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3 recherche sur le mot-clé 'genetic variation'
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A systematic variant annotation approach for ranking genes associated with autism spectrum disorders / E. LARSEN in Molecular Autism, 7 (2016)
[article]
Titre : A systematic variant annotation approach for ranking genes associated with autism spectrum disorders Type de document : Texte imprimé et/ou numérique Auteurs : E. LARSEN, Auteur ; I. MENASHE, Auteur ; M. N. ZIATS, Auteur ; W. PEREANU, Auteur ; A. PACKER, Auteur ; Sharmila BANERJEE-BASU, Auteur Article en page(s) : 44p. Langues : Anglais (eng) Mots-clés : Algorithms Autism Spectrum Disorder/genetics/physiopathology DNA-Binding Proteins/genetics Databases, Genetic Datasets as Topic Gene Expression Genetic Predisposition to Disease Genetic Variation Homeodomain Proteins/genetics Humans Molecular Sequence Annotation Nerve Tissue Proteins/genetics Research Design Transcription Factors/genetics Autistic disorder Autosomal recessive Common variants Genetic variation Rare variants Index. décimale : PER Périodiques Résumé : BACKGROUND: The search for genetic factors underlying autism spectrum disorders (ASD) has led to the identification of hundreds of genes containing thousands of variants that differ in mode of inheritance, effect size, frequency, and function. A major challenge involves assessing the collective evidence in an unbiased, systematic manner for their functional relevance. METHODS: Here, we describe a scoring algorithm for prioritization of candidate genes based on the cumulative strength of evidence for each ASD-associated variant cataloged in AutDB (also known as SFARI Gene). We retrieved data from 889 publications to generate a dataset of 2187 rare and 711 common variants distributed across 461 genes implicated in ASD. Each individual variant was manually annotated with multiple attributes extracted from the original report, followed by score assignment using a set of standardized parameters yielding a single score for each gene. RESULTS: There was a wide variation in scores; SHANK3, CHD8, and ADNP had distinctly higher scores than all other genes in the dataset. Our gene scores were significantly correlated with other recently published rankings of ASD genes (RSpearman = 0.40-0.63; p< 0.0001), providing support for our scoring algorithm. CONCLUSIONS: This new resource, which is freely available, for the first time aggregates on one-platform variants identified from various study types (simplex, multiplex, multigenerational, and consanguineous families), from both common and rare variants, and also incorporates their putative functional consequences to arrive at a genetically and biologically driven ranking scheme. This work represents a major step in moving from simply cataloging autism variants to using data-driven approaches to gain insight into their significance. En ligne : http://dx.doi.org/10.1186/s13229-016-0103-y Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=328
in Molecular Autism > 7 (2016) . - 44p.[article] A systematic variant annotation approach for ranking genes associated with autism spectrum disorders [Texte imprimé et/ou numérique] / E. LARSEN, Auteur ; I. MENASHE, Auteur ; M. N. ZIATS, Auteur ; W. PEREANU, Auteur ; A. PACKER, Auteur ; Sharmila BANERJEE-BASU, Auteur . - 44p.
Langues : Anglais (eng)
in Molecular Autism > 7 (2016) . - 44p.
Mots-clés : Algorithms Autism Spectrum Disorder/genetics/physiopathology DNA-Binding Proteins/genetics Databases, Genetic Datasets as Topic Gene Expression Genetic Predisposition to Disease Genetic Variation Homeodomain Proteins/genetics Humans Molecular Sequence Annotation Nerve Tissue Proteins/genetics Research Design Transcription Factors/genetics Autistic disorder Autosomal recessive Common variants Genetic variation Rare variants Index. décimale : PER Périodiques Résumé : BACKGROUND: The search for genetic factors underlying autism spectrum disorders (ASD) has led to the identification of hundreds of genes containing thousands of variants that differ in mode of inheritance, effect size, frequency, and function. A major challenge involves assessing the collective evidence in an unbiased, systematic manner for their functional relevance. METHODS: Here, we describe a scoring algorithm for prioritization of candidate genes based on the cumulative strength of evidence for each ASD-associated variant cataloged in AutDB (also known as SFARI Gene). We retrieved data from 889 publications to generate a dataset of 2187 rare and 711 common variants distributed across 461 genes implicated in ASD. Each individual variant was manually annotated with multiple attributes extracted from the original report, followed by score assignment using a set of standardized parameters yielding a single score for each gene. RESULTS: There was a wide variation in scores; SHANK3, CHD8, and ADNP had distinctly higher scores than all other genes in the dataset. Our gene scores were significantly correlated with other recently published rankings of ASD genes (RSpearman = 0.40-0.63; p< 0.0001), providing support for our scoring algorithm. CONCLUSIONS: This new resource, which is freely available, for the first time aggregates on one-platform variants identified from various study types (simplex, multiplex, multigenerational, and consanguineous families), from both common and rare variants, and also incorporates their putative functional consequences to arrive at a genetically and biologically driven ranking scheme. This work represents a major step in moving from simply cataloging autism variants to using data-driven approaches to gain insight into their significance. En ligne : http://dx.doi.org/10.1186/s13229-016-0103-y Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=328 Identification of likely associations between cerebral folate deficiency and complex genetic- and metabolic pathogenesis of autism spectrum disorders by utilization of a pilot interaction modeling approach / Daniel KRSI?KA in Autism Research, 10-8 (August 2017)
[article]
Titre : Identification of likely associations between cerebral folate deficiency and complex genetic- and metabolic pathogenesis of autism spectrum disorders by utilization of a pilot interaction modeling approach Type de document : Texte imprimé et/ou numérique Auteurs : Daniel KRSI?KA, Auteur ; Jan GERYK, Auteur ; Markéta VL?KOVÁ, Auteur ; Marketa HAVLOVICOVA, Auteur ; Milan MACEK, Auteur ; Radka POUROVÁ, Auteur Article en page(s) : p.1424-1435 Langues : Anglais (eng) Mots-clés : autism spectrum disorders cerebral folate deficiency knowledge databases folate genetic variation interaction modeling metabolic pathways Index. décimale : PER Périodiques Résumé : Recently, cerebral folate deficiency (CFD) was suggested to be involved in the pathogenesis of autism spectrum disorders (ASD). However, the exact role of folate metabolism in the pathogenesis of ASD, identification of underlying pathogenic mechanisms and impaired metabolic pathways remain unexplained. The aim of our study was to develop and test a novel, unbiased, bioinformatics approach in order to identify links between ASD and disturbed cerebral metabolism by focusing on abnormal folate metabolism, which could foster patient stratification and novel therapeutic interventions. An unbiased, automatable, computational workflow interaction model was developed using available data from public databases. The interaction network model of ASD-associated genes with known cerebral expression and function (SFARI) and metabolic networks (MetScape), including connections to known metabolic substrates, metabolites and cofactors involving folates, was established. Intersection of bioinformatically created networks resulted in a limited amount of interaction modules pointing to common disturbed metabolic pathways, linking ASD to CFD. Two independent interaction modules (comprising three pathways) covering enzymes encoded by ASD-related genes and folate cofactors utilizing enzymes were generated. Module 1 suggested possible interference of CFD with serine and lysine metabolism, while module 2 identified correlations with purine metabolism and inosine monophosphate production. Since our approach was primarily conceived as a proof of principle, further amendments of the presented initial model are necessary to obtain additional actionable outcomes. Our modelling strategy identified not only previously known interactions supported by evidence-based analyses, but also novel plausible interactions, which could be validated in subsequent functional and/or clinical studies. En ligne : http://dx.doi.org/10.1002/aur.1780 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=310
in Autism Research > 10-8 (August 2017) . - p.1424-1435[article] Identification of likely associations between cerebral folate deficiency and complex genetic- and metabolic pathogenesis of autism spectrum disorders by utilization of a pilot interaction modeling approach [Texte imprimé et/ou numérique] / Daniel KRSI?KA, Auteur ; Jan GERYK, Auteur ; Markéta VL?KOVÁ, Auteur ; Marketa HAVLOVICOVA, Auteur ; Milan MACEK, Auteur ; Radka POUROVÁ, Auteur . - p.1424-1435.
Langues : Anglais (eng)
in Autism Research > 10-8 (August 2017) . - p.1424-1435
Mots-clés : autism spectrum disorders cerebral folate deficiency knowledge databases folate genetic variation interaction modeling metabolic pathways Index. décimale : PER Périodiques Résumé : Recently, cerebral folate deficiency (CFD) was suggested to be involved in the pathogenesis of autism spectrum disorders (ASD). However, the exact role of folate metabolism in the pathogenesis of ASD, identification of underlying pathogenic mechanisms and impaired metabolic pathways remain unexplained. The aim of our study was to develop and test a novel, unbiased, bioinformatics approach in order to identify links between ASD and disturbed cerebral metabolism by focusing on abnormal folate metabolism, which could foster patient stratification and novel therapeutic interventions. An unbiased, automatable, computational workflow interaction model was developed using available data from public databases. The interaction network model of ASD-associated genes with known cerebral expression and function (SFARI) and metabolic networks (MetScape), including connections to known metabolic substrates, metabolites and cofactors involving folates, was established. Intersection of bioinformatically created networks resulted in a limited amount of interaction modules pointing to common disturbed metabolic pathways, linking ASD to CFD. Two independent interaction modules (comprising three pathways) covering enzymes encoded by ASD-related genes and folate cofactors utilizing enzymes were generated. Module 1 suggested possible interference of CFD with serine and lysine metabolism, while module 2 identified correlations with purine metabolism and inosine monophosphate production. Since our approach was primarily conceived as a proof of principle, further amendments of the presented initial model are necessary to obtain additional actionable outcomes. Our modelling strategy identified not only previously known interactions supported by evidence-based analyses, but also novel plausible interactions, which could be validated in subsequent functional and/or clinical studies. En ligne : http://dx.doi.org/10.1002/aur.1780 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=310 MicroRNAs as biomarkers for psychiatric disorders with a focus on autism spectrum disorder: Current progress in genetic association studies, expression profiling, and translational research / Yubin HU in Autism Research, 10-7 (July 2017)
[article]
Titre : MicroRNAs as biomarkers for psychiatric disorders with a focus on autism spectrum disorder: Current progress in genetic association studies, expression profiling, and translational research Type de document : Texte imprimé et/ou numérique Auteurs : Yubin HU, Auteur ; Erik A. EHLI, Auteur ; Dorret I. BOOMSMA, Auteur Article en page(s) : p.1184-1203 Langues : Anglais (eng) Mots-clés : microRNA miRNA psychiatric disorders autism spectrum disorder biomarkers genetic variation expression profiling animal studies Index. décimale : PER Périodiques Résumé : MicroRNAs (miRNAs) are a group of small noncoding RNA molecules, 18–25 nucleotides in length, which can negatively regulate gene expression at the post-transcriptional level by binding to messenger RNAs. About half of all identified miRNAs in humans are expressed in the brain and display regulatory functions important for many biological processes related to the development of the central nervous system (CNS). Disruptions in miRNA biogenesis and miRNA-target interaction have been related to CNS diseases, including psychiatric disorders. In this review, we focus on the role of miRNAs in autism spectrum disorder (ASD) and summarize recent findings about ASD-associated genetic variants in miRNA genes, in miRNA biogenesis genes, and miRNA targets. We discuss deregulation of miRNA expression in ASD and functional validation of ASD-related miRNAs in animal models. Including miRNAs in studies of ASD will contribute to our understanding of its etiology and pathogenesis and facilitate the discrimination between different disease subgroups. En ligne : http://dx.doi.org/10.1002/aur.1789 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=309
in Autism Research > 10-7 (July 2017) . - p.1184-1203[article] MicroRNAs as biomarkers for psychiatric disorders with a focus on autism spectrum disorder: Current progress in genetic association studies, expression profiling, and translational research [Texte imprimé et/ou numérique] / Yubin HU, Auteur ; Erik A. EHLI, Auteur ; Dorret I. BOOMSMA, Auteur . - p.1184-1203.
Langues : Anglais (eng)
in Autism Research > 10-7 (July 2017) . - p.1184-1203
Mots-clés : microRNA miRNA psychiatric disorders autism spectrum disorder biomarkers genetic variation expression profiling animal studies Index. décimale : PER Périodiques Résumé : MicroRNAs (miRNAs) are a group of small noncoding RNA molecules, 18–25 nucleotides in length, which can negatively regulate gene expression at the post-transcriptional level by binding to messenger RNAs. About half of all identified miRNAs in humans are expressed in the brain and display regulatory functions important for many biological processes related to the development of the central nervous system (CNS). Disruptions in miRNA biogenesis and miRNA-target interaction have been related to CNS diseases, including psychiatric disorders. In this review, we focus on the role of miRNAs in autism spectrum disorder (ASD) and summarize recent findings about ASD-associated genetic variants in miRNA genes, in miRNA biogenesis genes, and miRNA targets. We discuss deregulation of miRNA expression in ASD and functional validation of ASD-related miRNAs in animal models. Including miRNAs in studies of ASD will contribute to our understanding of its etiology and pathogenesis and facilitate the discrimination between different disease subgroups. En ligne : http://dx.doi.org/10.1002/aur.1789 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=309