Cortical Overgrowth in a Preclinical Forebrain Organoid Model of CNTNAP2-Associated Autism Spectrum Disorder
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA730556 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14570244.fastq.gz | Fastqsanger.gz | |||
| SRR14570245.fastq.gz | Fastqsanger.gz | |||
| SRR14570246.fastq.gz | Fastqsanger.gz | |||
| SRR14570247.fastq.gz | Fastqsanger.gz | |||
| SRR14570248.fastq.gz | Fastqsanger.gz |
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Project description:We utilized forebrain organoids generated from induced pluripotent stem cells of patients with a syndromic form of Autism Spectrum Disorder (ASD) with a homozygous protein-truncating mutation in CNTNAP2, to study its effects on embryonic cortical development. Patients with this mutation present with clinical characteristics of brain overgrowth. Patient-derived forebrain organoids displayed an increase in volume and total cell number that is driven by increased neural progenitor proliferation. Single-cell RNA sequencing revealed PFC-excitatory neurons to be the key cell types expressing CNTNAP2. Gene ontology analysis of differentially expressed genes (DEgenes) corroborates aberrant cellular proliferation. Moreover, the DEgenes are enriched for ASD-associated genes. The cell-type-specific signature genes of the CNTNAP2-expressing neurons are associated with clinical phenotypes previously described in patients. The organoid overgrowth phenotypes were largely rescued after correction of the mutation using CRISPR-Cas9. This CNTNAP2-organoid model provides opportunity for further mechanistic inquiry and development of new therapeutic strategies for ASD.
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Project description:Autism Spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder where patients have impaired social behavior and communication, and restricted interests. Although various studies have been carried out to unveil the mechanisms associated with ASD, its pathophysiology is still poorly understood. Genetic variants on CNTNAP2 have been found and considered representative ASD genetic risk factors, and disruption of Cntnap2 causes ASD phenotypes in mice. Here, we performed an integrative multi-omics analysis by combining quantitative proteometabolomics data of Cntnap2 knockout (KO) mice with multi-omics data from ASD patients and forebrain organoids to elucidate Cntnap2-dependent molecular networks of ASD. First, we found Cntnap2-associated molecular signatures and cellular processes by conducting mass spectrometry-based proteometabolomic analysis of the medial prefrontal cortex of the Cntnap2 KO mouse model. Then, we narrowed these identified processes into bona fide ASD molecular processes by incorporating multi-omics data of ASD patients' prefrontal cortex. Further, we mapped cell-type-specific ASD networks by reanalyzing single-cell RNA-seq data of forebrain organoids derived from patients with CNTNAP2 mutation. Finally, we constructed a Cntnap2-associated ASD network model consisting of mitochondrial dysfunction, axonal impairment, and synaptic activity. Our results may shed light on understanding of the Cntnap2-dependent molecular networks of ASD.
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Project description:Interneurons are fundamental cells for maintaining the excitation-inhibition balance in the brain in health and disease. While interneurons have been shown to play a key role in the pathophysiology of autism spectrum disorder (ASD) in adult mice, little is known about how their maturation is altered in the developing striatum in ASD. Here, we aimed to track striatal developing interneurons and elucidate the molecular and physiological alterations in the Cntnap2 knockout mouse model. Using Stereo-seq and single-cell RNA sequencing data, we first characterized the pattern of expression of Cntnap2 in the adult brain and at embryonic stages in the medial ganglionic eminence (MGE), a transitory structure producing most cortical and striatal interneurons. We found that Cntnap2 is enriched in the striatum, compared to the cortex, particularly in the developing striatal cholinergic interneurons. We then revealed enhanced MGE-derived cell proliferation, followed by increased cell loss during the canonical window of developmental cell death in the Cntnap2 knockout mice. We uncovered specific cellular and molecular alterations in the developing Lhx6-expressing cholinergic interneurons of the striatum, which impacts interneuron firing properties during the first postnatal week. Overall, our work unveils some of the mechanisms underlying the shift in the developmental trajectory of striatal interneurons which greatly contribute to the ASD pathogenesis.
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Project description:To assess the clinical impact of splice-altering noncoding mutations in autism spectrum disorder (ASD), we used a deep learning framework (SpliceAI) to predict the splice-altering potential of de novo mutations in 3,953 individuals with ASD from the Simons Simplex Collection. To validate these predictions, we selected 36 individuals that harbored predicted de-novo cryptic splice mutations; each individual represented the only case of autism within their immediate family. We obtained peripheral blood-derived lymphoblastoid cell lines (LCLs) and performed high-depth mRNA sequencing (approximately 350 million 150 bp single-end reads per sample). We used OLego to align the reads against a reference created from hg19 by substituting de novo variants of each individual with the corresponding alternate allele.
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Project description:BackgroundComorbidity of Autism Spectrum Disorders with seizures or abnormal EEG (Autism-Epilepsy Phenotype) suggests shared pathomechanisms, and might be a starting point to identify distinct populations within the clinical complexity of the autistic spectrum. In this study, we tried to assess whether distinct subgroups, having distinctive clinical hallmarks, emerge from this comorbid condition.MethodsTwo-hundred and six individuals with idiopathic Autism Spectrum Disorders were subgrouped into three experimental classes depending on the presence of seizures and EEG abnormalities. Neurobehavioral, electroclinical and auxological parameters were investigated to identify differences among groups and features which increase the risk of seizures. Our statistical analyses used ANOVA, post-hoc multiple comparisons, and the Chi-squared test to analyze continuous and categorical variables. A correspondence analysis was also used to decompose significant Chi-squared and reduce variables dimensions.ResultsThe high percentage of children with seizures (28.2% of our whole cohort) and EEG abnormalities (64.1%) confirmed that the prevalence of epilepsy in Autism Spectrum Disorders exceeds that of the general population. Seizures were associated with severe intellectual disability, and not with autism severity. Interestingly, tall stature (without macrocephaly) was significantly associated with EEG abnormalities or later onset seizures. However, isolated macrocephaly was equally distributed among groups or associated with early onset seizures when accompanied by tall stature.ConclusionsTall stature seems to be a phenotypic "biomarker" of susceptibility to EEG abnormalities or late epilepsy in Autism Spectrum Disorders and, when concurring with macrocephaly, predisposes to early onset seizures. Growth pattern might act as an endophenotypic marker in Autism-Epilepsy comorbidity, delineating distinct pathophysiological subtypes and addressing personalized diagnostic work-up and therapeutic approaches.
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