Zhi Zhou1, Yanhua Chen1, Jiuming He1, Jing Xu1, Ruiping Zhang1, Yan Mao2, Zeper Abliz1,3. 1. State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China. 2. Xinjiang Institute of Materia Medica, Urumqi 830004, China. 3. Minzu University of China, Beijing 100081, P. R. China.
Abstract
AIM: In metabolomics research, the use of different blood collection methods may influence endogenous metabolites. MATERIALS & METHODS: Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants. RESULTS: Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma.
AIM: In metabolomics research, the use of different blood collection methods may influence endogenous metabolites. MATERIALS & METHODS: Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants. RESULTS: Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma.
Authors: Michael R La Frano; Suzan L Carmichael; Chen Ma; Macy Hardley; Tong Shen; Ron Wong; Lorenzo Rosales; Kamil Borkowski; Theresa L Pedersen; Gary M Shaw; David K Stevenson; Oliver Fiehn; John W Newman Journal: Metabolomics Date: 2018-11-15 Impact factor: 4.290