A Novel Approach to the Isolation of Disease Markers: Quantitative Analysis of Amino Acids in Exhaled Breath Condensates from Sleep Apnea Patients with Enhanced Sampling and LC-ESI-MS

2Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Interest in obstructive sleep apnea is rising due to its neurocognitive and cardiovascular impacts, including systemic hypertension, myocardial infarction, and cerebrovascular events. Obstructive sleep apnea diagnosis can be suggested through symptoms like snoring, daytime sleepiness, and physical signs like increased neck circumference; however, overnight polysomnography is recommended to confirm. Exhaled breath condensate has emerged as a novel, noninvasive technique for biomarker sample collection. It is simple, rapid, repeatable, and suitable for young children and severely ill patients. A direct method using liquid chromatography–mass spectrometry coupled with hydrophilic interaction chromatography was established for quantitative analysis of amino acids in human exhaled breath condensate samples. The separation was performed using XBridge Amide BEH column and a mobile phase of ammonium formate buffer in gradient conditions. The method exhibited a low detection limit (0.08–1.28 ng/mL), good linearity (R2 between 0.9909 and 0.9987), and high recoveries (93–101.3%) for 21 studied amino acids with interday RSD of 2.1–7.7%. The LC-MS method was verified and applied to determine amino acids in exhaled breath condensate samples from obstructive sleep apnea patients, offering fast, reliable analysis without derivatization as a noninvasive alternative to standard methods.

Cite

CITATION STYLE

APA

Kaliszewska, A., Struczyński, P., Kwiatkowska, S., Nowak, D., Bączek, T., & Konieczna, L. (2025). A Novel Approach to the Isolation of Disease Markers: Quantitative Analysis of Amino Acids in Exhaled Breath Condensates from Sleep Apnea Patients with Enhanced Sampling and LC-ESI-MS. Journal of Separation Science, 48(1). https://doi.org/10.1002/jssc.70079

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free