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Multilevel Analysis of Cortical Interneuron Dysfunction in Fragile X Syndrome

Multilevel Analysis of Cortical Interneuron Dysfunction in Fragile X Syndrome
脆性 X 综合征皮质中间神经元功能障碍的多层次分析
批准号:
10570398
负责人:
Edmund Au
金额:
$24.17万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-12-01 至 2024-11-30

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英文摘要
PROJECT SUMMARY: Fragile X Syndrome (FXS) is a common genetic form of intellectual disability that is frequently co-morbid with autism-like clinical features. It is caused by epigenetic silencing of the FMR1 gene, which encodes for the protein FMRP, an RNA binding protein with a strong preference for mRNAs important in synaptic structure and function. Indeed, there are well-documented synaptic defects observed in both human patients and in the mouse model for FXS (Fmr1 knockout). In excitatory pyramidal neurons, these synaptic defects are well-described but much less is known about the remaining 20% of cortical neurons, inhibitory cortical interneurons, in FXS. Since interneuron dysfunction has been implicated in both schizophrenia as well as ASD, they are an appealing cell population to study in the context of FXS. Our Central Hypothesis is that cortical interneurons dysfunction plays an important role in FXS etiology and that interneuron phenotypes can be revealed at the cell type numbers, distribution and synaptic levels. In this proposal, we will conduct a multi-level analysis of interneurons in Fmr1-/- mice using a number of novel approaches that we recently developed. The proposed work is Highly Significant in that interneurons are poorly understood in the context of FXS despite their importance in the etiology of other neurodevelopmental disorders. The work is also Highly Innovative because it brings to bear a number of novel approaches to unearth interneuron phenotypes in FXS: detailed spatial analysis of interneuron distribution and machine learning strategies to examine interneurons synapses at the individual and population level. First, we will use automated seg- mentation and positional registration to study interneuron subtype numbers, layering and cortical distribu- tion in Fmr1-/- and controls. Second, we will employ a novel machine learning pipeline to measure inter- neuron synaptic target specificity in Fmr1 mutant and controls. Third, we will - in a manner similar to single cell RNA-seq principle component analysis - analyze individual synaptic boutons by multidimen- sional spatial feature analysis. This allows us to perform unsupervised cluster analysis of interneuron syn- aptic boutons and reveal population level differences between Fmr1-/- and control synapses. Taken together, our data will shed new light on an understudied cell population – cortical interneurons - in FXS etiology and open new avenues of investigation into synaptic defects underlying FXS and ASD.
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