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Classification of autism spectrum disorder from blood metabolites: Robustness to the presence of co-occurring conditions / Troy VARGASON in Research in Autism Spectrum Disorders, 77 (September 2020)
[article]
Titre : Classification of autism spectrum disorder from blood metabolites: Robustness to the presence of co-occurring conditions Type de document : Texte imprimé et/ou numérique Auteurs : Troy VARGASON, Auteur ; Emily ROTH, Auteur ; Genevieve GRIVAS, Auteur ; Jennifer FERINA, Auteur ; Richard E. FRYE, Auteur ; Juergen HAHN, Auteur Article en page(s) : 101644 Langues : Anglais (eng) Mots-clés : Autism spectrum disorder Co-occurring conditions Folate-dependent one-carbon metabolism Transsulfuration Multivariate analysis Classification Index. décimale : PER Périodiques Résumé : Background Previous studies have found plasma measurements of metabolites from the folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathways to be useful for differentiating individuals with autism spectrum disorder (ASD) from their typically developing peers. However, ASD is heterogeneous due to wide variation in the presence of co-occurring behavioral and medical conditions, and it is unknown how these conditions influence the ability to identify ASD based on FOCM/TS metabolites. Method This study employs a previously developed multivariate model that makes use of five FOCM/TS measurements (S-adenosylmethionine/S-adenosylhomocysteine, glutamylcysteine, glutathione disulfide, free cystine/free cysteine, and percent oxidized glutathione) to distinguish children with ASD from typically developing children. The model is used here to evaluate an independent cohort of individuals having ASD with diagnosed co-occurring conditions (age range 2–17 years old) and assess classifier performance in the presence/absence of these conditions. The four categories of co-occurring conditions considered were allergic disorders, gastrointestinal disorders, immune/metabolic disorders, and neurological disorders. All data were collected and retrospectively analyzed from previous clinical studies. Results The model was able to identify 124 of 131 participants with ASD (94.7 %) correctly regardless of co-occurring condition status. Model performance was generally not sensitive to the absence or presence of most co-occurring conditions, with the exceptions of ever/never having allergies or gastrointestinal symptoms, or currently (not) having any condition, all of which had minor impacts on model prediction accuracy. Conclusion The results of this exploratory study suggest that a FOCM/TS-based classifier for diagnosing ASD may potentially be robust to variations in co-occurring conditions and potentially applicable across ASD subtypes. Larger, more comprehensive follow-up studies with typically developing and/or developmentally delayed control groups are required to provide a more conclusive assessment of classifier robustness to co-occurring conditions. En ligne : https://doi.org/10.1016/j.rasd.2020.101644 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=432
in Research in Autism Spectrum Disorders > 77 (September 2020) . - 101644[article] Classification of autism spectrum disorder from blood metabolites: Robustness to the presence of co-occurring conditions [Texte imprimé et/ou numérique] / Troy VARGASON, Auteur ; Emily ROTH, Auteur ; Genevieve GRIVAS, Auteur ; Jennifer FERINA, Auteur ; Richard E. FRYE, Auteur ; Juergen HAHN, Auteur . - 101644.
Langues : Anglais (eng)
in Research in Autism Spectrum Disorders > 77 (September 2020) . - 101644
Mots-clés : Autism spectrum disorder Co-occurring conditions Folate-dependent one-carbon metabolism Transsulfuration Multivariate analysis Classification Index. décimale : PER Périodiques Résumé : Background Previous studies have found plasma measurements of metabolites from the folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathways to be useful for differentiating individuals with autism spectrum disorder (ASD) from their typically developing peers. However, ASD is heterogeneous due to wide variation in the presence of co-occurring behavioral and medical conditions, and it is unknown how these conditions influence the ability to identify ASD based on FOCM/TS metabolites. Method This study employs a previously developed multivariate model that makes use of five FOCM/TS measurements (S-adenosylmethionine/S-adenosylhomocysteine, glutamylcysteine, glutathione disulfide, free cystine/free cysteine, and percent oxidized glutathione) to distinguish children with ASD from typically developing children. The model is used here to evaluate an independent cohort of individuals having ASD with diagnosed co-occurring conditions (age range 2–17 years old) and assess classifier performance in the presence/absence of these conditions. The four categories of co-occurring conditions considered were allergic disorders, gastrointestinal disorders, immune/metabolic disorders, and neurological disorders. All data were collected and retrospectively analyzed from previous clinical studies. Results The model was able to identify 124 of 131 participants with ASD (94.7 %) correctly regardless of co-occurring condition status. Model performance was generally not sensitive to the absence or presence of most co-occurring conditions, with the exceptions of ever/never having allergies or gastrointestinal symptoms, or currently (not) having any condition, all of which had minor impacts on model prediction accuracy. Conclusion The results of this exploratory study suggest that a FOCM/TS-based classifier for diagnosing ASD may potentially be robust to variations in co-occurring conditions and potentially applicable across ASD subtypes. Larger, more comprehensive follow-up studies with typically developing and/or developmentally delayed control groups are required to provide a more conclusive assessment of classifier robustness to co-occurring conditions. En ligne : https://doi.org/10.1016/j.rasd.2020.101644 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=432 Maternal metabolic profile predicts high or low risk of an autism pregnancy outcome / Kathryn HOLLOWOOD in Research in Autism Spectrum Disorders, 56 (December 2018)
[article]
Titre : Maternal metabolic profile predicts high or low risk of an autism pregnancy outcome Type de document : Texte imprimé et/ou numérique Auteurs : Kathryn HOLLOWOOD, Auteur ; Stepan MELNYK, Auteur ; Oleksandra PAVLIV, Auteur ; Teresa EVANS, Auteur ; Ashley SIDES, Auteur ; Rebecca J. SCHMIDT, Auteur ; Irva HERTZ-PICCIOTTO, Auteur ; William ELMS, Auteur ; Elizabeth GUERRERO, Auteur ; Uwe KRUGER, Auteur ; Juergen HAHN, Auteur ; S. Jill JAMES, Auteur Article en page(s) : p.72-82 Langues : Anglais (eng) Mots-clés : Autism Pregnancy Metabolic profile Folate Transmethylation Transsulfuration Fisher discriminant analysis Index. décimale : PER Périodiques Résumé : Background Currently there is no test for pregnant mothers that can predict the probability of having a child that will be diagnosed with autism spectrum disorder (ASD). Recent estimates indicate that if a mother has previously had a child with ASD, the risk of having a second child with ASD is ?18.7% (High Risk) whereas the risk of ASD in the general population is ?1.7% (Low Risk). Methods In this study, metabolites of the folate-dependent transmethylation and transsulfuration biochemical pathways of pregnant mothers were measured to determine whether or not the risk of having a child with autism could be predicted by her metabolic profile. Pregnant mothers who have had a child with autism before were separated into two groups based on the diagnosis of their child whether the child had autism (ASD) or not (TD). Then these mothers were compared to a group of control mothers who have not had a child with autism before. A total of 107 mothers were in the High Risk category and 25 mothers in the Low Risk category. The High Risk category was further separated into 29 mothers in the ASD group and 78 mothers in the TD group. Results The metabolic results indicated that among High Risk mothers, it was not possible to predict an autism pregnancy outcome. However, the metabolic profile was able to predict with approximately 90% sensitivity and specificity whether a mother fell into the High Risk group (18.7% risk) or Low Risk group (1.7% risk). Conclusions Based upon these measurements it is not possible to determine during a pregnancy if a child will be diagnosed with ASD by age 3. However, differences in the folate-dependent transmethylation and transsulfuration metabolites are indicative of the risk level (High Risk of 18.7% vs. Low Risk of 1.7%) of the mother for having a child with ASD. En ligne : https://doi.org/10.1016/j.rasd.2018.09.003 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=369
in Research in Autism Spectrum Disorders > 56 (December 2018) . - p.72-82[article] Maternal metabolic profile predicts high or low risk of an autism pregnancy outcome [Texte imprimé et/ou numérique] / Kathryn HOLLOWOOD, Auteur ; Stepan MELNYK, Auteur ; Oleksandra PAVLIV, Auteur ; Teresa EVANS, Auteur ; Ashley SIDES, Auteur ; Rebecca J. SCHMIDT, Auteur ; Irva HERTZ-PICCIOTTO, Auteur ; William ELMS, Auteur ; Elizabeth GUERRERO, Auteur ; Uwe KRUGER, Auteur ; Juergen HAHN, Auteur ; S. Jill JAMES, Auteur . - p.72-82.
Langues : Anglais (eng)
in Research in Autism Spectrum Disorders > 56 (December 2018) . - p.72-82
Mots-clés : Autism Pregnancy Metabolic profile Folate Transmethylation Transsulfuration Fisher discriminant analysis Index. décimale : PER Périodiques Résumé : Background Currently there is no test for pregnant mothers that can predict the probability of having a child that will be diagnosed with autism spectrum disorder (ASD). Recent estimates indicate that if a mother has previously had a child with ASD, the risk of having a second child with ASD is ?18.7% (High Risk) whereas the risk of ASD in the general population is ?1.7% (Low Risk). Methods In this study, metabolites of the folate-dependent transmethylation and transsulfuration biochemical pathways of pregnant mothers were measured to determine whether or not the risk of having a child with autism could be predicted by her metabolic profile. Pregnant mothers who have had a child with autism before were separated into two groups based on the diagnosis of their child whether the child had autism (ASD) or not (TD). Then these mothers were compared to a group of control mothers who have not had a child with autism before. A total of 107 mothers were in the High Risk category and 25 mothers in the Low Risk category. The High Risk category was further separated into 29 mothers in the ASD group and 78 mothers in the TD group. Results The metabolic results indicated that among High Risk mothers, it was not possible to predict an autism pregnancy outcome. However, the metabolic profile was able to predict with approximately 90% sensitivity and specificity whether a mother fell into the High Risk group (18.7% risk) or Low Risk group (1.7% risk). Conclusions Based upon these measurements it is not possible to determine during a pregnancy if a child will be diagnosed with ASD by age 3. However, differences in the folate-dependent transmethylation and transsulfuration metabolites are indicative of the risk level (High Risk of 18.7% vs. Low Risk of 1.7%) of the mother for having a child with ASD. En ligne : https://doi.org/10.1016/j.rasd.2018.09.003 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=369