Neurometabolite levels in the brains of patients with autism spectrum disorders: A meta-analysis of proton magnetic resonance spectroscopy studies (N = 1501)

GABA and Glx predict EEG responses of visual sensitivity in autism

The mechanisms underlying atypical sensory processing in autism remain to be elucidated, but research points toward a role of the glutamatergic/GABAergic balance. To investigate the potential relationships between visual sensitivity and its molecular correlates in autism, we combined data from electroencephalography (EEG) and magnetic resonance spectroscopy (MRS) studies. Twenty autistic adults and sixteen neurotypical adults (NT) participated in both an EEG study assessing visual sensitivity (Sapey-Triomphe et al., Autism Research, 2023) and in an MRS study measuring Glx and GABA+ concentrations in the occipital cortex (Sapey-Triomphe et al., Molecular Autism, 2021). These studies revealed no group differences in neural detection thresholds or in Glx/GABA levels in the occipital cortex. Neural detection thresholds for contrast and spatial frequency (SF) were determined using fast periodic visual stimulations and neural frequency tagging. In the present study, Glx/GABA+ concentrations in the occipital cortex and neural detection thresholds did not differ between groups. Interestingly, lower Glx/GABA+ ratios were associated with lower contrast detection thresholds and higher SF detection thresholds. These correlations were also significant within the neurotypical and autistic groups. This report suggests that the Glx/GABA balance regulates visual detection thresholds across individuals. In both autistic and NTs, lower Glx/GABA ratios in the occipital cortex allow for better detection of visual inputs at the neural level. This study sheds light on the neurochemical underpinnings of visual sensitivity in autism and warrants further investigation.

Autism spectrum disorder: Cadmium and mercury concentrations in different biological samples, a systematic literature review and meta-analysis of human studies

The present study was conducted to investigate the differences in cadmium (Cd) and mercury (Hg) concentrations between children with autism spectrum disorder (ASD) and controls. In this systematic review and meta-analysis study, three thousand one hundred forty-five studies were collected from scientific databases including Web of Science, Scopus, PubMed, and Google Scholar from January 2000 to October 2022 and were investigated for eligibility. As a result, 37 studies published in the period from 2003 to 2022 met our inclusion criteria and were considered in the meta-analysis. The heterogeneity assumption was evaluated using the Chi-squared-based Q-test and I-squared (I2) statistics. The pooled estimates were shown in the forest plots with Hedges' g (95% confidence interval) values. The random effects model demonstrated that there is no significant difference in the blood (Hedges' g: 0.14, 95% CI: 0.45, 0.72, p > 0.05), hair (Hedges' g: 0.12, 95% CI: 0.26, 0.50, p > 0.05), and urinary (Hedges' g: 0.05, 95% CI: 0.86, 0.76, p > 0.05) Cd levels of the case group versus control subjects. Moreover, the pooled findings of studies showed no significant difference in the blood (Hedges' g: 1.69, 95% CI: 0.09, 3.48, p > 0.05), hair (Hedges' g: 3.42, 95% CI: 1.96, 8.80, p > 0.05), and urinary (Hedges' g: 0.49, 95% CI: 1.29 - 0.30, p > 0.05) Hg concentrations. The results demonstrated no significant differences in Hg and Cd concentrations in different biological samples of children with ASD compared to control subjects.

Brain glutathione and GABA+ levels in autistic children

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a cohort of children aged 8-12 years with ASD (n = 52) and typically developing children (TDC, n = 49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

Identification of Immune Infiltration and Iron Metabolism-Related Subgroups in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with a broad spectrum of symptoms and prognoses. Effective therapy requires understanding this variability. ASD children's cognitive and immunological development may depend on iron homoeostasis. This study employs a machine learning model that focuses on iron metabolism hub genes to identify ASD subgroups and describe immune infiltration patterns. A total of 97 control and 148 ASD samples were obtained from the GEO database. Differentially expressed genes (DEGs) and an iron metabolism gene collection achieved the intersection of 25 genes. Unsupervised cluster analysis determined molecular subgroups in individuals with ASD based on 25 genes related to iron metabolism. We assessed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, gene set variation analysis (GSVA), and immune infiltration analysis to compare iron metabolism subtype effects. We employed machine learning to identify subtype-predicting hub genes and utilized both training and validation sets to assess gene subtype prediction accuracy. ASD can be classified into two iron-metabolizing molecular clusters. Metabolic enrichment pathways differed between clusters. Immune infiltration showed that clusters differed immunologically. Cluster 2 had better immunological scores and more immune cells, indicating a stronger immune response. Machine learning screening identified SELENBP1 and CAND1 as important genes in ASD's iron metabolism signaling pathway. These genes express in the brain and have AUC values over 0.8, implying significant predictive power. The present study introduces iron metabolism signaling pathway indicators to predict ASD subtypes. ASD is linked to immune cell infiltration and iron metabolism disorders.

Metabolomics and transcriptomics analysis of prefrontal cortex in the Pax2 neuron-specific deletion mice

Restricted and repetitive behaviors (RRBs) are one of the characteristics of various neuropsychiatric disorders with complex and diverse molecular mechanisms. Repetitive self-grooming behavior is one of the manifestations of RRBs in humans and rodents. Research on the neural mechanism of repetitive self-grooming behavior is expected to reveal the underlying logic of the occurrence of RRBs. Pax2 is an important member of the paired-box transcription factor family. It is expressed in different regions of the developing central nervous system. Our previous study showed that Pax2 heterozygous gene knockout mice (Pax2+/- KO mice) exhibit significantly increased self-grooming, which suggests that the Pax2 gene is involved in the control of self-grooming behavior, but the molecular mechanism is still unclear. In this study, we further constructed the Pax2 neuron-specific deletion mice (Nestin-Pax2 mice). Targeted metabolomics and transcriptomics techniques was used to analyze. The results showed that there is an excitatory/inhibitory imbalance of the neurotransmitter system and the Arc gene was significantly up-regulated in the prefrontal cortex (PFC) of Nestin-Pax2 mice. This study suggests that the potential regulatory mechanism of the increased repetitive self-grooming behavior in Pax2 gene deletion mice is that the deletion of the Pax2 gene affects the expression of Arc in the PFC, leading to impaired synaptic plasticity and excitatory/inhibitory imbalance, and participating in the occurrence of repetitive self-grooming behavior.

Transcriptome Analysis and Epigenetics Regulation in the Hippocampus and the Prefrontal Cortex of VPA-Induced Rat Model

Autism spectrum disorders (ASD) are a highly heterogeneous group of neurodevelopmental disorders caused by complex interaction between various genes and environmental factors. As the hippocampus and prefrontal cortex are involved in social recognition, they are the regions of the brain implicated in autism. The effects of prenatal exposure to valproic acid (VPA) can induce an ASD phenotype in both humans and rats; this tool is commonly used to model the complexity of ASD symptoms in the laboratory. However, researchers rarely undertake epigenetic regulation of the brain regions using this model. The present study has addressed this gap by examining gene expression abnormalities in the hippocampus and prefrontal cortex in the VPA rat model of ASD. mRNA and miRNA sequencing was performed on samples from the hippocampus and prefrontal cortex of the VPA model of autism. According to the analysis, 3000 mRNAs in the hippocampus and 2187 mRNAs in the prefrontal cortex showed a significant difference in expression between the VPA and saline groups. In addition, there were 115 DE miRNAs in the hippocampus and 14 DE miRNAs in the prefrontal cortex. Further, the predicted and validated target mRNA of DE miRNA enriched pathways involved neurotransmitter uptake, long-term synaptic depression, and AMPA receptor complex (anti-GluA2-b) in the hippocampus; as well as the neuroactive ligand-receptor interaction and regulation of postsynaptic membrane potential in the prefrontal cortex. This revealed the negative regulation network of miRNAs-mRNAs in the hippocampus and prefrontal cortex, while filtering out key genes (miR-10a-5p and Grm3). Finally, the significant variable miR-10a-5p and its negative regulated genes (Grm3) were verified in both brain regions by QPCR. Importantly, the fact that miR-10a-5p downregulated Grm3 in both the hippocampus and the prefrontal cortex may play a potentially significant role in the occurrence and development of autism. This study suggests that the VPA model has the potential to reproduce ASD-related hippocampus and prefrontal cortex abnormalities, at the epigenetic and transcriptional levels. Furthermore, the network of miRNAs-mRNAs was confirmed; this negative regulatory relationship may play a key role in determining the occurrence and development of autism. The study of this topic help better understand the pathogenesis of ASD.

Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.