Frontiers in Immunology (Aug 2024)

Identification of predictive models including polymorphisms in cytokines genes and clinical variables associated with post-transplant complications after identical HLA-allogeneic stem cell transplantation

  • Paula Muñiz,
  • Paula Muñiz,
  • María Martínez-García,
  • María Martínez-García,
  • Rebeca Bailén,
  • Rebeca Bailén,
  • María Chicano,
  • María Chicano,
  • Gillen Oarbeascoa,
  • Gillen Oarbeascoa,
  • Juan Carlos Triviño,
  • Ismael de la Iglesia-San Sebastian,
  • Ismael de la Iglesia-San Sebastian,
  • Sara Fernández de Córdoba,
  • Sara Fernández de Córdoba,
  • Javier Anguita,
  • Javier Anguita,
  • Mi Kwon,
  • Mi Kwon,
  • José Luis Díez-Martín,
  • José Luis Díez-Martín,
  • José Luis Díez-Martín,
  • Pablo M. Olmos,
  • Pablo M. Olmos,
  • Carolina Martínez-Laperche,
  • Carolina Martínez-Laperche,
  • Ismael Buño,
  • Ismael Buño,
  • Ismael Buño,
  • Ismael Buño

DOI
https://doi.org/10.3389/fimmu.2024.1396284
Journal volume & issue
Vol. 15

Abstract

Read online

BackgroundsAlthough allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a potentially curative therapy for hematological malignancies, it can be associated with relevant post-transplant complications. Several reports have shown that polymorphisms in immune system genes are correlated with the development of post-transplant complications. Within this context, this work focuses on identifying novel polymorphisms in cytokine genes and developing predictive models to anticipate the risk of developing graft-versus-host disease (GVHD), transplantation-related mortality (TRM), relapse and overall survival (OS).MethodsOur group developed a 132-cytokine gene panel which was tested in 90 patients who underwent an HLA-identical sibling-donor allo-HSCT. Bayesian logistic regression (BLR) models were used to select the most relevant variables. Based on the cut-off points selected for each model, patients were classified as being at high or low-risk for each of the post-transplant complications (aGVHD II-IV, aGVHD III-IV, cGVHD, mod-sev cGVHD, TRM, relapse and OS).ResultsA total of 737 polymorphisms were selected from the custom panel genes. Of these, 41 polymorphisms were included in the predictive models in 30 cytokine genes were selected (17 interleukins and 13 chemokines). Of these polymorphisms, 5 (12.2%) were located in coding regions, and 36 (87.8%) in non-coding regions. All models had a statistical significance of p<0.0001.ConclusionOverall, genomic polymorphisms in cytokine genes make it possible to anticipate the development all complications studied following allo-HSCT and, consequently, to optimize the clinical management of patients.

Keywords