Abstract
BackgroundCircadian rhythms in body temperature coordinate peripheral molecular clocks, hence they could potentially predict optimal treatment timing (chronotherapy) in individual patients. Circadian parameters in chest surface body temperature (Chesttemp) were recorded remotely and in real time through the use of wearable sensors.MethodsThe dynamics of circadian oscillations in Chesttemp and core body temperature (Coretemp) and their moderation by sex and age were analysed in 38 men and 50 women, aged 21–78 years. In two studies (ST1 and ST2), Chesttemp was measured every minute and teletransmitted using a BLE-connected sensor for 3.6–28.3 days. Additionally, in ST2, Coretemp was recorded per minute in 33 age- and sex-stratified subjects using electronic ingestible pills with radio-frequency transmissions. Circadian parameters were computed using spectral analysis and cosinor modelling. The temporal relations between Chesttemp and Coretemp cosinor parameters were summarised with principal component (PC) analysis. The effect of sex and age was analysed through multivariate regression.ResultsUsing spectral analysis, a dominant period of 24- or 12-h was identified in 93.2% of the Chesttemp and in 100% of the Coretemp time series. The circadian parameters varied largely between-subjects both for Chesttemp (ranges: mesors, 33.2–36.6°C; amplitudes, 0.2–2.5°C; acrophases, 14:05–7:40), and Coretemp (mesors, 36.6–37.5°C; amplitudes, 0.2–0.7°C; bathyphases, 23:50–6:50). Higher PC loadings mainly corresponded to (i) large Chesttemp amplitudes, and phase advance of both temperature rhythms for the first PC (PC1, 27.2% of variance var.), (ii) high mesors in both temperature rhythms for PC2 (22.4% var.), and (iii) large Coretemp amplitudes for PC3 (12.9% var.). Chesttemp and Coretemp mesors and PC2 loadings decreased in females, while remaining quite stable in males as a function of age. In contrast, Coretemp amplitude and PC3 loadings increased with age in females, but decreased in males. Finally, older subjects, both female and male, displayed a reduction in ultradian variabilities, and an increase in both Chesttemp circadian amplitude and PC1 loadings.InterpretationThe dynamics relations between Chesttemp and Coretemp rhythms were largely moderated by age and sex, with results suggesting that treatment timing could be most critical for therapeutic index in women and in order people.
Highlights
The circadian timing system (CTS) involves a complex network of molecular clocks that reside within each cell and are coordinated by a central pacemaker, the suprachiasmatic nuclei (SCN) in the hypothalamus (Hastings et al, 2003; Bass and Lazar, 2016; Panda, 2016)
The SCN generate the circadian rhythms in rest-activity and in body temperature, which have been proposed as CTS biomarkers (Ballesta et al, 2017)
From Spectral Analysis Circadian rhythm in Chesttemp was identified in 82 out of 88 subjects (93.1%), as revealed by the fact that 60 and 22 subjects had a dominant period around 24- or 12-h in ST1 and ST2, respectively (Figures 2A,B)
Summary
The circadian timing system (CTS) involves a complex network of molecular clocks that reside within each cell and are coordinated by a central pacemaker, the suprachiasmatic nuclei (SCN) in the hypothalamus (Hastings et al, 2003; Bass and Lazar, 2016; Panda, 2016). Others and we have hypothesized earlier that their recording would convey critical information for the optimal timing of the delivery of medications (chronotherapy) in individual patients (Lévi et al, 2010; Tudela et al, 2010; Roche et al, 2014). Such personalized chronotherapy is needed for the optimization of treatment effects, because of large inter-subject differences in circadian rhythms from genes to biomarkers (Roche et al, 2014; Lévi et al, 2020). Circadian rhythms in body temperature coordinate peripheral molecular clocks, they could potentially predict optimal treatment timing (chronotherapy) in individual patients. Circadian parameters in chest surface body temperature (Chesttemp) were recorded remotely and in real time through the use of wearable sensors
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