Dataset Information

Circadian and wake-dependent changes in human plasma polar metabolites during prolonged wakefulness: A preliminary analysis.

ABSTRACT: Establishing circadian and wake-dependent changes in the human metabolome are critical for understanding and treating human diseases due to circadian misalignment or extended wake. Here, we assessed endogenous circadian rhythms and wake-dependent changes in plasma metabolites in 13 participants (4 females) studied during 40-hours of wakefulness. Four-hourly plasma samples were analyzed by hydrophilic interaction liquid chromatography (HILIC)-LC-MS for 1,740 metabolite signals. Group-averaged (relative to DLMO) and individual participant metabolite profiles were fitted with a combined cosinor and linear regression model. In group-level analyses, 22% of metabolites were rhythmic and 8% were linear, whereas in individual-level analyses, 14% of profiles were rhythmic and 4% were linear. We observed metabolites that were significant at the group-level but not significant in a single individual, and metabolites that were significant in approximately half of individuals but not group-significant. Of the group-rhythmic and group-linear metabolites, only 7% and 12% were also significantly rhythmic or linear, respectively, in ?50% of participants. Owing to large inter-individual variation in rhythm timing and the magnitude and direction of linear change, acrophase and slope estimates also differed between group- and individual-level analyses. These preliminary findings have important implications for biomarker development and understanding of sleep and circadian regulation of metabolism.

SUBMITTER: Grant LK

PROVIDER: S-EPMC6418225 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Circadian and wake-dependent changes in human plasma polar metabolites during prolonged wakefulness: A preliminary analysis.

Grant Leilah K LK Ftouni Suzanne S Nijagal Brunda B De Souza David P DP Tull Dedreia D McConville Malcolm J MJ Rajaratnam Shantha M W SMW Lockley Steven W SW Anderson Clare C

Scientific reports 20190314 1

Establishing circadian and wake-dependent changes in the human metabolome are critical for understanding and treating human diseases due to circadian misalignment or extended wake. Here, we assessed endogenous circadian rhythms and wake-dependent changes in plasma metabolites in 13 participants (4 females) studied during 40-hours of wakefulness. Four-hourly plasma samples were analyzed by hydrophilic interaction liquid chromatography (HILIC)-LC-MS for 1,740 metabolite signals. Group-averaged (re ...[more]

PMID: 30872634

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Project description:Measuring individual circadian phase is important to diagnose and treat circadian rhythm sleep-wake disorders and circadian misalignment, inform chronotherapy, and advance circadian science. Initial findings using blood transcriptomics to predict the circadian phase marker dim-light melatonin onset (DLMO) show promise. Alternatively, there are limited attempts using metabolomics to predict DLMO and no known omics-based biomarkers predict dim-light melatonin offset (DLMOff). We analyzed the human plasma metabolome during adequate and insufficient sleep to predict DLMO and DLMOff using one blood sample. Sixteen (8 male/8 female) healthy participants aged 22.4 ± 4.8 years (mean ± SD) completed an in-laboratory study with 3 baseline days (9 h sleep opportunity/night), followed by a randomized cross-over protocol with 9-h adequate sleep and 5-h insufficient sleep conditions, each lasting 5 days. Blood was collected hourly during the final 24 h of each condition to independently determine DLMO and DLMOff. Blood samples collected every 4 h were analyzed by untargeted metabolomics and were randomly split into training (68%) and test (32%) sets for biomarker analyses. DLMO and DLMOff biomarker models were developed using partial least squares regression in the training set followed by performance assessments using the test set. At baseline, the DLMOff model showed the highest performance (0.91 R2 and 1.1 ± 1.1 h median absolute error ± interquartile range [MdAE ± IQR]), with significantly (p < 0.01) lower prediction error versus the DLMO model. When all conditions (baseline, 9 h, and 5 h) were included in performance analyses, the DLMO (0.60 R2; 2.2 ± 2.8 h MdAE; 44% of the samples with an error under 2 h) and DLMOff (0.62 R2; 1.8 ± 2.6 h MdAE; 51% of the samples with an error under 2 h) models were not statistically different. These findings show promise for metabolomics-based biomarkers of circadian phase and highlight the need to test biomarkers that predict multiple circadian phase markers under different physiological conditions.

Dataset Information

Circadian and wake-dependent changes in human plasma polar metabolites during prolonged wakefulness: A preliminary analysis.

Publications

Circadian and wake-dependent changes in human plasma polar metabolites during prolonged wakefulness: A preliminary analysis.

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