Exhaled air analysis for pulmonary arterial hypertension fingerprints identification. (25th November 2020)

• Record Type: Journal Article
• Authors: Swinarew, A.S; Kusz, B; Skoczynski, S; Gabor, J; Okla, H; Mika, B; Skoczylas, I; Gasior, M; Kopec, G; Mizia-Stec, K
• Is Part Of: European heart journal. Volume 41:(2020)Supplement 2
• Publication Date: 2020-11-25
• Subjects: Hypertension - Diagnostic Methods; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/ehjci/ehaa946.2752
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Background: Pulmonary arterial hypertension (PAH) is a rare disease which is often diagnosed in the late phase as its symptoms are non-specific and there is a lack of screening tests. Therefore, there is a strong need for identifying of its biomarkers. Aim: To identify the biomarkers for PAH in the exhaled breath and in the serum. Methods: The breath phase of all the patients was collected on the highly porous aseptic material by the use of special patented holder PL 232911. The collected air was then examined with gas chromatography mass spectrometry (GC/MS). For the control of the obtained results plasma of all the patients was examined by the use of Ultra High Performance Liquid Chromatography (UHPLC). A group of 10 patients (2 men, 8 women, mean age 60.4±10.9 years, BMI 27.6±6.0 kg/m 2 ) with diagnosed PAH as well as the group of 10 healthy persons (6 men, 4 women, mean age 35±11 years, BMI 25.6±6.0 kg/m 2 ) were enrolled into the study. Results: The obtained spectral and chromatographic results clearly presents the qualitative and quantitative QA/QC sensitivity to the metabolites changes in the patient's breath. The identification of changes in ratio of the whole spectra of biomarkers can allow to obtain a multi-dimensional pathways for PAH diagnostics fig. 1. The chromatography data from patients suffering from PAH have been processed by the aid of signal processing toolbox in MATLAB. Only the peaks of the prominence of at least 10000 (experimentally established) have been taken under consideration. The prominence of a peak measures how much the peak stands out due to its intrinsic height and its location relative to other peaks. Next, for the each found peak the arguments of the two neighboring local minima, have been determined and the integration range for calculating the area under the each peak have been established. The ratio of the area under the significant peak to its prominence have been applied for further analysis. Conclusions: Based on our preliminary results it seems that our method is specific and sensitive in the range of selected bio-fingerprints in patients with PAH. If confirmed on larger population the molecular level breath analysis can be used as a screening test as well as complementary diagnostic method in PAH to the standard clinical practice. Funding Acknowledgement: Type of funding source: Public Institution(s). Main funding source(s): University of Silesia in Katowice