1. Chen CM, Yang P, Wu MT, Chuang TC, Huang TY. {{Deriving and validating biomarkers associated with autism spectrum disorders from a large-scale resting-state database}}. {Sci Rep};2019 (Jun 21);9(1):9043.
Resting-state functional magnetic resonance imaging (MRI) has been used to investigate the brain activity related to autism spectrum disorder (ASD). In this study, we applied information from a large-scale dataset, the Autism Brain Imaging Data Exchange (ABIDE), to clinical applications. We recruited 21 patients with ASD and 23 individuals with neurotypical development (TD). We applied ASD biomarkers derived from ABIDE datasets and subsequently investigated the relationship between the MRI biomarkers and indicators from clinical screening questionnaires, the social responsiveness scale (SRS), and the Swanson, Nolan, and Pelham Questionnaire IV. The results indicated that the biomarkers generated from the default mode and executive control networks significantly differed between the participants with ASD and TD. In particular, the biomarkers derived from the default mode network were negatively correlated with the raw scores and model factors of the SRS. In summary, this study transferred the efforts of the global autism research community to clinical applications and identified connectivity-based biomarkers in ASD.
Lien vers le texte intégral (Open Access ou abonnement)
2. Kang JN, Song JJ, Casanova MF, Sokhadze EM, Li XL. {{Effects of repetitive transcranial magnetic stimulation on children with low-function autism}}. {CNS Neurosci Ther};2019 (Jun 22)
BACKGROUND: Autism spectrum disorder (ASD) is a very complex neurodevelopmental disorder, characterized by social difficulties and stereotypical or repetitive behavior. Some previous studies using low-frequency repetitive transcranial magnetic stimulation (rTMS) have proven of benefit in ASD children. METHODS: In this study, 32 children (26 males and six females) with low-function autism were enrolled, 16 children (three females and 13 males; mean +/- SD age: 7.8 +/- 2.1 years) received rTMS treatment twice every week, while the remaining 16 children (three females and 13 males; mean +/- SD age: 7.2 +/- 1.6 years) served as waitlist group. This study investigated the effects of rTMS on brain activity and behavioral response in the autistic children. RESULTS: Peak alpha frequency (PAF) is an electroencephalographic measure of cognitive preparedness and might be a neural marker of cognitive function for the autism. Coherence is one way to assess the brain functional connectivity of ASD children, which has proven abnormal in previous studies. The results showed significant increases in the PAF at the frontal region, the left temporal region, the right temporal region and the occipital region and a significant increase of alpha coherence between the central region and the right temporal region. Autism Behavior Checklist (ABC) scores were also compared before and after receiving rTMS with positive effects shown on behavior. CONCLUSION: These findings supported our hypothesis by demonstration of positive effects of combined rTMS neurotherapy in active treatment group as compared to the waitlist group, as the rTMS group showed significant improvements in behavioral and functional outcomes as compared to the waitlist group.
Lien vers le texte intégral (Open Access ou abonnement)
3. Osredkar J, Gosar D, Macek J, Kumer K, Fabjan T, Finderle P, Sterpin S, Zupan M, Jekovec Vrhovsek M. {{Urinary Markers of Oxidative Stress in Children with Autism Spectrum Disorder (ASD)}}. {Antioxidants (Basel)};2019 (Jun 20);8(6)
Background: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction, restricted interest and repetitive behavior. Oxidative stress in response to environmental exposure plays a role in virtually every human disease and represents a significant avenue of research into the etiology of ASD. The aim of this study was to explore the diagnostic utility of four urinary biomarkers of oxidative stress. Methods: One hundred and thirty-nine (139) children and adolescents with ASD (89% male, average age = 10.0 years, age range = 2.1 to 18.1 years) and 47 healthy children and adolescents (49% male, average age 9.2, age range = 2.5 to 20.8 years) were recruited for this study. Their urinary 8-OH-dG, 8-isoprostane, dityrosine and hexanoil-lisine were determined by using the ELISA method. Urinary creatinine was determined with the kinetic Jaffee reaction and was used to normalize all biochemical measurements. Non-parametric tests and support vector machines (SVM) with three different kernel functions (linear, radial, polynomial) were used to explore and optimize the multivariate prediction of an ASD diagnosis based on the collected biochemical measurements. The SVM models were first trained using data from a random subset of children and adolescents from the ASD group (n = 70, 90% male, average age = 9.7 years, age range = 2.1 to 17.8 years) and the control group (n = 24, 45.8% male, average age = 9.4 years, age range = 2.5 to 20.8 years) using bootstrapping, with additional synthetic minority over-sampling (SMOTE), which was utilized because of unbalanced data. The computed SVM models were then validated using the remaining data from children and adolescents from the ASD (n = 69, 88% male, average age = 10.2 years, age range = 4.3 to 18.1 years) and the control group (n = 23, 52.2% male, average age = 8.9 years, age range = 2.6 to 16.7 years). Results: Using a non-parametric test, we found a trend showing that the urinary 8-OH-dG concentration was lower in children with ASD compared to the control group (unadjusted p = 0.085). When all four biochemical measurements were combined using SVMs with a radial kernel function, we could predict an ASD diagnosis with a balanced accuracy of 73.4%, thereby accounting for an estimated 20.8% of variance (p < 0.001). The predictive accuracy expressed as the area under the curve (AUC) was solid (95% CI = 0.691-0.908). Using the validation data, we achieved significantly lower rates of classification accuracy as expressed by the balanced accuracy (60.1%), the AUC (95% CI = 0.502-0.781) and the percentage of explained variance (R(2) = 3.8%). Although the radial SVMs showed less predictive power using the validation data, they do, together with ratings of standardized SVM variable importance, provide some indication that urinary levels of 8-OH-dG and 8-isoprostane are predictive of an ASD diagnosis. Conclusions: Our results indicate that the examined urinary biomarkers in combination may differentiate children with ASD from healthy peers to a significant extent. However, the etiological importance of these findings is difficult to assesses, due to the high-dimensional nature of SVMs and a radial kernel function. Nonetheless, our results show that machine learning methods may provide significant insight into ASD and other disorders that could be related to oxidative stress. Lien vers le texte intégral (Open Access ou abonnement)
4. Saghazadeh A, Ataeinia B, Keynejad K, Abdolalizadeh A, Hirbod-Mobarakeh A, Rezaei N. {{Anti-inflammatory cytokines in autism spectrum disorders: A systematic review and meta-analysis}}. {Cytokine};2019 (Jun 19);123:154740.
BACKGROUND: In the search for the causes of autism spectrum disorders (ASD), inflammatory markers have emerged as potential candidates. The present meta-analysis was performed on studies examining circulating concentrations of anti-inflammatory cytokines in people with ASD compared with control subjects without ASD. METHODS: We identified potentially eligible studies by systematically searching electronic databases from inception to February 2018. RESULTS: Twenty-five studies with a total of 1754 participants (1022 patients with ASD and 732 control subjects) were included in the mate-analysis; 4 for interferon (IFN)-alpha, 9 for interleukin (IL)-1 receptor antagonist (Ra), 9 for IL-4, 6 for IL-5, 3 for IL-9, 14 for IL-10, 7 for IL-13, and 6 for transforming growth factor (TGF)-beta. We found a moderate decrease in plasma levels of IL-10 (SMD=-0.59) and a small decrease in serum levels of IL-1Ra (SMD=-0.25) in patients with ASD. On the contrary, serum IL-5 levels were slightly increased (SMD=0.26) in these patients. We conducted meta-regression analyses to investigate the possible effect of moderatos on the effect size (ES) of difference in mean levels of IL-10. Difference in the mean age between patients and controls showed a negative influence on the ES and was able to explain about 0.4 of total between-study variance. In contrast, latitude exerted a positive effect on the ES and explained a lower proportion (0.1) of total between-study variance. CONCLUSIONS: This meta-analysis provides evidence for the lower concentration of anti-inflammatory cytokines IL-10 and IL-1Ra in autistic patients compared with control subjects. Also, meta-regression analyses point to the interaction of latitude, age, and gender with peripheral alterations of associated anti-inflammatory cytokines.
