Associations of sleep duration and quality with serum and hepatic lipids: The Netherlands Epidemiology of Obesity Study

Associations between sleep duration trajectories and risk of cardio-metabolic disease among middle-aged and older Chinese adults

BACKGROUND

The association of a single time-point measure of sleep duration with cardio-metabolic disease has been extensively studied, but few studies have focused on the impact of sleep duration trajectory. This study aims to model the sleep duration trajectory as predictors for the subsequent development of cardio-metabolic disease.

METHODS

This study recruited a notably large population (n = 9883) of subjects aged at least 45 years from the China Health and Retirement Longitudinal Study (CHARLS), who participated in sequential surveys conducted in 2011, 2013, 2015, and 2018. Sleep duration trajectories were plotted using data of night sleep duration recorded at intervals from 2011 to 2015 by latent class trajectory model. The onset of cardio-metabolic diseases from 2015 to 2018 were confirmed and then the risk of different sleep duration trajectories on incident cardio-metabolic disease was examined using cox proportional hazards regression model.

RESULTS

We identified four sleep duration trajectories. Compared to the normal-stable trajectory, the short-stable trajectory was significantly associated with higher risk of incident stroke (hazard ratio [HR], 1.32; 95 % confidence interval [CI], 1.02 to 1.70), dyslipidemia (HR, 1.22; 95%CI, 1.01 to 1.49), and diabetes (HR, 1.42; 95%CI, 1.13 to 1.78) within three years of follow-up, and the short-increasing trajectory predicted a higher risk of incident stroke (HR, 2.38; 95%CI, 1.25 to 4.55).

CONCLUSIONS

Short sleep trajectory could increase the risk of incident stroke, dyslipidemia, and diabetes, and an increasing sleep trajectory was associated with increased risk of incident stroke among middle-aged and older Chinese adults.

Sleep and nighttime behavior disorders in older adults: associations with hypercholesterolemia and hypertriglyceridemia at baseline, and a predictive analysis of incident cases at 12 months follow-up

INTRODUCTION

Sleep disorders, particularly insomnia and obstructive sleep apnea, are associated with dyslipidemia in the general population. The study's aim was to explore the association between pathological Cholesterol and Triglyceride levels, and sleep and nighttime behavior disorders (SNBD) in older adults, whether they might predict SNBD onset, and to emphasize the role of body mass index (BMI) in this association.

METHODS

Alzheimer's Disease Neuroimaging Initiative (ADNI) population with complete Cholesterol, Triglyceride, SNBD, and neurocognitive data were included. Logistic regression was performed to study the association between hypercholesterolemia, hypertriglyceridemia, and SNBD at baseline and at 12 months. Relevant confounders, particularly BMI, were adjusted for.

RESULTS

Among the 2,216 included cases, 1,045 (47%) were females, and the median age was 73 years (IQR: 68, 78). At baseline, 357 (16%) had SNBD and 327 (18%) at 12 months; 187 of them were incident cases. There were more cases of baseline SNBD in the hypertriglyceridemia group than in those without (19% vs. 14%, P-value = 0.003). Similarly, more follow-up SNBD cases had hypertriglyceridemia at baseline (21% vs. 16%, P-value = 0.025). SNBD cases at baseline had significantly higher serum Triglyceride levels than those without (132 vs. 118mg/dL, P-value < 0.001). Only hypertriglyceridemia was significantly associated with baseline SNBD (crude OR = 1.43, 95%CI: 1.13,1.80, P-value = 0.003), even after adjustment for confounding factors (adj. OR = 1.36, 95%CI: 1.06,1.74, P-value = 0.016) and (BMI-adj. OR = 1.29, 95%CI: 1.00,1.66, P-value = 0.048). None of the dyslipidemia forms did predict incident cases at 12 months.

CONCLUSIONS

Hypertriglyceridemia, but not hypercholesterolemia, was associated with higher odds of SNBD. The association was independent of BMI. None of the dyslipidemia forms did predict incident SNBD over 12 months. Sleep disorders should motivate a systematic screening of dyslipidemia in older adults and vice versa.

A Large-Scale Genome-Wide Gene-Sleep Interaction Study in 732,564 Participants Identifies Lipid Loci Explaining Sleep-Associated Lipid Disturbances

We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.

High serum Cholesterol and Triglyceride levels in older adults: associations with sleep and nighttime behavior disorders at baseline and a prediction analysis of incidental cases at 12 months follow-up

Introduction

This study explored the association between dyslipidemia and sleep and nighttime behavior disorders (SNBD) in the elderly.

Methods

ADNI population with complete Cholesterol, Triglyceride, SNBD, and neurocognitive data were included. Logistic regression was performed to study the association between dyslipidemia and SNBD at baseline and 12 months. Relevant confounders were adjusted for.

Results

Among the 2,216 included cases, 1,045 (47%) were females, and the median age was 73 (IQR: 68, 78). At baseline, 357 (16%) had SNBD, and 327 (18%) at 12 months; 187 were incident cases.There were more cases of baseline SNBD in the hypertriglyceridemia group than in those without (19% vs. 14%, p-value=0.003). Similarly, more follow-up SNBD cases had hypertriglyceridemia at baseline (21% vs. 16%, p-value=0.025). SNBD cases at baseline had significantly higher serum Triglyceride levels than those without (132 vs. 118mg/dL, p-value<0.001).Only hypertriglyceridemia was significantly associated with baseline SNBD (crude OR=1.43, 95%CI: 1.13,1.80, p-value=0.003), even after adjustment for confounding factors (adj.OR=1.36, 95%CI: 1.06,1.74, p-value=0.016) and (BMI-adj.OR=1.29, 95%CI: 1.00,1.66, p-value=0.048). None of the dyslipidemia forms did predict incident cases at 12 months.

Conclusions

Hypertriglyceridemia, but not hypercholesterolemia, was associated with higher odds of SNBD. None of the dyslipidemia forms predicted incidental SNBD over 12 months.

Is poor sleep quality associated with lipid profile in elderly population? Finding from Iranian Longitudinal Study on Ageing

BACKGROUND

Abnormal lipid profile as one of reversible cardiovascular disease risk factors might be affected by poor sleep quality.

AIM

This study aimed to assess the association between poor sleep quality and serum concentration of lipid profile in Iranian elderly population.

METHODS

The study was performed on a representative sample of 3452 Iranian older people (≥60 years) who contributed in the Iranian Longitudinal Study on Ageing (IRLSA). Sleep quality was measured through the validated Persian version of Pittsburgh Sleep Quality Index (PSQI). Fasting blood samples were collected from the participants to measure plasma levels lipid profile. We used multiple linear regression model to evaluate the independent association of poor sleep quality with lipid profile.

RESULTS

The mean age of participants was 68.0±6.7 years and 52.5% of them were male. In total, 52.4% of study population reported poor sleep quality (PSQI>5). Mean serum concentration of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) was 143.2±74.2 mg/dl, 195.6±43.2 mg/dl, 112.9±31.0 mg/dl, and 57.3±12.4 mg/dl, respectively. Poor sleep quality was significantly associated with serum levels of TG (β=17.85; P=0.006), LDL-C (β=5.45; P=0.039) and HDL-C (β=-2.13; P=0.039) after adjusting for studied covariates.

CONCLUSION

Our study illustrates that poor sleep quality is a risk factor for poorer lipid profile. Therefore, early behavioral or pharmacological interventions that improve sleep quality are necessary to modify lipid profile in elderly population.

Objective sleep and cardiometabolic biomarkers: results from the community of mine study

Study Objectives

Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity.

Methods

Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity.

Results

We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity.

Conclusions

In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

Metabolic risk factors and psychosocial problems independently explain poor sleep quality and obstructive sleep apnea symptoms among adults in urban India

STUDY OBJECTIVES

To determine if metabolic risk factors are associated with poor sleep quality and obstructive sleep apnea-like symptoms (OSA symptoms) independent of psychosocial problems and demographic and lifestyle factors in older Indian adults.

METHODOLOGY

We analyzed baseline data from adults (≥ 50 years) from a population-based cohort, the LoCARPoN study, in India. Variables were grouped as (a) demographic and lifestyle factors such as smoking, alcohol use, and physical activity; (b) psychosocial problems including symptoms of depression, anxiety, and perceived stress; and (c) metabolic risk factors including glycated hemoglobin, high-density lipoprotein, low-density lipoprotein, total cholesterol, body mass index, and hypertension. Variables were examined as predictors of poor sleep quality and OSA symptoms. Groups of variables were added stepwise to a logistic regression. Variance explained by nested models was quantified using McFadden's pseudo R2, and change was formally tested with the log-likelihood ratio test.

RESULTS

Among 7505 adults, the prevalence of poor sleep quality was 16.9% (95% CI: 16.0, 17.7), and OSA symptoms were present in 7.0% (95% CI: 6.4, 7.6). Psychosocial problems had a strong independent association with both poor sleep quality (pseudo R2 increased from 0.10 to 0.15, p < 0.001) and more OSA symptoms (pseudo R2 increased from 0.08 to 0.10, p < 0.001). Metabolic risk factors had a modest independent association with sleep quality (pseudo R2 increased from 0.14 to 0.15, p < 0.01), but a strong association with OSA symptoms (pseudo R2 increased from 0.08 to 0.10, p < 0.001).

CONCLUSION

Psychosocial and metabolic risk factors were independently associated with sleep quality and OSA symptoms. This fact implied that OSA symptoms may affect both mental health and physical health. Our findings have public health implications because the number and proportion of the elderly in India is increasing, while the prevalence of metabolic risk factors and psychosocial problems is high already. These facts have the potential to exacerbate not only the burden of sleep disorders and OSA symptoms but also associated cardiovascular and neurologic sequelae, further stretching the Indian health-care system.

Nutritional geometry framework of sleep

AIMS

Sleep is a fundamental physiological function and is essential for all animals. Sleep is affected by diet compositions including protein (P) and carbohydrates (C), but there has not been a systematic investigation on the effect of dietary macronutrient balance on sleep.

MAIN METHODS

We used the nutritional geometry framework (NGF) to explore the interactive effects on sleep of protein (P) and carbohydrates (C) in the model organism Drosophila. Both female and male flies were fed various diets containing seven ratios of protein-to-carbohydrates at different energetic levels for 5 days and sleep was monitored by the Drosophila Activity Monitor (DAM) system.

KEY FINDINGS

Our results showed that the combination of low protein and high carbohydrates (LPHC) prolonged sleep time and sleep quality, with fewer sleep episodes and longer sleep duration. We further found that the effects of macronutrients on sleep mirrored levels of hemolymph glucose and whole-body glycogen. Moreover, transcriptomic analyses revealed that a high-protein, low-carbohydrate (HPLC) diet significantly elevated the gene expression of metabolic pathways when compared to the LPHC diet, with the glycine, serine, and threonine metabolism pathway being most strongly elevated. Further studies confirmed that the contents of glycine, serine, and threonine affected sleep.

SIGNIFICANCE

Our results demonstrate that sleep is affected by the dietary balance of protein and carbohydrates possibly mediated by the change in glucose, glycogen, glycine, serine, and threonine.

Sex-specific association of sleep duration with subclinical indicators of metabolic diseases among asymptomatic adults

Background

Accumulating evidence suggests sleep duration may be involved in metabolic regulation. However, studies regarding the association with the early stage of the metabolic disease are limited, and the findings were inconsistent.

Methods

A study among 4922 asymptomatic adults was conducted based on a Chinese national survey in 2009. The early stage of metabolic diseases was evaluated using three proxies: triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C), the product of triglyceride and fasting glucose (TyG), and lipid accumulation product (LAP). Multivariable linear and logistic regression models were used to explore the associations of sleep duration with the three indicators.

Results

The linear regression models revealed that, among females, sleep duration <7 h per day, compared with 7-9 h, was associated with an increased value of LAP and TyG by 25.232% (95%CI: 10.738%, 41.623%) and 0.104 (95%CI: 0.024, 0.185), respectively, in the crude model. The effects were attenuated but remained significant for LAP (11.405%; 95%CI: 1.613%, 22.262%). Similarly, the logistic regression models further found that sleep duration <7 h per day could increase the risk of elevated LAP (OR: 1.725, 95CI%:1.042, 2.856) after adjusting for multiple covariates. By contrast, no associations were found among males.

Conclusions

Short sleep duration was associated with subclinical indicators of metabolic diseases, and females were more susceptible to the association.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01626-w.

Difficulty of falling asleep and non-high-density lipoprotein cholesterol level among Canadian older adults: a cross-sectional analysis of the Canadian Longitudinal Study for Aging baseline data

OBJECTIVE

To examine whether difficulty of falling asleep (DoFA) is associated with non-high-density lipoprotein cholesterol (non-HDL-C) level among Canadian older adults.

METHODS

26,954 individuals aged 45–85 years from the baseline data of the Canadian Longitudinal Study for Aging were included in this study. DoFA was categorized into five groups by answer to the question “Over the last month, how often did it take you more than 30 min to fall asleep?” Response options are “Never, < 1 time/week, 1−2 times/week, 3−5 times/week, or 6−7 times/week”. Non-HDL-C, the difference of total cholesterol and HDL-C, were categorized into five categories based on these cut-offs (< 2.6 mmol/L, 2.6−3.7 mmol/L, 3.7−4.8 mmol/L, 4.8−5.7 mmol/L, and ≥ 5.7 mmol/L). Ordinal logistic regression (logit link) continuation ratio models were used to estimate the odds of higher non-HDL-C levels for DoFA status. Adjusted means of non-HDL-C by DoFA status were estimated by general linear models. All analyses were sex separately using analytic weights to ensure generalizability.

RESULTS

The proportions of DoFA in five categories were 41.6%, 25.7%, 13.6%, 9.4%, 9.7% for females and 52.9%, 24.9%, 10.5%, 6.1%, 5.6% for males, respectively. After adjustment of demographical and other covariates (such as depression, comorbidity, sleeping hour, etc.) compared to those who reported never having DoFA, the ORs (95% CIs) of higher levels of non-HDL-C for those whose DoFA status in < 1 time/week, 1−2 times/week, 3−5 times/week, and 6−7 times/week were 1.12 (1.05−1.21), 1.09 (0.99−1.18), 1.20 (1.09−1.33), 1.29 (1.17−1.43) in females and 1.05 (0.98−1.13), 0.95 (0.87−1.05), 1.21 (1.08−1.37), 0.97 (0.85−1.09) in males, respectively. The adjusted means of non-HDL-C among the five DoFA status were 3.68 mmol/L, 3.73 mmol/L, 3.74 mmol/L, 3.82 mmol/L, 3.84 mmol/L for females and 3.54 mmol/L, 3.58 mmol/L, 3.51 mmol/L, 3.69 mmol/L, 3.54 mmol/L for males, respectively.

CONCLUSIONS

The results of this study have identified a risk association pattern between DoFA status and non-HDL-C levels in females but not in males. Further research is needed to confirm these findings.

Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

BACKGROUND

Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease.

METHODS

We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions.

RESULTS

We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures.

CONCLUSIONS

Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

Associations of sleep duration and quality with serum and hepatic lipids: The Netherlands Epidemiology of Obesity Study

Short and long sleep duration and poor sleep quality may affect serum and hepatic lipid content, but available evidence is inconsistent. Therefore, we aimed to investigate the associations of sleep duration and quality with serum and hepatic lipid content in a large population‐based cohort of middle‐aged individuals. The present cross‐sectional study was embedded in the Netherlands Epidemiology of Obesity (NEO) study and consisted of 4260 participants (mean age, 55 years; proportion men, 46%) not using lipid‐lowering agents. Self‐reported sleep duration and quality were assessed using the Pittsburgh Sleep Quality Index questionnaire (PSQI). Outcomes of this study were fasting lipid profile (total cholesterol, low‐density lipoprotein [LDL]‐cholesterol, high‐density lipoprotein [HDL]‐cholesterol and triglycerides), postprandial triglyceride (response) levels, and hepatic triglyceride content (HTGC) as measured with magnetic resonance spectroscopy. We performed multivariable linear regression analyses, adjusted for confounders and additionally for measures that link to adiposity (e.g. body mass index [BMI] and sleep apnea). We observed that relative to the group with median sleep duration (≈7.0 hr of sleep), the group with shortest sleep (≈5.0 hr of sleep) had 1.5‐fold higher HTGC (95% confidence interval [CI]: 1.0‐2.2). The group with PSQI score ≥ 10 had a 1.1‐fold (95% CI: 1.0‐1.2) higher serum triglyceride level compared with the group with PSQI ≤ 5. However, these associations disappeared after adjustment for BMI and sleep apnea. Therefore, we concluded that previously observed associations of shorter sleep duration and poorer sleep quality with an adverse lipid profile, may be explained by BMI and sleep apnea, rather than by a direct effect of sleep on the lipid profile.