Pubmed du 02/11/23
1. Chen L, Xiong XY, Yao TT, Gui LN, Luo F, Du Y, Cheng Y. Corrigendum to « Blood exosome sensing via neuronal insulin-like growth factor-1 regulates autism-related phenotypes » [Pharmacol. Res. 197 (2023) 106965]. Pharmacological research. 2023: 107014.
Lien vers le texte intégral (Open Access ou abonnement)
2. Gibson JM, Vazquez AH, Yamashiro K, Jakkamsetti V, Ren C, Lei K, Dentel B, Pascual JM, Tsai PT. Cerebellar contribution to autism-relevant behaviors in fragile X syndrome models. Cell reports. 2023; 42(12): 113533.
Cerebellar dysfunction has been linked to autism spectrum disorders (ASDs). Although cerebellar pathology has been observed in individuals with fragile X syndrome (FXS) and in mouse models of the disorder, a cerebellar functional contribution to ASD-relevant behaviors in FXS has yet to be fully characterized. In this study, we demonstrate a critical cerebellar role for Fmr1 (fragile X messenger ribonucleoprotein 1) in ASD-relevant behaviors. First, we identify reduced social behaviors, sensory hypersensitivity, and cerebellar dysfunction, with loss of cerebellar Fmr1. We then demonstrate that cerebellar-specific expression of Fmr1 is sufficient to impact social, sensory, cerebellar dysfunction, and cerebro-cortical hyperexcitability phenotypes observed in global Fmr1 mutants. Moreover, we demonstrate that targeting the ASD-implicated cerebellar region Crus1 ameliorates behaviors in both cerebellar-specific and global Fmr1 mutants. Together, these results demonstrate a critical role for the cerebellar contribution to FXS-related behaviors, with implications for future therapeutic strategies.
Lien vers le texte intégral (Open Access ou abonnement)
3. Hartley G, Sirois F, Purrington J, Rabey Y. Adverse Childhood Experiences and Autism: A Meta-Analysis. Trauma, violence & abuse. 2023: 15248380231213314.
Evidence suggests that autistic children have a higher probability of experiencing adverse childhood experiences (ACEs) compared to their non-autistic peers. This meta-analysis (PROSPERO: CRD42022262635) aimed to quantify the association of autism and ACEs. Eight databases and Google Scholar were searched for studies that reported dichotomous outcomes regarding the associations between ACEs and autistic individuals, compared to non-autistic individuals. A random-effects model was used to calculate the average Odds Ratio (OR) of the relationship between a diagnosis of autism and ACEs. A total of 40 studies with 5,619,584 participants were included, generating an overall average OR 2.11 (CI 1.61, 2.77). Significant differences in the magnitude of association were found across studies with regards to the type of ACEs studied, comparison groups, and population type. Overall, moderate certainty evidence (downgraded for bias) indicates that autistic individuals are at greater risk of experiencing ACEs, compared to non-autistic individuals. Appropriate support for autistic individuals and their families are required to prevent ACEs and treat the impact of ACEs.
Lien vers le texte intégral (Open Access ou abonnement)
4. Shilbayeh SAR, Adeen IS, Alhazmi AS, Ibrahim SF, Al Enazi FAR, Ghanem EH, Binduraihem AM. The Frequency of CYP2D6 and CYP3A4/5 Genotypes and The Impact of Their Allele Translation and Phenoconversion-Predicted Enzyme Activity on Risperidone Pharmacokinetics in Saudi Children with Autism. Biochemical genetics. 2023.
Data on the role of CYP2D6 and CYP3A4/5 polymorphisms in relation to risperidone (RIS) pharmacokinetics (PK) in children are relatively limited and inconsistent. This is partially attributable to the limited coverage of CYP2D6 and CYP3A4/5 metabolizer phenotypes, particularly those of poor and ultrarapid metabolizers (PMs and UMs), which has led to calls for studies of populations with a non-European background that may carry variants that are less frequent in Europeans. Children ≤ 18 years old with at least 8 weeks of a RIS-based regimen were recruited from three autism centers in Riyadh, Saudi Arabia. The primary outcomes measured were plasma concentrations of RIS and 9-hydroxyrisperidone (9-OH-RIS) and their dose-adjusted (C/D) ratios as a function of phenotypes and activity score (AS). For accurate DNA genotyping, targeted pharmacogenomic testing with the Axiom PharmacoFocus Array was performed via examination of a broad collection of probesets targeting CYP2D6 and CYP3A4/5 variants. The frequency of genotypes/phenotypes and the impact of their allele translation and phenoconversion-predicted enzyme activity were examined. The final cohort included 83 individuals. The most common CYP2D6 phenotype in our population was normal metabolizers (NMs, 66.3%). Inconsistent with some previous studies, the three phenotypes of intermediate metabolizers (IMs), NMs, and UMs were significantly different in terms of RIS concentration, the RIS/9-OH-RIS ratio, the RIS C/D ratio and the 9-OH-RIS C/D ratio. According to AS analyses, there were statistically significant differences in the RIS concentration (P = 0.013), RIS/9-OH-RIS ratio (P < 0.001) and RIS C/D ratio (P = 0.030) when patients were categorized into AS ≤ 1 vs. AS > 1. None of the CYP3A4/5 star allele translated phenotypes revealed a significant influence on any of the RIS PK parameters. Notably, neither CYP2D6 nor CYP3A4/5 phenotyping demonstrated a significant impact on the total active moiety, suggesting that other gene variants could modulate RIS PK. The study confirmed the previously reported partial impact of the CYP2D6 gene on RIS PK. However, future studies using contemporary genotyping techniques targeting a wide range of variants in other candidate genes must be conducted to further examine their interactive effects on RIS PK and the clinical response.
Lien vers le texte intégral (Open Access ou abonnement)
5. Suen YN, Chau APY, Wong SMY, Hui CLM, Chan SKW, Lee EHM, Wong MTH, Chen EYH. Comorbidity of autism spectrum and attention deficit/hyperactivity disorder symptoms and their associations with 1-year mental health outcomes in adolescents and young adults. Psychiatry research. 2023; 331: 115657.
Autism spectrum (ASD) and attention deficit/hyperactivity disorders (ADHD) share genetic, neurological, and behavioural features. However, related research in Asia is limited. We collected self-reported ASD and ADHD symptoms from 2186 Hong Kong adolescents and young adults aged 15-24 years, among whom, 1200 provided 1-year data on mental health-related outcomes. Comparative and network analyses were performed. Rating scale cutoff scores were used to divide participants into ASD, ADHD, comorbid, and control groups. The prevalence rates of ASD, ADHD, and comorbidities in Hong Kong were 13.3 %, 10.6 %, and 2.7 %, respectively. Compared with the control group, the comorbid group experienced more psychotic-like experiences (PLEs), the ASD group had poorer functioning, and the ADHD group had higher depression and anxiety symptoms and a lower quality of life after 1 year. The ability to switch attention, preference for routines and difficulty with change, and problems with organisation and planning were positively associated with depressive symptoms, forgetfulness and working memory issues with anxiety symptoms, and heightened sensory input and difficulties in sustaining attention and task completion with PLEs after 1 year. Our findings provide insight into support strategies to address the needs of young Asians to improving their well-being and long-term outcomes.
Lien vers le texte intégral (Open Access ou abonnement)
6. Tang T, Li C, Zhang S, Chen Z, Yang L, Mu Y, Chen J, Xu P, Gao D, Li F, He B, Zhu Y. A Hybrid Graph Network Model for ASD Diagnosis Based on Resting-state EEG Signals. Brain research bulletin. 2023: 110826.
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12% and 85.32% in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.
