4.7 Article

Volatile organic compound profiling to explore primary graft dysfunction after lung transplantation

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SCIENTIFIC REPORTS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-022-05994-2

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  1. European Union
  2. University of Liege (ULiege)
  3. Burroughs Welcome Fund Institutional Program Unifying Population and Laboratory Based Sciences [1014106]
  4. National Institute of Health Research, UK
  5. Cystic Fibrosis Trust
  6. Royal Brompton and Harefield National Health Service Foundation Trust
  7. Cystic Fibrosis Foundation
  8. United States National Institutes of Health
  9. [T32LM012204]

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Primary graft dysfunction (PGD) is a major determinant of morbidity and mortality following lung transplantation, with delineating its basic mechanisms and molecular signatures remaining a fundamental challenge. This study found that the pulmonary volatile organic compound (VOC) spectrum relates to PGD and postoperative outcomes, providing a potential method for differentiating patients with different grades of PGD.
Primary graft dysfunction (PGD) is a major determinant of morbidity and mortality following lung transplantation. Delineating basic mechanisms and molecular signatures of PGD remain a fundamental challenge. This pilot study examines if the pulmonary volatile organic compound (VOC) spectrum relate to PGD and postoperative outcomes. The VOC profiles of 58 bronchoalveolar lavage fluid (BALF) and blind bronchial aspirate samples from 35 transplant patients were extracted using solid-phase-microextraction and analyzed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. The support vector machine algorithm was used to identify VOCs that could differentiate patients with severe from lower grade PGD. Using 20 statistically significant VOCs from the sample headspace collected immediately after transplantation (< 6 h), severe PGD was differentiable from low PGD with an AUROC of 0.90 and an accuracy of 0.83 on test set samples. The model was somewhat effective for later time points with an AUROC of 0.80. Three major chemical classes in the model were dominated by alkylated hydrocarbons, linear hydrocarbons, and aldehydes in severe PGD samples. These VOCs may have important clinical and mechanistic implications, therefore large-scale study and potential translation to breath analysis is recommended.

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