Background Cold syndrome CS and Heat syndrome ( H S)S), with the opposite clinical manifestations, are two main syndrome types of pediatric community acquired pneumonia ( in Traditional Chinese medicine TCM )). According to research of syndrome types among CAP children, about 2.92% of them can be identified with CS while 91.25% with HS. This study aim s t o analyze plasma metabolic profiles and find out potential biomarkers for distinguishing H S from CS.
Methods A total of 296 patients and 55 healthy controls (HC) were divided into discovery group ( n =213, HS=160, CS=23, HC= 30) and validation group N=138, HS=93, CS=20, HC = Plasma metabolic profiles were detected by ultra performance liquid chromatography combined with linear ion trap quadrupole-Orbitrap mass spectrometry (UPLC/LTQ Orbitrap MS) in both positive and negative mode. Finally, plasma metabolic profiles were obtained through principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS DA)DA). Differential metabolites in CS and HS were screened by counting the value of fold change (FC 1.5 or 0.667 P value ( P 0.05 ) and false discovery rate (FDR 0.05 Diagnostic accuracy of potential biomarkers was evaluated by receiver operating characteristic (ROC) curve.
Results Among all metabolites 3 amino acids including alanine, phenylalanine, arginine, and 4 glycerophospholipids including lysoPC20:1, lysoPE16:0, lysoPE18:0, PE(16:0 22:6) were increased (FC 1.5 FDR 0.05) in CS versus HC . While 6 glycerophospholipids including PC(18:1 18:1), PC(20:4 20:4), lysoPE 20:4, lysoPE 18:2, lysoPE 22:6 and
PE(16:0 18:2) were decreased (FC 0. 667 FDR 0.05) in HS versus HC. However, Ceramide(d18:1 24:1) was increased in HS versus HC . Differential metabolites were mainly involved in amino acid, glycerophospholipid and linoleic acid metabolism via KEGG pathway analysis P<0.05) and they all exhibited good diagnostic abilities with ROC analysis AUC 0.9 54 Mo reover, lyso PC20:1, lysoPE16:0, lysoPE18:2, lysoPE20:4, lysoPE22:6, PC(18:1_18:1), PC(20:4_20: and PC(P 16:0_22:4) may serve as potential biomarkers for distinguishing HS from CS.
Conclusions Plasma metabolism of amino acids and lipids (triglyceride, glycerophospholipid and sphingomyelin were largely disturbed in CAP children with CS or HS. Among them, detection of glycerophospholipids via metabolomics can help diagnose these two syndrome types on clinic.