Airway molecular signatures in antibody-mediated lung transplant rejection

Severe antibody-mediated rejection (AMR) is associated with chronic lung allograft dysfunction (CLAD) and death in lung transplant recipients. However, AMR diagnostics are imprecise, and new biomarkers are needed. We assessed whether airway inflammation gene signatures could distinguish AMR cases from controls. We analyzed small airway brush RNA sequencing from 16 AMR cases and 39 controls across 2 centers. We compared gene signatures for complement activation, molecular target of rapamycin (mTOR) signaling, and natural killer cell-mediated injury. Differential gene expression and pathway analyses sought AMR molecular features. Additionally, we evaluated the airway inflammation 2 (AI2) score, previously associated with CLAD and graft failure, in relation to AMR clinical features and survival outcomes. AMR airway brushes demonstrated transcriptional evidence of airway inflammation and upregulation of complement and natural killer cell pathways. The AI2 score was significantly elevated in AMR cases (P < .001) and was associated with AMR-compatible histology, donor-specific antibodies, complement binding, and acute graft dysfunction. Increasing AI2 scores were associated with worse retransplant-free survival, independent of other AMR features. In small airways, lung transplant AMR predominantly exhibits molecular features of cellular rejection rather than a distinct humoral rejection profile. Airway brush transcriptomics may provide a valuable tool for characterizing and prognosticating suspected AMR.

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Publication Details

Journal
American Journal of Transplantation
Published
2026-02-01
DOI
https://doi.org/10.1016/j.ajt.2026.02.002
Primary Topic
Transplantation: Methods and Outcomes
Type
article
Field-Weighted Citation Impact
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article

Airway molecular signatures in antibody-mediated lung transplant rejection

Jeffrey A. Golden, Nicholas A. Kolaitis, Carlo J. Iasella, Kaitlyn Devonshire et al.
American Journal of Transplantation
Transplantation: Methods and Outcomes
article

Airway molecular signatures in antibody-mediated lung transplant rejection

Jeffrey A. Golden, Nicholas A. Kolaitis, Carlo J. Iasella, Kaitlyn Devonshire, Steven Hays, Aida Venado Estrada, Kaveh Moghbeli, Rupal Shah, Amanda Zeng, Kong Chen, John F. McDyer, John R. Greenland, Jonathan P. Singer, Daniel R. Calabrese, Lorriana E. Leard, Rashmi Prava Mohanty, Charles R. Langelier
article en

Abstract

Severe antibody-mediated rejection (AMR) is associated with chronic lung allograft dysfunction (CLAD) and death in lung transplant recipients. However, AMR diagnostics are imprecise, and new biomarkers are needed. We assessed whether airway inflammation gene signatures could distinguish AMR cases from controls. We analyzed small airway brush RNA sequencing from 16 AMR cases and 39 controls across 2 centers. We compared gene signatures for complement activation, molecular target of rapamycin (mTOR) signaling, and natural killer cell-mediated injury. Differential gene expression and pathway analyses sought AMR molecular features. Additionally, we evaluated the airway inflammation 2 (AI2) score, previously associated with CLAD and graft failure, in relation to AMR clinical features and survival outcomes. AMR airway brushes demonstrated transcriptional evidence of airway inflammation and upregulation of complement and natural killer cell pathways. The AI2 score was significantly elevated in AMR cases (P < .001) and was associated with AMR-compatible histology, donor-specific antibodies, complement binding, and acute graft dysfunction. Increasing AI2 scores were associated with worse retransplant-free survival, independent of other AMR features. In small airways, lung transplant AMR predominantly exhibits molecular features of cellular rejection rather than a distinct humoral rejection profile. Airway brush transcriptomics may provide a valuable tool for characterizing and prognosticating suspected AMR.

American Journal of Transplantation
University of Pittsburgh (US), University of California, San Francisco (US), University of California System (US), Chan Zuckerberg Initiative (United States) (US), San Francisco VA Health Care System (US)
Good health and well-being
Openalex Percentile: Top 58%
Transplantation: Methods and Outcomes
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