FoxG1 regulates the formation of cortical GABAergic circuit during an early postnatal critical period resulting in autism spectrum disorder-like phenotypes

AbstractAbnormalities in GABAergic inhibitory circuits have been implicated in the aetiology of autism spectrum disorder (ASD). ASD is caused by genetic and environmental factors. Several genes have been associated with syndromic forms of ASD, including FOXG1. However, when and how dysregulation of FOXG1 can result in defects in inhibitory circuit development and ASD-like social impairments is unclear. Here, we show that increased or decreased FoxG1 expression in both excitatory and inhibitory neurons results in ASD-related circuit and social behavior deficits in our mouse models. We observe that the second postnatal week is the critical period when regulation of FoxG1 expression is required to prevent subsequent ASD-like social impairments. Transplantation of GABAergic precursor cells prior to this critical period and reduction in GABAergic tone via Gad2 mutation ameliorates and exacerbates circuit functionality and social behavioral defects, respectively. Our results provide mechanistic insight into the developmental timing of inhibitory circuit formation underlying ASD-like phenotypes in mouse models.

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Intranasal oxytocin administration ameliorates social behavioral deficits in a POGZWT/Q1038R mouse model of autism spectrum disorder

Molecular Brain ◽

10.1186/s13041-021-00769-8 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Kohei Kitagawa ◽

Kensuke Matsumura ◽

Masayuki Baba ◽

Momoka Kondo ◽

Tomoya Takemoto ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Social Behavior ◽

Mouse Model ◽

Mouse Models ◽

De Novo ◽

Neurodevelopmental Disorder ◽

Autism Spectrum ◽

Spectrum Disorder ◽

De Novo Mutation ◽

Behavioral Deficits

AbstractAutism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by core symptoms of impaired social behavior and communication. Recent studies have suggested that the oxytocin system, which regulates social behavior in mammals, is potentially involved in ASD. Mouse models of ASD provide a useful system for understanding the associations between an impaired oxytocin system and social behavior deficits. However, limited studies have shown the involvement of the oxytocin system in the behavioral phenotypes in mouse models of ASD. We have previously demonstrated that a mouse model that carries the ASD patient-derived de novo mutation in the pogo transposable element derived with zinc finger domain (POGZWT/Q1038R mice), showed ASD-like social behavioral deficits. Here, we have explored whether oxytocin (OXT) administration improves impaired social behavior in POGZWT/Q1038R mice and found that intranasal oxytocin administration effectively restored the impaired social behavior in POGZWT/Q1038R mice. We also found that the expression level of the oxytocin receptor gene (OXTR) was low in POGZWT/Q1038R mice. However, we did not detect significant changes in the number of OXT-expressing neurons between the paraventricular nucleus of POGZWT/Q1038R mice and that of WT mice. A chromatin immunoprecipitation assay revealed that POGZ binds to the promoter region of OXTR and is involved in the transcriptional regulation of OXTR. In summary, our study demonstrate that the pathogenic mutation in the POGZ, a high-confidence ASD gene, impairs the oxytocin system and social behavior in mice, providing insights into the development of oxytocin-based therapeutics for ASD.

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A novel automated autism spectrum disorder detection system

Complex & Intelligent Systems ◽

10.1007/s40747-021-00408-8 ◽

2021 ◽

Author(s):

Shu Lih Oh ◽

V. Jahmunah ◽

N. Arunkumar ◽

Enas W. Abdulhay ◽

Raj Gururajan ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Developmental Disorder ◽

Detection System ◽

Brain Activity ◽

Limited Range ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Nonlinear Features ◽

Genetic And Environmental Factors ◽

Future Work

AbstractAutism spectrum disorder (ASD) is a neurological and developmental disorder that begins early in childhood and lasts throughout a person’s life. Autism is influenced by both genetic and environmental factors. Lack of social interaction, communication problems, and a limited range of behaviors and interests are possible characteristics of autism in children, alongside other symptoms. Electroencephalograms provide useful information about changes in brain activity and hence are efficaciously used for diagnosis of neurological disease. Eighteen nonlinear features were extracted from EEG signals of 40 children with a diagnosis of autism spectrum disorder and 37 children with no diagnosis of neuro developmental disorder children. Feature selection was performed using Student’s t test, and Marginal Fisher Analysis was employed for data reduction. The features were ranked according to Student’s t test. The three most significant features were used to develop the autism index, while the ranked feature set was input to SVM polynomials 1, 2, and 3 for classification. The SVM polynomial 2 yielded the highest classification accuracy of 98.70% with 20 features. The developed classification system is likely to aid healthcare professionals as a diagnostic tool to detect autism. With more data, in our future work, we intend to employ deep learning models and to explore a cloud-based detection system for the detection of autism. Our study is novel, as we have analyzed all nonlinear features, and we are one of the first groups to have uniquely developed an autism (ASD) index using the extracted features.

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