Identification of metabolic pathway disturbances using multimodal metabolomics in autistic disorders in a Middle Eastern population

Bitar, Tania; Mavel, Sylvie; Emond, Patrick; Nadal-Desbarats, Lydie; Lefèvre, Antoine; Mattar, Hanna; Soufia, Michel; Blasco, Hélène; Vourc’h, Patrick; Hleihel, Walid; Andres, Christian R.

doi:10.1016/j.jpba.2018.01.007

Cited by 52 publications

(42 citation statements)

References 47 publications

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“…Thus, metabolomics provides a powerful tool to map these perturbations and their relationship to disease and response to therapy. In fact, some studies have been carried out to investigate metabolomics biomarkers in the brain [ 65 , 66 ], plasma [ 67 , 68 , 70 ], dried blood [ 79 ] and urine [ 72 , 73 , 74 , 75 , 76 , 77 , 78 ] samples of ASD patients ( Table 2 ). Yap and coworkers used a proton nuclear magnetic resonance ( 1 H-NMR) spectroscopy method that showed increased levels of taurine and low content of glutamate in urine samples of ASD patients [ 72 ].…”

Section: Metabolomicsmentioning

confidence: 99%

“…Recently, Dieme et al detected increased levels of indoxyl, indoxyl sulfate and N -acetylarginine, and decreased levels of methylguanidine and other compounds, such as desaminotyrosine and dihydrouracil [ 77 ]. Bitar et al, in a group of 40 ASD children and 40 age-matched controls, highlighted perturbations in various compounds [ 78 ], including 2-hydroxybutyrate, glutamate, creatine, and tyrosine. In addition, the authors also identified metabolites, including cysteic acid, guanine and trigonelline.…”

Section: Metabolomicsmentioning

confidence: 99%

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Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Ristori

Mortera

Marzano

et al. 2020

IJMS

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Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

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Section: Metabolomicsmentioning

confidence: 99%

Section: Metabolomicsmentioning

confidence: 99%

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Ristori

Mortera

Marzano

et al. 2020

IJMS

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show abstract

“…Because of the low concentration of Cys compared with glycine and glutamate, Cys limits amino acid for glutathione synthesis [48]. Bitar et al (2018) reported changes in the concentration of metabolites related to oxidative stress, including glutathione metabolism, and also changes in methionine, Cys, arginine, and proline metabolism pathways in the urine of 40 ASD individuals [3]. A low level of Cys was found in young ASD children and a high level in older children (older than five years).…”

Section: Discussionmentioning

confidence: 99%

“…The identification of an abnormal metabolite in the blood and urine of individuals with ASD has the potential to aid diagnosis and identify ASD subtypes, which would result in the greater individualization of therapeutic decisions. Compared with blood, the collection of urine samples is relatively simple, convenient, and non-invasive [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Higher Levels of Low Molecular Weight Sulfur Compounds and Homocysteine Thiolactone in the Urine of Autistic Children

et al. 2020

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In this study, the levels of concentration of homocysteine thiolactone (HTL), cysteine (Cys), and cysteinylglycine (CysGly) in the urine of autistic and non-autistic children were investigated and compared. HTL has never been analyzed in autistic children. The levels of low molecular weight sulfur compounds in the urine of both groups were determined by validated methods based on high-performance liquid chromatography with spectrofluorometric and diode-array detectors. The statistical data show a significant difference between the examined groups. Children with autism were characterized by a significantly higher level of HTL (p = 5.86 × 10−8), Cys (p = 1.49 × 10−10) and CysGly (p = 1.06 × 10−8) in urine compared with the control group. A difference in the p-value of <0.05 is statistically significant. Higher levels of HTL, Cys, and CysGly in the urine of 41 children with autism, aged 3 to 17, were observed. The obtained results may indicate disturbances in the metabolism of methionine, Cys, and glutathione in some autistic patients. These preliminary results suggest that further research with more rigorous designs and a large number of subjects is needed.

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“…Other metabolic profiles in ASD implicate aromatic and phenolic metabolites, including derivatives of nicotinic, amino acid, and hippurate metabolism (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). Various amino acids are detected at differential levels across studies and across sample types, but any consistent patterns are difficult to discern (15,24,26,29,(31)(32)(33)(34).…”

Section: Introductionmentioning

confidence: 99%

Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder

Needham

Adame

Serena

et al. 2020

Preprint

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Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with hallmark behavioral manifestations including impaired social communication and restricted repetitive behavior. In addition, many affected individuals display metabolic imbalances, immune dysregulation, gastrointestinal (GI) dysfunction, and altered gut microbiome compositions. We sought to better understand non-behavioral features of ASD by determining molecular signatures in peripheral tissues. Herein, we present the untargeted metabolome of 231 plasma and 97 fecal samples from a large cohort of children with ASD and typically developing (TD) controls. Differences in lipid, amino acid, and xenobiotic metabolism discriminate ASD and TD samples. We reveal correlations between specific metabolite profiles and clinical behavior scores, and identify metabolites particularly associated with GI dysfunction in ASD. These findings support a connection between GI physiology, metabolism, and complex behavioral traits, and may advance discovery and development of molecular biomarkers for ASD. Sterol 1 1 1 Gly, Ser, Thr 0 1 1

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Identification of metabolic pathway disturbances using multimodal metabolomics in autistic disorders in a Middle Eastern population

Cited by 52 publications

References 47 publications

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Higher Levels of Low Molecular Weight Sulfur Compounds and Homocysteine Thiolactone in the Urine of Autistic Children

Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder

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