1. Castagnola S, Bardoni B, Maurin T. {{The Search for an Effective Therapy to Treat Fragile X Syndrome: Dream or Reality?}}. {Front Synaptic Neurosci}. 2017; 9: 15.
Fragile X Syndrome (FXS) is the most common form of intellectual disability and a primary cause of autism. It originates from the lack of the Fragile X Mental Retardation Protein (FMRP), which is an RNA-binding protein encoded by the Fragile X Mental Retardation Gene 1 (FMR1) gene. Multiple roles have been attributed to this protein, ranging from RNA transport (from the nucleus to the cytoplasm, but also along neurites) to translational control of mRNAs. Over the last 20 years many studies have found a large number of FMRP mRNA targets, but it is still not clear which are those playing a critical role in the etiology of FXS. So far, no therapy for FXS has been found, making the quest for novel targets of considerable importance. Several pharmacological approaches have been attempted, but, despite some promising preclinical results, no strategy gave successful outcomes, due either to the induction of major side effects or to the lack of improvement of the phenotypes. However, these studies suggested that, in order to measure the effectiveness of a specific treatment, trials should be redesigned and new endpoints defined in FXS patients. Nevertheless, the search for new therapeutic targets for FXS is very active. In this context, the advances in animal modeling, coupled with better understanding of neurobiology and physiopathology of FXS, are of crucial importance in developing new selected treatments. Here, we discuss the pathways that were recently linked to the physiopathology of FXS (mGluR, GABAR, insulin, Insulin-like Growth Factor 1 (IGF-1), MPP-9, serotonin, oxytocin and endocannabinoid signaling) and that suggest new approaches to find an effective therapy for this disorder. Our goal with this review article is to summarize some recent relevant findings on FXS treatment strategies in order to have a clearer view of the different pathways analyzed to date emphasizing those shared with other synaptic disorders.
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2. Guo M, Zhu J, Yang T, Lai X, Liu X, Liu J, Chen J, Li T. {{Vitamin A improves the symptoms of autism spectrum disorders and decreases 5-hydroxytryptamine (5-HT): A pilot study}}. {Brain Res Bull}. 2017; 137: 35-40.
Autism spectrum disorders (ASD) are complicated neurodevelopmental disorders. Many studies have demonstrated that children with autism have multiple nutritional deficiencies and increased serum 5-hydroxytryptamine (5-HT) levels. In our previous study, 77.9% of autistic children were found to have vitamin A deficiency, and the concentration of vitamin A was negatively associated with the CARS score. In the present study, we sought to test whether vitamin A supplementation could improve autistic symptoms and decrease serum 5-HT levels. The DSM-V criteria and CARS score were used for symptom description and symptom assessment of the patients, respectively, before and after vitamin A supplementation (VAS). Serum retinol and 5-HT levels, mRNA levels of RAR alpha, beta, and gamma and TpH 1 expression were detected in autistic children before and after VAS and in normal children. Serum retinol levels in children with ASD were significantly lower than in control children. Serum 5-HT levels in children with ASD were higher than in control children, which were correlated with symptom severity of children with autism. After VA supplementation, the children with ASD exhibited significant improvement in autism symptoms. Serum retinol concentrations of children with ASD were significantly increased, and serum 5-HT levels were decreased. Moreover, statistically significant changes were observed in mRNA expression levels of RAR alpha, RAR gamma and TpH 1 after VAS compared to baseline. This study suggested that VA supplementation may improve symptoms and reduce 5-HT levels in children with ASD, indicating that VA supplementation is a reasonable therapy at least for a subset of children with autism.
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3. Kaur M, S MS, A NB. {{Comparing motor performance, praxis, coordination, and interpersonal synchrony between children with and without Autism Spectrum Disorder (ASD)}}. {Res Dev Disabil}. 2017; 72: 79-95.
Children with Autism Spectrum Disorder (ASD) have basic motor impairments in balance, gait, and coordination as well as autism-specific impairments in praxis/motor planning and interpersonal synchrony. Majority of the current literature focuses on isolated motor behaviors or domains. Additionally, the relationship between cognition, symptom severity, and motor performance in ASD is unclear. We used a comprehensive set of measures to compare gross and fine motor, praxis/imitation, motor coordination, and interpersonal synchrony skills across three groups of children between 5 and 12 years of age: children with ASD with high IQ (HASD), children with ASD with low IQ (LASD), and typically developing (TD) children. We used the Bruininks-Oseretsky Test of Motor Proficiency and the Bilateral Motor Coordination subtest of the Sensory Integration and Praxis Tests to assess motor performance and praxis skills respectively. Children were also examined while performing simple and complex rhythmic upper and lower limb actions on their own (solo context) and with a social partner (social context). Both ASD groups had lower gross and fine motor scores, greater praxis errors in total and within various error types, lower movement rates, greater movement variability, and weaker interpersonal synchrony compared to the TD group. In addition, the LASD group had lower gross motor scores and greater mirroring errors compared to the HASD group. Overall, a variety of motor impairments are present across the entire spectrum of children with ASD, regardless of their IQ scores. Both, fine and gross motor performance significantly correlated with IQ but not with autism severity; however, praxis errors (mainly, total, overflow, and rhythmicity) strongly correlated with autism severity and not IQ. Our study findings highlight the need for clinicians and therapists to include motor evaluations and interventions in the standard-of-care of children with ASD and for the broader autism community to recognize dyspraxia as an integral part of the definition of ASD.
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4. Osokine I, Erlebacher A. {{Inflammation and Autism: From Maternal Gut to Fetal Brain}}. {Trends Mol Med}. 2017.
Maternal immune activation (MIA) during pregnancy is associated with an increased risk of behavioral disorders in the offspring of affected mothers. Two recent studies highlight how maternal inflammation disrupts inhibitory interneuron networks and suggest that the maternal gut microbiome may be a contributing risk factor for MIA-induced behavioral abnormalities.
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5. Stefanik L, Erdman L, Ameis SH, Foussias G, Mulsant BH, Behdinan T, Goldenberg A, O’Donnell LJ, Voineskos AN. {{Brain-Behavior Participant Similarity Networks Among Youth and Emerging Adults with Schizophrenia Spectrum, Autism Spectrum, or Bipolar Disorder and Matched Controls}}. {Neuropsychopharmacology}. 2017.
There is considerable heterogeneity in social cognitive and neurocognitive performance among people with schizophrenia spectrum disorders (SSD), autism spectrum disorders (ASD), bipolar disorder (BD), and healthy individuals. This study used Similarity Network Fusion (SNF), a novel data-driven approach, to identify participant similarity networks based on relationships among demographic, brain imaging, and behavioral data. T1-weighted and diffusion-weighted magnetic resonance images were obtained for 174 adolescents and young adults (aged 16-35 years) with an SSD (n=51), an ASD without intellectual disability (n=38), euthymic BD (n=34), and healthy controls (n=51). A battery of social cognitive and neurocognitive tasks were administered. Data integration, cluster determination, and biological group formation were then obtained using SNF. We identified four new groups of individuals, each with distinct neural circuit-cognitive profiles. The most influential variables driving the formation of the new groups were robustly reliable across embedded resampling techniques. The data-driven groups showed considerably greater differentiation on key social and neurocognitive circuit nodes than groups generated by diagnostic analyses or dimensional social cognitive analyses. The data-driven groups were validated through functional outcome and brain network property measures not included in the SNF model. Cutting across diagnostic boundaries, our approach can effectively identify new groups of people based on a profile of neuroimaging and behavioural data. Our findings bringing us closer to disease subtyping that can be leveraged toward targeting of specific neural circuitry among participant subgroups to ameliorate social cognitive and neurocognitive deficits.Neuropsychopharmacology accepted article preview online, 06 November 2017. doi:10.1038/npp.2017.274.
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6. Yang X, Liang S, Wang L, Han P, Jiang X, Wang J, Hao Y, Wu L. {{Sialic Acid and Anti-ganglioside Antibody Levels in Children with Autism Spectrum Disorders}}. {Brain Res}. 2017.
BACKGROUND: Autism spectrum disorders (ASD) may result from a combination of genetic and environmental factors, and impact neurological functions and behaviors. Sialic acid (SA) is an indispensable nutrient for early brain development, and its polymer polySia (PSA) can modify neural cell adhesion molecules (NCAM), thereby indirectly mediating neuronal outgrowth, synaptic connectivity and memory formation. To investigate the association between SA and ASD, we conducted a case-control study. METHODS: The study sample included 82 autistic children and 60 healthy children. We measured the levels of plasma SA and serum anti-gangliosides M1 antibodies (anti-GM1 antibodies) in the ASD and control groups. We also examined the severity of autistic children. RESULTS: The level of plasma SA in the control group was significantly higher than that in the ASD group (p < 0.01). Autistic children had higher positive rates of anti-GM1 antibodies (37.8%) than controls (21.67%, P = 0.04). However, there was no correlation between autistic severity and the levels of SA. SA may be as a biomarker for diagnosis of ASD with a positive predictive value of 84.42%, a negative predictive value of 73.85% and an area under the ROC curve value of 0.858. CONCLUSIONS: These results indicate that SA and anti-GM1 antibodies are associated with ASD. Our data suggested that future studies to explore the function of SA in the etiology of ASD may be needed. Lien vers le texte intégral (Open Access ou abonnement)
7. Zhou J, He F, Yang F, Yang Z, Xie Y, Zhou S, Liang J, Xu R, Wang Y, Guo H, Zhou W, Wang M. {{Increased stool immunoglobulin A level in children with autism spectrum disorders}}. {Res Dev Disabil}. 2017.
BACKGROUND: There are currently no effective treatments for the core symptoms of autism spectrum disorders (ASDs). However, alleviating gastrointestinal (GI) problems, which are prevalent in ASD patients, can significantly improve the core symptoms of autism. Previous studies have associated GI disorders in ASD patients with abnormal gut microbiota, although few disease-related microorganisms have been identified. Considering that the gut microbiome affects the intestinal immune system and the patient’s behavior, and that immunoglobulin A (IgA) is the main antibody secreted by intestinal immune cells, we investigated stool IgA content as a means of understanding the gut immune status of ASD patients. The IgA level in gut can be used as factor to know the Gene x Environment interactions and diagnose of ASDs. METHODS: We enrolled 43 ASD patients and 31 gender- and age-matched healthy children. Stool IgA content was measured by enzyme-linked immunosorbent assay. RESULTS: We found that IgA levels were significantly higher in stool samples from ASD patients than from healthy children (p<0.05, Student's t test). CONCLUSIONS: This finding may suggest the presence of gut immune abnormalities in ASD patients. Further studies with larger patient and control cohorts will be necessary to determine whether stool IgA levels can be used as a biomarker for ASDs. Lien vers le texte intégral (Open Access ou abonnement)
