Predicting circadian phase across populations: a comparison of mathematical models and wearable devices.

From smart work scheduling to optimal drug timing, there is enormous potential in translating circadian rhythms research results for precision medicine in the real world. However, the pursuit of such effort requires the ability to accurately estimate circadian phase outside of the laboratory. One approach is to predict circadian phase noninvasively using light and activity measurements and mathematical models of the human circadian clock. Most mathematical models take light as an input and predict the effect of light on the human circadian system. However, consumer-grade wearables that are already owned by millions of individuals record activity instead of light, which prompts an evaluation of the accuracy of predicting circadian phase using motion alone. Here, we evaluate the ability of four different models of the human circadian clock to estimate circadian phase from data acquired by wrist-worn wearable devices. Multiple datasets across populations with varying degrees of circadian disruption were used for generalizability. Though the models we test yield similar predictions, analysis of data from 27 shift workers with high levels of circadian disruption shows that activity, which is recorded in almost every wearable device, is better at predicting circadian phase than measured light levels from wrist-worn devices when processed by mathematical models. In those living under normal living conditions, circadian phase can typically be predicted to within 1 h, even with data from a widely available commercial device (the Apple Watch). These results show that circadian phase can be predicted using existing data passively collected by millions of individuals with comparable accuracy to much more invasive and expensive methods.

Association between Timing of Energy Intake and Insulin Sensitivity: A Cross-Sectional Study.

In addition to the caloric and macronutrient composition of meals, timing of energy consumption may be important for optimal glucose metabolism. Our goal was to examine whether the habitual timing of energy intake was associated with insulin sensitivity in healthy volunteers. Volunteers without diabetes aged 21-50 years completed a 3-day food diary and underwent an oral glucose tolerance test to estimate insulin sensitivity (n = 44). From the food diary, we calculated the proportions of the total energy and macronutrients consumed in the morning and evening, and the clock time at which 25%, 50% and 75% of total energy was consumed. A greater proportion of energy intake in the morning was significantly associated with higher insulin sensitivity estimated by Matsuda Index (B = 2.8 per 10%; 95%CI: 0.3, 5.2). The time at which 25% of energy was consumed was associated with insulin sensitivity estimated by Matsuda Index (B = -1.6 per hour; 95%CI: -3.0, -0.3) and QUICKI (B = -1.4 per hour, 95%CI: -2.8, -0.1). The timing of carbohydrate consumption demonstrated similar associations. Greater energy intake earlier in the day was associated with higher insulin sensitivity in individuals without diabetes.

Glycation of human cortical and cancellous bone captures differences in the formation of Maillard reaction products between glucose and ribose.

To better understand some aspects of bone matrix glycation, we used an in vitro glycation approach. Within two weeks, our glycation procedures led to the formation of advanced glycation end products (AGEs) at the levels that corresponded to approx. 25-30 years of the natural in vivo glycation. Cortical and cancellous bones from human tibias were glycated in vitro using either glucose (glucosylation) or ribose (ribosylation). Both glucosylation and ribosylation led to the formation of higher levels of AGEs and pentosidine (PEN) in cancellous than cortical bone dissected from all tested donors (young, middle-age and elderly men and women). More efficient glycation of bone matrix proteins in cancellous bone most likely depended on the higher porosity of this tissue, which facilitated better accessibility of the sugars to the matrix proteins. Notably, glycation of cortical bone from older donors led to much higher AGEs levels as compared to young donors. Such efficient in vitro glycation of older cortical bone could result from aging-related increase in porosity caused by the loss of mineral content. In addition, more pronounced glycation in vivo would be driven by elevated oxidation processes. Interestingly, the levels of PEN formation differed pronouncedly between glucosylation and ribosylation. Ribosylation generated very high levels of PEN (approx. 6- vs. 2.5-fold higher PEN level than in glucosylated samples). Kinetic studies of AGEs and PEN formation in human cortical and cancellous bone matrix confirmed higher accumulation of fluorescent crosslinks for ribosylation. Our results suggest that in vitro glycation of bone using glucose leads to the formation of lower levels of AGEs including PEN, whereas ribosylation appears to support a pathway toward PEN formation. Our studies may help to understand differences in the progression of bone pathologies related to protein glycation by different sugars, and raise awareness for excessive sugar supplementation in food and drinks.