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Cited by 139Metabolomics and Mass Spectrometry StudiesCircadian rhythm and melatoninSleep and Work-Related Fatigue

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Identification of Human Plasma Metabolites Exhibiting Time-of-Day Variation Using an Untargeted Liquid Chromatography–Mass Spectrometry Metabolomic Approach

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Ang, Joo Ern, Revell, Victoria, Mann, Anuska, Mäntele, Simone, Otway, Daniella T., Johnston, Jonathan D., Thumser, Alfred E., Skene, Debra J., Raynaud, Florence·2012·Chronobiology International
DOI 10.3109/07420528.2012.699122PMC PMC3433180
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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.

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Crossref · 10.3109/07420528.2012.699122

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Figures

FIGURE 1 Flowchart summarizing data analysis workflow.
FIGURE 1 Flowchart summarizing data analysis workflow.CC BY · PubMed Central
FIGURE 2 Time profiles of four plasma metabolites with different acrophases: (a) acetylcarnitine, (b) LysoPE(18:1), (c) proline, and (d) cortisol. On the horizontal axis, black bar indicates lights-off (0 lux) and white bar lights-on (440–825 lux). Internal standard (IS) shows the analytical variation of each ion in the pooled, replicate samples analyzed throughout the LC-MS run.
FIGURE 2 Time profiles of four plasma metabolites with different acrophases: (a) acetylcarnitine, (b) LysoPE(18:1), (c) proline, and (d) cortisol. On the horizontal axis, black bar indicates lights-off (0 lux) and white bar lights-on (440–825 lux). Internal standard (IS) shows the analytical variation of each ion in the pooled, replicate samples analyzed throughout the LC-MS run.CC BY · PubMed Central
FIGURE 3 Plasma acetylcarnitine profiles for eight individuals maintained under controlled light/dark, sleep/wake, posture, and calorific intake conditions. Black bar indicates lights-off (0 lux) and white bar lights-on (440–825 lux).
FIGURE 3 Plasma acetylcarnitine profiles for eight individuals maintained under controlled light/dark, sleep/wake, posture, and calorific intake conditions. Black bar indicates lights-off (0 lux) and white bar lights-on (440–825 lux).CC BY · PubMed Central
FIGURE 4 (Top panel) The temporal profile of palmitoylcarnitine in human plasma. (Bottom panel) CPT1a gene expression in a mouse model from an independent study (Hughes et al., 2009). Black/gray bars indicate lights-off and the white bar lights-on.
FIGURE 4 (Top panel) The temporal profile of palmitoylcarnitine in human plasma. (Bottom panel) CPT1a gene expression in a mouse model from an independent study (Hughes et al., 2009). Black/gray bars indicate lights-off and the white bar lights-on.CC BY · PubMed Central
SUPPLEMENTARY FIGURE 1 Venn diagram showing overlapping sets of metabolite features detected by OPLS-DA of paired time points and repeated-measures ANOVA across all time points.
SUPPLEMENTARY FIGURE 1 Venn diagram showing overlapping sets of metabolite features detected by OPLS-DA of paired time points and repeated-measures ANOVA across all time points.CC BY · PubMed Central
SUPPLEMENTARY FIGURE 2 Plasma profiles of metabolite feature with mass/charge 455.19 Da and retention time 5.7 min for eight individuals detected by repeated-measures ANOVA but not pairwise OPLS-DA comparisons, illustrating higher intersubject variability relative to intrasubject time-of-day variation. All participants were maintained under controlled light/dark, sleep/wake, posture, and calorific intake conditions. Black bar indicates lights-off (0 lux) and white bar lights-on (440–825 lux).
SUPPLEMENTARY FIGURE 2 Plasma profiles of metabolite feature with mass/charge 455.19 Da and retention time 5.7 min for eight individuals detected by repeated-measures ANOVA but not pairwise OPLS-DA comparisons, illustrating higher intersubject variability relative to intrasubject time-of-day variation. All participants were maintained under controlled light/dark, sleep/wake, posture, and calorific intake conditions. Black bar indicates lights-off (0 lux) and white bar lights-on (440–825 lux).CC BY · PubMed Central

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Citations

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Research works printed but not linked: 4

  1. Horne JA, 1976, Int. J. Chronobiol, 4, 97
  2. Nelson W, 1979, Chronobiologia, 6, 305
  3. Pandher R, 2012, Metabolomics., 317
  4. Schofield WN, 1985, Hum. Nutr. Clin. Nutr., 39, 5

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Metadata

Authors
Ang, J. E., Revell, V., Mann, A., Mäntele, S., Otway, D. T., Johnston, J. D., Thumser, A. E., Skene, D. J., & Raynaud, F.
Affiliations
  • Institute of Cancer Research (GB)
  • University of Surrey (GB)
Corresponding author
  • Ang, Joo Ern
  • Raynaud, Florence
ORCID
Venue
Chronobiology International
Publisher
Informa UK Limited
Published
2012-07-23
Volume
29
Issue
7
Pages
868-881
ISSN
  • 0742-0528 (ISSN-L)
  • 1525-6073
DOI
10.3109/07420528.2012.699122
PMC
PMC3433180
OpenAlex
W2043615829
Cited by
138
References
35
Citations by year
2026: 5 · 2025: 6 · 2024: 8 · 2023: 14 · 2022: 12 · 2021: 14 · 2020: 14 · 2019: 9 · 2018: 8 · 2017: 10 · 2016: 12 · 2015: 13 · 2014: 9 · 2013: 4
FWCI
3.47
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Chronobiology International (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Surrey Research Insight Open Access (The University of Surrey) (submittedVersion)
Funders
  • Wellcome Trust (090952/Z/09/Z)
  • Cancer Research UK (11566, C309/A8274, C309/A2187)
  • Biotechnology and Biological Sciences Research Council (BB/I019405/1, BB/D526853/1)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
Keywords
circadian rhythm, diurnal variation, plasma metabolites, acylcarnitines, phospholipids, corticosteroids, bilirubin, amino acids, daily rhythms, cosinor analysis, untargeted metabolomics, sleep timing, metabolite identification
MeSH terms
Acetylcarnitine, Blood Chemical Analysis, Chromatography, Liquid, Circadian Rhythm, Humans, Hydrocortisone, Lysophospholipids, Male, Middle Aged, Proline, Mass Spectrometry, Metabolomics, Metabolome

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