Frontiers in Immunology (Apr 2023)

Clinical relevance of cell-free DNA quantification and qualification during the first month after lung transplantation

  • Pascal Pedini,
  • Pascal Pedini,
  • Benjamin Coiffard,
  • Nicem Cherouat,
  • Sylvia Casas,
  • Frédéric Fina,
  • Audrey Boutonnet,
  • Jean Baptiste Baudey,
  • Printil Aho,
  • Agnes Basire,
  • Sophie Simon,
  • Coralie Frassati,
  • Jacques Chiaroni,
  • Jacques Chiaroni,
  • Martine Reynaud-Gaubert,
  • Christophe Picard,
  • Christophe Picard

DOI
https://doi.org/10.3389/fimmu.2023.1183949
Journal volume & issue
Vol. 14

Abstract

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BackgroundMany studies have reported the relevance of donor-derived cfDNA (dd-cfDNA) after lung transplantation (LTx) to diagnose and monitor acute rejection (AR) or chronic rejection or infection (INF). However, the analysis of cfDNA fragment size has not been studied. The aim of this study was to determine the clinical relevance of dd-cfDNA and cfDNA size profiles in events (AR and INF) during the first month after LTx.MethodsThis prospective, single-center study includes 62 LTx recipients at the Marseille Nord Hospital, France. Total cfDNA quantification was performed by fluorimetry and digital PCR, dd-cfDNA by NGS (AlloSeq cfDNA-CareDX®), and the size profile by BIABooster (Adelis®). A bronchoalveolar lavage and transbronchial biopsies at D30 established the following groups: not-injured and injured graft (AR, INF, or AR+INF).ResultsQuantification of total cfDNA was not correlated with the patient’s status at D30. The percentage of dd-cfDNA was significantly higher for injured graft patients at D30 (p=0.0004). A threshold of 1.72% of dd-cfDNA correctly classified the not-injured graft patients (negative predictive value of 91.4%). Among recipients with dd-cfDNA >1.72%, the quantification of small sizes (80-120bp) >3.70% identified the INF with high performance (specificity and positive predictive value of 100%).ConclusionWith the aim of considering cfDNA as a polyvalent non-invasive biomarker in transplantation, an algorithm combining the quantification of dd-cfDNA and small sizes of DNA may significantly classify the different types of allograft injuries.

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