Enhancing Night and Day Circadian Contrast through Sleep Education in Prediabetes and Type 2 Diabetes Mellitus: A Randomized Controlled Trial

Greater sleep variability is associated with higher systemic inflammation in type 2 diabetes

Sleep irregularity and variability have been shown to be detrimental to cardiometabolic health. The present pilot study explored if higher day-to-day sleep irregularity and variability were associated with systemic inflammation, as assessed by high-sensitivity C-reactive protein, in type 2 diabetes. Thirty-five patients with type 2 diabetes (mean age 54.3 years, 54.3% female) who were not shift-workers participated. The presence of diabetic retinopathy was determined. The standard deviation of sleep duration and sleep midpoint across all recorded nights were used to quantify sleep variability and regularity, respectively, assessed by 14-day actigraphy. The presence and severity of sleep apnea were assessed using an overnight home monitor. Low-density lipoprotein, haemoglobin A1C and high-sensitivity C-reactive protein were collected. Multiple regression analysis using natural-log-transformed values was performed to establish an independent association between sleep variability and high-sensitivity C-reactive protein. Twenty-two (62.9%) patients had diabetic retinopathy. The median (interquartile range) of high-sensitivity C-reactive protein was 2.4 (1.4, 4.6) mg L-1. Higher sleep variability was significantly associated with higher high-sensitivity C-reactive protein (r = 0.342, p = 0.044), as was haemoglobin A1C (r = 0.431, p = 0.010) and low-density lipoprotein (r = 0.379, p = 0.025), but not sleep regularity, sleep apnea severity or diabetic retinopathy. Multiple regression analysis showed that higher sleep variability (B = 0.907, p = 0.038) and higher HbA1c (B = 1.519, p = 0.035), but not low-density lipoprotein, contributed to higher high-sensitivity C-reactive protein. In conclusion, higher sleep variability in patients with type 2 diabetes who were not shift-workers was independently associated with higher systemic inflammation, conferring increased cardiovascular risk. Whether sleep interventions to reduce sleep variability can reduce systemic inflammation and improve cardiometabolic health should be investigated.

Circadian desynchrony and glucose metabolism

The circadian timing system controls glucose metabolism in a time-of-day dependent manner. In mammals, the circadian timing system consists of the main central clock in the bilateral suprachiasmatic nucleus (SCN) of the anterior hypothalamus and subordinate clocks in peripheral tissues. The oscillations produced by these different clocks with a period of approximately 24-h are generated by the transcriptional-translational feedback loops of a set of core clock genes. Glucose homeostasis is one of the daily rhythms controlled by this circadian timing system. The central pacemaker in the SCN controls glucose homeostasis through its neural projections to hypothalamic hubs that are in control of feeding behavior and energy metabolism. Using hormones such as adrenal glucocorticoids and melatonin and the autonomic nervous system, the SCN modulates critical processes such as glucose production and insulin sensitivity. Peripheral clocks in tissues, such as the liver, muscle, and adipose tissue serve to enhance and sustain these SCN signals. In the optimal situation all these clocks are synchronized and aligned with behavior and the environmental light/dark cycle. A negative impact on glucose metabolism becomes apparent when the internal timing system becomes disturbed, also known as circadian desynchrony or circadian misalignment. Circadian desynchrony may occur at several levels, as the mistiming of light exposure or sleep will especially affect the central clock, whereas mistiming of food intake or physical activity will especially involve the peripheral clocks. In this review, we will summarize the literature investigating the impact of circadian desynchrony on glucose metabolism and how it may result in the development of insulin resistance. In addition, we will discuss potential strategies aimed at reinstating circadian synchrony to improve insulin sensitivity and contribute to the prevention of type 2 diabetes.

Lack of Efficacy of Suvorexant in People with Insomnia and Poorly Controlled Type 2 Diabetes

Objective/Background

Sleep disturbance is a common and underappreciated feature of diabetes and sleep may contribute to glycemic control in people with type 2 diabetes (T2D). We conducted a 3-month trial to examine the efficacy of suvorexant in improving sleep and health outcomes in people with suboptimally controlled T2D and insomnia.

Participants/Methods

This parallel, double-blind, randomized placebo-controlled trial was conducted using the sequential parallel comparison design (SPCD). Sixty-nine people with poorly controlled T2D (HbA1c ≥ 6.5) were randomized to placebo and/or suvorexant (10-20 mg). The primary outcome was subjective total sleep time (sTST), and secondary outcomes were Insomnia Severity Index (ISI) score and wake time after sleep onset (WASO). Exploratory outcomes included sleep efficiency, hemoglobin A1c (HbA1c), and C-reactive protein (CRP). Exploratory analyses were conducted on relationships between sleep and diabetes outcomes.

Results

There were no significant improvements in sTST (p = 0.27), ISI (p = 0.86), or WASO (p = 0.94) among participants taking suvorexant compared to placebo. There were also no significant changes in any of the exploratory endpoints. Improvements in sleep were associated with improvements in both objective (ie, HbA1c) and subjective (ie, Diabetes Distress Scale) measures of diabetes, as well as reductions in depressive symptoms, independent of treatment assignment.

Conclusion

The study did not find evidence that suvorexant is efficacious for insomnia in people with poorly controlled T2D. The associations of improved sleep with improvements in both diabetes-related metrics and depressive symptoms across groups highlight the importance of identifying and treating sleeping difficulties in this population.

CT Registration #

Nct03818581.

Association between sleep variability and time in range of glucose levels in patients with type 1 diabetes: Cross-sectional study

OBJECTIVE

Sleep and circadian disturbances emerge as novel factors influencing glycemic control in type 1 diabetes (T1D). We aimed to explore the associations among sleep, behavioral circadian parameters, self-care, and glycemic parameters in T1D.

METHODS

Seventy-six non-shift-working adult T1D patients participated. Blinded 7-day continuous glucose monitoring (CGM) and hemoglobin A1C (A1C) were collected. Percentages of time-in-range (glucose levels 70-180 mg/dL) and glycemic variability (measured by the coefficient of variation [%CV]) were calculated from CGM. Sleep (duration and efficiency) was recorded using 7-day actigraphy. Variability (standard deviation) of midsleep time was used to represent sleep variability. Nonparametric behavioral circadian variables were derived from actigraphy activity recordings. Self-care was measured by diabetes self-management questionnaire-revised. Multiple regression analyses were performed to identify independent predictors of glycemic parameters.

RESULTS

Median (interquartile range) age was 34.0 (27.2, 43.1) years, 48 (63.2%) were female, and median (interquartile range) A1C was 6.8% (6.2, 7.4). Sleep duration, efficiency, and nonparametric behavioral circadian variables were not associated with glycemic parameters. After adjusting for age, sex, insulin delivery mode/CGM use, and ethnicity, each hour increase in sleep variability was associated with 9.64% less time-in-range (B = -9.64, 95% confidence interval [-16.29, -2.99], p ≤ .001). A higher diabetes self-management questionnaire score was an independent predictor of lower A1C (B = -0.18, 95% confidence interval [-0.32, -0.04]).

CONCLUSION

Greater sleep timing variability is independently associated with less time spent in the desirable glucose range in this T1D cohort. Reducing sleep timing variability could potentially lead to improved metabolic control and should be explored in future research.

DATA AVAILABILITY STATEMENT

Data are available upon a reasonable request to the corresponding author.

Unraveling the associations and causalities between glucose metabolism and multiple sleep traits

Purpose

The aim of our study is to estimate the associations and causalities of glucose metabolism traits of fasting blood glucose (FBG), fasting insulin (FINS), glycosylated hemoglobin (HbA1c), and 2-h glucose post-challenge (2hGlu) with sleep traits consisting of excessive daytime sleepiness (EDS), insomnia, and sleep duration.

Methods

We employed standard quantitative analysis procedures to assess the associations between sleep traits and glucose metabolism. Moreover, we acquired published genome-wide association studies (GWAS) summary statistics for these traits and conducted Mendelian randomization (MR) analyses to estimate their causal directions and effects. Inverse variance weighting (IVW) was employed as the primary approach, followed by sensitivity analyses.

Results

A total of 116 studies with over 840,000 participants were included in the quantitative analysis. Our results revealed that participants with abnormal glucose metabolism had higher risks for EDS (OR [95% CI] = 1.37 [1.10,1.69]), insomnia (OR [95% CI] = 1.65 [1.24,2.20]), and both short and long sleep duration (OR [95% CI] = 1.35 [1.12,1.63]; OR [95% CI] = 1.38 [1.13,1.67] respectively). In addition, individuals with these sleep traits exhibited alterations in several glycemic traits compared with non-affected controls. In MR analysis, the primary analysis demonstrated causal effects of 2hGlu on risks of EDS (OR [95% CI] = 1.022 [1.002,1.042]) and insomnia (OR [95% CI] = 1.020[1.001,1.039]). Furthermore, FINS was associated with short sleep duration (OR [95% CI] = 1.043 [1.018,1.068]), which reversely presented a causal influence on HbA1c (β [95% CI] = 0.131 [0.022,0.239]). These results were confirmed by sensitivity analysis.

Conclusion

Our results suggested mutual risk and causal associations between the sleep traits and glycemic traits, shedding new light on clinical strategies for preventing sleep disorders and regulating glucose metabolism. Future studies targeting these associations may hold a promising prospect for public health.

Effects of sleep disturbance on dyspnoea and impaired lung function following hospital admission due to COVID-19 in the UK: a prospective multicentre cohort study

BACKGROUND

Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea.

METHODS

CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2-7 months after hospital discharge and a later time point 10-14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107).

FINDINGS

2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4-6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5-8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (-19%; 95% CI -20 to -16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18-39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27-41% of this effect.

INTERPRETATION

Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition.

FUNDING

UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.

The association between rest-activity parameters and hemoglobin A1c in patients with prediabetes

Circadian abnormalities can adversely affect glucose metabolism. This study determined whether behavioral circadian parameters, as assessed by rest-activity rhythm, were predictors of glycemic control in patients with prediabetes. Seventy-nine patients with prediabetes participated. Nonparametric rest-activity rhythm parameters, sleep duration and efficiency were obtained from 7-d actigraphy recordings. Sleep-disordered breathing severity was assessed using a home sleep apnea test. Hemoglobin A1c (HbA1c) was obtained to evaluate glycemic control. The results revealed that shorter sleep duration, lower relative amplitude and higher L5 (average activity of the least active 5-h period) were associated with higher HbA1c, while other sleep variables were not related to HbA1c. Multiple stepwise regression analysis adjusting for age, sex, body mass index and sleep duration revealed that lower relative amplitude, but not L5, was independently associated with higher HbA1c (B = -0.027, p = 0.031). In summary, among patients with prediabetes, an abnormal circadian rhythm was associated with higher HbA1c, implying a greater risk of developing diabetes. These results support the role of circadian rhythmicity in glucose control among those with prediabetes.