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The molecular features of chronic lung allograft dysfunction in lung transplant airway mucosa

K. Halloran, M. Mackova, MD. Parkes, A. Hirji, J. Weinkauf, IL. Timofte, GI. Snell, GP. Westall, R. Lischke, A. Zajacova, J. Havlin, R. Hachem, D. Kreisel, D. Levine, B. Kubisa, M. Piotrowska, S. Juvet, S. Keshavjee, P. Jaksch, W. Klepetko, PF. Halloran

. 2022 ; 41 (12) : 1689-1699. [pub] 20220827

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc22032411

BACKGROUND: Many lung transplants fail due to chronic lung allograft dysfunction (CLAD). We recently showed that transbronchial biopsies (TBBs) from CLAD patients manifest severe parenchymal injury and dedifferentiation, distinct from time-dependent changes. The present study explored time-selective and CLAD-selective transcripts in mucosal biopsies from the third bronchial bifurcation (3BMBs), compared to those in TBBs. METHODS: We used genome-wide microarray measurements in 324 3BMBs to identify CLAD-selective changes as well as time-dependent changes and develop a CLAD classifier. CLAD-selective transcripts were identified with linear models for microarray data (limma) and were used to build an ensemble of 12 classifiers to predict CLAD. Hazard models and random forests were then used to predict the risk of graft loss using the CLAD classifier, transcript sets associated with rejection, injury, and time. RESULTS: T cell-mediated rejection and donor-specific antibody were increased in CLAD 3BMBs but most had no rejection. Like TBBs, 3BMBs showed a time-dependent increase in transcripts expressed in inflammatory cells that was not associated with CLAD or survival. Also like TBBs, the CLAD-selective transcripts in 3BMBs reflected severe parenchymal injury and dedifferentiation, not inflammation or rejection. While 3BMBs and TBBs did not overlap in their top 20 CLAD-selective transcripts, many CLAD-selective transcripts were significantly increased in both for example LOXL1, an enzyme controlling matrix remodeling. In Cox models for one-year survival, the 3BMB CLAD-selective transcripts and CLAD classifier predicted graft loss and correlated with CLAD stage. Many 3BMB CLAD-selective transcripts were also increased by injury in kidney transplants and correlated with decreased kidney survival, including LOXL1. CONCLUSIONS: Mucosal and transbronchial biopsies from CLAD patients reveal a diffuse molecular injury and dedifferentiation state that impacts prognosis and correlates with the physiologic disturbances. CLAD state in lung transplants shares features with failing kidney transplants, indicating elements shared by the injury responses of distressed organs.

Citace poskytuje Crossref.org

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$a BACKGROUND: Many lung transplants fail due to chronic lung allograft dysfunction (CLAD). We recently showed that transbronchial biopsies (TBBs) from CLAD patients manifest severe parenchymal injury and dedifferentiation, distinct from time-dependent changes. The present study explored time-selective and CLAD-selective transcripts in mucosal biopsies from the third bronchial bifurcation (3BMBs), compared to those in TBBs. METHODS: We used genome-wide microarray measurements in 324 3BMBs to identify CLAD-selective changes as well as time-dependent changes and develop a CLAD classifier. CLAD-selective transcripts were identified with linear models for microarray data (limma) and were used to build an ensemble of 12 classifiers to predict CLAD. Hazard models and random forests were then used to predict the risk of graft loss using the CLAD classifier, transcript sets associated with rejection, injury, and time. RESULTS: T cell-mediated rejection and donor-specific antibody were increased in CLAD 3BMBs but most had no rejection. Like TBBs, 3BMBs showed a time-dependent increase in transcripts expressed in inflammatory cells that was not associated with CLAD or survival. Also like TBBs, the CLAD-selective transcripts in 3BMBs reflected severe parenchymal injury and dedifferentiation, not inflammation or rejection. While 3BMBs and TBBs did not overlap in their top 20 CLAD-selective transcripts, many CLAD-selective transcripts were significantly increased in both for example LOXL1, an enzyme controlling matrix remodeling. In Cox models for one-year survival, the 3BMB CLAD-selective transcripts and CLAD classifier predicted graft loss and correlated with CLAD stage. Many 3BMB CLAD-selective transcripts were also increased by injury in kidney transplants and correlated with decreased kidney survival, including LOXL1. CONCLUSIONS: Mucosal and transbronchial biopsies from CLAD patients reveal a diffuse molecular injury and dedifferentiation state that impacts prognosis and correlates with the physiologic disturbances. CLAD state in lung transplants shares features with failing kidney transplants, indicating elements shared by the injury responses of distressed organs.
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$a Mackova, Martina $u University of Alberta, Edmonton, Alberta, Canada
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$a Timofte, Irina L $u University of Maryland, Baltimore, Maryland
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$a Snell, Greg I $u Alfred Hospital Lung Transplant Service, Melbourne, Victoria, Australia
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$a Westall, Glen P $u Alfred Hospital Lung Transplant Service, Melbourne, Victoria, Australia
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$a Lischke, Robert $u University Hospital Motol, Prague, Czech Republic
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$a Zajacova, Andrea $u University Hospital Motol, Prague, Czech Republic
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$a Havlin, Jan $u University Hospital Motol, Prague, Czech Republic
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$a Kreisel, Daniel $u Washington University in St Louis, St. Louis, Missouri
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$a Levine, Deborah $u University of Texas at San Antonio, San Antonio, Texas
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$a Kubisa, Bartosz $u Pomeranian Medical University, Szczecin, Poland
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$a Piotrowska, Maria $u Pomeranian Medical University, Szczecin, Poland
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$a Juvet, Stephen $u Toronto Lung Transplant Program, University Health Network, Toronto, Ontario, Canada
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$a Keshavjee, Shaf $u Toronto Lung Transplant Program, University Health Network, Toronto, Ontario, Canada
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$a Jaksch, Peter $u Medical University of Vienna, Vienna, Austria
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$a Klepetko, Walter $u Medical University of Vienna, Vienna, Austria
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