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Multi-omics profiling predicts allograft function after lung transplantation
- Source :
- European Respiratory Journal. 59:2003292
- Publication Year :
- 2021
- Publisher :
- European Respiratory Society (ERS), 2021.
-
Abstract
- RationaleLung transplantation is the ultimate treatment option for patients with end-stage respiratory diseases but bears the highest mortality rate among all solid organ transplantations due to chronic lung allograft dysfunction (CLAD). The mechanisms leading to CLAD remain elusive due to an insufficient understanding of the complex post-transplant adaptation processes.ObjectivesTo better understand these lung adaptation processes after transplantation and to investigate their association with future changes in allograft function.MethodsWe performed an exploratory cohort study of bronchoalveolar lavage samples from 78 lung recipients and donors. We analysed the alveolar microbiome using 16S rRNA sequencing, the cellular composition using flow cytometry, as well as metabolome and lipidome profiling.Measurements and main resultsWe established distinct temporal dynamics for each of the analysed data sets. Comparing matched donor and recipient samples, we revealed that recipient-specific as well as environmental factors, rather than the donor microbiome, shape the long-term lung microbiome. We further discovered that the abundance of certain bacterial strains correlated with underlying lung diseases even after transplantation. A decline in forced expiratory volume during the first second (FEV1) is a major characteristic of lung allograft dysfunction in transplant recipients. By using a machine learning approach, we could accurately predict future changes in FEV1 from our multi-omics data, whereby microbial profiles showed a particularly high predictive power.ConclusionBronchoalveolar microbiome, cellular composition, metabolome and lipidome show specific temporal dynamics after lung transplantation. The lung microbiome can predict future changes in lung function with high precision.
- Subjects :
- Pulmonary and Respiratory Medicine
Lung microbiome
Lung
medicine.diagnostic_test
business.industry
Microbiota
medicine.medical_treatment
Lipidome
Allografts
Bioinformatics
Cohort Studies
Transplantation
medicine.anatomical_structure
Bronchoalveolar lavage
RNA, Ribosomal, 16S
Metabolome
Humans
Medicine
Lung transplantation
Microbiome
business
Lung Transplantation
Retrospective Studies
Subjects
Details
- ISSN :
- 13993003 and 09031936
- Volume :
- 59
- Database :
- OpenAIRE
- Journal :
- European Respiratory Journal
- Accession number :
- edsair.doi.dedup.....ed84150c608441b3b17ccbff7c5bea7f