity were identified in our experimental conditions. Further studies with higher numbers of gilts and salivary sampling points are necessary to ascertain their reliability