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      The molecular basis of p21-activated kinase-associated neurodevelopmental disorders: From genotype to phenotype

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          Abstract

          Although the identification of numerous genes involved in neurodevelopmental disorders (NDDs) has reshaped our understanding of their etiology, there are still major obstacles in the way of developing therapeutic solutions for intellectual disability (ID) and other NDDs. These include extensive clinical and genetic heterogeneity, rarity of recurrent pathogenic variants, and comorbidity with other psychiatric traits. Moreover, a large intragenic mutational landscape is at play in some NDDs, leading to a broad range of clinical symptoms. Such diversity of symptoms is due to the different effects DNA variations have on protein functions and their impacts on downstream biological processes. The type of functional alterations, such as loss or gain of function, and interference with signaling pathways, has yet to be correlated with clinical symptoms for most genes. This review aims at discussing our current understanding of how the molecular changes of group I p21-activated kinases ( PAK1, 2 and 3), which are essential actors of brain development and function; contribute to a broad clinical spectrum of NDDs. Identifying differences in PAK structure, regulation and spatio-temporal expression may help understanding the specific functions of each group I PAK. Deciphering how each variation type affects these parameters will help uncover the mechanisms underlying mutation pathogenicity. This is a prerequisite for the development of personalized therapeutic approaches.

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          Most cited references231

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          An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex.

          The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function. To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex. We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type. Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain. For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycolytic enzyme pyruvate kinase. This dataset will provide a powerful new resource for understanding the development and function of the brain. To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://web.stanford.edu/group/barres_lab/brain_rnaseq.html) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain. Copyright © 2014 the authors 0270-6474/14/3411929-19$15.00/0.
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            The contribution of de novo coding mutations to autism spectrum disorder.

            Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.
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              Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci.

              Analysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1).
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                02 March 2023
                2023
                : 17
                : 1123784
                Affiliations
                [1] 1Institut des Neurosciences Paris-Saclay, UMR 9197, CNRS, Université Paris-Saclay , Saclay, France
                [2] 2Department of Genetics, EA7450 BioTARGen, University Hospital of Caen , Caen, France
                [3] 3Department of Genetics, University Hospital of Tours, UMR 1253, iBrain, Université de Tours, INSERM , Tours, France
                Author notes

                Edited by: Barbara Bardoni, UMR 7275 Institut de Pharmacologie Moléculaire et Cellulaire (IPMC), France

                Reviewed by: Maria Giuseppina Miano, Institute of Genetics and Biophysics Adriano Buzzati-Traverso (CNR), Italy; Sangeeta Nath, Manipal Academy of Higher Education, India; Curtis Benson, Yale University, United States

                *Correspondence: Jean-Vianney Barnier, jean-vianney.barnier@ 123456universite-paris-saclay.fr

                This article was submitted to Neurodevelopment, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2023.1123784
                10017488
                36937657
                804f8c08-41f8-4337-aeba-cc989f86594d
                Copyright © 2023 Dobrigna, Poëa-Guyon, Rousseau, Vincent, Toutain and Barnier.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 December 2022
                : 13 February 2023
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 233, Pages: 21, Words: 19259
                Funding
                This research was funded by the Centre National de la Recherche Scientifique (CNRS) and the Université Paris-Saclay and grants from Agence National de la Recherche (ANR) ANR-21-CE17-0053 ID-GePhe-PAK and from the Fondation Jérôme Lejeune 2022-#2160.
                Categories
                Neuroscience
                Review

                Neurosciences
                intellectual disability,autism spectrum disorder (asd),neurodevelopmental disorders,genotype/phenotype correlation,p21-activated kinase,mutations

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