2017
DOI: 10.7554/elife.20214
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Blood transcriptome based biomarkers for human circadian phase

Abstract: Diagnosis and treatment of circadian rhythm sleep-wake disorders both require assessment of circadian phase of the brain’s circadian pacemaker. The gold-standard univariate method is based on collection of a 24-hr time series of plasma melatonin, a suprachiasmatic nucleus-driven pineal hormone. We developed and validated a multivariate whole-blood mRNA-based predictor of melatonin phase which requires few samples. Transcriptome data were collected under normal, sleep-deprivation and abnormal sleep-timing condi… Show more

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Cited by 125 publications
(166 citation statements)
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References 79 publications
(131 reference statements)
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“…While sleep quality is inherently subjective, objectively measurable correlates of poor sleep quality have been proposed, including frequency of arousals [41] and sleep discontinuity [42]. Likewise, while circadian phase preference is inherently subjective, the timing of the circadian pacemaker (biological clock) can be measured objectively based on the timing of the dim light melatonin onset [43] or, more recently, through transcriptome-based biomarkers in blood [44]. Thus, given sufficient resources, future research should be able to address questions about athletes' sleep disturbances and the underlying causes more definitively.…”
Section: Limitationsmentioning
confidence: 99%
“…While sleep quality is inherently subjective, objectively measurable correlates of poor sleep quality have been proposed, including frequency of arousals [41] and sleep discontinuity [42]. Likewise, while circadian phase preference is inherently subjective, the timing of the circadian pacemaker (biological clock) can be measured objectively based on the timing of the dim light melatonin onset [43] or, more recently, through transcriptome-based biomarkers in blood [44]. Thus, given sufficient resources, future research should be able to address questions about athletes' sleep disturbances and the underlying causes more definitively.…”
Section: Limitationsmentioning
confidence: 99%
“…Clinical use of circadian biomarkers will require fast, cost-effective, and non-invasive sampling techniques and an optimal detection platform. Finally, head-to-head comparisons are necessary to link the molecular clock phase predicted from skin biomarkers with the melatonin phase predicted from blood [11,[13][14][15]17] and other physiological phases (e.g., core body temperature) [29].…”
Section: Discussionmentioning
confidence: 99%
“…However, DLMO is inconvenient, costly, difficult to standardize, and thus rarely used 3 clinically. With the development of high-throughput molecular detection platforms and computational techniques, recent efforts shifted to machine learning predictions based on the transcriptome or metabolome from one or two samples of whole blood [11][12][13][14][15][16], or a specific blood cell type (e.g., CD14 + monocytes) [17]. Using these developed machine learning approaches, the DLMO phase (or sampling time) could be accurately assigned within 3 h from a single blood sample.…”
Section: Introductionmentioning
confidence: 99%
“…Laing et al (32) published a study that uses a partial least squares regression method to estimate melatonin cycles from transcriptome data. They used a large, novel human transcriptome dataset, which consisted of timecourses of melatonin and gene expression in sleep deprived states.…”
Section: S136 Plsrmentioning
confidence: 99%