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

Roles of AMPA receptors in social behaviors

As a crucial player in excitatory synaptic transmission, AMPA receptors (AMPARs) contribute to the formation, regulation, and expression of social behaviors. AMPAR modifications have been associated with naturalistic social behaviors, such as aggression, sociability, and social memory, but are also noted in brain diseases featuring impaired social behavior. Understanding the role of AMPARs in social behaviors is timely to reveal therapeutic targets for treating social impairment in disorders, such as autism spectrum disorder and schizophrenia. In this review, we will discuss the contribution of the molecular composition, function, and plasticity of AMPARs to social behaviors. The impact of targeting AMPARs in treating brain disorders will also be discussed.

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.

Understanding the role of AMPA receptors in autism: insights from circuit and synapse dysfunction

Autism spectrum disorders represent a diverse etiological spectrum that converge on a syndrome characterized by discrepant deficits in developmental domains often highlighted by concerns in socialization, sensory integration, and autonomic functioning. Importantly, the incidence and prevalence of autism spectrum disorders have seen sharp increases since the syndrome was first described in the 1940s. The wide etiological spectrum and rising number of individuals being diagnosed with the condition lend urgency to capturing a more nuanced understanding of the pathogenic mechanisms underlying the autism spectrum disorders. The current review seeks to understand how the disruption of AMPA receptor (AMPAr)-mediated neurotransmission in the cerebro-cerebellar circuit, particularly in genetic autism related to SHANK3 or SYNGAP1 protein dysfunction function and autism associated with in utero exposure to the anti-seizure medications valproic acid and topiramate, may contribute to the disease presentation. Initially, a discussion contextualizing AMPAr signaling in the cerebro-cerebellar circuitry and microstructural circuit considerations is offered. Subsequently, a detailed review of the literature implicating mutations or deletions of SHANK3 and SYNGAP1 in disrupted AMPAr signaling reveals how bidirectional pathogenic modulation of this key circuit may contribute to autism. Finally, how pharmacological exposure may interact with this pathway, via increased risk of autism diagnosis with valproic acid and topiramate exposure and potential treatment of autism using AMPAr modulator perampanel, is discussed. Through the lens of the review, we will offer speculation on how neuromodulation may be used as a rational adjunct to therapy. Together, the present review seeks to synthesize the disparate considerations of circuit understanding, genetic etiology, and pharmacological modulation to understand the mechanistic interaction of this important and 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.