A clinical proteomics study of exhaled breath condensate and biomarkers for pulmonary embolism.

IF 3.7 4区 医学 Q1 BIOCHEMICAL RESEARCH METHODS
Inger Lise Gade, Signe Juul Riddersholm, Thomas Stilling-Vinther, Rasmus Froberg Brøndum, Tue Bjerg Bennike, Bent Honoré
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引用次数: 0

Abstract

Pulmonary embolism (PE) can be a diagnostic challenge. Current diagnostic markers for PE are unspecific and new diagnostic tools are needed. The air we exhale is a possible new source for biomarkers which can be tapped into by analysing the exhaled breath condensate (EBC). We analysed the EBC from patients with PE and controls to investigate if the EBC is a useful source for new diagnostic biomarkers of PE. We collected and analysed EBC samples from patients with suspected PE and controls matched on age and sex. Patients in whom PE was ruled out after diagnostic work-up were included in the control group to increase the sensitivity and generalizability of the identified markers. EBC samples were collected using an RTube™. The protein composition of the EBCs were analysed using data dependent label-free quantitative nano liquid chromatography-tandem mass spectrometry. EBC samples from 28 patients with confirmed PE, and 49 controls were analysed. A total of 928 EBC proteins were identified in the 77 EBC samples. As expected, a low protein concentration was determined which resulted in many proteins with unmeasurable levels in several samples. The levels of HSPA5, PEBP1 and SFTPA2 were higher and levels of POF1B, EPPK1, PSMA4, ALDOA, and CFL1 were lower in PE compared with controls. In conclusion, the human EBC contained a variety of endogenous proteins and may be a source for new diagnostic markers of PE and other diseases.

呼气冷凝物和肺栓塞生物标志物的临床蛋白质组学研究。
肺栓塞(PE)可能是一个诊断挑战。目前PE的诊断标志物是非特异性的,需要新的诊断工具。我们呼出的空气是生物标志物的一个可能的新来源,可以通过分析呼出的呼吸冷凝物(EBC)来利用它。我们分析了PE患者和对照组的EBC,以研究EBC是否是PE新诊断生物标志物的有用来源。将诊断检查后排除PE的患者纳入对照组,以提高已识别标志物的敏感性和可推广性。使用RTube采集EBC样本™. 使用数据依赖性无标记定量纳米液相色谱-串联质谱法分析EBCs的蛋白质组成。对28名确诊PE患者和49名对照组的EBC样本进行了分析。在77个EBC样品中共鉴定出928个EBC蛋白。正如预期的那样,确定了低蛋白质浓度,这导致在几个样品中许多蛋白质的水平无法测量。与对照组相比,PE中HSPA5、PEBP1和SFTPA2的水平较高,POF1B、EPPK1、PSMA4、ALDOA和CFL1的水平较低。总之,人类EBC含有多种内源性蛋白质,可能是PE和其他疾病新诊断标志物的来源。该项目在ClinicalTrials.gov上注册(标识符NCT04010760)。
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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.
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