A novel method to separate circadian from non-circadian masking effects to enhance estimation of circadian timing and amplitude from core body temperature

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dc.contributor.authorNguyen, P.D.
dc.contributor.authorDunbar, C.
dc.contributor.authorScott, H.
dc.contributor.authorLechat, B.
dc.contributor.authorManners, J.
dc.contributor.authorMicic, G.
dc.contributor.authorLovato, N.
dc.contributor.authorReynolds, A.C.
dc.contributor.authorLack, L.
dc.contributor.authorAdams, R.
dc.contributor.authorEckert, D.
dc.contributor.authorVakulin, A.
dc.contributor.authorCatcheside, P.G.
dc.date.issued2025
dc.description.abstractStudy objectives: Circadian disruption contributes to adverse effects on sleep, performance, and health. One accepted method to track continuous daily changes in central circadian timing is to measure core body temperature (CBT), and establish daily, circadian-related CBT minimum time (Tmin). This method typically applies cosine-model fits to measured CBT data, which may not adequately account for substantial masking of circadian effects, and thus estimates of the circadian-related Tmin. This study introduced a novel physiology-grounded analytic approach to separate circadian from non-circadian effects on CBT, which we compared against traditional cosine-based methods. Methods: The dataset comprised 33 healthy participants (mean ± SD 32 ± 13 years) attending a 39-h inlaboratory study with an initial overnight sleep followed by an extended wake period. CBT data were collected at 30-s intervals via ingestible capsules. Our design captured CBT during both the baseline sleep period and during extended wake period (without sleep) and allowed us to model the influence of circadian and noncircadian effects of sleep, wake, and activity on CBT using physiology-guided generalized additive models. Results: Compared to the traditional cosine model, the new model exhibited superior fits to CBT (Pearson R 0.90 [95 %CI; [0.83–0.96] versus 0.81 [0.55–0.93]). The difference between estimated vs measured circadian Tmin, derived from the day without sleep, was better fit with our method (0.2 [– 0.5,0.3] hours) versus previous methods (1.4 [1.1 to 1.7] hours). Conclusions: This new method provides improved demasking of non-circadian influences compared to traditional cosine methods, including the removal of a sleep-related bias towards an earlier estimate of circadian Tmin.
dc.description.statementofresponsibilityPhuc D. Nguyen, Claire Dunbar, Hannah Scott, Bastien Lechat, Jack Manners, Gorica Micic, Nicole Lovato, Amy C. Reynolds, Leon Lack, Robert Adams, Danny Eckert, Andrew Vakulin, Peter G. Catcheside
dc.identifier.citationSleep Medicine, 2025; 132:106530-1-106530-4
dc.identifier.doi10.1016/j.sleep.2025.106530
dc.identifier.issn1389-9457
dc.identifier.issn1878-5506
dc.identifier.orcidAdams, R. [0000-0002-7572-0796]
dc.identifier.urihttps://hdl.handle.net/2440/147961
dc.language.isoen
dc.publisherElsevier
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1116942
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/2029399
dc.rights© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
dc.source.urihttps://doi.org/10.1016/j.sleep.2025.106530
dc.subjectCircadian modelling; Circadian timing; Non-circadian masking effects; Core body temperature
dc.subject.meshHumans
dc.subject.meshBody Temperature
dc.subject.meshWakefulness
dc.subject.meshSleep
dc.subject.meshCircadian Rhythm
dc.subject.meshAdult
dc.subject.meshFemale
dc.subject.meshMale
dc.subject.meshYoung Adult
dc.titleA novel method to separate circadian from non-circadian masking effects to enhance estimation of circadian timing and amplitude from core body temperature
dc.typeJournal article
pubs.publication-statusPublished

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