An atlas of genetic correlations between gestational age and common psychiatric disorders / Yao YAO in Autism Research, 15-6 (June 2022)  

Public ISBD [article]  inAutism Research > 15-6 (June 2022) . - p.1008-1017 Titre : An atlas of genetic correlations between gestational age and common psychiatric disorders Type de document : texte imprimé Auteurs : Yao YAO, Auteur ; Chun'e LI, Auteur ; Peilin MENG, Auteur ; Bolun CHENG, Auteur ; Shiqiang CHENG, Auteur ; Li LIU, Auteur ; Xuena YANG, Auteur ; Yumeng JIA, Auteur ; Yan WEN, Auteur ; Feng ZHANG, Auteur Article en page(s) : p.1008-1017 Langues : Anglais (eng) Mots-clés : Attention Deficit Disorder with Hyperactivity/genetics  Autism Spectrum Disorder/genetics  Depressive Disorder, Major/genetics  Female  Genetic Predisposition to Disease  Genome-Wide Association Study  Gestational Age  Humans  Infant, Newborn  Mendelian Randomization Analysis  Premature Birth/genetics  Proteomics  genetic correlation  linkage disequilibrium score regression  psychiatric disorders Index. décimale : PER Périodiques Résumé : We aim to systematically explore the potential genetic correlations between five major psychiatric disorders and gestational ages. Genome-wide association study (GWAS) summary datasets of attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) in discovery were downloaded from the Psychiatric GWAS Consortium (PGC) website. Suggestive (Raw p?< 0.05) genetic associations in the discovery phrase were further replicated in independent GWASs which downloaded from PGC, the FinnGen study or Integrative Psychiatric Research (iPSYCH) website. GWASs of gestational duration, preterm and post-term birth were derived from previous studies of infants from the Early Growth Genetics (EGG) Consortium, the iPSYCH study, and the Genomic and Proteomic Network for Preterm Birth Research (GPN). We calculated genetic correlations using linkage disequilibrium score (LDSC) regression. Mendelian randomization (MR) analyses were performed to investigate the causal effects. We identified four suggestive genetic correlations between psychiatric disorders and gestational age factors in discovery LDSC and two replicated in a confirmation LDSC: gestational duration and ADHD (r(g) = -0.1405, FDR p = 0.0406), post-term birth and SCZ (r(g) = -0.2003, FDR p = 0.0042). We also observed causal effect of post-term birth on SCZ by MR (P(Weighted median) = 0.037, P(Inverse variance weighted) = 0.007). Our analysis suggested no significant evidence of horizontal pleiotropy and heterogeneity. This study showed the genetic correlation evidences between gestational age phenotypes and psychiatric disorders, providing novel clues for understanding the pathogenic factors of common psychiatric disorders. LAY SUMMARY: Whereas gestational age factors were reported to be associated with psychiatric disorders, the genetic relationship and causality remain to be revealed. The present study reported the first large-scale genetic correlations investigation of the associations between gestational age phenotypes and psychiatric disorders. Results indicate causal relationships between post-term birth and schizophrenia (SCZ), as well as suggestive genetic correlations between gestational duration and attention deficit/hyperactivity disorder (ADHD). This study provided novel clues for understanding the pathogenic factors of common psychiatric disorders. En ligne : http://dx.doi.org/10.1002/aur.2719 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=476 [article] An atlas of genetic correlations between gestational age and common psychiatric disorders [texte imprimé] / Yao YAO, Auteur ; Chun'e LI, Auteur ; Peilin MENG, Auteur ; Bolun CHENG, Auteur ; Shiqiang CHENG, Auteur ; Li LIU, Auteur ; Xuena YANG, Auteur ; Yumeng JIA, Auteur ; Yan WEN, Auteur ; Feng ZHANG, Auteur . - p.1008-1017. Langues : Anglais (eng) in Autism Research > 15-6 (June 2022) . - p.1008-1017 Mots-clés : Attention Deficit Disorder with Hyperactivity/genetics  Autism Spectrum Disorder/genetics  Depressive Disorder, Major/genetics  Female  Genetic Predisposition to Disease  Genome-Wide Association Study  Gestational Age  Humans  Infant, Newborn  Mendelian Randomization Analysis  Premature Birth/genetics  Proteomics  genetic correlation  linkage disequilibrium score regression  psychiatric disorders Index. décimale : PER Périodiques Résumé : We aim to systematically explore the potential genetic correlations between five major psychiatric disorders and gestational ages. Genome-wide association study (GWAS) summary datasets of attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) in discovery were downloaded from the Psychiatric GWAS Consortium (PGC) website. Suggestive (Raw p?< 0.05) genetic associations in the discovery phrase were further replicated in independent GWASs which downloaded from PGC, the FinnGen study or Integrative Psychiatric Research (iPSYCH) website. GWASs of gestational duration, preterm and post-term birth were derived from previous studies of infants from the Early Growth Genetics (EGG) Consortium, the iPSYCH study, and the Genomic and Proteomic Network for Preterm Birth Research (GPN). We calculated genetic correlations using linkage disequilibrium score (LDSC) regression. Mendelian randomization (MR) analyses were performed to investigate the causal effects. We identified four suggestive genetic correlations between psychiatric disorders and gestational age factors in discovery LDSC and two replicated in a confirmation LDSC: gestational duration and ADHD (r(g) = -0.1405, FDR p = 0.0406), post-term birth and SCZ (r(g) = -0.2003, FDR p = 0.0042). We also observed causal effect of post-term birth on SCZ by MR (P(Weighted median) = 0.037, P(Inverse variance weighted) = 0.007). Our analysis suggested no significant evidence of horizontal pleiotropy and heterogeneity. This study showed the genetic correlation evidences between gestational age phenotypes and psychiatric disorders, providing novel clues for understanding the pathogenic factors of common psychiatric disorders. LAY SUMMARY: Whereas gestational age factors were reported to be associated with psychiatric disorders, the genetic relationship and causality remain to be revealed. The present study reported the first large-scale genetic correlations investigation of the associations between gestational age phenotypes and psychiatric disorders. Results indicate causal relationships between post-term birth and schizophrenia (SCZ), as well as suggestive genetic correlations between gestational duration and attention deficit/hyperactivity disorder (ADHD). This study provided novel clues for understanding the pathogenic factors of common psychiatric disorders. En ligne : http://dx.doi.org/10.1002/aur.2719 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=476

Association Between Maternal Obesity and Autism Spectrum Disorder in Offspring: A Meta-analysis / Ya-Min LI in Journal of Autism and Developmental Disorders, 46-1 (January 2016)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 46-1 (January 2016) . - p.95-102 Titre : Association Between Maternal Obesity and Autism Spectrum Disorder in Offspring: A Meta-analysis Type de document : texte imprimé Auteurs : Ya-Min LI, Auteur ; Jian-Jun OU, Auteur ; Li LIU, Auteur ; Dan ZHANG, Auteur ; Jing-Ping ZHAO, Auteur ; Si-Yuan TANG, Auteur Année de publication : 2016 Article en page(s) : p.95-102 Langues : Anglais (eng) Mots-clés : Obésité maternelle  Maternal obesity  Autism spectrum disorder  Offspring  Meta-analysis Index. décimale : PER Périodiques Résumé : As the link between maternal obesity and risk of autism among offspring is unclear, the present study assessed this association. A systematic search of an electronic database was performed to identify observational studies that examined the association between maternal obesity and autism. The outcome measures were odds ratios comparing offspring autism risk between obese and normal-weight mothers. Five observational studies were included in the meta-analysis. A fixed-effects model was used since low heterogeneity was observed between studies. The pooled adjusted odds ratio was 1.47 (95 % CI 1.24–1.74). The meta-analysis results support an increased risk of autism spectrum disorder in children of women who were obese during pregnancy. However, further study is warranted to confirm these results. En ligne : http://dx.doi.org/10.1007/s10803-015-2549-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=278 [article] Association Between Maternal Obesity and Autism Spectrum Disorder in Offspring: A Meta-analysis [texte imprimé] / Ya-Min LI, Auteur ; Jian-Jun OU, Auteur ; Li LIU, Auteur ; Dan ZHANG, Auteur ; Jing-Ping ZHAO, Auteur ; Si-Yuan TANG, Auteur . - 2016 . - p.95-102. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 46-1 (January 2016) . - p.95-102 Mots-clés : Obésité maternelle  Maternal obesity  Autism spectrum disorder  Offspring  Meta-analysis Index. décimale : PER Périodiques Résumé : As the link between maternal obesity and risk of autism among offspring is unclear, the present study assessed this association. A systematic search of an electronic database was performed to identify observational studies that examined the association between maternal obesity and autism. The outcome measures were odds ratios comparing offspring autism risk between obese and normal-weight mothers. Five observational studies were included in the meta-analysis. A fixed-effects model was used since low heterogeneity was observed between studies. The pooled adjusted odds ratio was 1.47 (95 % CI 1.24–1.74). The meta-analysis results support an increased risk of autism spectrum disorder in children of women who were obese during pregnancy. However, further study is warranted to confirm these results. En ligne : http://dx.doi.org/10.1007/s10803-015-2549-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=278

DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics / Li LIU in Molecular Autism, (March 2014)  

Public ISBD [article]  inMolecular Autism > (March 2014) . - p.1-18 Titre : DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics Type de document : texte imprimé Auteurs : Li LIU, Auteur ; Jing LEI, Auteur ; Stephan J. SANDERS, Auteur ; Arthur Jeremy WILLSEY, Auteur ; Yan KOU, Auteur ; Abdullah Ercument CICEK, Auteur ; Lambertus KLEI, Auteur ; Cong LU, Auteur ; Xin HE, Auteur ; Mingfeng LI, Auteur ; Rebecca A. MUHLE, Auteur ; Avi MA’AYAN, Auteur ; James P. NOONAN, Auteur ; Nenad Å ESTAN, Auteur ; Kathryn MCFADDEN, Auteur ; Matthew W. STATE, Auteur ; Joseph D. BUXBAUM, Auteur ; Bernie DEVLIN, Auteur ; Kathryn ROEDER, Auteur Article en page(s) : p.1-18 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes. En ligne : http://dx.doi.org/10.1186/2040-2392-5-22 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=276 [article] DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics [texte imprimé] / Li LIU, Auteur ; Jing LEI, Auteur ; Stephan J. SANDERS, Auteur ; Arthur Jeremy WILLSEY, Auteur ; Yan KOU, Auteur ; Abdullah Ercument CICEK, Auteur ; Lambertus KLEI, Auteur ; Cong LU, Auteur ; Xin HE, Auteur ; Mingfeng LI, Auteur ; Rebecca A. MUHLE, Auteur ; Avi MA’AYAN, Auteur ; James P. NOONAN, Auteur ; Nenad Å ESTAN, Auteur ; Kathryn MCFADDEN, Auteur ; Matthew W. STATE, Auteur ; Joseph D. BUXBAUM, Auteur ; Bernie DEVLIN, Auteur ; Kathryn ROEDER, Auteur . - p.1-18. Langues : Anglais (eng) in Molecular Autism > (March 2014) . - p.1-18 Index. décimale : PER Périodiques Résumé : De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes. En ligne : http://dx.doi.org/10.1186/2040-2392-5-22 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=276

Genome-wide association study and identification of chromosomal enhancer maps in multiple brain regions related to autism spectrum disorder / Liang ZHANG in Autism Research, 12-1 (January 2019)  

Public ISBD [article]  inAutism Research > 12-1 (January 2019) . - p.26-32 Titre : Genome-wide association study and identification of chromosomal enhancer maps in multiple brain regions related to autism spectrum disorder Type de document : texte imprimé Auteurs : Liang ZHANG, Auteur ; Li LIU, Auteur ; Yan WEN, Auteur ; Mei MA, Auteur ; Shiqiang CHENG, Auteur ; Junhua YANG, Auteur ; Pengli LI, Auteur ; Bastian CHENG, Auteur ; Yanan DU, Auteur ; Xingmei LIANG, Auteur ; Yan ZHAO, Auteur ; Miao DING, Auteur ; Xiaonan GUO, Auteur ; Feng ZHANG, Auteur Année de publication : 2019 Article en page(s) : p.26-32 Langues : Anglais (eng) Mots-clés : autism  biological pathways  brain regions  enhancer Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a complex developmental disorder with strong genetic components involved. Recent studies have demonstrated the importance of non-coding regulatory variants for complex diseases. To explore the roles of chromosomal enhancer regions in the pathogenesis of ASD, we conducted an integrative analysis of genome-wide association study (GWAS) and brain region related enhancer-gene networks for ASD. The GWAS data of ASD were driven from a published study, involving 7,387 ASD cases and 8,567 controls. The enhancer-gene networks of eight brain regions were used here. The GWAS of ASD was first merged respectively with the enhancer datasets of eight brain regions. Pathway enrichment analysis was then performed to detect ASD associated pathways based on the enhancer-related single nucleotide polymorphism (SNPs) of each brain region. We detected multiple genes with brain region specific or common association signals, such as PGM3 (P value = 1.93 x 10(-5) ) and RWDD2A (P value = 1.93 x 10(-5) ) for hippocampus middle, and ENPP4 (all P values <0.05), and ENPP5 (all P values <0.05) for seven brain regions. By comparing the pathway enrichment analysis results of various brain regions, several cross brain regions pathways were detected for ASD, such as REACTOME_POTASSIUM_CHANNELS (all P values <0.05) for six brain regions and KEGG_CELL_ADHESION_MOLECULES_CAMS (all P values <0.05) for seven brain regions. In addition, several pathways were also identified for specific brain regions, such as REACTOME_CD28_DEPENDENT_PI3K_AKT_SIGNALING (P value = 4.00 x 10(-3) ) for angular gyrus, REACTOME_SIGNALING_BY_CONSTITUTIVELY_ACTIVE_EGFR (P value = 2.22 x 10(-3) ) for anterior caudate, and KEGG_PRION_DISEASES (P value = 1.00 x 10(-4) ) for germinal matrix. Our results provide novel clues for understanding the genetic basis of ASD. Autism Research 2019, 12: 26-32. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: ASD is a complex developmental disorder with strong genetic components, but the pathogenesis of ASD is still unclear. Using the latest GWAS data and enhancer map, we explored the brain region related biological pathways associated with ASD. Our results provide novel clues for revealing the functional relevance of enhancer variants with ASD and understanding the genetic basis of ASD. En ligne : http://dx.doi.org/10.1002/aur.2001 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=376 [article] Genome-wide association study and identification of chromosomal enhancer maps in multiple brain regions related to autism spectrum disorder [texte imprimé] / Liang ZHANG, Auteur ; Li LIU, Auteur ; Yan WEN, Auteur ; Mei MA, Auteur ; Shiqiang CHENG, Auteur ; Junhua YANG, Auteur ; Pengli LI, Auteur ; Bastian CHENG, Auteur ; Yanan DU, Auteur ; Xingmei LIANG, Auteur ; Yan ZHAO, Auteur ; Miao DING, Auteur ; Xiaonan GUO, Auteur ; Feng ZHANG, Auteur . - 2019 . - p.26-32. Langues : Anglais (eng) in Autism Research > 12-1 (January 2019) . - p.26-32 Mots-clés : autism  biological pathways  brain regions  enhancer Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a complex developmental disorder with strong genetic components involved. Recent studies have demonstrated the importance of non-coding regulatory variants for complex diseases. To explore the roles of chromosomal enhancer regions in the pathogenesis of ASD, we conducted an integrative analysis of genome-wide association study (GWAS) and brain region related enhancer-gene networks for ASD. The GWAS data of ASD were driven from a published study, involving 7,387 ASD cases and 8,567 controls. The enhancer-gene networks of eight brain regions were used here. The GWAS of ASD was first merged respectively with the enhancer datasets of eight brain regions. Pathway enrichment analysis was then performed to detect ASD associated pathways based on the enhancer-related single nucleotide polymorphism (SNPs) of each brain region. We detected multiple genes with brain region specific or common association signals, such as PGM3 (P value = 1.93 x 10(-5) ) and RWDD2A (P value = 1.93 x 10(-5) ) for hippocampus middle, and ENPP4 (all P values <0.05), and ENPP5 (all P values <0.05) for seven brain regions. By comparing the pathway enrichment analysis results of various brain regions, several cross brain regions pathways were detected for ASD, such as REACTOME_POTASSIUM_CHANNELS (all P values <0.05) for six brain regions and KEGG_CELL_ADHESION_MOLECULES_CAMS (all P values <0.05) for seven brain regions. In addition, several pathways were also identified for specific brain regions, such as REACTOME_CD28_DEPENDENT_PI3K_AKT_SIGNALING (P value = 4.00 x 10(-3) ) for angular gyrus, REACTOME_SIGNALING_BY_CONSTITUTIVELY_ACTIVE_EGFR (P value = 2.22 x 10(-3) ) for anterior caudate, and KEGG_PRION_DISEASES (P value = 1.00 x 10(-4) ) for germinal matrix. Our results provide novel clues for understanding the genetic basis of ASD. Autism Research 2019, 12: 26-32. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: ASD is a complex developmental disorder with strong genetic components, but the pathogenesis of ASD is still unclear. Using the latest GWAS data and enhancer map, we explored the brain region related biological pathways associated with ASD. Our results provide novel clues for revealing the functional relevance of enhancer variants with ASD and understanding the genetic basis of ASD. En ligne : http://dx.doi.org/10.1002/aur.2001 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=376

Integrative analysis of transcriptome-wide association study and mRNA expression profiles identifies candidate genes associated with autism spectrum disorders / Hong HUANG in Autism Research, 12-1 (January 2019)  

Public ISBD [article]  inAutism Research > 12-1 (January 2019) . - p.33-38 Titre : Integrative analysis of transcriptome-wide association study and mRNA expression profiles identifies candidate genes associated with autism spectrum disorders Type de document : texte imprimé Auteurs : Hong HUANG, Auteur ; Shiqiang CHENG, Auteur ; Miao DING, Auteur ; Yan WEN, Auteur ; Mei MA, Auteur ; Liang ZHANG, Auteur ; Pengli LI, Auteur ; Bastian CHENG, Auteur ; Xingmei LIANG, Auteur ; Li LIU, Auteur ; Yanan DU, Auteur ; Yan ZHAO, Auteur ; Om Prakash KAFLE, Auteur ; Bei HAN, Auteur ; Feng ZHANG, Auteur Article en page(s) : p.33-38 Langues : Anglais (eng) Mots-clés : autism spectrum disorders  gene set enrichment analysis  mRNA expression profiles  transcriptome-wide association study Index. décimale : PER Périodiques Résumé : Autism spectrum disorders (ASD) are a group of highly heritable psychiatric syndromes with high prevalence. The genetic mechanism of ASD remains elusive now. Here we conducted a transcriptome-wide association study (TWAS) of ASD. The GWAS summary data of ASD was driven from the Psychiatric Genomics Consortium (PGC) portal, totally involving 5,305 ASD cases and 5,305 controls. FUSION software was applied to the GWAS summary data for tissue-related TWAS of ASD considering brain and blood. The ASD associated genes identified by TWAS were further validated by mRNA expression profiling of ASD and the Simons Foundation for Autism Research (SFARI) Gene tool. DAVID 6.8 was used to perform gene ontology (GO) enrichment analysis of ASD associated genes identified by TWAS. TWAS identified 85 genes with TWAS P value <0.05 for ASD. Further comparing the 85 genes with the differentially expressed genes identified by mRNA expression profiling of ASD patients found 5 overlapped genes, including MUTYH (PTWAS = 0.0460, PmRNA = 0.0040), ARHGAP27 (PTWAS = 0.0100, PmRNA = 0.0016), GCA (PTWAS = 0.0480, PmRNA = 0.0063), CCDC14 (PTWAS = 0.0067, PmRNA = 0.0035), and MED15 (PTWAS = 0.0324, PmRNA = 0.0092). Gene Ontology (GO) enrichment analysis of the genes identified by TWAS detected 10 significant GO terms, such as mitochondrion (P = 0.0051), NAD or NADH binding (P = 0.0169), mitochondrial part (P = 0.0386) and 2-oxoglutarate metabolic process (P = 0.0399). In conclusion, this study identified multiple ASD associated genes and gene sets, providing novel clues for revealing the pathogenesis of ASD. Autism Research 2019, 12: 33-38. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Recent genetic studies of autism spectrum disorders (ASD) have found multiple ASD related genes. However, the results of these studies were hardly replicated with each other, providing limited clues for exploring the genetic mechanism of ASD. This study detected a group of candidate genes showing transcriptome-wide associations with ASD. These results may provide novel clues for revealing the pathogenesis of ASD. En ligne : http://dx.doi.org/10.1002/aur.2048 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=376 [article] Integrative analysis of transcriptome-wide association study and mRNA expression profiles identifies candidate genes associated with autism spectrum disorders [texte imprimé] / Hong HUANG, Auteur ; Shiqiang CHENG, Auteur ; Miao DING, Auteur ; Yan WEN, Auteur ; Mei MA, Auteur ; Liang ZHANG, Auteur ; Pengli LI, Auteur ; Bastian CHENG, Auteur ; Xingmei LIANG, Auteur ; Li LIU, Auteur ; Yanan DU, Auteur ; Yan ZHAO, Auteur ; Om Prakash KAFLE, Auteur ; Bei HAN, Auteur ; Feng ZHANG, Auteur . - p.33-38. Langues : Anglais (eng) in Autism Research > 12-1 (January 2019) . - p.33-38 Mots-clés : autism spectrum disorders  gene set enrichment analysis  mRNA expression profiles  transcriptome-wide association study Index. décimale : PER Périodiques Résumé : Autism spectrum disorders (ASD) are a group of highly heritable psychiatric syndromes with high prevalence. The genetic mechanism of ASD remains elusive now. Here we conducted a transcriptome-wide association study (TWAS) of ASD. The GWAS summary data of ASD was driven from the Psychiatric Genomics Consortium (PGC) portal, totally involving 5,305 ASD cases and 5,305 controls. FUSION software was applied to the GWAS summary data for tissue-related TWAS of ASD considering brain and blood. The ASD associated genes identified by TWAS were further validated by mRNA expression profiling of ASD and the Simons Foundation for Autism Research (SFARI) Gene tool. DAVID 6.8 was used to perform gene ontology (GO) enrichment analysis of ASD associated genes identified by TWAS. TWAS identified 85 genes with TWAS P value <0.05 for ASD. Further comparing the 85 genes with the differentially expressed genes identified by mRNA expression profiling of ASD patients found 5 overlapped genes, including MUTYH (PTWAS = 0.0460, PmRNA = 0.0040), ARHGAP27 (PTWAS = 0.0100, PmRNA = 0.0016), GCA (PTWAS = 0.0480, PmRNA = 0.0063), CCDC14 (PTWAS = 0.0067, PmRNA = 0.0035), and MED15 (PTWAS = 0.0324, PmRNA = 0.0092). Gene Ontology (GO) enrichment analysis of the genes identified by TWAS detected 10 significant GO terms, such as mitochondrion (P = 0.0051), NAD or NADH binding (P = 0.0169), mitochondrial part (P = 0.0386) and 2-oxoglutarate metabolic process (P = 0.0399). In conclusion, this study identified multiple ASD associated genes and gene sets, providing novel clues for revealing the pathogenesis of ASD. Autism Research 2019, 12: 33-38. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Recent genetic studies of autism spectrum disorders (ASD) have found multiple ASD related genes. However, the results of these studies were hardly replicated with each other, providing limited clues for exploring the genetic mechanism of ASD. This study detected a group of candidate genes showing transcriptome-wide associations with ASD. These results may provide novel clues for revealing the pathogenesis of ASD. En ligne : http://dx.doi.org/10.1002/aur.2048 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=376

Plasma Amino Acid Profile in Children with Autism Spectrum Disorder in Southern China: Analysis of 110 Cases / Wen-Xiong CHEN in Journal of Autism and Developmental Disorders, 54-4 (April 2024)  

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Rare deleterious mutations of the gene EFR3A in autism spectrum disorders / Abha R. GUPTA in Molecular Autism, (April 2014)  

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