Metabolic Profiling Early Post-Allogeneic Haematopoietic Cell Transplantation in the Context of CMV Infection

Kirstine K. Rasmussen*, Quenia dos Santos, Cameron Ross MacPherson, Adrian G. Zucco, Lars Klingen Gjærde, Emma E. Ilett, Isabelle Lodding, Marie Helleberg, Jens D. Lundgren, Susanne D. Nielsen, Susanne Brix, Henrik Sengeløv, Daniel D. Murray

*Corresponding author for this work

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Abstract

Immune dysfunction resulting from allogeneic haematopoietic stem cell transplantation (aHSCT) predisposes one to an elevated risk of cytomegalovirus (CMV) infection. Changes in metabolism have been associated with adverse outcomes, and in this study, we explored the associations between metabolic profiles and post-transplantation CMV infection using plasma samples collected 7–33 days after aHSCT. We included 68 aHSCT recipients from Rigshospitalet, Denmark, 50% of whom experienced CMV infection between days 34–100 post-transplantation. First, we investigated whether 12 metabolites selected based on the literature were associated with an increased risk of post-transplantation CMV infection. Second, we conducted an exploratory network-based analysis of the complete metabolic and lipidomic profiles in relation to clinical phenotypes and biological pathways. Lower levels of trimethylamine N-oxide were associated with subsequent CMV infection (multivariable logistic regression: OR = 0.63; 95% CI = [0.41; 0.87]; p = 0.01). Explorative analysis revealed 12 clusters of metabolites or lipids, among which one was predictive of CMV infection, and the others were associated with conditioning regimens, age upon aHSCT, CMV serostatus, and/or sex. Our results provide evidence for an association between the metabolome and CMV infection post-aHSCT that is independent of known risk factors.

Original languageEnglish
Article number968
JournalMetabolites
Volume13
Issue number9
Number of pages11
ISSN2218-1989
DOIs
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

Keywords

  • aHSCT
  • CMV
  • correlation network analysis
  • cytomegalovirus
  • lipidomics
  • metabolomics
  • TMAO
  • WGCNA

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