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Identification of human plasma metabolites exhibiting time-of-day variation using an untargeted liquid chromatography-mass spectrometry metabolomic approach.

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.

journal_name

Chronobiol Int

journal_title

Chronobiology international

authors

Ang JE,Revell V,Mann A,Mäntele S,Otway DT,Johnston JD,Thumser AE,Skene DJ,Raynaud F

doi

10.3109/07420528.2012.699122

subject

Has Abstract

pub_date

2012-08-01 00:00:00

pages

868-81

issue

eissn

0742-0528

issn

1525-6073

journal_volume

pub_type

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Identification of human plasma metabolites exhibiting time-of-day variation using an untargeted liquid chromatography-mass spectrometry metabolomic approach.