title: Impact of Pre-analytic Blood Sample Collection Factors on Metabolomics.
abstract: Many epidemiologic studies are using metabolomics to discover markers of carcinogenesis. However, limited data are available on the influence of pre-analytic blood collection factors on metabolite measurement.
  
  
  
  We quantified 166 metabolites in archived plasma from 423 Health Professionals Follow-up Study and Nurses' Health Study participants using liquid chromatography-tandem mass spectrometry (LC-MS). We compared multivariable-adjusted geometric mean metabolite LC-MS peak areas across fasting time, season of blood collection, and time of day of blood collection categories.
  
  
  
  The majority of metabolites (160 of 166 metabolites) had geometric mean peak areas that were within 15% comparing samples donated after fasting 9 to 12 versus ≥13 hours; greater differences were observed in samples donated after fasting ≤4 hours. Metabolite peak areas generally were similar across season of blood collection, although levels of certain metabolites (e.g., bile acids and purines/pyrimidines) tended to be different in the summer versus winter months. After adjusting for fasting status, geometric mean peak areas for bile acids and vitamins, but not other metabolites, differed by time of day of blood collection.
  
  
  
  Fasting, season of blood collection, and time of day of blood collection were not important sources of variability in measurements of most metabolites in our study. However, considering blood collection variables in the design or analysis of studies may be important for certain specific metabolites, particularly bile acids, purines/pyrimidines, and vitamins.
  
  
  
  These results may be useful for investigators formulating analysis plans for epidemiologic metabolomics studies, including determining which metabolites to a priori exclude from analyses. Cancer Epidemiol Biomarkers Prev; 25(5); 823-9. ©2016 AACR.
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
authors.forename: Mary K
authors.initials: MK
authors.lastname: Townsend
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Bao
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Poole
authors.affiliation: Slone Epidemiology Center, Boston University, Boston, MA.
authors.forename: Kimberly A
authors.initials: KA
authors.lastname: Bertrand
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
authors.forename: Peter
authors.initials: P
authors.lastname: Kraft
authors.affiliation: Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.|Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA.
authors.forename: Brian M
authors.initials: BM
authors.lastname: Wolpin
authors.affiliation: Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA.
authors.forename: Clary B
authors.initials: CB
authors.lastname: Clish
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.|Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
authors.forename: Shelley S
authors.initials: SS
authors.lastname: Tworoger
mesh_terms: D000328:Adult; D000368:Aged; D001800:Blood Specimen Collection / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D055432:Metabolomics / Q000379:methods*; D008875:Middle Aged