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Blood transcriptome based biomarkers for human circadian phase.
Laing, Emma E; Möller-Levet, Carla S; Poh, Norman; Santhi, Nayantara; Archer, Simon N; Dijk, Derk-Jan.
Afiliação
  • Laing EE; Department of Microbial Sciences, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Möller-Levet CS; Bioinformatics Core Facility, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Poh N; Department of Computer Science, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom.
  • Santhi N; Surrey Sleep Research Centre, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Archer SN; Surrey Sleep Research Centre, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Dijk DJ; Surrey Sleep Research Centre, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
Elife ; 62017 02 20.
Article em En | MEDLINE | ID: mdl-28218891
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 conditions to assess robustness of the predictor. Partial least square regression (PLSR), applied to the transcriptome, identified a set of 100 biomarkers primarily related to glucocorticoid signaling and immune function. Validation showed that PLSR-based predictors outperform published blood-derived circadian phase predictors. When given one sample as input, the R2 of predicted vs observed phase was 0.74, whereas for two samples taken 12 hr apart, R2 was 0.90. This blood transcriptome-based model enables assessment of circadian phase from a few samples.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores / Ritmo Circadiano / Perfilação da Expressão Gênica / Melatonina Tipo de estudo: Evaluation_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores / Ritmo Circadiano / Perfilação da Expressão Gênica / Melatonina Tipo de estudo: Evaluation_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article