Genome-wide gene-sleep interaction study identifies novel lipid loci in 732,564 participants.

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.

Sleep is essential for life, and inappropriate sleep duration patterns may lead to chronic consequences regarding human health. Several studies have confirmed the presence of a U-shaped association between sleep duration and mortality. Moreover, many consequences related to cardiometabolic aspects have been suggested in patients with abnormal sleep durations. In this study, we analyzed the associations between sleep duration, total sleep time (TST), the risk of all-cause mortality, and 10-year cardiovascular risk in a cohort of patients at a sleep medicine center in Santiago, Chile. We conducted a prospective cohort study of patients (SantOSA). A short TST was defined as ≤6 h, a normal TST as 6 to 9 h, and a long TST as ≥9 h. Adjusted hazard ratios (aHRs) for all-cause mortality were calculated. A cross-sectional analysis between TST and 10-year cardiovascular risk (calculated using the Framingham 2008 formula) was determined using logistic regression models. A total of 1385 subjects were included in the results (78% male; median age: 53, interquartile range (IQR): 42-64 years; median BMI: 29.5, IQR: 16.7-33.1). A total of 333 subjects (24%) reported short TSTs, 938 (67.7%) reported normal TSTs, and 114 (8.3%) reported long TSTs. In the fully adjusted model, the association remained significant for short (aHR: 2.51 (1.48-4.25); p-value = 0.01) and long TSTs (aHR: 3.97 (1.53-10.29); p-value = 0.04). Finally, a U-shaped association was found between short and long TSTs, with an increase in cardiovascular risk at 10 years. Compared with normal TSTs, short (≤6 h) and long (≥9 h) TSTs were significantly associated with all-cause mortality and increased 10-year cardiovascular risk.

The aims were (1) to investigate differences by ethnicity and socioeconomic status (SES) in objective measures of sleep in children aged 7-9 years and (2) determine whether measures of sleep predict child achievement in reading or mathematics after controlling for ethnicity and SES. Four groups of parent-child dyads were recruited: Māori, low-SES schools (n = 18); Māori, high-SES schools (n = 17); New Zealand European, low-SES schools (n = 18); New Zealand European, high-SES schools (n = 17). Child sleep was measured by actigraphy. Parents and teachers reported child daytime sleepiness and behavior, and children completed a self-report of anxiety symptoms. Teachers also reported on child achievement in reading and mathematics. Children from low-SES schools went to bed later on school nights (F[1,68] = 12.150, P = .001) and woke later (F[1,68] = 15.978, P < .001) than children from high-SES schools but had similar sleep duration. There were no differences related to ethnicity. Children from low-SES schools were almost 3 times more likely to be below national standards for mathematics. Children not meeting academic standards in mathematics had a later sleep start time, lower sleep period efficiency, and a decreased total sleep time. However, when SES and sleep period efficiency were modeled together neither were found to significantly influence achievement in mathematics. In this study, SES influenced sleep timing but not the quality and quantity of sleep in 7- to 9-year-old children, and a significant independent effect of sleep efficiency on learning could not be demonstrated.

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.

Sleep quality in patients studied with laboratory-based polysomnography may differ from sleep quality in patients studied at home but remains clinically relevant and important to describe. We assessed objective sleep quality and explored factors associated with poor sleep in patients undergoing laboratory-based polysomnography. We reviewed diagnostic polysomnography studies from a 10-year period at a single sleep center. Total sleep time (TST) and sleep efficiency (SE) were assessed as markers of sleep quality. Poor sleep was defined as TST ≤ 4 hours or SE ≤ 50%. Multivariable analysis was performed to determine associations between objective sleep quality as an outcome and multiple candidate predictors including age, sex, race, body mass index, comorbidities, severity of obstructive sleep apnea, and central nervous system medications. Among 4957 patients (age 53 ± 15 years), average TST and median SE were 5.8 hours and 79%, respectively. There were 556 (11%) and 406 (8%) patients who had poor sleep based on TST and SE, respectively. In multivariable analysis, those who were older (per 10 years: 1.48 [1.34, 1.63]), male (1.38 [1.14,1.68]), and had severe obstructive sleep apnea (1.76 [1.28, 2.43]) were more likely to have short sleep. Antidepressant use was associated with lower odds of short sleep (0.77 [0.59,1.00]). Older age (per 10 years: 1.48 [1.34, 1.62]), male sex (1.34 [1.07,1.68]), and severe obstructive sleep apnea (2.16 [1.47, 3.21]) were associated with higher odds of poor SE. We describe TST and SE from a single sleep center cohort. Multiple demographic characteristics were associated with poor objective sleep in patients during laboratory-based polysomnography. Harrison EI, Roth RH, Lobo JM, et al. Sleep time and efficiency in patients undergoing laboratory-based polysomnography. J Clin Sleep Med. 2021;17(8):1591-1598.

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2×10−8. This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

Introduction In the postpartum period, many women experience sleep deficiency due to caring for their infant. Racial disparities exist in sleep characteristics in the adult population, with Black adults having shorter total sleep time (TST) and worse sleep efficiency (SE) than White adults. However, few studies have investigated sleep changes in postpartum Black and White women. The purpose of this study was to examine trajectories of sleep characteristics from 6-8 weeks to 12 months postpartum in Black and White women. Methods Black (n=48) and White (n=86) women who gave birth to a singleton infant at ≥37 weeks gestation, wore an Actiwatch Spectrum Plus (Phillips Respironics, Inc) at 6-8 weeks, 4, 6, 9, and 12 months postpartum. Participants were instructed to wear the monitor, complete a sleep diary, and to maintain their normal daily activities over 7 days. Daily time in bed (TIB), TST, SE, and wake after sleep onset (WASO) were determined. Results Trajectories of TIB, TST, SE and WASO were not different between Black and White women from 6-8 weeks to 12 months postpartum. However, Black women had shorter TIB and TST, and lower sleep efficiency (p&amp;lt;0.001 for all). WASO was similar between Black and White women. For the entire sample, TIB significantly decreased from 470±74 (mean±SD) minutes at 6-8 weeks to 459±54 minutes at 12 months (p=0.0038). TST significantly increased from 347±86 minutes at 6-8 weeks to 369±70 minutes at 4 months (p=0.0085) but did not change at the later timepoints. SE increased from 80±8% at 6-8 weeks to 83±7% at 6 months (p=0.0034) but did not change at the later timepoints. WASO decreased from 54±24 minutes at 6-8 weeks to 46±21 minutes at 4 months (p&amp;lt;0.0001) but did not change at later timepoints. Conclusion In the first year postpartum, Black and White women had similar trajectories for sleep characteristics, but Black women had shorter TIB and TST and lower SE than White women. TIB and WASO decreased while TST and SE increased over time. The first 4 to 6 months show the greatest changes. Support (If Any) NIH Grant R21MD012740

Large-Scale, Genome-Wide Gene-Diet Interaction Testing for HbA1c Using Derived Dietary Patterns in the UK Biobank

> It is not in the stars to hold our destiny but in ourselves > > —William Shakespeare The widespread availability and lower costs of genotyping and sequencing have resulted in the performance of a large number of genotype–phenotype association studies in cardiovascular medicine. The stringent requirements for correction for multiple testing and replication have particularly favored genotype–phenotype studies examining the association between genetic variation and quantitative traits that allows for greater statistical power. Multiple genome-wide association studies and a subsequent meta-analysis have identified >180 common and rare genetic variants associated with lipid traits.1,2 However, the effect size of these individual genetic variants is small, explaining only a small fraction of phenotypic variation prompting investigators to use genetic risk scores (GRS) that represent an aggregate of genetic risk to demonstrate clinical utility. Single-nucleotide polymorphisms (SNPs) and GRS have been used to predict cardiovascular disease such as coronary artery disease (CAD) and hypertension, surrogate markers of disease such as coronary calcium, cardiovascular outcomes such as myocardial infarction, and intermediate traits such as blood pressure and lipids.3 Article, see p 495 The Global Lipids Genetics Consortium has performed the largest genetic association study of lipid levels in 188 577 individuals from a total of 60 studies.1,2 There were 157 genetic loci that were identified, 95 were described previously and 62 were novel. The lipid level variance explained by the novel loci in this study ranged from 1.6% for high-density lipoprotein cholesterol (HDL-C) levels to 2.6% for total cholesterol levels. The total lipid variance explained by the previously described loci was 10% to 12%. The population studied was predominantly of European ancestry, and subjects on lipid-lowering therapy were excluded. The association of these genetic loci with lipid levels and a change in lipid levels with intervention in a prediabetic population …

Introduction Sleep-related behaviors in the realm of pediatrics encompass elements that facilitate sleep, such as a regular sleep schedule, following a bedtime routine, and positive parent-child interactions before bedtime. Several studies have shown a positive association between an early bedtime, consistent routines and parent-infant interaction promoting infant independence in falling asleep with longer sleep duration and less night awakenings. Nonetheless, few studies have investigated bedtime regularity. Thus, we examined the relationships among infants' bedtime, bedtime regularity, total sleep time, night awakenings and sleep latency in infants over the course of one month, utilizing subjective and objective sleep data Methods We recruited 253 infants 4-11 months old (mean 6.7±2months), 46% males. Parents completed surveys on socio-demographic information and the Brief Infant Sleep Questionnaire-Revised (BISQ-R). Objective sleep measures including average bedtime (BT), total sleep time (TST), number of night awakenings (NA) and the standard deviation for bedtime (BTV), were collected for one month using Nanit auto-videosomography (mean 24±5.3nights). Linear and logistic regressions modeled the relationship between BT and BTV as predictors of objective metrics of TST and NA and sleep latency collected from the BISQ-R. Infant’s sex and age were included as covariates. Results Compared to a BTV of 15minutes or less, a BTV of 45minutes to 1 hour was associated with a TST shorter by 28.0±10.2minutes, and a BTV of more than 1hour to TST shorter by 33.5±11.8min. Compared to a BT before 7pm, later BT was associated with a shorter TST. Specifically, TST was 19.7±10 min (p=0.03) less when BT was between 7-8PM, 63.8±10.0 min (p&amp;lt; 0.001) less for BT at 8-9PM, and 126.4±12.7 min (p&amp;lt; 0.001) less when BT was after 9PM. NA were not associated with BT or BTV. BT was associated with sleep latency, with infants going to bed after 9pm being more likely to take more than 16 min to fall asleep compared to infants going to bed before 7pm (OR 9.9 CI 1.22-80.4,p=0.03). Conclusion Higher BTV and BT after 7PM were independently associated with shorter TST in infants. These results provide important information for clinical practice and further work should explore how to incorporate this information in sleep interventions. Support (if any)

Radon is a risk factor for lung cancer and uranium miners are more exposed than the general population. A genome-wide interaction analysis was carried out to identify genomic loci, genes or gene sets that modify the susceptibility to lung cancer given occupational exposure to the radioactive gas radon. Samples from 28 studies provided by the International Lung Cancer Consortium were pooled with samples of former uranium miners collected by the German Federal Office of Radiation Protection. In total, 15,077 cases and 13,522 controls, all of European ancestries, comprising 463 uranium miners were compared. The DNA of all participants was genotyped with the OncoArray. We fitted single-marker and in multi-marker models and performed an exploratory gene-set analysis to detect cumulative enrichment of significance in sets of genes. We discovered a genome-wide significant interaction of the marker rs12440014 within the gene CHRNB4 (OR = 0.26, 95% CI 0.11-0.60, p = 0.0386 corrected for multiple testing). At least suggestive significant interaction of linkage disequilibrium blocks was observed at the chromosomal regions 18q21.23 (p = 1.2 × 10-6), 5q23.2 (p = 2.5 × 10-6), 1q21.3 (p = 3.2 × 10-6), 10p13 (p = 1.3 × 10-5) and 12p12.1 (p = 7.1 × 10-5). Genes belonging to the Gene Ontology term "DNA dealkylation involved in DNA repair" (GO:0006307; p = 0.0139) or the gene family HGNC:476 "microRNAs" (p = 0.0159) were enriched with LD-blockwise significance. The well-established association of the genomic region 15q25 to lung cancer might be influenced by exposure to radon among uranium miners. Furthermore, lung cancer susceptibility is related to the functional capability of DNA damage signaling via ubiquitination processes and repair of radiation-induced double-strand breaks by the single-strand annealing mechanism.

PurposeThe present study was aimed to identify inappropriate sleep duration and its correlates among the Bangladeshi older adults during the COVID-19 pandemic. Material and methodsThis cross-sectional study was carried out among 1030 older adults aged 60 years and above in Bangladesh. Information was collected through telephone interviews using a pretested semi-structures questionnaire installed in SurveyCTO mobile app. Sleep duration was defined as total sleep time (TST) in last 24 h including day and nighttime sleep. TST was further categorized into shorter (<7 h), recommended (7–8 h), and longer sleep (>8 h) according to 2015 National Sleep Foundation guideline. The multinomial logistic regression model identified the factors associated with sleep duration. ResultsMean TST was 7.9 h (SD=1.62). Of the total participants, 28.2% had longer and 17.8% shorter sleep duration. In the regression model, participants’ age of ≥80 years (OR: 3.36, 1.46–7.73), monthly family income of <5,000 Bangladeshi Taka (OR: 3.50, 1.79–6.82), difficulty in getting medicine during COVID-19 (OR: 1.72, 1.05–2.82), lack of communication during the pandemic (OR: 2.20, 1.43–3.40) and receiving COVID-19 related information from friends/family/neighbours (OR: 1.83, 1.11–3.01) were significantly associated with shorter TST. On the other hand, monthly family income of < 5,000 Bangladeshi Taka (OR: 2.00, 1.13–3.53), difficulty in getting medicine during COVID-19 pandemic (OR: 2.01, 1.33–3.03) and receiving COVID-19 related information from radio/TV (OR: 2.09, 1.22–3.59) were associated with longer TST. ConclusionsThe study findings suggest implementing sleep management program for older adults in Bangladesh, particularly during emergencies like COVID-19.

Although questionnaire-based cross-sectional research suggests that screen time before bed correlates with poor sleep, self-reported data seem unlikely to capture the complexity of modern screen use, requiring objective night-by-night measures to advance this field. To examine whether evening screen time is associated with sleep duration and quality that night in youths. This repeated-measures cohort study was performed from March to December 2021 in participant homes in Dunedin, New Zealand. Participants included healthy youths aged 11 to 14.9 years. Data were analyzed from October to November 2023. Objectively measured screen time, captured using wearable or stationary video cameras from 2 hours before bedtime until the first time the youth attempted sleep (shut-eye time) over 4 nonconsecutive nights. Video data were coded using a reliable protocol (κ = 0.92) to quantify device (8 options [eg, smartphone]) and activity (10 options [eg, social media]) type. Sleep duration and quality were measured objectively via wrist-worn accelerometers. The association of screen use with sleep measures was analyzed on a night-by-night basis using mixed-effects regression models including participant as a random effect and adjusted for weekends. Of the 79 participants (47 [59.5%] male; mean [SD] age, 12.9 [1.1] years), all but 1 had screen time before bed. Screen use in the 2 hours before bed had no association with most measures of sleep health that night (eg, mean difference in total sleep time, 0 minutes [95% CI, -3 to 20 minutes] for every 10 minutes more total screen time). All types of screen time were associated with delayed sleep onset but particularly interactive screen use (mean difference, 10 minutes; 95% CI, 4 to 16 minutes for every additional 10 minutes of interactive screen time). Every 10 minutes of additional screen time in bed was associated with shorter total sleep time (mean difference, -3 minutes; 95% CI, -6 to -1 minute). The mean difference in total sleep time was -9 minutes (95% CI, -16 to -2 minutes) for every 10 minutes of interactive screen use and -4 minutes (95% CI, -7 to 0 minutes) for passive screen use. In particular, gaming (mean difference, -17 minutes; 95% CI, -28 to -7 minutes for every 10 minutes of gaming) and multitasking (mean difference, -35 minutes; 95% CI, -67 to -4 minutes on nights with vs without multitasking) were associated with less total sleep time. In this repeated-measures cohort study, use of an objective method showed that screen time once in bed was associated with impairment of sleep, especially when screen time was interactive or involved multitasking. These findings suggest that current sleep hygiene recommendations to restrict all screen time before bed seem neither achievable nor appropriate.

The diagnosis of insomnia rests on self-report of difficulty initiating or maintaining sleep. However, subjective reports may be unreliable, and possibly may vary by the method of inquiry. We investigated this possibility by comparing within-individual response to direct versus indirect time queries after overnight polysomnography. We obtained self-reported sleep-wake times via morning questionnaires in 879 consecutive adult diagnostic polysomnograms. Responses were compared within subjects (direct versus indirect query) and across groups defined by apnea-hypopnea index and by self-reported insomnia symptoms in pre-sleep questionnaires. Direct queries required a time duration response, while indirect queries required clock times from which we calculated time durations. Direct and indirect queries of sleep latency were the same in only 41% of cases, and total sleep time queries matched in only 5.4%. For both latency and total sleep, the most common discrepancy involved the indirect value being larger than the direct response. The discrepancy between direct and indirect queries was not related to objective sleep metrics. The degree of discrepancy was not related to the presence of insomnia symptoms, although patients reporting insomnia symptoms showed underestimation of total sleep duration by direct response. Self-reported sleep latency and total sleep time are often internally inconsistent when comparing direct and indirect survey queries of each measure. These discrepancies represent substantive challenges to effective clinical practice, particularly when diagnosis and management depends on self-reported sleep patterns, as with insomnia. Although self-reported sleep-wake times remains fundamental to clinical practice, objective measures provide clinically relevant adjunctive information.

Joint association of physical activity and night sleep duration with the risk of atherosclerotic cardiovascular disease.