使用表观遗传学工具箱
来分析与精神分裂症风险相关的常见变异
。

IF 8.3 2区 医学 Q1 Medicine
Prashanth Rajarajan, Schahram Akbarian
{"title":"使用表观遗传学工具箱\u2028来分析与精神分裂症风险相关的常见变异\u2029。","authors":"Prashanth Rajarajan,&nbsp;Schahram Akbarian","doi":"10.31887/DCNS.2019.21.4/sakbarian","DOIUrl":null,"url":null,"abstract":"<p><p>Schizophrenia is a debilitating psychiatric disorder with a complex genetic architecture and limited understanding of its neuropathology, reflected by the lack of diagnostic measures and effective pharmacological treatments. Geneticists have recently identified more than 145 risk loci comprising hundreds of common variants of small effect sizes, most of which lie in noncoding genomic regions. This review will discuss how the epigenetic toolbox can be applied to contextualize genetic findings in schizophrenia. Progress in next-generation sequencing, along with increasing methodological complexity, has led to the compilation of genome-wide maps of DNA methylation, histone modifications, RNA expression, and more. Integration of chromatin conformation datasets is one of the latest efforts in deciphering schizophrenia risk, allowing the identification of genes in contact with regulatory variants across 100s of kilobases. Large-scale multiomics studies will facilitate the prioritization of putative causal risk variants and gene networks that contribute to schizophrenia etiology, informing clinical diagnostics and treatment downstream.\u2029.</p>","PeriodicalId":54343,"journal":{"name":"Dialogues in Clinical Neuroscience","volume":"21 4","pages":"407-416"},"PeriodicalIF":8.3000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/23/8b/DialoguesClinNeurosci-21-407.PMC6952750.pdf","citationCount":"2","resultStr":"{\"title\":\"Use of the epigenetic toolbox\\u2028to contextualize common variants associated with schizophrenia risk\\u2029.\",\"authors\":\"Prashanth Rajarajan,&nbsp;Schahram Akbarian\",\"doi\":\"10.31887/DCNS.2019.21.4/sakbarian\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Schizophrenia is a debilitating psychiatric disorder with a complex genetic architecture and limited understanding of its neuropathology, reflected by the lack of diagnostic measures and effective pharmacological treatments. Geneticists have recently identified more than 145 risk loci comprising hundreds of common variants of small effect sizes, most of which lie in noncoding genomic regions. This review will discuss how the epigenetic toolbox can be applied to contextualize genetic findings in schizophrenia. Progress in next-generation sequencing, along with increasing methodological complexity, has led to the compilation of genome-wide maps of DNA methylation, histone modifications, RNA expression, and more. Integration of chromatin conformation datasets is one of the latest efforts in deciphering schizophrenia risk, allowing the identification of genes in contact with regulatory variants across 100s of kilobases. Large-scale multiomics studies will facilitate the prioritization of putative causal risk variants and gene networks that contribute to schizophrenia etiology, informing clinical diagnostics and treatment downstream.\\u2029.</p>\",\"PeriodicalId\":54343,\"journal\":{\"name\":\"Dialogues in Clinical Neuroscience\",\"volume\":\"21 4\",\"pages\":\"407-416\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/23/8b/DialoguesClinNeurosci-21-407.PMC6952750.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dialogues in Clinical Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.31887/DCNS.2019.21.4/sakbarian\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dialogues in Clinical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.31887/DCNS.2019.21.4/sakbarian","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 2

摘要

精神分裂症是一种使人衰弱的精神疾病,具有复杂的遗传结构,对其神经病理学的了解有限,这反映在缺乏诊断措施和有效的药物治疗上。遗传学家最近已经确定了超过145个风险位点,其中包括数百种影响较小的常见变异,其中大多数位于非编码基因组区域。这篇综述将讨论表观遗传学工具箱如何应用于精神分裂症的遗传发现。新一代测序技术的进步,以及方法复杂性的增加,导致了DNA甲基化、组蛋白修饰、RNA表达等全基因组图谱的编制。染色质构象数据集的整合是破译精神分裂症风险的最新努力之一,允许识别与成百上千个碱基的调节变异相关的基因。大规模多组学研究将促进推定的因果风险变异和导致精神分裂症病因的基因网络的优先排序,为下游的临床诊断和治疗提供信息。
。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Use of the epigenetic toolbox
to contextualize common variants associated with schizophrenia risk
.

Use of the epigenetic toolbox
to contextualize common variants associated with schizophrenia risk
.

Use of the epigenetic toolbox
to contextualize common variants associated with schizophrenia risk
.

Schizophrenia is a debilitating psychiatric disorder with a complex genetic architecture and limited understanding of its neuropathology, reflected by the lack of diagnostic measures and effective pharmacological treatments. Geneticists have recently identified more than 145 risk loci comprising hundreds of common variants of small effect sizes, most of which lie in noncoding genomic regions. This review will discuss how the epigenetic toolbox can be applied to contextualize genetic findings in schizophrenia. Progress in next-generation sequencing, along with increasing methodological complexity, has led to the compilation of genome-wide maps of DNA methylation, histone modifications, RNA expression, and more. Integration of chromatin conformation datasets is one of the latest efforts in deciphering schizophrenia risk, allowing the identification of genes in contact with regulatory variants across 100s of kilobases. Large-scale multiomics studies will facilitate the prioritization of putative causal risk variants and gene networks that contribute to schizophrenia etiology, informing clinical diagnostics and treatment downstream.
.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Dialogues in Clinical Neuroscience
Dialogues in Clinical Neuroscience Medicine-Psychiatry and Mental Health
CiteScore
19.30
自引率
1.20%
发文量
1
期刊介绍: Dialogues in Clinical Neuroscience (DCNS) endeavors to bridge the gap between clinical neuropsychiatry and the neurosciences by offering state-of-the-art information and original insights into pertinent clinical, biological, and therapeutic aspects. As an open access journal, DCNS ensures accessibility to its content for all interested parties. Each issue is curated to include expert reviews, original articles, and brief reports, carefully selected to offer a comprehensive understanding of the evolving landscape in clinical neuroscience. Join us in advancing knowledge and fostering dialogue in this dynamic field.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信