Genetic determinants of daytime napping and effects on cardiometabolic health

Association between napping and 24-hour blood pressure variability among university students: A pilot study

Background

Blood pressure variability (BPV) has been reported to be a predictor of cardiovascular and some cognitive diseases. However, the association between napping and BPV remains unknown. This study aimed to explore the association between napping and BPV.

Materials and methods

A cross-sectional study including 105 university students was conducted. Participants' 24 h ambulatory blood pressure monitoring (24 h ABPM) were measured, and napping behaviors were investigated. BPV were measured by the 24 h ABPM, included standard deviation (SD), coefficient of variation (CV), and average real variability (ARV).

Results

Among the participants, 61.9% reported daytime napping. We found that nap duration was significantly associated with daytime CV of diastolic blood pressure (DBP) (r = 0.250, P = 0.010), nighttime CV of systolic blood pressure (SBP) (r = 0.217, P = 0.026), 24 h WCV of DBP (r = 0.238, P = 0.014), 24 h ARV of SBP (r = 0.246, P = 0.011) and 24 h ARV of DBP (r = 0.291, P = 0.003). Compared with the no napping group, 24 h WCV of DBP, daytime CV of DBP, and daytime SD of DBP were significantly higher in participants with napping duration >60 min. With multiple regression analysis we found that nap duration was an independent predictor for 24 h ARV of SBP (β = 0.859, 95% CI, 0.101-1.616, P = 0.027) and 24 h ARV of DBP (β = 0.674, 95% CI, 0.173-1.175, P = 0.009).

Conclusions

Napping durations are associated with BPV among university students. Especially those with napping durations >60 min had a significantly higher BPV than those non-nappers.

Genetics of circadian rhythms and sleep in human health and disease

Circadian rhythms and sleep are fundamental biological processes integral to human health. Their disruption is associated with detrimental physiological consequences, including cognitive, metabolic, cardiovascular and immunological dysfunctions. Yet many of the molecular underpinnings of sleep regulation in health and disease have remained elusive. Given the moderate heritability of circadian and sleep traits, genetics offers an opportunity that complements insights from model organism studies to advance our fundamental molecular understanding of human circadian and sleep physiology and linked chronic disease biology. Here, we review recent discoveries of the genetics of circadian and sleep physiology and disorders with a focus on those that reveal causal contributions to complex diseases.

Daytime naps and depression risk: A meta-analysis of observational studies

Background

The relationship between daytime napping and depression remains debatable. Thus, a meta-analysis in this study was conducted to evaluate the relationship between daytime napping and depression.

Methods

The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched up to February 2022, and the reference lists of the included studies were also retrieved. A random-effects model was used to estimate the combined effect size.

Results

Nine studies with 649,111 participants were included in the final analysis. The pooled odds ratio (OR) was 1.15 (95% confidence interval: 1.01-1.31) with a significant heterogeneity (I ² = 91.3%, P for heterogeneity <0.001), and the results demonstrated an increased risk of depressive symptoms among daytime nappers. Visual inspection of the funnel plot and Egger's and Begg's tests identified no obvious evidence of publication bias.

Conclusion

This meta-analysis indicates that daytime naps are a predictor of depression. The effects of daytime napping on depression may vary depending on the characteristics of people, the pattern of naps, and the individual's sleep experience. The findings may have significant implications for future research on depression.

Association of daytime napping frequency and schizophrenia: a bidirectional two-sample Mendelian randomization study

BACKGROUND

The bidirectional causal association between daytime napping frequency and schizophrenia is unclear.

METHODS

A bidirectional two-sample Mendelian randomization (MR) analysis was conducted with summary statistics of top genetic variants associated with daytime napping frequency and schizophrenia from genome-wide association studies (GWAS). The single nucleotide polymorphisms (SNPs) data of daytime napping frequency GWAS came from the UK Biobank (n = 452,633) and 23andMe study cohort (n = 541,333), while the schizophrenia GWAS came from the Psychiatric Genomics Consortium (PGC, 36,989 cases and 113,075 controls). The inverse variance weighted (IVW) analysis was the primary method, with the weighted median, MR-Robust Adjusted Profile Score (RAPS), Radial MR and MR-Pleiotropy Residual Sum Outlier (PRESSO) as sensitivity analysis.

RESULTS

The MR analysis showed a bidirectional causal relationship between more frequent daytime napping and the occurrence of schizophrenia, with the odds ratio (OR) for one-unit increase in napping category (never, sometimes, usually) on schizophrenia was 3.38 (95% confidence interval [CI]: 2.02-5.65, P = 3.58 × 10^-6), and the beta for the occurrence of schizophrenia on daytime napping frequency was 0.0112 (95%CI: 0.0060-0.0163, P = 2.04 × 10^-5). The sensitivity analysis obtained the same conclusions.

CONCLUSION

Our findings support the bidirectional causal association between more daytime napping frequency and schizophrenia, implying that daytime napping frequency is a potential intervention for the progression and treatment of schizophrenia.

HCDT: an integrated highly confident drug-target resource

Drug-target association plays an important role in drug discovery, drug repositioning, drug synergy prediction, etc. Currently, a lot of drug-related databases, such as DrugBank and BindingDB, have emerged. However, these databases are separate, incomplete and non-uniform with different criteria. Here, we integrated eight drug-related databases; collected, filtered and supplemented drugs, target genes and experimentally validated (highly confident) associations and built a highly confident drug-target (HCDT: http://hainmu-biobigdata.com/hcdt) database. HCDT database includes 500 681 HCDT associations between 299 458 drugs and 5618 target genes. Compared to individual databases, HCDT database contains 1.1 to 254.2 times drugs, 1.8-5.5 times target genes and 1.4-27.7 times drug-target associations. It is normative, publicly available and easy for searching, browsing and downloading. Together with multi-omics data, it will be a good resource in analyzing the drug functional mechanism, mining drug-related biological pathways, predicting drug synergy, etc. Database URL: http://hainmu-biobigdata.com/hcdt.

Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits

There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.

What have we learned about sleep from selective breeding strategies?

Selective breeding is a classic technique that enables an experimenter to modify a heritable target trait as desired. Direct selective breeding for extreme sleep and circadian phenotypes in flies successfully alters these behaviors, and sleep and circadian perturbations emerge as correlated responses to selection for other traits in mice, rats, and dogs. The application of sequencing technologies to the process of selective breeding identifies the genetic network impacting the selected trait in a holistic way. Breeding techniques preserve the extreme phenotypes generated during selective breeding, generating community resources for further functional testing. Selective breeding is thus a unique strategy that can explore the phenotypic limits of sleep and circadian behavior, discover correlated responses of traits having shared genetic architecture with the target trait, identify naturally-occurring genomic variants and gene expression changes that affect trait variability, and pinpoint genes with conserved roles.

Self-reported daytime napping, daytime sleepiness, and other sleep phenotypes in the development of cardiometabolic diseases: a Mendelian randomization study

AIMS

Sleep disorders are associated with an increased risk of cardiometabolic diseases in observational studies, but the causality remains unclear. In this study, we leveraged two-sample Mendelian randomization (MR) analyses to assess the causal associations of self-reported daytime napping, daytime sleepiness, and other sleep phenotypes with cardiometabolic diseases including ischaemic stroke (IS), coronary artery disease (CAD), heart failure (HF), and Type 2 diabetes mellitus (T2DM).

METHODS AND RESULTS

We selected genetic variants as instrumental variables for self-reported daytime napping, daytime sleepiness, morning person, insomnia, short sleep duration, and long sleep duration from European-descent genome-wide association studies (GWASs). Summary statistics for cardiometabolic diseases originated from four different GWASs with a total of 2 500 086 participants. We used the inverse-variance weighted method to explore the role of self-reported sleep phenotypes on the aetiology of cardiometabolic diseases in the main analyses, followed by several sensitivity analyses for robustness validation. Genetically predicted self-reported daytime napping [T2DM: OR, 1.56 (95% confidence interval, 1.21-2.02)], insomnia [IS: OR, 1.07 (1.04-1.11)]; CAD: OR, 1.13 (1.08-1.17); HF: OR, 1.10 (1.07-1.14); T2DM: OR, 1.16 (1.11-1.22); and short sleep duration [CAD: OR, 1.37 (1.21-1.55)] were causally associated with an elevated risk of cardiometabolic diseases. Moreover, genetically determined self-reported daytime sleepiness [CAD: OR, 2.05 (1.18-3.57); HF: OR, 1.82 (1.15-2.87)] and morning person [HF: 1.06 OR, (1.01-1.11)] had potential detrimental effect on cardiometabolic risks.

CONCLUSION

Self-reported daytime napping, insomnia, and short sleep duration had causal roles in the development of cardiometabolic diseases, while self-reported daytime sleepiness and morning person was the potential risk factor for cardiometabolic diseases.

Sleep exerts lasting effects on hematopoietic stem cell function and diversity

A sleepless night may feel awful in its aftermath, but sleep's revitalizing powers are substantial, perpetuating the idea that convalescent sleep is a consequence-free physiological reset. Although recent studies have shown that catch-up sleep insufficiently neutralizes the negative effects of sleep debt, the mechanisms that control prolonged effects of sleep disruption are not understood. Here, we show that sleep interruption restructures the epigenome of hematopoietic stem and progenitor cells (HSPCs) and increases their proliferation, thus reducing hematopoietic clonal diversity through accelerated genetic drift. Sleep fragmentation exerts a lasting influence on the HSPC epigenome, skewing commitment toward a myeloid fate and priming cells for exaggerated inflammatory bursts. Combining hematopoietic clonal tracking with mathematical modeling, we infer that sleep preserves clonal diversity by limiting neutral drift. In humans, sleep restriction alters the HSPC epigenome and activates hematopoiesis. These findings show that sleep slows decay of the hematopoietic system by calibrating the hematopoietic epigenome, constraining inflammatory output, and maintaining clonal diversity.

Genetic estimation of correlations and causalities between multifaceted modifiable factors and gastro-oesophageal reflux disease

BACKGROUND

Gastro-oesophageal reflux disease (GORD) is a common gastrointestinal dysfunction that significantly affects the quality of daily life, and health interventions are challenging to prevent the risk of GORD. In this study, we used Mendelian randomization framework to genetically determine the causal associations between multifaceted modifiable factors and the risk of GORD.

MATERIALS AND METHODS

Sixty-six exposures with available instrumental variables (IVs) across 6 modifiable pathways were included in the univariable MR analysis (UVMR). Summary-level genome-wide association studies (GWAS) datasets for GORD were retrieved from the Neale Lab (GORD Neale , Ncases = 29975, Ncontrols = 390556) and FinnGen (GORD Finn , Ncases = 13141, Ncontrols = 89695). Using the METAL software, meta-analysis for single nucleotide polymorphisms (SNPs) from GORD Neale and GORD Finn was conducted with an inverse variance weighted (IVW) fixed-effect model. Moreover, we leveraged partition around medoids (PAM) clustering algorithm to cluster genetic correlation subtypes, whose hub exposures were conditioned for multivariable MR (MVMR) analyses. P-values were adjusted with Bonferroni multiple comparisons.

RESULTS

Significant causal associations were identified between 26 exposures (15 risk exposures and 11 protective exposures) and the risk of GORD. Among them, 13 risk exposures [lifetime smoking, cigarette consumption, insomnia, short sleep, leisure sedentary behavior (TV watching), body mass index (BMI), body fat percentage, whole body fat mass, visceral adipose tissue, waist circumference, hip circumference, major depressive disorder, and anxious feeling], and 10 protective exposures (leisure sedentary behavior (computer use), sitting height, hand grip strength (left and right), birth weight, life satisfaction, positive affect, income, educational attainment, and intelligence) showed novel significant causal associations with the risk of GORD. Moreover, 13 exposures still demonstrated independent associations with the risk of GORD following MVMR analyses conditioned for hub exposures (educational attainment, smoking initiation and BMI). In addition, 12 exposures showed suggestive causal associations with the risk of GORD.

CONCLUSION

This study systematically elucidated the modifiable factors causally associated with the risk of GORD from multifaceted perspectives, which provided implications for prevention and treatment of GORD.

Influence of DNA-Polymorphisms in Selected Circadian Clock Genes on Clock Gene Expression in Subjects from the General Population and Their Association with Sleep Duration

Background and Objectives: Circadian rhythms have an important implication in numerous physiological and metabolic processes, including the sleep/wake cycle. Inter-individual differences in factors associated with circadian system may be due to gene differences in gene expression. Although several studies have analyzed the association between DNA polymorphisms and circadian variables, the influence on gene expression has been poorly analyzed. Our goal was to analyze the association of genetic variations in the clock genes and the gene expression level. Materials and Methods: We carried out a cross-sectional study of 102 adults (50.9% women). RNA and DNA were isolated from blood and single-nucleotide polymorphisms (SNPs), and the main circadian clock genes were determined. Gene expression of CLOCK, PER1, and VRK2 genes was measured by Reverse-transcription polymerase chain reaction (RT-PCR). The association between the DNA-SNPs and gene expression was analyzed at the gene level. In addition, a polygenic risk score (PRS), including all the significant SNPs related to gene expression, was created for each gene. Multivariable model analysis was performed. Results: Sex-specific differences were detected in PER1 expression, with these being higher in women (p = 0.034). No significant differences were detected in clock genes expression and lifestyle variables. We observed a significant association between the ARNTL-rs7924734, ARNTL-rs10832027, VRK2- rs2678902 SNPs, and CLOCK gene expression; the PER3-rs228642 and PER3-rs10127838 were related to PER1 expression, and the ARNTL-rs10832027, ARNTL-rs11022778, and MNTR1B-rs10830963 were associated with VRK2 gene expression (p < 0.05). The specific PRS created was significantly associated with each of the gene expressions analyzed (p < 0.001). Finally, sleep duration was associated with PER3-rs238666 (p = 0.008) and CLOCK-rs4580704 (p = 0.023). Conclusion: We detected significant associations between DNA-SNPs in the clock genes and their gene expression level in leukocytes and observed some differences in gene expression per sex. Moreover, we reported for the first time an association between clock gene polymorphisms and CLOCK, PER1, and VRK2 gene expression. These findings need further investigation.

Hunt for mammalian sleep-regulating genes

Genetics is one of the various approaches adopted to understand and control mammalian sleep. Reverse genetics, which is usually applied to analyze sleep in gene-deficient mice, has been the mainstream field of genetic studies on sleep for the past three decades and has revealed that various molecules, including orexin, are involved in sleep regulation. Recently, forward genetic studies in humans and mice have identified gene mutations responsible for heritable sleep abnormalities, such as SIK3, NALCN, DEC2, the neuropeptide S receptor, and β1 adrenergic receptor. Furthermore, the protein kinase A-SIK3 pathway was shown to represent the intracellular neural signaling for sleep need. Large-scale genome-wide analyses of human sleep have been conducted, and many gene loci associated with individual differences in sleep have been found. The development of genome-editing technology and gene transfer by an adeno-associated virus has updated and expanded the genetic studies on mammals. These efforts are expected to elucidate the mechanisms of sleep–wake regulation and develop new therapeutic interventions for sleep disorders.

Association of Nap Frequency With Hypertension or Ischemic Stroke Supported by Prospective Cohort Data and Mendelian Randomization in Predominantly Middle-Aged European Subjects

BACKGROUND AND PURPOSE

The aim of this study was to investigate the association between daytime napping frequency and the incidence of essential hypertension or stroke as well as to validate causality in this relationship via Mendelian randomization (MR).

METHODS

We conducted Cox regression analysis on 358 451 participants free of hypertension or stroke from UK Biobank. To validate the results of the observational analysis, we conducted a 2-sample MR for daytime napping frequency (123 single-nucleotide polymorphisms) with essential hypertension in FinnGen Biobank, stroke, and ischemic stroke in MEGASTROKE consortium and performed a corresponding 1-sample MR on the UK Biobank data.

RESULTS

Compared with never napping, usually napping was associated with a higher risk of essential hypertension (hazard ratio, 1.12 [95% CI, 1.08-1.17]), stroke (hazard ratio, 1.24 [95% CI, 1.10-1.39], and ischemic stroke (hazard ratio, 1.20 [95% CI, 1.05-1.36]) in our prospective observational analysis. Both the 1-sample and 2-sample MR results indicated that increased daytime napping frequency was likely to be a potential causal risk factor for essential hypertension in FinnGEN (odds ratio, 1.43 [95% CI, 1.06-1.92]) and UK Biobank (odds ratio, 1.40 [95% CI, 1.28-1.58]). The 2-sample MR results supported the potential causal effect of nap frequency on ischemic stroke in MEGASTROKE (odds ratio, 1.29 [95% CI, 1.04-1.62]).

CONCLUSIONS

Prospective observational and MR analyses provided evidence that increased daytime nap frequency may represent a potential causal risk factor for essential hypertension. The potential causal association of increased nap frequency with ischemic stroke was supported by 2-sample MR and prospective observational results.

Orexin 2 receptor-selective agonist danavorexton improves narcolepsy phenotype in a mouse model and in human patients

Narcolepsy type 1 (NT1) is a sleep disorder caused by a loss of orexinergic neurons. Narcolepsy type 2 (NT2) is heterogeneous; affected individuals typically have normal orexin levels. Following evaluation in mice, the effects of the orexin 2 receptor (OX2R)-selective agonist danavorexton were evaluated in single- and multiple-rising-dose studies in healthy adults, and in individuals with NT1 and NT2. In orexin/ataxin-3 narcolepsy mice, danavorexton reduced sleep/wakefulness fragmentation and cataplexy-like episodes during the active phase. In humans, danavorexton administered intravenously was well tolerated and was associated with marked improvements in sleep latency in both NT1 and NT2. In individuals with NT1, danavorexton dose-dependently increased sleep latency in the Maintenance of Wakefulness Test, up to the ceiling effect of 40 min, in both the single- and multiple-rising-dose studies. These findings indicate that OX2Rs remain functional despite long-term orexin loss in NT1. OX2R-selective agonists are a promising treatment for both NT1 and NT2.

Evaluating the Bidirectional Causal Association Between Daytime Napping and Alzheimer’s Disease Using Mendelian Randomization

Background: Until now, both cross-sectional and longitudinal studies have identified controversial findings about the association between daytime napping and Alzheimer’s disease (AD) or cognitive decline. Therefore, it remains unclear about the causal association between daytime napping and AD or cognitive decline. Objective: We aim to investigate the causal association between daytime napping and AD. Methods: Here, we conduct a bidirectional Mendelian randomization (MR) analysis to investigate the causal association between daytime napping and AD using large-scale GWAS datasets from daytime napping including 452,633 individuals of European ancestry and AD including 35,274 AD and 59,163 controls of European ancestry. A total of five MR methods are selected including inverse-variance weighted (IVW), weighted median, MR-Egger, MR-PRESSO, and contamination mixture method. Results: MR analysis highlights significant causal association of AD with daytime napping using IVW (beta = -0.006, 95% CI [–0.009, –0.002], p = 2.00E-03), but no significant causal association of daytime napping with AD using IVW (OR = 0.76, 95% CI 0.53-1.10, p = 1.40E-01). Conclusion: Our bidirectional MR analysis demonstrates the causal effect of AD on daytime napping. However, there is no causal effect of daytime napping on AD. Our current findings are consistent with recent evidence from other MR studies that highlight little evidence supporting a causal effect of sleep traits on AD and support the causal effect of AD on sleep traits.

Alleviating insomnia should decrease the risk of irritable bowel syndrome: Evidence from Mendelian randomization

Background: Associations have been reported between sleep and irritable bowel syndrome (IBS). However, whether there exists a causation between them is still unknown.

Methods: We employed the Mendelian randomization (MR) design to explore the causal relationship between sleep and IBS. All genetic associations with sleep-related traits reached genome-wide significance (p-value < 5 × 10-8). The genetic associations with IBS were obtained from two independent large genome-wide association studies (GWAS), where non-FinnGen GWAS was in the discovery stage and FinnGen GWAS was in the validation stage. Primarily, the inverse-variance weighted method was employed to estimate the causal effects, and a meta-analysis was performed to combine the MR estimates.

Results: In the discovery, we observed that genetic liability to the “morning” chronotype could lower the risk of IBS [OR = 0.81 (0.76, 0.86)]. Also, the genetic liability to insomnia can increase the risk of IBS [OR = 2.86 (1.94, 4.23)] and such causation was supported by short sleep duration. In the validation stage, only insomnia displayed statistical significance [OR = 2.22 (1.09, 4.51)]. The meta-analysis suggested two genetically-determined sleep exposures can increase the risk of IBS, including insomnia [OR = 2.70 (1.92, 3.80)] and short sleep duration [OR = 2.46 (1.25, 4.86)]. Furthermore, the multivariable MR analysis suggested insomnia is an independent risk factor for IBS after adjusting for chronotype [OR = 2.32 (1.57, 3.43)] and short sleep duration [OR = 1.45 (1.13, 1.85)]. IBS cannot increase the risk of insomnia in the reverse MR analysis.

Conclusion: Genetic susceptibility to insomnia can increase the risk of IBS, and improving sleep quality, especially targeting insomnia, can help to prevent IBS.

Daytime napping and cardiovascular risk factors, cardiovascular disease, and mortality: A systematic review

Associations between night sleep duration and cardiovascular risk factors in adults have been well documented. However, the associations for daytime napping remain unclear. In this review, six databases were searched for eligible publications to April 8, 2022. A total of 11 articles were identified for umbrella review on the association of daytime napping with diabetes, metabolic syndrome (MetS), cardiovascular disease (CVD), and mortality in adults, 97 for systematic review on the association with CVD and several CVD risk factors. Our umbrella review showed that the associations of daytime napping with diabetes, MetS, CVD, and mortality in most meta-analyses were mainly supported by weak or suggestive evidence. Our systematic review showed that long daytime napping (≥1 h/d) was associated with higher odds of several CVD risk factors, CVD, and mortality, but no significant association was found between short daytime napping and most of the abovementioned outcomes. Our dose-response meta-analyses showed that daytime napping <30 min/d was not significantly associated with higher odds of most CVD risk factors and CVD among young and middle-aged adults. However, among older adults aged >60 years, we observed significant dose-response associations of daytime napping with higher odds of diabetes, dyslipidemia, MetS, and mortality starting from 0 min/d.

Association of Sleep Duration, Napping, and Sleep Patterns With Risk of Cardiovascular Diseases: A Nationwide Twin Study

Background

Although sleep disorders have been linked to cardiovascular diseases (CVDs), the association between sleep characteristics and CVDs remains inconclusive. We aimed to examine the association of nighttime sleep duration, daytime napping, and sleep patterns with CVDs and explore whether genetic and early‐life environmental factors account for this association.

Methods and Results

In the Swedish Twin Registry, 12 268 CVD‐free twin individuals (mean age=70.3 years) at baseline were followed up to 18 years to detect incident CVDs. Sleep duration, napping, and sleep patterns (assessed by sleep duration, chronotype, insomnia, snoring, and daytime sleepiness) were self‐reported at baseline. CVDs were ascertained through the Swedish National Patient Registry and the Cause of Death Register. Data were analyzed using a Cox model. In the multiadjusted Cox model, compared with 7 to 9 hours/night, the hazard ratios (HRs) of CVDs were 1.14 (95% CI, 1.01–1.28) for <7 hours/night and 1.10 (95% CI, 1.00–1.21) for ≥10 hours/night, respectively. Compared with no napping, napping 1 to 30 minutes (HR, 1.11 [95% CI, 1.03–1.18]) and >30 minutes (HR, 1.23 [95% CI, 1.14–1.33]) were related to CVDs. Furthermore, a poor sleep pattern was associated with CVDs (HR, 1.22 [95% CI, 1.05–1.41]). The co‐twin matched control analyses showed similar results as the unmatched analyses, and there was no significant interaction between sleep characteristics and zygosity (P values >0.05).

Conclusions

Short or long sleep (<7 or ≥10 hours/night), napping, and poor sleep patterns are associated with an increased CVD risk. Genetic and early‐life environmental factors may not account for the sleep–CVD association.

Genetic evidence for a potential causal relationship between insomnia symptoms and suicidal behavior: a Mendelian randomization study

Insomnia and restless leg syndrome (RLS) are associated with increased risk for suicidal behavior (SB), which is often comorbid with mood or thought disorders; however, it is unclear whether these relationships are causal. We performed a two-sample Mendelian randomization study using summary-level genetic associations with insomnia symptoms and RLS against the outcomes of risk of major depressive disorder (MDD), bipolar disorder (BP), schizophrenia (SCZ), and SB. The inverse-variance weighted method was used in the main analysis. We performed replication and sensitivity analyses to examine the robustness of the results. We identified outcome cohorts for MDD (n = 170,756 cases/329,443 controls), BP (n = 20,352/31,358), SCZ (n = 69,369/236,642), SB-Cohort-2019 (n = 6569/14,996 all with MDD, BP or SCZ; and SB within individual disease categories), and SB-Cohort-2020 (n = 29,782/519,961). Genetically proxied liability to insomnia symptoms significantly associated with increased risk of MDD (odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.2-1.26, P = 1.37 × 10-61), BP (OR = 1.15, 95% CI = 1.07-1.23, P = 5.11 × 10-5), SB-Cohort-2019 (OR = 1.17, 95% CI = 1.07-1.27, P = 2.30 × 10-4), SB-Cohort-2019 in depressed patients (OR = 1.34, 95% CI = 1.16-1.54, P = 5.97 × 10-5), and SB-Cohort-2020 (OR = 1.24, 95% CI = 1.18-1.3, P = 1.47 × 10-18). Genetically proxied liability to RLS did not significantly influence the risk of any of the outcomes (all corrected P > 0.05). Results were replicated for insomnia with MDD and SB in Mass General Brigham Biobank and were consistent in multiple lines of sensitivity analyses. In conclusion, human genetic evidence supports for the first time a potentially independent and causal effect of insomnia on SB and encourages further clinical investigation of treatment of insomnia for prevention or treatment of SB.

The causal relationship between sleep traits and the risk of schizophrenia: a two-sample bidirectional Mendelian randomization study

BACKGROUND

Observational studies suggest that sleep disturbances are commonly associated with schizophrenia. However, it is uncertain whether this relationship is causal. To investigate the bidirectional causal relation between sleep traits and schizophrenia, we performed a two-sample bidirectional Mendelian randomization (MR) study with the fixed effects inverse-variance weighted (IVW) method.

METHODS

As genetic variants for sleep traits, we selected variants from each meta-analysis of genome-wide association studies (GWASs) conducted using data from the UK Biobank (UKB).

RESULTS

We found that morning diurnal preference was associated with a lower risk of schizophrenia, while long sleep duration and daytime napping were associated with a higher risk of schizophrenia. Multivariable MR analysis also showed that sleep duration was associated with a higher risk of schizophrenia after adjusting for other sleep traits. Furthermore, genetically predicted schizophrenia was negatively associated with morning diurnal preference and short sleep duration and was positively associated with daytime napping and long sleep duration.

CONCLUSIONS

Therefore, sleep traits were identified as a potential treatment target for patients with schizophrenia.

Associations of sleep and circadian phenotypes with COVID-19 susceptibility and hospitalization: an observational cohort study based on the UK Biobank and a two-sample Mendelian randomization study

Study Objectives

Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes.

Methods

Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Beta values and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods.

Results

In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR=1.24, 95% CI=1.02-1.5; daytime napping [sometimes vs. never]: RR=1.12, 95% CI=1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR= 1.04, 95% CI=1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes.

Conclusions

Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate.

A rare genetic variant in the cleavage site of prepro-orexin is associated with idiopathic hypersomnia

Idiopathic hypersomnia (IH) is a rare, heterogeneous sleep disorder characterized by excessive daytime sleepiness. In contrast to narcolepsy type 1, which is a well-defined type of central disorders of hypersomnolence, the etiology of IH is poorly understood. No susceptibility loci associated with IH have been clearly identified, despite the tendency for familial aggregation of IH. We performed a variation screening of the prepro-orexin/hypocretin and orexin receptors genes and an association study for IH in a Japanese population, with replication (598 patients and 9826 controls). We identified a rare missense variant (g.42184347T>C; p.Lys68Arg; rs537376938) in the cleavage site of prepro-orexin that was associated with IH (minor allele frequency of 1.67% in cases versus 0.32% in controls, P = 2.7 × 10-8, odds ratio = 5.36). Two forms of orexin (orexin-A and -B) are generated from cleavage of one precursor peptide, prepro-orexin. The difference in cleavage efficiency between wild-type (Gly-Lys-Arg; GKR) and mutant (Gly-Arg-Arg; GRR) peptides was examined by assays using proprotein convertase subtilisin/kexin (PCSK) type 1 and PCSK type 2. In both PCSK1 and PCSK2 assays, the cleavage efficiency of the mutant peptide was lower than that of the wild-type peptide. We also confirmed that the prepro-orexin peptides themselves transmitted less signaling through orexin receptors than mature orexin-A and orexin-B peptides. These results indicate that a subgroup of IH is associated with decreased orexin signaling, which is believed to be a hallmark of narcolepsy type 1.

Validation of Candidate Sleep Disorder Risk Genes Using Zebrafish

Sleep disorders and chronic sleep disturbances are common and are associated with cardio-metabolic diseases and neuropsychiatric disorders. Several genetic pathways and neuronal mechanisms that regulate sleep have been described in animal models, but the genes underlying human sleep variation and sleep disorders are largely unknown. Identifying these genes is essential in order to develop effective therapies for sleep disorders and their associated comorbidities. To address this unmet health problem, genome-wide association studies (GWAS) have identified numerous genetic variants associated with human sleep traits and sleep disorders. However, in most cases, it is unclear which gene is responsible for a sleep phenotype that is associated with a genetic variant. As a result, it is necessary to experimentally validate candidate genes identified by GWAS using an animal model. Rodents are ill-suited for this endeavor due to their poor amenability to high-throughput sleep assays and the high costs associated with generating, maintaining, and testing large numbers of mutant lines. Zebrafish (Danio rerio), an alternative vertebrate model for studying sleep, allows for the rapid and cost-effective generation of mutant lines using the CRISPR/Cas9 system. Numerous zebrafish mutant lines can then be tested in parallel using high-throughput behavioral assays to identify genes whose loss affects sleep. This process identifies a gene associated with each GWAS hit that is likely responsible for the human sleep phenotype. This strategy is a powerful complement to GWAS approaches and holds great promise to identify the genetic basis for common human sleep disorders.

Association of Poor Sleep Burden in Middle Age and Older Adults With Risk for Delirium During Hospitalization

BACKGROUND

Delirium is a distressing neurocognitive disorder recently linked to sleep disturbances. However, the longitudinal relationship between sleep and delirium remains unclear. This study assessed the associations of poor sleep burden, and its trajectory, with delirium risk during hospitalization.

METHODS

About 321 818 participants from the UK Biobank (mean age 58 ± 8 years [SD]; range 37-74 years) reported (2006-2010) sleep traits (sleep duration, excessive daytime sleepiness, insomnia-type complaints, napping, and chronotype-a closely related circadian measure for sleep timing), aggregated into a sleep burden score (0-9). New-onset delirium (n = 4 775) was obtained from hospitalization records during a 12-year median follow-up. About 42 291 (mean age 64 ± 8 years; range 44-83 years) had repeat sleep assessment on average 8 years after their first.

RESULTS

In the baseline cohort, Cox proportional hazards models showed that moderate (aggregate scores = 4-5) and severe (scores = 6-9) poor sleep burden groups were 18% (hazard ratio = 1.18 [95% confidence interval: 1.08-1.28], p < .001) and 57% (1.57 [1.38-1.80], p < .001), more likely to develop delirium, respectively. The latter risk magnitude is equivalent to 2 additional cardiovascular risks. These findings appeared robust when restricted to postoperative delirium and after exclusion of underlying dementia. Higher sleep burden was also associated with delirium in the follow-up cohort. Worsening sleep burden (score increase ≥2 vs no change) further increased the risk for delirium (1.79 [1.23-2.62], p = .002) independent of their baseline sleep score and time lag. The risk was highest in those younger than 65 years at baseline (p for interaction <.001).

CONCLUSION

Poor sleep burden and worsening trajectory were associated with increased risk for delirium; promotion of sleep health may be important for those at higher risk.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

A variant in orexin receptor-2 is associated with self-reported daytime sleepiness in the Japanese population

Excessive daytime sleepiness is characterized by a persistent feeling of having trouble staying awake, typically with inappropriate sleep episodes. Orexin (hypocretin) is a neuropeptide that regulates sleep-wake cycles and rapid eye movement sleep. Several large-scale genome-wide association studies (GWASs) in European populations have found genetic variants in orexin receptor-1 (OX1R) and -2 (OX2R) that are associated with sleep traits including daytime sleepiness. To identify genetic variants associated with daytime sleepiness, we performed an association study of genetic variants in prepro-orexin, OX1R, and OX2R in 14,329 Japanese individuals from the Tohoku Medical Megabank Project cohort. A genetic variant in OX2R was significantly associated with self-reported daytime sleepiness after Bonferroni correction (rs188018846: P = 8.4E-05). In addition, a missense variant in OX2R identified by the European GWASs showed a nominally significant association with daytime sleepiness in a Japanese population (p.Ile308Val, rs2653349: P = 0.044). Multiple genetic variants in OX2R can affect daytime sleepiness in general populations.

Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank

BACKGROUND

Genetic and lifestyle factors have considerable effects on obesity and related diseases, yet their effects in a clinical cohort are unknown. This study in a patient biobank examined associations of a BMI polygenic risk score (PRS), and its interactions with lifestyle risk factors, with clinically measured BMI and clinical phenotypes.

METHODS

The Mass General Brigham (MGB) Biobank is a hospital-based cohort with electronic health record, genetic, and lifestyle data. A PRS for obesity was generated using 97 genetic variants for BMI. An obesity lifestyle risk index using survey responses to obesogenic lifestyle risk factors (alcohol, education, exercise, sleep, smoking, and shift work) was used to dichotomize the cohort into high and low obesogenic index based on the population median. Height and weight were measured at a clinical visit. Multivariable linear cross-sectional associations of the PRS with BMI and interactions with the obesity lifestyle risk index were conducted. In phenome-wide association analyses (PheWAS), similar logistic models were conducted for 675 disease outcomes derived from billing codes.

RESULTS

Thirty-three thousand five hundred eleven patients were analyzed (53.1% female; age 60.0 years; BMI 28.3 kg/m²), of which 17,040 completed the lifestyle survey (57.5% female; age: 60.2; BMI: 28.1 (6.2) kg/m²). Each standard deviation increment in the PRS was associated with 0.83 kg/m² unit increase in BMI (95% confidence interval (CI) =0.76, 0.90). There was an interaction between the obesity PRS and obesity lifestyle risk index on BMI. The difference in BMI between those with a high and low obesogenic index was 3.18 kg/m² in patients in the highest decile of PRS, whereas that difference was only 1.55 kg/m² in patients in the lowest decile of PRS. In PheWAS, the obesity PRS was associated with 40 diseases spanning endocrine/metabolic, circulatory, and 8 other disease groups. No interactions were evident between the PRS and the index on disease outcomes.

CONCLUSIONS

In this hospital-based clinical biobank, obesity risk conferred by common genetic variants was associated with elevated BMI and this risk was attenuated by a healthier patient lifestyle. Continued consideration of the role of lifestyle in the context of genetic predisposition in healthcare settings is necessary to quantify the extent to which modifiable lifestyle risk factors may moderate genetic predisposition and inform clinical action to achieve personalized medicine.

Obesity indicators as mediators of association between daytime napping and type 2 diabetes mellitus: the Guangzhou Biobank Cohort Study

OBJECTIVE

To examine the mediating effect of obesity indicators on the association between daytime napping and type 2 diabetes mellitus (T2DM) qualitatively and quantitatively using baseline data from the Guangzhou Biobank Cohort Study.

METHODS

Twenty-nine thousand three hundred fifty-five participants aged 50+ years were included in this cross-sectional study. Mediation analysis was used to assess the mediating effect of body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) on the association between daytime napping and T2DM after adjustment for sex, age, education, occupation, smoking status, alcohol use and physical activity.

RESULTS

The mean (standard deviation) age of participants was 61.5 ( 7.1) years. The prevalence of T2DM and daytime napping was 12.5% and 65.2%, respectively. After adjustment for potential confounders, WC, WHR and WHtR showed partial mediating effects on the association between daytime napping and T2DM, with the proportion (95% confidence interval) of mediation effect being 10.17% (8.14-14.43%), 14.91% (11.95-21.24%) and 9.36% (7.49-13.29%), respectively. No mediating effect of BMI or HC on the association between daytime napping and T2DM was found.

CONCLUSIONS

Our results showed significant mediating effects of WC, WHR and WHtR on the association between daytime napping and T2DM, suggesting that waist circumference management could be important in daytime nappers.

Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort

PURPOSE

Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits.

PATIENTS AND METHODS

We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correlations between sleep health score and other functionally relevance traits.

RESULTS

GWAS identified multiple variants near known candidate genes associated with sleep health score, such as MEIS1, FBXL13, MED20 and SMAD5. HDHD2 (PPWAS = 0.0146) and GFAP (PPWAS = 0.0236) were identified associated with sleep health score by PWAS. TWAS identified ORC4 (PTWAS = 0.0212) and ZNF732 (PTWAS = 0.0349) considering mRNA expression level. LDSC found significant genetic correlations of sleep health score with 3 sleep behaviors (including insomnia, snoring, dozing), 4 psychiatry disorders (major depressive disorder, attention deficit/hyperactivity disorder, schizophrenia, autism spectrum disorder), and 9 plasma protein (such as Stabilin-1, Stromelysin-2, Cytochrome c) (all LDSC PLDSC < 0.05).

CONCLUSION

Our results advance the comprehensive understanding of the aetiology and genetic architecture of the sleep health score, refine the understanding of the relationship of sleep health score with other traits and diseases, and may serve as potential targets for future mechanistic studies of sleep phenotype.

Differential Sleep Traits Have No Causal Effect on Inflammatory Bowel Diseases: A Mendelian Randomization Study

Background: Previous studies suggested an association of sleep disorders with inflammatory bowel disease (IBD) and indicated that using pharmacological treatments for the modulation of circadian rhythms might prevent IBD pathogenesis or aggravation, but whether the effect of sleep traits on IBD was causal is inconclusive and, therefore, prevents drug repurposing based on the previous studies. We aimed to examine the causal effect of different sleep traits on the pathogenesis of IBD. Methods: Genetic instruments for sleep traits were selected from the largest GWAS studies available in the UK Biobank (n = 449,734) and the 23andMe Research (n = 541,333). A two-sample Mendelian randomization (MR) study was conducted to examine the association of the genetic instruments with IBD (12,882 cases and 21,770 controls), ulcerative colitis (6,968 cases, 20,464 controls), and Crohn's disease (5,956 cases and 14,927 controls). We applied the inverse-variance weighted (IVW) method to estimate causal effects, and we used the weighted median and MR-Egger method for sensitivity analyses. Results: We found that sleep duration (OR, 1.00, 95% CI 1.00-1.01), short sleep duration (OR, 1.07, 95% CI 0.41-2.83), morningness (OR, 1.05, 95% CI 0.87-1.27), daytime napping (OR, 1.64, 95% CI 0.62-4.4), frequent insomnia (OR, 1.17, 95% CI 0.8-1.72), any insomnia (OR, 1.17, 95% CI 0.69-1.97), and snoring (OR, 0.31, 95% CI 0.06-1.54) had no causal effect on IBD, and these sleep traits had no causal effect on ulcerative colitis and Crohn's disease either. Most of the sensitivity analyses showed consistent results with those of the IVW method. Conclusion: Our MR study did not support the causal effect of sleep traits on IBD. Pharmacological modulation of circadian rhythms for the prevention of IBD pathogenesis was unwarranted.

GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent, and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understanding their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together, these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

Delta-5-desaturase: A novel therapeutic target for cancer management

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D5D is an independent prognostic factor in cancer.

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D5D aggravates cancer progression via mediating AA/PGE₂ production from DGLA.

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AA/PGE₂ promotes cancer progression via regulating the tumor microenvironment.

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Inhibition of D5D redirects COX-2 catalyzed DGLA peroxidation, producing 8-HOA.

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8-HOA suppress cancer by regulating proliferation, apoptosis, and metastasis.

Delta-5 desaturase (D5D) is a rate-limiting enzyme that introduces double-bonds to the delta-5 position of the n-3 and n-6 polyunsaturated fatty acid chain. Since fatty acid metabolism is a vital factor in cancer development, several recent studies have revealed that D5D activity and expression could be an independent prognostic factor in cancers. However, the mechanistic basis of D5D in cancer progression is still controversial. The classical concept believes that D5D could aggravate cancer progression via mediating arachidonic acid (AA)/prostaglandin E₂ production from dihomo-γ-linolenic acid (DGLA), resulting in activation of EP receptors, inflammatory pathways, and immunosuppression. On the contrary, D5D may prevent cancer progression through activating ferroptosis, which is iron-dependent cell death. Suppression of D5D by RNA interference and small-molecule inhibitor has been identified as a promising anti-cancer strategy. Inhibition of D5D could shift DGLA peroxidation pattern from generating AA to a distinct anti-cancer free radical byproduct, 8-hydroxyoctanoic acid, resulting in activation of apoptosis pathway and simultaneously suppression of cancer cell survival, proliferation, migration, and invasion. Hence, understanding the molecular mechanisms of D5D on cancer may therefore facilitate the development of novel therapeutical applications. Given that D5D may serve as a promising target in cancer, in this review, we provide an updated summary of current knowledge on the role of D5D in cancer development and potentially useful therapeutic strategies.

Cross-ancestry genome-wide association studies identified heterogeneous loci associated with differences of allele frequency and regulome tagging between participants of European descent and other ancestry groups from the UK Biobank

To investigate cross-ancestry genetics of complex traits, we conducted a phenome-wide analysis of loci with heterogeneous effects across African, Admixed-American, Central/South Asian, East Asian, European and Middle Eastern participants of the UK Biobank (N = 441 331). Testing 843 phenotypes, we identified 82 independent genomic regions mapping variants showing genome-wide significant (GWS) associations (P < 5 × 10-8) in the trans-ancestry meta-analysis and GWS heterogeneity among the ancestry-specific effects. These included (i) loci with GWS association in one ancestry and concordant but heterogeneous effects among the other ancestries and (ii) loci with a GWS association in one ancestry group and an experiment-wide significant discordant effect (P < 6.1 × 10-4) in at least another ancestry. Since the trans-ancestry GWS associations were mostly driven by the European ancestry sample size, we investigated the differences of the allele frequency (ΔAF) and linkage disequilibrium regulome tagging (ΔLD) between European populations and the other ancestries. Within loci with concordant effects, the degree of heterogeneity was associated with European-Middle Eastern ΔAF (P = 9.04 × 10-6) and ΔLD of European populations with respect to African, Admixed-American and Central/South Asian groups (P = 8.21 × 10-4, P = 7.17 × 10-4 and P = 2.16 × 10-3, respectively). Within loci with discordant effects, ΔAF and ΔLD of European populations with respect to African and Central/South Asian ancestries were associated with the degree of heterogeneity (ΔAF: P = 7.69 × 10-3 and P = 5.31 × 10-3, ΔLD: P = 0.016 and P = 2.65 × 10-4, respectively). Considering the traits associated with cross-ancestry heterogeneous loci, we observed enrichments for blood biomarkers (P = 5.7 × 10-35) and physical appearance (P = 1.38 × 10-4). This suggests that these specific phenotypic classes may present considerable cross-ancestry heterogeneity owing to large allele frequency and LD variation among worldwide populations.

Genetics of Sleep and Insights into Its Relationship with Obesity

Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the considerable involvement of the circadian clock in sleep and metabolism, few shared genes, including FTO, were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring.Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. Bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity, but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Fate or coincidence: do COPD and major depression share genetic risk factors?

Major depressive disorder (MDD) is a common comorbidity in chronic obstructive pulmonary disease (COPD), affecting up to 57% of patients with COPD. Although the comorbidity of COPD and MDD is well established, the causal relationship between these two diseases is unclear. A large-scale electronic health record clinical biobank and genome-wide association study summary statistics for MDD and lung function traits were used to investigate potential shared underlying genetic susceptibility between COPD and MDD. Linkage disequilibrium score regression was used to estimate genetic correlation between phenotypes. Polygenic risk scores (PRS) for MDD and lung function traits were developed and used to perform a phenome-wide association study (PheWAS). Multi-trait-based conditional and joint analysis identified single-nucleotide polymorphisms (SNPs) influencing both lung function and MDD. We found genetic correlations between MDD and all lung function traits were small and not statistically significant. A PRS-MDD was significantly associated with an increased risk of COPD in a PheWAS [odds ratio (OR) = 1.12, 95% confidence interval (CI): 1.09-1.16] when adjusting for age, sex and genetic ancestry, but this relationship became attenuated when controlling for smoking history (OR = 1.08, 95% CI: 1.04-1.13). No significant associations were found between the lung function PRS and MDD. Multi-trait-based conditional and joint analysis identified three SNPs that may contribute to both traits, two of which were previously associated with mood disorders and COPD. Our findings suggest that the observed relationship between COPD and MDD may not be driven by a strong shared genetic architecture.

Habitual Sleep Duration, Daytime Napping, and Dietary Intake: A Mendelian Randomization Study

BACKGROUND

Chronic inadequate sleep and frequent daytime napping may inflict deleterious health effects including weight gain, cardiometabolic and psychiatric diseases, and cancer. It is plausible that these relations may be partly influenced by the consumption of suboptimal diets.

OBJECTIVES

The study aimed to identify potential causal links of genetically proxied longer habitual sleep duration and more frequent daytime napping on 61 dietary variables derived from an FFQ. In addition, the study aimed to assess potential bidirectional causal links between habitual sleep duration or daytime napping and macronutrient composition.

METHODS

Genetic variants robustly associated with habitual sleep duration and daytime napping from published genome-wide association analyses were used. Outcomes included 61 dietary variables estimated from FFQs in the UK Biobank (n = 361,194). For bidirectional associations with macronutrient composition, genetic variants associated with percentage of energy from carbohydrate, fat, and protein were used. Two-sample Mendelian randomization (MR) effects were estimated with inverse-variance weighted (IVW) analysis.

RESULTS

In 2-sample MR, genetically proxied longer sleep duration was associated with a 0.068 (95% CI: 0.034, 0.103) category increase in salad/raw vegetable intake [P false discovery rate (FDR) = 0.006] per hour of sleep and with "no major dietary changes in the past 5 years" (P FDR = 0.043). No associations were evident for daytime napping on dietary variables (all P FDR > 0.05). In addition, there were no bidirectional associations between habitual sleep duration or daytime napping with the relative intake of carbohydrate, fat, and protein (all P IVW > 0.05).

CONCLUSIONS

In this MR study, there was modest evidence for associations between habitual sleep duration with dietary intake and no evidence for associations between daytime napping frequency with dietary intake. These preliminary findings suggest that changes to habitual sleep duration or daytime napping frequency may have limited impact on long-term changes in dietary intake.