多组学介导的广泛关联研究:了解疾病的新方法。

Mengting Shao, Kaiyang Chen, Shuting Zhang, Min Tian, Yan Shen, Chen Cao, Ning Gu
{"title":"多组学介导的广泛关联研究:了解疾病的新方法。","authors":"Mengting Shao, Kaiyang Chen, Shuting Zhang, Min Tian, Yan Shen, Chen Cao, Ning Gu","doi":"10.1093/gpbjnl/qzae077","DOIUrl":null,"url":null,"abstract":"<p><p>The rapid development of multi-omics (transcriptome, proteome, cistrome, imaging, and regulome) mediated wide association studies methods have opened new avenues for biologists to understand the susceptibility genes underlying complex diseases. Thorough comparisons of these methods are essential for selecting the most appropriate tool for a given research objective. This review provides a detailed categorization and summary of the statistical models, use cases, and advantages of recent multi-omics mediated wide association studies. In addition, to illustrate gene-disease association studies based on transcriptome-wide association studies (TWAS), we collected 478 disease entries across 22 categories from 235 manually reviewed publications. Our analysis reveals that mental disorders are the most frequently studied by TWAS, indicating its potential to deepen our understanding of the genetic architecture of complex diseases. In summary, this review underscores the importance of multi-omics mediated wide association studies in elucidating complex diseases and highlights the significance of selecting the appropriate method for each study.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-omics Mediated Wide Association Studies: Novel Approaches for Understanding Diseases.\",\"authors\":\"Mengting Shao, Kaiyang Chen, Shuting Zhang, Min Tian, Yan Shen, Chen Cao, Ning Gu\",\"doi\":\"10.1093/gpbjnl/qzae077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The rapid development of multi-omics (transcriptome, proteome, cistrome, imaging, and regulome) mediated wide association studies methods have opened new avenues for biologists to understand the susceptibility genes underlying complex diseases. Thorough comparisons of these methods are essential for selecting the most appropriate tool for a given research objective. This review provides a detailed categorization and summary of the statistical models, use cases, and advantages of recent multi-omics mediated wide association studies. In addition, to illustrate gene-disease association studies based on transcriptome-wide association studies (TWAS), we collected 478 disease entries across 22 categories from 235 manually reviewed publications. Our analysis reveals that mental disorders are the most frequently studied by TWAS, indicating its potential to deepen our understanding of the genetic architecture of complex diseases. In summary, this review underscores the importance of multi-omics mediated wide association studies in elucidating complex diseases and highlights the significance of selecting the appropriate method for each study.</p>\",\"PeriodicalId\":94020,\"journal\":{\"name\":\"Genomics, proteomics & bioinformatics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genomics, proteomics & bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/gpbjnl/qzae077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics, proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gpbjnl/qzae077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

多组学(转录组、蛋白质组、表位组、成像和调控组)介导的广泛关联研究方法的快速发展为生物学家了解复杂疾病的易感基因开辟了新途径。要为特定的研究目标选择最合适的工具,就必须对这些方法进行全面比较。本综述对近期多组学介导的广泛关联研究的统计模型、用例和优势进行了详细分类和总结。此外,为了说明基于转录组范围关联研究(TWAS)的基因-疾病关联研究,我们从 235 篇人工审阅的出版物中收集了 22 个类别的 478 个疾病条目。我们的分析表明,精神疾病是最常被 TWAS 研究的疾病,这表明 TWAS 有可能加深我们对复杂疾病基因结构的了解。总之,本综述强调了多组学介导的广泛关联研究在阐明复杂疾病方面的重要性,并强调了为每项研究选择适当方法的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multi-omics Mediated Wide Association Studies: Novel Approaches for Understanding Diseases.

The rapid development of multi-omics (transcriptome, proteome, cistrome, imaging, and regulome) mediated wide association studies methods have opened new avenues for biologists to understand the susceptibility genes underlying complex diseases. Thorough comparisons of these methods are essential for selecting the most appropriate tool for a given research objective. This review provides a detailed categorization and summary of the statistical models, use cases, and advantages of recent multi-omics mediated wide association studies. In addition, to illustrate gene-disease association studies based on transcriptome-wide association studies (TWAS), we collected 478 disease entries across 22 categories from 235 manually reviewed publications. Our analysis reveals that mental disorders are the most frequently studied by TWAS, indicating its potential to deepen our understanding of the genetic architecture of complex diseases. In summary, this review underscores the importance of multi-omics mediated wide association studies in elucidating complex diseases and highlights the significance of selecting the appropriate method for each study.

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
自引率
0.00%
发文量
0
期刊最新文献
iMFP-LG: Identification of Novel Multi-Functional Peptides by Using Protein Language Models and Graph-Based Deep Learning. ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics. VISTA: A Tool for Fast Taxonomic Assignment of Viral Genome Sequences. Pangenome Reveals Gene Content Variations and Structural Variants Contributing to Pig Characteristics. SoyOD: An Integrated Soybean Multi-omics Database for Mining Genes and Biological Research.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1