Salivary metabolites profiling for diagnosis of COPD: an exploratory study.

IF 3.4 4区 医学 Q1 BIOCHEMICAL RESEARCH METHODS Journal of breath research Pub Date : 2025-03-13 DOI:10.1088/1752-7163/adba07
Zhang Zherong, Lv Yan, Gong Meng, Li Juan, Zhang Yayun, Wu Songze, Zhang Yu, Cheng Deyun, Fan Tao
{"title":"Salivary metabolites profiling for diagnosis of COPD: an exploratory study.","authors":"Zhang Zherong, Lv Yan, Gong Meng, Li Juan, Zhang Yayun, Wu Songze, Zhang Yu, Cheng Deyun, Fan Tao","doi":"10.1088/1752-7163/adba07","DOIUrl":null,"url":null,"abstract":"<p><p>Pulmonary function tests (PFTs) are the gold standard for diagnosing of Chronic obstructive pulmonary disease (COPD). Given its limitation in some scenarios, it is imperative to develop new high-throughput screening methods for biomarkers in diagnosing COPD. This study aims to explore the feasibility of screening novel diagnostic biomarkers based on salivary metabolomics for the limited availability of PFTs and difficulties in implementation at primary care facilities. Participants were recruited from the outpatient department of West China Hospital. Saliva samples were collected to analyze the metabolites through the UPLC-Q-Exactive Orbitrap-MS platform. The raw data from the mass spectrometer was preprocessed with R software after peak extraction. The Wilcoxon rank sum test, Fold change analysis, PCA and orthogonal partial least squares - discriminant analysis were used to identify potential biomarkers. The receiver operating characteristic curve was used to assess the diagnostic efficacy of the predictive model generated by potential biomarkers. Saliva samples were collected from 66 patients with COPD and 55 healthy volunteers. Significant differences in the salivary metabolome between COPD patients and healthy controls were identified, with 261 differential metabolites recognized, 16 of which were considered as potential biomarker. The diagnostic model generated by these 16 biomarkers can successfully distinguish COPD patients from healthy people. Salivary metabolomic profiling is likely to emerge as a promising method for screening potential diagnostic biomarkers of COPD. Further prospective studies with large sample size are needed to verify the predictive value of these biomarkers in COPD diagnosis.<b>Trial registration</b>The study is registered with the China Clinical Trial Registry (www.chictr.org.cn/searchprojEN.html) on 26 September 2022, registration number: ChiCTR2200064091.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":" ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of breath research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1088/1752-7163/adba07","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Pulmonary function tests (PFTs) are the gold standard for diagnosing of Chronic obstructive pulmonary disease (COPD). Given its limitation in some scenarios, it is imperative to develop new high-throughput screening methods for biomarkers in diagnosing COPD. This study aims to explore the feasibility of screening novel diagnostic biomarkers based on salivary metabolomics for the limited availability of PFTs and difficulties in implementation at primary care facilities. Participants were recruited from the outpatient department of West China Hospital. Saliva samples were collected to analyze the metabolites through the UPLC-Q-Exactive Orbitrap-MS platform. The raw data from the mass spectrometer was preprocessed with R software after peak extraction. The Wilcoxon rank sum test, Fold change analysis, PCA and orthogonal partial least squares - discriminant analysis were used to identify potential biomarkers. The receiver operating characteristic curve was used to assess the diagnostic efficacy of the predictive model generated by potential biomarkers. Saliva samples were collected from 66 patients with COPD and 55 healthy volunteers. Significant differences in the salivary metabolome between COPD patients and healthy controls were identified, with 261 differential metabolites recognized, 16 of which were considered as potential biomarker. The diagnostic model generated by these 16 biomarkers can successfully distinguish COPD patients from healthy people. Salivary metabolomic profiling is likely to emerge as a promising method for screening potential diagnostic biomarkers of COPD. Further prospective studies with large sample size are needed to verify the predictive value of these biomarkers in COPD diagnosis.Trial registrationThe study is registered with the China Clinical Trial Registry (www.chictr.org.cn/searchprojEN.html) on 26 September 2022, registration number: ChiCTR2200064091.

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
唾液代谢物分析诊断慢性阻塞性肺病:一项探索性研究。
肺功能测试(PFTs)是诊断慢性阻塞性肺疾病(COPD)的金标准。鉴于其在某些情况下的局限性,开发新的高通量筛选方法诊断COPD的生物标志物势在必行。本研究旨在探讨基于唾液代谢组学筛选新型诊断生物标志物的可行性,以解决pft可获得性有限和在初级保健机构实施困难的问题。方法:从华西医院门诊部招募参与者。采集唾液样品,通过UPLC-Q-Exactive Orbitrap-MS平台分析代谢物。提取峰后的质谱仪原始数据用R软件进行预处理。使用Wilcoxon秩和检验、Fold变化分析、PCA和OPLS-DA鉴定潜在的生物标志物。ROC曲线用于评估潜在生物标志物生成的预测模型的诊断效果。 ;结果:收集了66例COPD患者和55名健康志愿者的唾液样本。发现COPD患者与健康对照者的唾液代谢组存在显著差异,共发现261种差异代谢物,其中16种被认为是潜在的生物标志物。由这16个生物标志物生成的诊断模型可以成功地将COPD患者与健康人区分开来。唾液代谢组学分析可能成为筛选COPD潜在诊断生物标志物的一种有前景的方法。需要进一步的大样本量的前瞻性研究来验证这些生物标志物在COPD诊断中的预测价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of breath research
Journal of breath research BIOCHEMICAL RESEARCH METHODS-RESPIRATORY SYSTEM
CiteScore
7.60
自引率
21.10%
发文量
49
审稿时长
>12 weeks
期刊介绍: Journal of Breath Research is dedicated to all aspects of scientific breath research. The traditional focus is on analysis of volatile compounds and aerosols in exhaled breath for the investigation of exogenous exposures, metabolism, toxicology, health status and the diagnosis of disease and breath odours. The journal also welcomes other breath-related topics. Typical areas of interest include: Big laboratory instrumentation: describing new state-of-the-art analytical instrumentation capable of performing high-resolution discovery and targeted breath research; exploiting complex technologies drawn from other areas of biochemistry and genetics for breath research. Engineering solutions: developing new breath sampling technologies for condensate and aerosols, for chemical and optical sensors, for extraction and sample preparation methods, for automation and standardization, and for multiplex analyses to preserve the breath matrix and facilitating analytical throughput. Measure exhaled constituents (e.g. CO2, acetone, isoprene) as markers of human presence or mitigate such contaminants in enclosed environments. Human and animal in vivo studies: decoding the ''breath exposome'', implementing exposure and intervention studies, performing cross-sectional and case-control research, assaying immune and inflammatory response, and testing mammalian host response to infections and exogenous exposures to develop information directly applicable to systems biology. Studying inhalation toxicology; inhaled breath as a source of internal dose; resultant blood, breath and urinary biomarkers linked to inhalation pathway. Cellular and molecular level in vitro studies. Clinical, pharmacological and forensic applications. Mathematical, statistical and graphical data interpretation.
期刊最新文献
The role of metabolomics in chronic obstructive pulmonary disease: from analytic techniques to clinical applications. Exhaled Breath Analysis to Stratify Cardiovascular Risk Using Machine Learning Model: A Novel Frontier in Preventive Cardiology. Exhaled breath-based clusters in children with post-COVID condition. Efficacy and safety of probiotic therapy for halitosis: a systematic review and meta-analysis of randomized controlled trials. A Feasibility study using the ETL CoronaCheck® device to Identify iNciDent cases of SARS-CoV-2: FIND SARS-CoV-2.
×
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: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