对精神障碍诊断性生物标志物研究的反思

Meta-Radiology Pub Date : 2025-03-01 Epub Date: 2025-02-02 DOI:10.1016/j.metrad.2025.100135
Jin Liu, Haoting Wang, Lingjiang Li
{"title":"对精神障碍诊断性生物标志物研究的反思","authors":"Jin Liu,&nbsp;Haoting Wang,&nbsp;Lingjiang Li","doi":"10.1016/j.metrad.2025.100135","DOIUrl":null,"url":null,"abstract":"<div><div>For mental disorders, the identification of biomarkers with high specificity, sensitivity, and validity remains a major challenge due to their heterogeneity and symptomatic overlap across disorders. In this review, we provide an overview of current research on mental disorders and highlight two key strategies potentially capable of addressing ​ these challenges: data integration and methodological ​innovation. Effective biomarker identification requires integrating large-scale, multicenter, and multidimensional data integration, including psychological, biological, physiological, and behavioral data. Innovative data acquisition technologies and analytical methods, alongside ​ novel approaches such as leveraging treatment response to validate biomarkers, are equally pivotal ​for advancing the field. We anticipate that the progress in this domain will be bolstered by the integration of new methodologies and technologies.</div></div>","PeriodicalId":100921,"journal":{"name":"Meta-Radiology","volume":"3 1","pages":"Article 100135"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rethinking the studies of diagnostic biomarkers for mental disorders\",\"authors\":\"Jin Liu,&nbsp;Haoting Wang,&nbsp;Lingjiang Li\",\"doi\":\"10.1016/j.metrad.2025.100135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>For mental disorders, the identification of biomarkers with high specificity, sensitivity, and validity remains a major challenge due to their heterogeneity and symptomatic overlap across disorders. In this review, we provide an overview of current research on mental disorders and highlight two key strategies potentially capable of addressing ​ these challenges: data integration and methodological ​innovation. Effective biomarker identification requires integrating large-scale, multicenter, and multidimensional data integration, including psychological, biological, physiological, and behavioral data. Innovative data acquisition technologies and analytical methods, alongside ​ novel approaches such as leveraging treatment response to validate biomarkers, are equally pivotal ​for advancing the field. We anticipate that the progress in this domain will be bolstered by the integration of new methodologies and technologies.</div></div>\",\"PeriodicalId\":100921,\"journal\":{\"name\":\"Meta-Radiology\",\"volume\":\"3 1\",\"pages\":\"Article 100135\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meta-Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2950162825000037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/2 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meta-Radiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950162825000037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/2 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

对于精神障碍,由于其异质性和症状重叠,鉴定具有高特异性、敏感性和有效性的生物标志物仍然是一个主要挑战。在这篇综述中,我们提供了当前精神障碍研究的概述,并强调了两个关键的策略可能能够解决这些挑战:数据整合和方法创新。有效的生物标志物识别需要大规模、多中心、多维度的数据整合,包括心理、生物、生理和行为数据。创新的数据采集技术和分析方法,以及利用治疗反应来验证生物标志物等新方法,对于推动该领域的发展同样至关重要。我们预计,新方法和新技术的结合将加强这一领域的进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Rethinking the studies of diagnostic biomarkers for mental disorders
For mental disorders, the identification of biomarkers with high specificity, sensitivity, and validity remains a major challenge due to their heterogeneity and symptomatic overlap across disorders. In this review, we provide an overview of current research on mental disorders and highlight two key strategies potentially capable of addressing ​ these challenges: data integration and methodological ​innovation. Effective biomarker identification requires integrating large-scale, multicenter, and multidimensional data integration, including psychological, biological, physiological, and behavioral data. Innovative data acquisition technologies and analytical methods, alongside ​ novel approaches such as leveraging treatment response to validate biomarkers, are equally pivotal ​for advancing the field. We anticipate that the progress in this domain will be bolstered by the integration of new methodologies and technologies.
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
Deep learning reconstruction enhanced myocardial scar detection on late gadolinium enhancement MRI in patients with ventricular arrhythmias Enhancing the Prognosis of Nasopharyngeal Carcinoma Using Intra- and Peritumoral Radiomics Physics-Informed Deep Learning–Empowered Hybrid IVIM–DKI Using Four Nonzero b-Values for preoperative Identification of icrovascular Invasion in Hepatocellular Carcinoma The anterior cingulate cortex neurophenotypes predict suitability for anti-TNF-α agents in Crohn's disease X-ray classification and treatment of hypotrophic distraction osteogenesis in tibial bone transport
×
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学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
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