A team of scientists from Poland performed a breath phase analysis in patients with pulmonary arterial hypertension (PAH) to identify a range of PAH biomarkers and develop an automatic classification method for determining the changing metabolome trends. Their study was published in the International Journal of Environmental Research and Public Health.

The study authors recruited 37 patients with PAH. None of the included participants were diagnosed with an active inflammatory process, infectious disease, malignancy, or hematologic disorder.

The researchers collected the patients’ breath phases on a highly porous septic material using a special patented holder. Prior to this, the patients rinsed their mouths with a 30% ethanol solution and demineralized water.


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The collected air samples were transported to the laboratory within 2 hours and examined with headspace analysis using gas chromatography-mass spectrometry.

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The analysis revealed a large variety of metabolites, as well as the composition of volatile, semivolatile, and nonvolatile compounds absorbed through the formation of aerosols. However, there was no specific metabolome indicative of PAH.

In the second stage, the researchers performed a cluster analysis by using spectral clustering, k-means, density-based spatial clustering of applications with noise (DBSCAN), and agglomerative clustering algorithms.

After analyzing patient samples, the Python programming language was used to create a base of substances most often found in the breathing phase. Upon receiving the sample, the database system could be used to automatically provide information on what substances were identified.

“The identification of the changes in the ratio of the whole spectra of biomarkers allowed us to obtain a multidimensional pathway for PAH characteristics and showed the metabolome differences in the four subgroups divided by the cluster analysis,” Swinarew and colleagues wrote.

“Probably, the markers may indicate an increased risk for developing PAH and serve as a diagnostic screening tool in the future. The presented approach may also be considered as a very first attempt at PAH identification with the help of methods belonging to widely accepted artificial intelligence.”

Metabolic pathways involved in the pathobiology of PAH, such as the increased metabolism of tricarboxylic acid and fatty acid oxidation, produce potent PAH biomarkers when examined using breath phase analysis. At present, there are no effective blood or metabolic screening tests that can be used for the diagnosis of PAH.

Reference

Swinarew AS, Gabor J, Kusz B, et al. Exhaled air metabolome analysis for pulmonary arterial hypertension fingerprints identification-the preliminary studyInt J Environ Res Public Health. Published online December 28, 2022. doi:10.3390/ijerph20010503