Association analysis of two synapse-related gene mutations with autism spectrum disorder in a Chinese population / Fang HOU in Research in Autism Spectrum Disorders, 53 (September 2018)  

Public ISBD [article]  inResearch in Autism Spectrum Disorders > 53 (September 2018) . - p.67-72 Titre : Association analysis of two synapse-related gene mutations with autism spectrum disorder in a Chinese population Type de document : Texte imprimé et/ou numérique Auteurs : Fang HOU, Auteur ; Li LI, Auteur ; Jianhua GONG, Auteur ; Yanlin CHEN, Auteur ; Jia WANG, Auteur ; Lingfei LIU, Auteur ; Xiu LUO, Auteur ; HuaiTing GU, Auteur ; Jiajia ZHANG, Auteur ; Ranran SONG, Auteur Article en page(s) : p.67-72 Langues : Anglais (eng) Mots-clés : Polymorphism  Autism spectrum disorder Index. décimale : PER Périodiques Résumé : Background Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic basis. Recently, synaptic abnormality has been proved to have a strong association with the etiology of ASD. PSD95 and DLGAP2 are the members of postsynaptic scaffolding proteins that play crucial roles in synaptic plasticity and function. This study evaluated the association of the genetic variants in PSD95 and DLGAP2 with ASD. Methods We performed a case-control study in a Chinese population with samples of 529 cases and 1923 controls. We extracted genomic DNA from oral swabs and determined the SNP genotypes by using a PCR-RFLP assay. Results We sequenced five SNPs (rs7005715, rs2301963 and rs2906569 in DLGAP2; rs2521985 and rs2017365 in PSD95). Genetic analysis suggested the GA genotype and GG genotype of rs7005715 were significantly associated with increased risk of ASD (respectively: OR?=?1.357, 95%CI?=?1.103–1.669, P?=?0.016; OR?=?1.860, 95%CI?=?1.359–2.551, P? En ligne : https://doi.org/10.1016/j.rasd.2018.06.005 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=368 [article] Association analysis of two synapse-related gene mutations with autism spectrum disorder in a Chinese population [Texte imprimé et/ou numérique] / Fang HOU, Auteur ; Li LI, Auteur ; Jianhua GONG, Auteur ; Yanlin CHEN, Auteur ; Jia WANG, Auteur ; Lingfei LIU, Auteur ; Xiu LUO, Auteur ; HuaiTing GU, Auteur ; Jiajia ZHANG, Auteur ; Ranran SONG, Auteur . - p.67-72. Langues : Anglais (eng) in Research in Autism Spectrum Disorders > 53 (September 2018) . - p.67-72 Mots-clés : Polymorphism  Autism spectrum disorder Index. décimale : PER Périodiques Résumé : Background Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic basis. Recently, synaptic abnormality has been proved to have a strong association with the etiology of ASD. PSD95 and DLGAP2 are the members of postsynaptic scaffolding proteins that play crucial roles in synaptic plasticity and function. This study evaluated the association of the genetic variants in PSD95 and DLGAP2 with ASD. Methods We performed a case-control study in a Chinese population with samples of 529 cases and 1923 controls. We extracted genomic DNA from oral swabs and determined the SNP genotypes by using a PCR-RFLP assay. Results We sequenced five SNPs (rs7005715, rs2301963 and rs2906569 in DLGAP2; rs2521985 and rs2017365 in PSD95). Genetic analysis suggested the GA genotype and GG genotype of rs7005715 were significantly associated with increased risk of ASD (respectively: OR?=?1.357, 95%CI?=?1.103–1.669, P?=?0.016; OR?=?1.860, 95%CI?=?1.359–2.551, P? En ligne : https://doi.org/10.1016/j.rasd.2018.06.005 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=368

Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain / Yating MING ; Weixing ZHAO ; Rui FENG ; Yuanyue ZHOU ; Lijie WU ; Jia WANG ; Jinming XIAO ; Lei LI ; Xiaolong SHAN ; Jing CAO ; Xiaodong KANG ; Huafu CHEN ; Xujun DUAN in Molecular Autism, 14 (2023)  

Public ISBD [article]  inMolecular Autism > 14 (2023) . - 41 p. Titre : Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain Type de document : Texte imprimé et/ou numérique Auteurs : Yating MING, Auteur ; Weixing ZHAO, Auteur ; Rui FENG, Auteur ; Yuanyue ZHOU, Auteur ; Lijie WU, Auteur ; Jia WANG, Auteur ; Jinming XIAO, Auteur ; Lei LI, Auteur ; Xiaolong SHAN, Auteur ; Jing CAO, Auteur ; Xiaodong KANG, Auteur ; Huafu CHEN, Auteur ; Xujun DUAN, Auteur Article en page(s) : 41 p. Langues : Anglais (eng) Mots-clés : Child  Humans  Child, Preschool  Diffusion Tensor Imaging/methods  *Autistic Disorder/diagnostic imaging  Brain/diagnostic imaging  *White Matter/diagnostic imaging  Cluster Analysis Index. décimale : PER Périodiques Résumé : OBJECTIVE: There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have been divergent. The development of autistic people in early childhood is clouded by the concurrently rapid brain growth, which might lead to the inconsistent findings of atypical WM microstructure in autism. Here, we aimed to reveal the developmental nature of autistic children and delineate atypical WM microstructure throughout early childhood while taking developmental considerations into account. METHOD: In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 autistic children and 100 typically developing children (TDC), aged 4-7 years. Developmental prediction modeling using support vector regression based on TDC participants was conducted to estimate the WM atypical development index of autistic children. Then, subgroups of autistic children were identified by using the k-means clustering method and were compared to each other on the basis of demographic information, WM atypical development index, and autistic trait by using two-sample t-test. Relationship of the WM atypical development index with age was estimated by using partial correlation. Furthermore, we performed threshold-free cluster enhancement-based two-sample t-test for the group comparison in WM microstructures of each subgroup of autistic children with the rematched subsets of TDC. RESULTS: We clustered autistic children into two subgroups according to WM atypical development index. The two subgroups exhibited distinct developmental stages and age-dependent diversity. WM atypical development index was found negatively associated with age. Moreover, an inverse pattern of atypical WM microstructures and different clinical manifestations in the two stages, with subgroup 1 showing overgrowth with low level of autistic traits and subgroup 2 exhibiting delayed maturation with high level of autistic traits, were revealed. CONCLUSION: This study illustrated age-dependent heterogeneity in early childhood autistic children and delineated developmental stage-specific difference that ranged from an overgrowth pattern to a delayed pattern. Trial registration This study has been registered at ClinicalTrials.gov (Identifier: NCT02807766) on June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ). En ligne : https://dx.doi.org/10.1186/s13229-023-00573-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518 [article] Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain [Texte imprimé et/ou numérique] / Yating MING, Auteur ; Weixing ZHAO, Auteur ; Rui FENG, Auteur ; Yuanyue ZHOU, Auteur ; Lijie WU, Auteur ; Jia WANG, Auteur ; Jinming XIAO, Auteur ; Lei LI, Auteur ; Xiaolong SHAN, Auteur ; Jing CAO, Auteur ; Xiaodong KANG, Auteur ; Huafu CHEN, Auteur ; Xujun DUAN, Auteur . - 41 p. Langues : Anglais (eng) in Molecular Autism > 14 (2023) . - 41 p. Mots-clés : Child  Humans  Child, Preschool  Diffusion Tensor Imaging/methods  *Autistic Disorder/diagnostic imaging  Brain/diagnostic imaging  *White Matter/diagnostic imaging  Cluster Analysis Index. décimale : PER Périodiques Résumé : OBJECTIVE: There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have been divergent. The development of autistic people in early childhood is clouded by the concurrently rapid brain growth, which might lead to the inconsistent findings of atypical WM microstructure in autism. Here, we aimed to reveal the developmental nature of autistic children and delineate atypical WM microstructure throughout early childhood while taking developmental considerations into account. METHOD: In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 autistic children and 100 typically developing children (TDC), aged 4-7 years. Developmental prediction modeling using support vector regression based on TDC participants was conducted to estimate the WM atypical development index of autistic children. Then, subgroups of autistic children were identified by using the k-means clustering method and were compared to each other on the basis of demographic information, WM atypical development index, and autistic trait by using two-sample t-test. Relationship of the WM atypical development index with age was estimated by using partial correlation. Furthermore, we performed threshold-free cluster enhancement-based two-sample t-test for the group comparison in WM microstructures of each subgroup of autistic children with the rematched subsets of TDC. RESULTS: We clustered autistic children into two subgroups according to WM atypical development index. The two subgroups exhibited distinct developmental stages and age-dependent diversity. WM atypical development index was found negatively associated with age. Moreover, an inverse pattern of atypical WM microstructures and different clinical manifestations in the two stages, with subgroup 1 showing overgrowth with low level of autistic traits and subgroup 2 exhibiting delayed maturation with high level of autistic traits, were revealed. CONCLUSION: This study illustrated age-dependent heterogeneity in early childhood autistic children and delineated developmental stage-specific difference that ranged from an overgrowth pattern to a delayed pattern. Trial registration This study has been registered at ClinicalTrials.gov (Identifier: NCT02807766) on June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ). En ligne : https://dx.doi.org/10.1186/s13229-023-00573-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518

Neurexin gene family variants as risk factors for autism spectrum disorder / Jia WANG in Autism Research, 11-1 (January 2018)  

Public ISBD [article]  inAutism Research > 11-1 (January 2018) . - p.37-43 Titre : Neurexin gene family variants as risk factors for autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Jia WANG, Auteur ; Jianhua GONG, Auteur ; Li LI, Auteur ; Yanlin CHEN, Auteur ; Lingfei LIU, Auteur ; HuaiTing GU, Auteur ; Xiu LUO, Auteur ; Fang HOU, Auteur ; Jiajia ZHANG, Auteur ; Ranran SONG, Auteur Article en page(s) : p.37-43 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Increasing evidence suggests that abnormal synaptic function leads to neuronal developmental disorders and is an important component of the etiology of autism spectrum disorder (ASD). Neurexins are presynaptic cell?adhesion molecules that affect the function of synapses and mediate the conduction of nerve signals. Thus, neurexins are attractive candidate genes for autism. Since gene families have greater power to reveal genetic association than single genes, we designed this case?control study to investigate six genetic variants in three neurexin genes (NRXN1, NRXN2, and NRXN3) in a Chinese population including 529 ASD patients and 1,923 healthy controls. We found that two SNPs were significantly associated with ASD after false discovery rate (FDR) adjustment for multiple comparisons. The NRXN2 rs12273892 polymorphism T allele and AT genotype were significantly associated with increased risk of ASD (respectively: OR?=?1.328, 95% CI?=?1.133–1.557, P? En ligne : https://doi.org/10.1002/aur.1881 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=333 [article] Neurexin gene family variants as risk factors for autism spectrum disorder [Texte imprimé et/ou numérique] / Jia WANG, Auteur ; Jianhua GONG, Auteur ; Li LI, Auteur ; Yanlin CHEN, Auteur ; Lingfei LIU, Auteur ; HuaiTing GU, Auteur ; Xiu LUO, Auteur ; Fang HOU, Auteur ; Jiajia ZHANG, Auteur ; Ranran SONG, Auteur . - p.37-43. Langues : Anglais (eng) in Autism Research > 11-1 (January 2018) . - p.37-43 Index. décimale : PER Périodiques Résumé : Increasing evidence suggests that abnormal synaptic function leads to neuronal developmental disorders and is an important component of the etiology of autism spectrum disorder (ASD). Neurexins are presynaptic cell?adhesion molecules that affect the function of synapses and mediate the conduction of nerve signals. Thus, neurexins are attractive candidate genes for autism. Since gene families have greater power to reveal genetic association than single genes, we designed this case?control study to investigate six genetic variants in three neurexin genes (NRXN1, NRXN2, and NRXN3) in a Chinese population including 529 ASD patients and 1,923 healthy controls. We found that two SNPs were significantly associated with ASD after false discovery rate (FDR) adjustment for multiple comparisons. The NRXN2 rs12273892 polymorphism T allele and AT genotype were significantly associated with increased risk of ASD (respectively: OR?=?1.328, 95% CI?=?1.133–1.557, P? En ligne : https://doi.org/10.1002/aur.1881 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=333

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