Investigating plasma amino acids for differentiating individuals with autism spectrum disorder and typically developing peers / Troy VARGASON in Research in Autism Spectrum Disorders, 50 (June 2018)  

Public ISBD [article]  inResearch in Autism Spectrum Disorders > 50 (June 2018) . - p.60-72 Titre : Investigating plasma amino acids for differentiating individuals with autism spectrum disorder and typically developing peers Type de document : Texte imprimé et/ou numérique Auteurs : Troy VARGASON, Auteur ; Uwe KRUGER, Auteur ; Deborah L. MCGUINNESS, Auteur ; James B. ADAMS, Auteur ; Elizabeth GEIS, Auteur ; Eva GEHN, Auteur ; Devon COLEMAN, Auteur ; Juergen HAHN, Auteur Année de publication : 2018 Article en page(s) : p.60-72 Langues : Anglais (eng) Mots-clés : Autism spectrum disorder  Plasma amino acids  Fisher discriminant analysis  Classification  Multivariate statistics  Cross-validation Index. décimale : PER Périodiques Résumé : Background Plasma amino acid measurements have been extensively investigated in individuals with autism spectrum disorder (ASD). Results thus far have been inconclusive as studies generally disagree on which amino acids are different in individuals with ASD versus their typically developing (TD) peers, due in part to methodological limitations of several studies. Method This paper investigates plasma amino acids in children and adults with ASD using data from Arizona State University’s Comprehensive Nutritional and Dietary Intervention Study. Measurements from 64 individuals with ASD and 49 TD controls were analyzed using univariate and multivariate statistical techniques. Results Univariate analysis indicated increased median levels of glutamate (+21%, p?=?0.014) and serine (+8%, p?=?0.043), and increased mean levels of hydroxyproline (+17%, p?=?0.018) for the ASD cohort, although these differences were insignificant after correcting for multiple comparisons. A multivariate approach was used to classify study participants into ASD/TD cohorts using Fisher discriminant analysis (FDA) and its nonlinear extension, kernel Fisher discriminant analysis (KFDA). Model fitting with FDA using all available measurements produced Type I and Type II errors of 27.0% and 27.8%, respectively. KFDA was most effective when using hydroxyproline, leucine, and threonine as inputs; however, leave-one-out cross-validation with this nonlinear model only resulted in 70.3% sensitivity and 77.6% specificity. Conclusions The finding of elevated glutamate in ASD is in agreement with several other studies. Overall, however, these results suggest that plasma amino acid measurements are of limited use for purposes of ASD classification, which may explain some of the inconsistencies in results presented in the literature. En ligne : https://doi.org/10.1016/j.rasd.2018.03.004 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=356 [article] Investigating plasma amino acids for differentiating individuals with autism spectrum disorder and typically developing peers [Texte imprimé et/ou numérique] / Troy VARGASON, Auteur ; Uwe KRUGER, Auteur ; Deborah L. MCGUINNESS, Auteur ; James B. ADAMS, Auteur ; Elizabeth GEIS, Auteur ; Eva GEHN, Auteur ; Devon COLEMAN, Auteur ; Juergen HAHN, Auteur . - 2018 . - p.60-72. Langues : Anglais (eng) in Research in Autism Spectrum Disorders > 50 (June 2018) . - p.60-72 Mots-clés : Autism spectrum disorder  Plasma amino acids  Fisher discriminant analysis  Classification  Multivariate statistics  Cross-validation Index. décimale : PER Périodiques Résumé : Background Plasma amino acid measurements have been extensively investigated in individuals with autism spectrum disorder (ASD). Results thus far have been inconclusive as studies generally disagree on which amino acids are different in individuals with ASD versus their typically developing (TD) peers, due in part to methodological limitations of several studies. Method This paper investigates plasma amino acids in children and adults with ASD using data from Arizona State University’s Comprehensive Nutritional and Dietary Intervention Study. Measurements from 64 individuals with ASD and 49 TD controls were analyzed using univariate and multivariate statistical techniques. Results Univariate analysis indicated increased median levels of glutamate (+21%, p?=?0.014) and serine (+8%, p?=?0.043), and increased mean levels of hydroxyproline (+17%, p?=?0.018) for the ASD cohort, although these differences were insignificant after correcting for multiple comparisons. A multivariate approach was used to classify study participants into ASD/TD cohorts using Fisher discriminant analysis (FDA) and its nonlinear extension, kernel Fisher discriminant analysis (KFDA). Model fitting with FDA using all available measurements produced Type I and Type II errors of 27.0% and 27.8%, respectively. KFDA was most effective when using hydroxyproline, leucine, and threonine as inputs; however, leave-one-out cross-validation with this nonlinear model only resulted in 70.3% sensitivity and 77.6% specificity. Conclusions The finding of elevated glutamate in ASD is in agreement with several other studies. Overall, however, these results suggest that plasma amino acid measurements are of limited use for purposes of ASD classification, which may explain some of the inconsistencies in results presented in the literature. En ligne : https://doi.org/10.1016/j.rasd.2018.03.004 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=356

Maternal metabolic profile predicts high or low risk of an autism pregnancy outcome / Kathryn HOLLOWOOD in Research in Autism Spectrum Disorders, 56 (December 2018)  

Public ISBD [article]  inResearch in Autism Spectrum Disorders > 56 (December 2018) . - p.72-82 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 [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

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