We have contributed substantially to the human sleep/circadian biomarker field through our work on blood-based transcriptome biomarkers.
Through studying individuals under conditions of sleep restriction and circadian misalignment, we have identified novel machine learning-based methods of predicting circadian phase and sleep loss from just one or two blood samples.
Currently, we are focused on exploring novel biomarkers in clinical populations to determine the relationship between sleep/circadian system and disease progression, as well as to look for predictors of disease susceptibility.
Current research projects
study of the effects of simulated microgravity prolonged bed rest on sleep, circadian physiology, and time series transcriptomics; associations between sleep and circadian genomic variants and health in the UK Biobank.
Magee M, Sletten TL, Murray JM, Gordon CJ, Lovato N, Bartlett DJ, Kennaway DJ, Lockley SW, Lack LC, Grunstein RR, Archer SN, Rajaratnam SMW; Delayed Sleep on Melatonin (DelSoM) Study Group (2020) A PERIOD3 variable number tandem repeat polymorphism modulates melatonin treatment response in delayed sleep-wake phase disorder. J Pineal Res. 2020 Nov;69(4):e12684. doi: 10.1111/jpi.12684
Laing EE, Möller-Levet CS, Dijk DJ, Archer SN (2018) Identifying and validating mRNA biomarkers for acute and chronic insufficient sleep in humans: a machine learning approach. SLEEP doi:10.1093/sleep/zsy186
Archer SN, Laing EE, Möller-Levet CS, van der Veen DR, Bucca G, Lazar AS, Santhi N, Slak A, Kabiljo R, von Schantz M, Smith CP, Dijk DJ (2014) Mistimed sleep disrupts circadian regulation of the human transcriptome. PNAS 111(6):E682-91
Dijk DJ, Duffy JF. Novel Approaches for Assessing Circadian Rhythmicity in Humans: A Review. J Biol Rhythms. 2020 Oct;35(5):421-438. doi: 10.1177/0748730420940483. Epub 2020 Jul 23. PMID: 32700634; PMCID: PMC7543025.