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)  

Public ISBD [article]  inResearch in Autism Spectrum Disorders > 77 (September 2020) . - 101644 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 [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

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

Maternal risk factors vary between subpopulations of children with autism spectrum disorder / Genevieve GRIVAS in Autism Research, 15-11 (November 2022)  

Public ISBD [article]  inAutism Research > 15-11 (November 2022) . - p.2038-2055 Titre : Maternal risk factors vary between subpopulations of children with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Genevieve GRIVAS, Auteur ; Richard E. FRYE, Auteur ; Juergen HAHN, Auteur Article en page(s) : p.2038-2055 Langues : Anglais (eng) Mots-clés : Child  Pregnancy  Female  Humans  Autism Spectrum Disorder/complications/epidemiology/diagnosis  Case-Control Studies  Pregnancy Complications  Risk Factors  Immune System Diseases/complications  Seizures/complications  associated risk  autism spectrum disorder  co-occurring conditions  logistic regression  medical claims  retrospective analysis  subgroups Index. décimale : PER Périodiques Résumé : Previous work identified three subgroups of children with ASD based upon co-occurring conditions (COCs) diagnosed during the first 5 years of life. This work examines prenatal risk factors, given by maternal medical claims, for each of the three subgroups: children with a High-Prevalence of COCs, children with mainly developmental delay and seizures (DD/Seizure COCs), and children with a Low-Prevalence of COCs. While some risk factors are shared by all three subgroups, the majority of the factors identified for each subgroup were unique; infections, anti-inflammatory and other complex medications were associated with the High-Prevalence COCs group; immune deregulatory conditions such as asthma and joint disorders were associated with the DD/Seizure COCs group; and overall pregnancy complications were associated with the Low-Prevalence COCs group. Thus, we have found that the previously identified subgroups of children with ASD have distinct associated prenatal risk factors. As such, this work supports subgrouping children with ASD based upon COCs, which may provide a framework for elucidating some of the heterogeneity associated with ASD. En ligne : http://dx.doi.org/10.1002/aur.2809 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=488 [article] Maternal risk factors vary between subpopulations of children with autism spectrum disorder [Texte imprimé et/ou numérique] / Genevieve GRIVAS, Auteur ; Richard E. FRYE, Auteur ; Juergen HAHN, Auteur . - p.2038-2055. Langues : Anglais (eng) in Autism Research > 15-11 (November 2022) . - p.2038-2055 Mots-clés : Child  Pregnancy  Female  Humans  Autism Spectrum Disorder/complications/epidemiology/diagnosis  Case-Control Studies  Pregnancy Complications  Risk Factors  Immune System Diseases/complications  Seizures/complications  associated risk  autism spectrum disorder  co-occurring conditions  logistic regression  medical claims  retrospective analysis  subgroups Index. décimale : PER Périodiques Résumé : Previous work identified three subgroups of children with ASD based upon co-occurring conditions (COCs) diagnosed during the first 5 years of life. This work examines prenatal risk factors, given by maternal medical claims, for each of the three subgroups: children with a High-Prevalence of COCs, children with mainly developmental delay and seizures (DD/Seizure COCs), and children with a Low-Prevalence of COCs. While some risk factors are shared by all three subgroups, the majority of the factors identified for each subgroup were unique; infections, anti-inflammatory and other complex medications were associated with the High-Prevalence COCs group; immune deregulatory conditions such as asthma and joint disorders were associated with the DD/Seizure COCs group; and overall pregnancy complications were associated with the Low-Prevalence COCs group. Thus, we have found that the previously identified subgroups of children with ASD have distinct associated prenatal risk factors. As such, this work supports subgrouping children with ASD based upon COCs, which may provide a framework for elucidating some of the heterogeneity associated with ASD. En ligne : http://dx.doi.org/10.1002/aur.2809 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=488

Urinary essential elements of young children with autism spectrum disorder and their mothers / Fatir QURESHI in Research in Autism Spectrum Disorders, 72 (April 2020)  

Public ISBD [article]  inResearch in Autism Spectrum Disorders > 72 (April 2020) . - p.101518 Titre : Urinary essential elements of young children with autism spectrum disorder and their mothers Type de document : Texte imprimé et/ou numérique Auteurs : Fatir QURESHI, Auteur ; James B. ADAMS, Auteur ; Devon COLEMAN, Auteur ; David QUIG, Auteur ; Juergen HAHN, Auteur Article en page(s) : p.101518 Langues : Anglais (eng) Mots-clés : ASD  Metabolism  Essential elements  Urine analysis Index. décimale : PER Périodiques Résumé : Background Even though the cause of autism spectrum disorders (ASD) remains unknown, the current understanding points towards complex interactions between environmental and genetic factors. One important environmental factor to consider is intake of toxic and essential elements, and their role in metabolism. Essential elements have received considerably less attention in the literature than the presence of toxins in urine. Method The purpose of this investigation is to comprehensively assess the association between urinary element compositions of 28 mothers who had young children with ASD and 29 mothers who had young typically developing (TD) children, and in a subset of their children (21 with ASD and 26 TD). Results The results show that there are significant differences between the ASD and TD children cohorts’ concentrations for four specific elements (sulfur, phosphorous, molybdenum, and tin). Utilizing multivariate statistical techniques (Fisher’s discriminant analysis and support vector machines), it was possible to distinguish the ASD from the TD children groups with an 81 % accuracy after cross-validation utilizing the four significantly different elements. However, among the mother cohorts assessed, there were no significant differences between those that had children with ASD and those with TD children. There was a significant correlation of levels of phosphorus and sulfur in the children with ASD (r?=?0.63, p?=?3.0E-3) and in the TD children (r?=?0.47, p?=?0.02). Conclusions Notable differences were observed between the elemental concentration in urine of children with ASD and their TD peers. Analyzing cellular pathways related to these elements are promising areas of future research. En ligne : https://doi.org/10.1016/j.rasd.2020.101518 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=420 [article] Urinary essential elements of young children with autism spectrum disorder and their mothers [Texte imprimé et/ou numérique] / Fatir QURESHI, Auteur ; James B. ADAMS, Auteur ; Devon COLEMAN, Auteur ; David QUIG, Auteur ; Juergen HAHN, Auteur . - p.101518. Langues : Anglais (eng) in Research in Autism Spectrum Disorders > 72 (April 2020) . - p.101518 Mots-clés : ASD  Metabolism  Essential elements  Urine analysis Index. décimale : PER Périodiques Résumé : Background Even though the cause of autism spectrum disorders (ASD) remains unknown, the current understanding points towards complex interactions between environmental and genetic factors. One important environmental factor to consider is intake of toxic and essential elements, and their role in metabolism. Essential elements have received considerably less attention in the literature than the presence of toxins in urine. Method The purpose of this investigation is to comprehensively assess the association between urinary element compositions of 28 mothers who had young children with ASD and 29 mothers who had young typically developing (TD) children, and in a subset of their children (21 with ASD and 26 TD). Results The results show that there are significant differences between the ASD and TD children cohorts’ concentrations for four specific elements (sulfur, phosphorous, molybdenum, and tin). Utilizing multivariate statistical techniques (Fisher’s discriminant analysis and support vector machines), it was possible to distinguish the ASD from the TD children groups with an 81 % accuracy after cross-validation utilizing the four significantly different elements. However, among the mother cohorts assessed, there were no significant differences between those that had children with ASD and those with TD children. There was a significant correlation of levels of phosphorus and sulfur in the children with ASD (r?=?0.63, p?=?3.0E-3) and in the TD children (r?=?0.47, p?=?0.02). Conclusions Notable differences were observed between the elemental concentration in urine of children with ASD and their TD peers. Analyzing cellular pathways related to these elements are promising areas of future research. En ligne : https://doi.org/10.1016/j.rasd.2020.101518 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=420

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