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 2 separate cohorts.RESULTS Pathway analysis of 38 significantly altered metabolites and 1,148 differentially expressed genes uncovered a distinctly altered glycerophospholipid (GPL) metabolism network. Subsequently, we developed an aGvHD risk score (GRS) based on 5 metabolite 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.CONCLUSION 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) provided funding for material, processing, metabolomics, and transcriptomics studies. This work was also supported by Shanghai Sailing Program from Science and Technology Commission Shanghai Municipality (17YF1424700), the Scholarship from Shanghai Municipal Health and Family Planning Commission (2017BR012), and the Special Clinical Research in Health Industry in Shanghai (20184Y0054). The projects supporting young scholars are 17YF1424700 (to YL), 2017BR012 (to XH), and 20184Y0054 (to QC).
Yue Liu, Aijie Huang, Qi Chen, Xiaofei Chen, Yang Fei, Xiaoming Zhao, Weiping Zhang, Zhanying Hong, Zhenyu Zhu, Jianmin Yang, Yifeng Chai, Jianmin Wang, Xiaoxia Hu
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