COVID-19人群先天免疫系统分析

IF 7.4 2区 医学 Q1 IMMUNOLOGY
Sophie Müller , Joachim L. Schultze
{"title":"COVID-19人群先天免疫系统分析","authors":"Sophie Müller ,&nbsp;Joachim L. Schultze","doi":"10.1016/j.smim.2023.101778","DOIUrl":null,"url":null,"abstract":"<div><p>Recent developments in sequencing technologies, the computer and data sciences, as well as increasingly high-throughput immunological measurements have made it possible to derive holistic views on pathophysiological processes of disease and treatment effects directly in humans. We and others have illustrated that incredibly predictive data for immune cell function can be generated by single cell multi-omics (SCMO) technologies and that these technologies are perfectly suited to dissect pathophysiological processes in a new disease such as COVID-19, triggered by SARS-CoV-2 infection. Systems level interrogation not only revealed the different disease endotypes, highlighted the differential dynamics in context of disease severity, and pointed towards global immune deviation across the different arms of the immune system, but was already instrumental to better define long COVID phenotypes, suggest promising biomarkers for disease and therapy outcome predictions and explains treatment responses for the widely used corticosteroids. As we identified SCMO to be the most informative technologies in the vest to better understand COVID-19, we propose to routinely include such single cell level analysis in all future clinical trials and cohorts addressing diseases with an immunological component.</p></div>","PeriodicalId":49546,"journal":{"name":"Seminars in Immunology","volume":"68 ","pages":"Article 101778"},"PeriodicalIF":7.4000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10201327/pdf/","citationCount":"0","resultStr":"{\"title\":\"Systems analysis of human innate immunity in COVID-19\",\"authors\":\"Sophie Müller ,&nbsp;Joachim L. Schultze\",\"doi\":\"10.1016/j.smim.2023.101778\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Recent developments in sequencing technologies, the computer and data sciences, as well as increasingly high-throughput immunological measurements have made it possible to derive holistic views on pathophysiological processes of disease and treatment effects directly in humans. We and others have illustrated that incredibly predictive data for immune cell function can be generated by single cell multi-omics (SCMO) technologies and that these technologies are perfectly suited to dissect pathophysiological processes in a new disease such as COVID-19, triggered by SARS-CoV-2 infection. Systems level interrogation not only revealed the different disease endotypes, highlighted the differential dynamics in context of disease severity, and pointed towards global immune deviation across the different arms of the immune system, but was already instrumental to better define long COVID phenotypes, suggest promising biomarkers for disease and therapy outcome predictions and explains treatment responses for the widely used corticosteroids. As we identified SCMO to be the most informative technologies in the vest to better understand COVID-19, we propose to routinely include such single cell level analysis in all future clinical trials and cohorts addressing diseases with an immunological component.</p></div>\",\"PeriodicalId\":49546,\"journal\":{\"name\":\"Seminars in Immunology\",\"volume\":\"68 \",\"pages\":\"Article 101778\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10201327/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Seminars in Immunology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1044532323000696\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seminars in Immunology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1044532323000696","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

测序技术、计算机和数据科学的最新发展,以及越来越多的高通量免疫测量,使人们有可能直接从整体上了解疾病的病理生理过程和对人类的治疗效果。我们和其他人已经证明,单细胞多组学(SCMO)技术可以产生免疫细胞功能的令人难以置信的预测数据,这些技术非常适合于剖析由SARS-CoV-2感染引发的新冠肺炎等新疾病的病理生理过程。系统水平的询问不仅揭示了不同的疾病内型,强调了疾病严重程度下的差异动力学,并指出了免疫系统不同分支的全局免疫偏差,而且已经有助于更好地定义长期新冠肺炎表型,为疾病和治疗结果预测提供了有前景的生物标志物,并解释了广泛使用的皮质类固醇的治疗反应。由于我们确定SCMO是更好地了解新冠肺炎的最具信息性的技术,我们建议在所有未来的临床试验和队列中常规包括这种单细胞水平分析,以解决具有免疫成分的疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Systems analysis of human innate immunity in COVID-19

Systems analysis of human innate immunity in COVID-19

Recent developments in sequencing technologies, the computer and data sciences, as well as increasingly high-throughput immunological measurements have made it possible to derive holistic views on pathophysiological processes of disease and treatment effects directly in humans. We and others have illustrated that incredibly predictive data for immune cell function can be generated by single cell multi-omics (SCMO) technologies and that these technologies are perfectly suited to dissect pathophysiological processes in a new disease such as COVID-19, triggered by SARS-CoV-2 infection. Systems level interrogation not only revealed the different disease endotypes, highlighted the differential dynamics in context of disease severity, and pointed towards global immune deviation across the different arms of the immune system, but was already instrumental to better define long COVID phenotypes, suggest promising biomarkers for disease and therapy outcome predictions and explains treatment responses for the widely used corticosteroids. As we identified SCMO to be the most informative technologies in the vest to better understand COVID-19, we propose to routinely include such single cell level analysis in all future clinical trials and cohorts addressing diseases with an immunological component.

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
Seminars in Immunology
Seminars in Immunology 医学-免疫学
CiteScore
11.40
自引率
1.30%
发文量
50
审稿时长
89 days
期刊介绍: Seminars in Immunology is a specialized review journal that serves as a valuable resource for scientists in the field of immunology. The journal's approach is thematic, with each issue dedicated to a specific topic of significant interest to immunologists. It covers a wide range of research areas, from the molecular and cellular foundations of the immune response to the potential for its manipulation, highlighting recent advancements in these areas. Each thematic issue is curated by a guest editor, who is recognized as an expert in the field internationally. The content of each issue typically includes six to eight authoritative invited reviews, which delve into various aspects of the chosen topic. The goal of these reviews is to provide a comprehensive, coherent, and engaging overview of the subject matter, ensuring that the information is presented in a timely manner to maintain its relevance. The journal's commitment to quality and timeliness is further supported by its inclusion in the Scopus database, which is a leading abstract and citation database of peer-reviewed literature. Being indexed in Scopus helps to ensure that the journal's content is accessible to a broad audience of researchers and professionals in immunology and related fields.
×
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