bims-ciryme Biomed News
on Circadian rhythms and metabolism
Issue of 2022‒11‒20
three papers selected by
Gabriela Da Silva Xavier
University of Birmingham


  1. Sci Rep. 2022 Nov 14. 12(1): 19519
      The circadian rhythm is a biological oscillation of physiological activities with a period of approximately 24 h, that is driven by a cell-autonomous oscillator called the circadian clock. The current model of the mammalian circadian clock is based on a transcriptional-translational negative feedback loop in which the protein products of clock genes accumulate in a circadian manner and repress their own transcription. However, several studies have revealed that constitutively expressed clock genes can maintain circadian oscillations. To understand the underlying mechanism, we expressed Bmal1 in Bmal1-disrupted cells using a doxycycline-inducible promoter and monitored Bmal1 and Per2 promoter activity using luciferase reporters. Although the levels of BMAL1 and other clock proteins, REV-ERBα and CLOCK, showed no obvious rhythmicity, robust circadian oscillation in Bmal1 and Per2 promoter activities with the correct phase relationship was observed, which proceeded in a doxycycline-concentration-dependent manner. We applied transient response analysis to the Bmal1 promoter activity in the presence of various doxycycline concentrations. Based on the obtained transfer functions, we suggest that, at least in our experimental system, BMAL1 is not directly involved in the oscillatory process, but modulates the oscillation robustness by regulating basal clock gene promoter activity.
    DOI:  https://doi.org/10.1038/s41598-022-24188-4
  2. Nat Protoc. 2022 Nov 14.
      Circadian clocks drive cyclic variations in many aspects of physiology, but some daily variations are evoked by periodic changes in the environment or sleep-wake state and associated behaviors, such as changes in posture, light levels, fasting or eating, rest or activity and social interactions; thus, it is often important to quantify the relative contributions of these factors. Yet, circadian rhythms and these evoked effects cannot be separated under typical 24-h day conditions, because circadian phase and the length of time awake or asleep co-vary. Nathaniel Kleitman's forced desynchrony (FD) protocol was designed to assess endogenous circadian rhythmicity and to separate circadian from evoked components of daily rhythms in multiple parameters. Under FD protocol conditions, light intensity is kept low to minimize its impact on the circadian pacemaker, and participants have sleep-wake state and associated behaviors scheduled to an imposed non-24-h cycle. The period of this imposed cycle, Τ, is chosen so that the circadian pacemaker cannot entrain to it and therefore continues to oscillate at its intrinsic period (τ, ~24.15 h), ensuring circadian components are separated from evoked components of daily rhythms. Here we provide detailed instructions and troubleshooting techniques on how to design, implement and analyze the data from an FD protocol. We provide two procedures: one with general guidance for designing an FD study and another with more precise instructions for replicating one of our previous FD studies. We discuss estimating circadian parameters and quantifying the separate contributions of circadian rhythmicity and the sleep-wake cycle, including statistical analysis procedures and an R package for conducting the non-orthogonal spectral analysis method that enables an accurate estimation of period, amplitude and phase.
    DOI:  https://doi.org/10.1038/s41596-022-00746-y
  3. Ann N Y Acad Sci. 2022 Nov 13.
      The global epidemic of obesity and type 2 diabetes parallels the rampant state of sleep deprivation in our society. Epidemiological studies consistently show an association between insufficient sleep and metabolic dysfunction. Mechanistically, sleep and circadian rhythm exert considerable influences on hormones involved in appetite regulation and energy metabolism. As such, data from experimental sleep deprivation in humans demonstrate that insufficient sleep induces a positive energy balance with resultant weight gain, due to increased energy intake that far exceeds the additional energy expenditure of nocturnal wakefulness, and adversely impacts glucose metabolism. Conversely, animal models have found that sleep loss-induced energy expenditure exceeds caloric intake resulting in net weight loss. However, animal models have significant limitations, which may diminish the clinical relevance of their metabolic findings. Clinically, insomnia disorder and insomnia symptoms are associated with adverse glucose outcomes, though it remains challenging to isolate the effects of insomnia on metabolic outcomes independent of comorbidities and insufficient sleep durations. Furthermore, both pharmacological and behavioral interventions for insomnia may have direct metabolic effects. The goal of this review is to establish an updated framework for the causal links between insufficient sleep and insomnia and risks for type 2 diabetes and obesity.
    Keywords:  diabetes; insomnia; insufficient sleep; metabolism; obesity
    DOI:  https://doi.org/10.1111/nyas.14926