• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

对自闭症家族中变异相互作用的分析表明，中枢神经系统发育过程涉及到一些基因。

Analysis of variant interactions in families with autism points to genes involved in the development of the central nervous system.

作者信息

Kaczyński Jacek, Pasenkiewicz-Gierula Marta

机构信息

Department of Biochemistry, Biophysics and Biotechnology, Jagiellonian University in Kraków, Kraków, Poland.

出版信息

PLoS One. 2025 Jun 11;20(6):e0326022. doi: 10.1371/journal.pone.0326022. eCollection 2025.

DOI:10.1371/journal.pone.0326022
PMID:40498723
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12157340/
Abstract

Whole-genome sequencing data of simplex families with autism spectrum disorder (ASD) were analyzed by searching for statistical interactions between loci. The resulting variant pairs mapped to 411 genes, of which 368 had not been associated with ASD before. The variants were used to build an ASD predictor based on an open-source machine learning library. The predictor correctly classifies over 78% of samples from a test set with an average significance level of 8.9· 10-158. Gene Ontology (GO) enrichment analysis of the identified risk genes points to functions related to the development of the Central Nervous System (CNS). Clustering cases on the basis of risk variants improves predictor accuracy and reveals additional overrepresented GO terms. Some of the detected statistical interactions can be linked to known biological interactions between genes involved in the development of the CNS. Analysis of the statistical interactions also points to genes whose biological functions are not yet known.

摘要

通过搜索基因座之间的统计相互作用，对患有自闭症谱系障碍（ASD）的单纯家庭的全基因组测序数据进行了分析。得到的变异对映射到411个基因，其中368个基因以前未与ASD相关联。这些变异被用于基于一个开源机器学习库构建ASD预测模型。该预测模型能正确分类来自测试集的超过78%的样本，平均显著性水平为8.9·10-158。对已识别的风险基因进行基因本体论（GO）富集分析，结果指向与中枢神经系统（CNS）发育相关的功能。基于风险变异对病例进行聚类可提高预测模型的准确性，并揭示其他过度富集的GO术语。一些检测到的统计相互作用可与中枢神经系统发育中涉及的基因之间已知的生物学相互作用联系起来。对统计相互作用的分析还指向了生物学功能尚不清楚的基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/e5bf0bb4c985/pone.0326022.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/b0e42c5b481e/pone.0326022.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/adc3269a740b/pone.0326022.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/81bf8ef27b64/pone.0326022.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/e5bf0bb4c985/pone.0326022.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/b0e42c5b481e/pone.0326022.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/adc3269a740b/pone.0326022.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/81bf8ef27b64/pone.0326022.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d2/12157340/e5bf0bb4c985/pone.0326022.g004.jpg

相似文献

1
Analysis of variant interactions in families with autism points to genes involved in the development of the central nervous system.对自闭症家族中变异相互作用的分析表明，中枢神经系统发育过程涉及到一些基因。
PLoS One. 2025 Jun 11;20(6):e0326022. doi: 10.1371/journal.pone.0326022. eCollection 2025.
2
Whole Exome Sequencing Identifies Novel De Novo Variants Interacting with Six Gene Networks in Autism Spectrum Disorder.全外显子组测序鉴定出与自闭症谱系障碍中六个基因网络相互作用的新型新生变异。
Genes (Basel). 2020 Dec 22;12(1):1. doi: 10.3390/genes12010001.
3
Widespread signatures of positive selection in common risk alleles associated to autism spectrum disorder.与自闭症谱系障碍相关的常见风险等位基因中广泛存在的正选择特征。
PLoS Genet. 2017 Feb 10;13(2):e1006618. doi: 10.1371/journal.pgen.1006618. eCollection 2017 Feb.
4
Leveraging blood serotonin as an endophenotype to identify de novo and rare variants involved in autism.利用血液血清素作为内表型来鉴定自闭症相关的新生和罕见变异。
Mol Autism. 2017 Mar 21;8:14. doi: 10.1186/s13229-017-0130-3. eCollection 2017.
5
Clustering Analysis Supports the Detection of Biological Processes Related to Autism Spectrum Disorder.聚类分析支持检测与自闭症谱系障碍相关的生物学过程。
Genes (Basel). 2020 Dec 9;11(12):1476. doi: 10.3390/genes11121476.
6
Coupling of autism genes to tissue-wide expression and dysfunction of synapse, calcium signalling and transcriptional regulation.将自闭症基因与突触、钙信号和转录调节的组织广泛表达和功能障碍偶联。
PLoS One. 2020 Dec 18;15(12):e0242773. doi: 10.1371/journal.pone.0242773. eCollection 2020.
7
Whole genome sequencing and variant discovery in the ASPIRE autism spectrum disorder cohort.ASPIRE 自闭症谱系障碍队列的全基因组测序和变异发现。
Clin Genet. 2019 Sep;96(3):199-206. doi: 10.1111/cge.13556. Epub 2019 May 30.
8
Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.外群机器学习方法识别出与自闭症谱系障碍相关的非编码DNA中的单核苷酸变异。
Pac Symp Biocomput. 2019;24:260-271.
9
Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology.利用机器学习和基因功能相似性（通过基因本体论评估）识别疾病基因。
PLoS One. 2018 Dec 10;13(12):e0208626. doi: 10.1371/journal.pone.0208626. eCollection 2018.
10
Contribution of Multiple Inherited Variants to Autism Spectrum Disorder (ASD) in a Family with 3 Affected Siblings.家族中 3 名受影响的兄弟姐妹的自闭症谱系障碍 (ASD) 中多种遗传变异的贡献。
Genes (Basel). 2021 Jul 8;12(7):1053. doi: 10.3390/genes12071053.

本文引用的文献

1
A Systematic Compilation of Human SH3 Domains: A Versatile Superfamily in Cellular Signaling.人类 SH3 结构域的系统编制：细胞信号转导中的多功能超家族。
Cells. 2023 Aug 12;12(16):2054. doi: 10.3390/cells12162054.
2
Glycosylation and behavioral symptoms in neurological disorders.糖基化与神经障碍中的行为症状。
Transl Psychiatry. 2023 May 8;13(1):154. doi: 10.1038/s41398-023-02446-x.
3
A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction.基于机器学习的疾病风险预测的特征选择方法综述
Front Bioinform. 2022 Jun 27;2:927312. doi: 10.3389/fbinf.2022.927312. eCollection 2022.
4
Neuronal Roles of the Multifunctional Protein Dipeptidyl Peptidase-like 6 (DPP6).多功能蛋白二肽基肽酶样 6（DPP6）的神经元作用。
Int J Mol Sci. 2022 Aug 16;23(16):9184. doi: 10.3390/ijms23169184.
5
Investigating the Role of GABA in Neural Development and Disease Using Mice Lacking GAD67 or VGAT Genes.使用缺乏 GAD67 或 VGAT 基因的小鼠研究 GABA 在神经发育和疾病中的作用。
Int J Mol Sci. 2022 Jul 19;23(14):7965. doi: 10.3390/ijms23147965.
6
Role of Munc18-1 in the biological functions and pathogenesis of neurological disorders (Review).Munc18-1 在神经紊乱的生物学功能和发病机制中的作用（综述）。
Mol Med Rep. 2021 Mar;23(3). doi: 10.3892/mmr.2021.11837. Epub 2021 Jan 26.
7
Interactome Mapping Provides a Network of Neurodegenerative Disease Proteins and Uncovers Widespread Protein Aggregation in Affected Brains.相互作用组图谱提供了一个神经退行性疾病蛋白的网络，并揭示了受影响大脑中广泛的蛋白质聚集。
Cell Rep. 2020 Aug 18;32(7):108050. doi: 10.1016/j.celrep.2020.108050.
8
A reference map of the human binary protein interactome.人类二进制蛋白质相互作用组参考图谱。
Nature. 2020 Apr;580(7803):402-408. doi: 10.1038/s41586-020-2188-x. Epub 2020 Apr 8.
9
Novel congenital disorder of O-linked glycosylation caused by GALNT2 loss of function.新型 O-连接糖基化发育障碍由 GALNT2 功能丧失引起。
Brain. 2020 Apr 1;143(4):1114-1126. doi: 10.1093/brain/awaa063.
10
Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder.全基因组从头风险评分提示自闭症谱系障碍中启动子变异的作用。
Science. 2018 Dec 14;362(6420). doi: 10.1126/science.aat6576.