BACKGROUND: Acute graft-versus-host disease (aGvHD) is a major factor that limits the successful outcomes of allogeneic hematopoietic cell transplantation (alloHSCT). Currently there are few validated biomarkers that can help predict the risk of aGvHD in clinical settings. METHODS: We performed an integrated metabolomics and transcriptomics study and identified biomarkers that distinguish alloHSCT recipients with aGvHD from alloHSCT recipients without aGvHD in two separate cohorts. RESULTS: Pathway analysis of 38 significantly altered metabolites and 1148 differentially expressed genes uncovered a distinctly altered glycerophospholipid (GPL) metabolism network. Subsequently, we developed an aGvHD risk score (GRS) based on 5 metabolites markers from GPL metabolism to predict the risk of aGvHD. GRS showed a positive predictive value of 92.2% and 89.6% in the training and validation cohorts, respectively. In addition, high GRS was correlated with poor overall survival. Gene expressions of GPL-related lipases were significantly altered in aGvHD samples, leading to dysregulated GPLs. CONCLUSIONS: Using integrative "Omic" analysis, we unraveled a comprehensive view of the molecular perturbations underlying the pathogenesis of aGvHD. Our work represents an initial investigation of a unique metabolic and transcriptomic network that may help identify aGvHD at an early stage and facilitate preemptive therapy. FUNDING: National Natural Science Foundation of China (NSFC; 81530047, 81870143, 81470321, 81770160, 81270567, 81270638, 81573396, 81703674). Shanghai Sailing Program from Science and Technology Commission Shanghai Municipality (17YF1424700). Scholarship from Shanghai Municipal Health and Family Planning Commission (2017BR012). Special Clinical Research in Health Industry in Shanghai (20184Y0054).
BACKGROUND: Acute graft-versus-host disease (aGvHD) is a major factor that limits the successful outcomes of allogeneic hematopoietic cell transplantation (alloHSCT). Currently there are few validated biomarkers that can help predict the risk of aGvHD in clinical settings. METHODS: We performed an integrated metabolomics and transcriptomics study and identified biomarkers that distinguish alloHSCT recipients with aGvHD from alloHSCT recipients without aGvHD in two separate cohorts. RESULTS: Pathway analysis of 38 significantly altered metabolites and 1148 differentially expressed genes uncovered a distinctly altered glycerophospholipid (GPL) metabolism network. Subsequently, we developed an aGvHD risk score (GRS) based on 5 metabolites markers from GPL metabolism to predict the risk of aGvHD. GRS showed a positive predictive value of 92.2% and 89.6% in the training and validation cohorts, respectively. In addition, high GRS was correlated with poor overall survival. Gene expressions of GPL-related lipases were significantly altered in aGvHD samples, leading to dysregulated GPLs. CONCLUSIONS: Using integrative "Omic" analysis, we unraveled a comprehensive view of the molecular perturbations underlying the pathogenesis of aGvHD. Our work represents an initial investigation of a unique metabolic and transcriptomic network that may help identify aGvHD at an early stage and facilitate preemptive therapy. FUNDING: National Natural Science Foundation of China (NSFC; 81530047, 81870143, 81470321, 81770160, 81270567, 81270638, 81573396, 81703674). Shanghai Sailing Program from Science and Technology Commission Shanghai Municipality (17YF1424700). Scholarship from Shanghai Municipal Health and Family Planning Commission (2017BR012). Special Clinical Research in Health Industry in Shanghai (20184Y0054).
Entities:
Keywords:
Bone marrow transplantation; Metabolism; Transplantation
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