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Identification of Human Plasma Metabolites Exhibiting Time-of-Day Variation Using an Untargeted Liquid Chromatography–Mass Spectrometry Metabolomic Approach
| Content Provider | Scilit |
|---|---|
| Author | Ang, Joo Ern Revell, Victoria Anuska, Mann Mäntele, Simone Otway, Daniella T. Johnston, Jonathan D. Thumser, Alfred E. Skene, Debra J. Raynaud, Florence |
| Copyright Year | 2012 |
| Abstract | Although daily rhythms regulate multiple aspects of human physiology, rhythmic control of the metabolome remains poorly understood. The primary objective of this proof-of-concept study was identification of metabolites in human plasma that exhibit significant 24-h variation. This was assessed via an untargeted metabolomic approach using liquid chromatography-mass spectrometry (LC-MS). Eight lean, healthy, and unmedicated men, mean age 53.6 (SD ± 6.0) yrs, maintained a fixed sleep/wake schedule and dietary regime for 1 wk at home prior to an adaptation night and followed by a 25-h experimental session in the laboratory where the light/dark cycle, sleep/wake, posture, and calorific intake were strictly controlled. Plasma samples from each individual at selected time points were prepared using liquid-phase extraction followed by reverse-phase LC coupled to quadrupole time-of-flight MS analysis in positive ionization mode. Time-of-day variation in the metabolites was screened for using orthogonal partial least square discrimination between selected time points of 10:00 vs. 22:00 h, 16:00 vs. 04:00 h, and 07:00 (d 1) vs. 16:00 h, as well as repeated-measures analysis of variance with time as an independent variable. Subsequently, cosinor analysis was performed on all the sampled time points across the 24-h day to assess for significant daily variation. In this study, analytical variability, assessed using known internal standards, was low with coefficients of variation <10%. A total of 1069 metabolite features were detected and 203 (19%) showed significant time-of-day variation. Of these, 34 metabolites were identified using a combination of accurate mass, tandem MS, and online database searches. These metabolites include corticosteroids, bilirubin, amino acids, acylcarnitines, and phospholipids; of note, the magnitude of the 24-h variation of these identified metabolites was large, with the mean ratio of oscillation range over MESOR (24-h time series mean) of 65% (95% confidence interval [CI]: 49-81%). Importantly, several of these human plasma metabolites, including specific acylcarnitines and phospholipids, were hitherto not known to be 24-h variant. These findings represent an important baseline and will be useful in guiding the design and interpretation of future metabolite-based studies. (Author correspondence: Jooern.Ang@icr.ac.uk or Florence.Raynaud@icr.ac.uk ) |
| Related Links | https://core.ac.uk/download/pdf/9550209.pdf http://www.tandfonline.com/doi/pdf/10.3109/07420528.2012.699122?needAccess=true https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3433180/pdf |
| Ending Page | 881 |
| Page Count | 14 |
| Starting Page | 868 |
| ISSN | 07420528 |
| e-ISSN | 15256073 |
| DOI | 10.3109/07420528.2012.699122 |
| Journal | Chronobiology international |
| Issue Number | 7 |
| Volume Number | 29 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2012-07-23 |
| Access Restriction | Open |
| Subject Keyword | Journal: Chronobiology International Biochemical Research Acylcarnitines Daily Variation Human Liquid Chromatography–mass Spectrometry Metabolomics Plasma Metabolites |
| Content Type | Text |
| Resource Type | Article |
| Subject | Physiology Physiology (medical) |
