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Reproducibility of non-fasting plasma metabolomics measurements across processing delays.
Wang, Ying; Carter, Brian D; Gapstur, Susan M; McCullough, Marjorie L; Gaudet, Mia M; Stevens, Victoria L.
Afiliação
  • Wang Y; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA. ying.wang@cancer.org.
  • Carter BD; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
  • Gapstur SM; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
  • McCullough ML; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
  • Gaudet MM; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
  • Stevens VL; Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
Metabolomics ; 14(10): 129, 2018 09 25.
Article em En | MEDLINE | ID: mdl-30830406
INTRODUCTION: Processing delays after blood collection is a common pre-analytical condition in large epidemiologic studies. It is critical to evaluate the suitability of blood samples with processing delays for metabolomics analysis as it is a potential source of variation that could attenuate associations between metabolites and disease outcomes. OBJECTIVES: We aimed to evaluate the reproducibility of metabolites over extended processing delays up to 48 h. We also aimed to test the reproducibility of the metabolomics platform. METHODS: Blood samples were collected from 18 healthy volunteers. Blood was stored in the refrigerator and processed for plasma at 0, 15, 30, and 48 h after collection. Plasma samples were metabolically profiled using an untargeted, ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) platform. Reproducibility of 1012 metabolites over processing delays and reproducibility of the platform were determined by intraclass correlation coefficients (ICCs) with variance components estimated from mixed-effects models. RESULTS: The majority of metabolites (approximately 70% of 1012) were highly reproducible (ICCs ≥ 0.75) over 15-, 30- or 48-h processing delays. Nucleotides, energy-related metabolites, peptides, and carbohydrates were most affected by processing delays. The platform was highly reproducible with a median technical ICC of 0.84 (interquartile range 0.68-0.93). CONCLUSION: Most metabolites measured by the UPLC-MS/MS platform show acceptable reproducibility up to 48-h processing delays. Metabolites of certain pathways need to be interpreted cautiously in relation to outcomes in epidemiologic studies with prolonged processing delays.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Carboidratos / Metabolômica / Nucleotídeos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Carboidratos / Metabolômica / Nucleotídeos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article