The effect of pre-analytical conditions on blood metabolomics in epidemiological studies

Background: Serum and plasma are commonly used biofluids for large-scale metabolomic-epidemiology studies. Their metabolomic profile is susceptible to changes due to variability in pre-analytical conditions and the impact of this is unclear. Methods: Participant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (N=151 traits). Metabolic concentrations were compared between reference (pre-storage: 4C, 1.5h; post-storage: no sample preparation or NMR-analysis delays) and four, pre-storage, blood processing conditions, where samples were incubated at (i) 4C, 24h; (ii) 4C, 48h; (iii) 21C, 24h; (iv) 21C, 48h, before centrifugation; and two, post-storage, sample processing conditions in which samples (i) thawed overnight, then left for 24h before addition of sodium buffer followed by immediate NMR analysis; (ii) thawed overnight, addition of sodium buffer, then left for 24h before profiling. Linear regression models with random-intercepts were used to assess the impact of these six pre-analytical conditions on EDTA-plasma/serum metabolome. Results: Fatty acids, beta-hydroxybutyrate, glycoprotein-acetyls and most lipid-related traits, in serum and plasma, were robust to the tested pre and post-storage conditions. Pre-storage conditions impacted concentrations of glycolysis metabolites, acetate, albumin and amino-acids by levels that could potentially bias research results (up to 1.4SD difference compared with reference). Post-storage conditions affected histidine, phenylalanine and LDL-particle-size, with differences up to 1.4SD. Conclusions: Most metabolic traits are robust to the pre- and post-storage conditions tested here and that may commonly occur in large-scale cohorts. However, concentrations of glycolysis metabolites, and amino-acids may be compromised.