• Lung Microbiome Profiles help identify at-risk Patients
    Sylvia Knapp
  • Konrad Hötzenecker

News & Views

Lung Microbiome Profiles help identify at-risk Patients

Feb 17 2022

Scientists from MedUni Vienna investigating deterioration in lung function, have discovered that the organ’s microbiome could be key to predicting future changes in its operational effectiveness.

Using Machine Learning, research groups led by Sylvia Knapp and Konrad Hötzenecker from the Department of Medicine I and Department of Thoracic Surgery, were able to show certain microbiome profiles of the lung post transplantation, have the capability to provide prognostic information. "This method therefore enables us to predict future changes in lung function – and so could help to identify at-risk patients early on," emphasises Knapp. Chronic Lung Allograft Dysfunction (CLAD ), affects up to 50% of lung transplant patients within the first five years following the procedure.

"We looked closely at how the environment of the lower airways changes over time in the allografts of a total of 78 patients following lung transplantation and adapts to the new host. For example, we investigated which bacteria, which immune cells and which metabolites are present and how these change in their new host," explains Knapp.

Moreover, the scientists discovered that certain bacteria, which are prevalent in some lung diseases prior to transplantation (e.g. in cystic fibrosis), can also move into the otherwise healthy lung following transplantation and become established. The conclusion: "That means that pre-existing conditions of the allograft recipient also determine the lung microbiome after transplantation."

Using Artificial Intelligence based on the analysis of the multiomics data – including not only the microbiome, but also the lipidome (lipid composition), the metabolome (metabolic building blocks of the cells) and clinical parameters – enabled them to predict changes in lung function. "Our calculations therefore show that certain microbiome profiles provide prognostic information," summarised Knapp and Hötzenecker.

"Multi-omics profiling predicts allograft function after lung transplantation". Martin L. Watzenböck, Anna-Dorothea Gorki, Federica Quattrone, Riem Gawish, Stefan Schwarz, Christopher Lambers, Peter Jaksch, Karin Lakovits, Sophie Zahalka, Nina Rahimi, Philipp Starkl, Dörte Symmank, Tyler Artner, Céline Pattaroni, Nikolaus Fortelny, Kristaps Klavins, Florian Frommlet, Benjamin J. Marsland, Konrad Hoetzenecker, Stefanie Widder, Sylvia Knapp. European Respiratory Journal 2021; DOI: 10.1183/13993003.03292-2020.

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