1H-13C NMR-based urine metabolic profiling in autism spectrum disorders.

International audienceAutism Spectrum Disorders (ASD) are a group of developmental disorders caused by environmental and genetic factors. Diagnosis is based on behavioral and developmental signs detected before 3 years of age with no reliable biological marker. The purpose of this study was to evaluate the potential use of a 2D NMR-based approach to express the global biochemical signature of autistic individuals compared to normal controls. This technique has greater spectral resolution than to 1D (1)H NMR spectroscopy, which is limited by overlapping signals. The urinary metabolic profiles of 30 autistic and 28 matched healthy children were obtained using a (1)H-(13)C NMR-based approach. The data acquired were processed by multivariate orthogonal partial least-squares discriminant analysis (OPLS-DA). Some discriminating metabolites were identified: β-alanine, glycine, taurine and succinate concentrations were significatively higher, and creatine and 3-methylhistidine concentrations were lower in autistic children than in controls. We also noted differences in several other metabolites that were unidentified but characterized by a cross peak correlation in (1)H-(13)C HSQC. Statistical models of (1)H and (1)H-(13)C analyses were compared and only 2D spectra allowed the characterization of statistically relevant changes [R(2)Y(cum)=0.78 and Q(2)(cum)=0.60] in the low abundance metabolites. This method has the potential to contribute to the diagnosis of neurodevelopment disorders but needs to be validated on larger cohorts and on other developmental disorders to define its specificity

GC-MS-based urine metabolic profiling of autism spectrum disorders.: GC-MS-based Urine Metabolic Profiling in ASD

International audienceAutism spectrum disorders (ASD) are a group of neurodevelopmental disorders resulting from multiple factors. Diagnosis is based on behavioural and developmental signs detected before 3 years of age, and there is no reliable biological marker. The purpose of this study was to evaluate the value of gas chromatography combined with mass spectroscopy (GC-MS) associated with multivariate statistical modeling to capture the global biochemical signature of autistic individuals. GC-MS urinary metabolic profiles of 26 autistic and 24 healthy children were obtained by liq/liq extraction, and were or were not subjected to an oximation step, and then were subjected to a persilylation step. These metabolic profiles were then processed by multivariate analysis, in particular orthogonal partial least-squares discriminant analysis (OPLS-DA, R(2)Y(cum) = 0.97, Q(2)(cum) = 0.88). Discriminating metabolites were identified. The relative concentrations of the succinate and glycolate were higher for autistic than healthy children, whereas those of hippurate, 3-hydroxyphenylacetate, vanillylhydracrylate, 3-hydroxyhippurate, 4-hydroxyphenyl-2-hydroxyacetate, 1H-indole-3-acetate, phosphate, palmitate, stearate, and 3-methyladipate were lower. Eight other metabolites, which were not identified but characterized by a retention time plus a quantifier and its qualifier ion masses, were found to differ between the two groups. Comparison of statistical models leads to the conclusion that the combination of data obtained from both derivatization techniques leads to the model best discriminating between autistic and healthy groups of children

Capture in the metabolic arena: co-selection of gamma and deltaretrovirus envelope glycoproteins and their receptors

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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

Perfusate Metabolomics Content and Expression of Tubular Transporters During Human Kidney Graft Preservation by Hypothermic Machine Perfusion

Background. Ischemia-related injury during the preimplantation period impacts kidney graft outcome. Evaluating these lesions by a noninvasive approach before transplantation could help us to understand graft injury mechanisms and identify potential biomarkers predictive of graft outcomes. This study aims to determine the metabolomic content of graft perfusion fluids and its dependence on preservation time and to explore whether tubular transporters are possibly involved in metabolomics variations. Methods. Kidneys were stored on hypothermic perfusion machines. We evaluated the metabolomic profiles of perfusion fluids (n=35) using liquid chromatography coupled with tandem mass spectrometry and studied the transcriptional expression of tubular transporters on preimplantation biopsies (n=26), both collected at the end of graft perfusion. We used univariate and multivariate analyses to assess the impact of perfusion time on these parameters and their relationship with graft outcome. Results. Seventy-two metabolites were found in preservation fluids at the end of perfusion, of which 40% were already present in the native conservation solution. We observed an increase of 23 metabolites with a longer perfusion time and a decrease of 8. The predictive model for time-dependent variation of metabolomics content showed good performance (R2=76%, Q2=54%, accuracy=41%, and permutation test significant). Perfusion time did not affect the mRNA expression of transporters. We found no correlation between metabolomics and transporters expression. Neither the metabolomics content nor transporter expression was predictive of graft outcome. Conclusions. Our results call for further studies, focusing on both intra- and extratissue metabolome, to investigate whether transporter alterations can explain the variations observed in the preimplantation period

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

NMR metabolic signatures of follicular fluid of mare, sow and cow

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Differential metabolic composition of the uterine fluid from fertile and subfertile hens after artificial insemination

Avian uterine fluid (UF) has been demonstrated to prolong sperm survival, to maintain the fertility potential of the fowl sperm, and to impact the filling rate of sperm storage tubules (SST) from the utero-vaginal junction (UVJ). The purpose of this study was to identify UF metabolites related to long-term sperm storage. Two genetic lines of hens exhibiting long (F+) or short (F-) sperm storage ability were used. Metabolites present in the UF either before or after insemination were identified and quantified using high resolution 1 H-NMR. The effect of the presence of sperm was investigated 24 hours, 1 week, 2 weeks and 3 weeks after a single artificial insemination. Thirteen metabolites were identified as discriminating between the UF collected before insemination from the two lines of hens. Among them, formate, organic acids (succinate, fumarate, lactate), dimethylamine and arabinose were significantly more abundant in F+ UF, whereas myo-inositol was significantly more abundant in F-UF (p<0.05). Pathway and metabolite set enrichment analyses revealed that preponderant metabolic pathways were over 2 representated in the F+ UF and involved pyruvate metabolism, citrate cycle and steroid biosynthesis (p<0.05). No metabolite was identified as discriminating in F+ UF, when compared before and after insemination. In contrast in the F-line of hens, 11 metabolites discriminated the UF collected before and after insemination. Actually, we observed that dimethylamine was significantly reduced, while fumarate and myo-inositol metabolites were significantly increased. Moreover, Warburg effect pathway involving glucose to lactate metabolism, was significantly enriched in F-after insemination. Our results indicate that in the hen, the metabolic composition of UF is related to the genetic traits F+/F-, and is differentially modified after insemination in both lines. It could be related to sperm storage. These lead us to conclude that: 1) the UF biochemical composition is associated with the sperm survival ability in SST, 2) is regulated by the presence of sperm, and 3) this regulation is related to the sperm survival ability in SST