Journal of Biological Rhythms最新文献

Obesity is a major public health concern, with disparities across racial and sex groups. While sleep duration has been extensively studied in relation to obesity, the role of sleep regularity remains less explored. In 2 nationally representative samples of US adults in the National Health and Nutrition Examination Survey (NHANES 2011/2012 & 2013/2014, n = 7085), we investigated the cross-sectional association between a sleep regularity index (SRI) derived from accelerometer data and obesity measures. Body mass index (BMI), waist circumference (WC), body roundness index (BRI), total fat mass, sagittal abdominal diameter (SAD), sagittal abdominal diameter to height ratio (SADHtR), fat mass index (FMI), lipid accumulation product (LAP), and visceral adiposity index (VAI) were derived from NHANES body measures. Multivariable-adjusted regression models were used to estimate multiplication factors (MF) and 95% confidence intervals (CIs) comparing mean BMI across quintiles of SRI and to test for effect modification by sex and ethnicity. Higher SRI was associated with significantly lower BMI (MF SRI_Q5vs.Q1: 0.92; 95% CI, 0.91-0.94; P_trend < 0.001), translating into 8% lower BMI among those with most versus least regular sleep. This association was more pronounced among women than men (MF SRI_Q5vs.Q1 women: 0.92; 95% CI, 0.90-0.95; men: 0.98; 95% CI, 0.96-1.00), with strongest effects in non-Hispanic White and other/multi-racial women (P_interaction < 0.001). Similar inverse associations were observed for all other obesity measures. In conclusion, sleep regularity, measured by the SRI, was inversely associated with BMI and any other obesity measures. The observed disparities suggest sleep regularity may contribute differentially to obesity risk by sex and race/ethnicity.

The purpose of this study was twofold: (a) to determine whether, and the extent to which, the challenge of a single night of total sleep deprivation (TSD) unmasks lingering brain health-related deficits in individuals who within the past 3 to 12 months had been diagnosed (yet medically cleared) with a mild traumatic brain injury (mTBI+), and (b) to determine whether mTBI+ results in any neurophysiobehavioral deficits in the ability to recover from TSD. Seven previously concussed (mTBI+) adults (24.5 ± 5.3 years old) and six non-concussed control (mTBI-) adults underwent 24 h TSD preceded by 8 h baseline sleep (BSL) and followed by 8 h recovery sleep (REC). Study measures included the psychomotor vigilance test (PVT) across the entire study and polysomnography during nighttime sleep and daytime nap tests. mTBI+ (vs mTBI-) subjects exhibited more minor lapses on the PVT across all study phases. NREM (N3) sleep and total sleep time (TST) amounts were lower and wake after sleep onset (WASO) was higher in mTBI+ subjects (vs mTBI) at baseline and REC. mTBI+ (vs mTBI-) subjects showed no main effects in maintenance of wakefulness across TSD. Although there is some evidence that TSD may unmask latent performance deficits in mTBI+ subjects, a definitive conclusion was precluded by differences in baseline sleep in mTBI+ (vs mTBI-) subjects, suggesting that they may habitually carry a relatively elevated sleep debt (vs mTBI- controls). Reversal of TSD-induced neurophysiobehavioral deficits following recovery sleep were comparable for both groups, revealing no significant abnormalities in the responsivity of the sleep homeostat in the mTBI+ subjects.

Light is the primary circadian time cue, but there are large interindividual differences in how sensitive the circadian system is to light. Currently, it is not well understood how individual differences in light sensitivity interact with real-world light environments to determine sleep and circadian timing. We used a validated computational model to simulate sleep and circadian timing (predicted dim light melatonin onset) under realistic assumptions about light and work schedules. Simulations were repeated varying light sensitivity (translated to equivalent ED50 values for interpretability), as well as evening, morning, and daytime illuminances. Brighter evening light led to later predicted circadian and sleep timing, with this effect being amplified by high light sensitivity. Reducing evening light was particularly beneficial for those with high light sensitivity or a long circadian period. Brighter morning light was beneficial for individuals with a long circadian period, or those with both high light sensitivity and high evening light. However, bright morning light could be maladaptive in individuals with a short circadian period or those with low light sensitivity and low evening light. Brighter daytime light attenuated the delaying effects of evening artificial light across conditions, indicating that increasing daytime light was the most universally beneficial lighting intervention. Our results demonstrate how circadian light sensitivity can be used to tailor individual-level solutions that support optimal sleep and circadian timing.

In animals, the brain contains circadian clock neurons that regulate activity rhythms. The fruit fly Drosophila melanogaster exhibits a bimodal activity pattern characterized by two peaks, in the morning (M) and evening (E), known as the M and E peaks. These activity peaks are orchestrated by a network of approximately 240 clock neurons. The neuropeptide pigment-dispersing factor (PDF) is expressed in two sets of clock neurons, the large ventrolateral neurons (l-LN_v) and the small ventrolateral neurons (s-LN_v). Mutants of Pdf, as well as flies lacking PDF neurons, exhibit a characteristic E activity that is commonly simplified to a phase-advanced pattern under 12 h:12 h light-dark cycles. Previous studies have demonstrated that l-LN_v neurons regulate the phase of the E peak; however, this effect is evident only under long photoperiod conditions. Therefore, the E peak phenotype observed in Pdf mutants remains incompletely explained. In this study, we employed genetic cell ablation and Pdf RNA interference using Gal4 lines specific to l-LN_v neurons in a well-controlled genetic background. Under long photoperiod conditions, flies lacking l-LN_v, s-LN_v, or both neuronal groups exhibited an early termination of E activity prior to lights-off, resulting in a phase-advanced E peak. Similar results were obtained in Pdf knockdown flies. Notably, l-LN_v neurons had a stronger effect on the timing of E activity termination than s-LN_v neurons. These findings demonstrate that LN_v neurons control the phase of E activity by modulating the timing of its offset, providing new insights into the neuronal mechanisms that shape daily activity patterns.

Chronobiology is one of the broadest disciplines in science - we can study and apply this system from molecules to shiftwork, from individuals to populations, from physiology to psychology, from mechanisms to medicine. Since I have an aversion against thinking in boxes, chronobiology was the only discipline I could faithfully live in for the past 55 years, giving me the privilege to witness its epitaxy from its pioneers to circadian medicine. I have tackled chronobiological questions with many different methods, but by far my favorite tool to understand are concepts.

While current mathematical models of human circadian rhythms accurately predict circadian phase responses to light in controlled laboratory experiments, they show reduced performance in the real world, especially among shift workers with irregular schedules and downstream erratic light diets. The source of the discrepancy between in-laboratory and ambulatory performance remains unclear. We evaluate the impact of initialization strategy, recording duration, and light exposure characteristics on model performance using wearable data from both individuals on regular schedules and shift workers. We implement a probabilistic initialization framework to account for unknown starting phase and assess model performance in prediction of phase from light input data against an in-lab measure of circadian phase (dim light melatonin onset). In participants with regular schedules, accuracy improved with longer recordings, while shift workers show no accuracy gains when having more nights of data. Light exposure patterns differed significantly between groups, with brighter and more regular day-to-day light exposure being weakly to moderately associated with improved model estimates, whereas fragmented patterns of light exposure increased uncertainty. These findings suggest that current models require adaptation, particularly in light sensitivity, to generalize to free-living, irregular conditions and support robust, scalable circadian tracking in real-world populations.

Rhythmicity is a central feature of behavioral and physiological processes, including sleep, immune responses, and metabolism. Research on brain control of these processes has largely focused on neurons, with less known about the role of clock genes in glial cells. In this study, we addressed the function of glial clocks by targeting the expression of key clock genes in glia of Drosophila melanogaster. Loss of the period (per) gene in glia increases sleep following aseptic injury and loss of either per or timeless (tim) significantly reduces locomotor activity in light:dark cycles and in constant dark, but other than this, the major effect of clock gene loss in glia is on metabolic function. We demonstrate that disruption of either tim or per in glia affects glycogen stores and reduces metabolic rate. Disruption of either tim or per in glia also affects rhythms of feeding and overall food consumption. Notably, these effects of clock disruption are mediated by distinct glial subtypes, especially cortex glia. We propose that the major role of glial clocks is in the control of energy homeostasis and metabolic rhythms, which likely also accounts for effects on locomotor activity. These findings link metabolism and behavior via circadian regulation in glia.

Circadian clocks regulate the immune system, rendering humans more susceptible to infections at certain times of the day. Circadian modulation of SARS-CoV-2 infection has not yet been clearly established, nonetheless the circadian control of other respiratory viruses such as influenza A makes apparent the need to study the interaction between circadian rhythms and COVID-19 disease progression. We incorporated circadian oscillations into a mechanistic model of SARS-CoV-2 dynamics and immune response fit to viral load data from COVID-19 patients. The model predicts that circadian variation of parameters associated with the innate immune response and viral death rate lead to faster clearance of the virus, whereas circadian variation of parameters representing the susceptible cell infection rate, the viral production rate, and the adaptive immune response lead to slower clearance of the virus. We then used a model of remdesivir to simulate antiviral therapy. Our model simulations predict that the effectiveness of the treatment depends on the time of day the drug is administered. This prediction is conditional on the plausible, but entirely hypothetical, circadian interactions added to the model. Based on our proof-of-concept modeling results, we advocate for experimental and clinical studies to assess the impact that dosing time of day may have on the efficacy and toxicity of current COVID-19 antiviral drugs.