Genetic determinants of daytime napping and effects on cardiometabolic health

Sleep and Cardiovascular Health

Sleep is recognized as a foundational pillar of health, essential for maintaining nearly all vital processes, and a crucial component of cardiovascular function. In recent years, there has been a paradigm shift to conceptualize sleep health as a combination of multiple domains, including duration, timing, quality, variability/regularity, habits/behaviors, and disordered sleep. This review provides a comprehensive overview of the current evidence linking the multifaceted elements that contribute to healthy sleep with cardiovascular and blood pressure-related outcomes. The reviewed literature indicates a strong relationship between sleep and cardiovascular health. However, the specific pathophysiological mechanisms that bridge the various dimensions of sleep with cardiovascular outcomes remain elusive. Given the global burden of cardiovascular disease, understanding the interplay between sleep and cardiovascular health has important implications for both individual and population health. Sustained efforts to move beyond a focus on discrete domains of sleep are essential to fully understand this complex and potentially bidirectional relationship. Promoting healthy sleep patterns and optimizing the management and treatment of sleep disorders are key steps toward developing more comprehensive strategies for reducing cardiovascular risk. Integrating sleep health into routine clinical care is identified as a critical opportunity to enhance cardiovascular disease prevention and management, particularly among vulnerable and high-risk populations.

Investigating the link between genetic predictive factors of brain functional networks and two specific sleep disorders: Sleep apnoea and snoring

BACKGROUND

Sleep disorders are a widespread public health issue globally. Investigating the causal relationship between resting-state brain functional abnormalities and sleep disorders can provide scientific evidence for precision medicine interventions.

METHODS

We screened single nucleotide polymorphisms (SNPs) associated with rs-fMRI phenotype as instrumental variables Using bidirectional two-sample Mendelian randomization (MR), mediation MR, and multivariate MR based on Bayesian methods, the study tested the causal relationship between genetically predicted rs-fMRI and nine common sleep disorders.

RESULTS

The main IVW-MR analysis identified four rs-fMRI phenotypes that are causally associated with the risk of sleep disorders. For example, increased amplitude in nodes of the parietal, precuneus, occipital, temporal, and cerebellum regions, as well as the default mode network (DMN), central executive network (CEN) and attention network (AN) was associated with an increased risk of sleep apnoea. Enhanced neural activity in the calcarine or lingual and cerebellum regions and increased functional connectivity with the visual and subcortical-cerebellum networks was associated with a reduced risk of snoring. The mediation MR analysis shows that, BMI plays a significant mediating role in the risk of sleep apnoea by modulating the amplitude of nodes in the parietal, temporal, and cerebellum regions, as well as the connectivity changes in the DMN, CEN, and AN.

CONCLUSIONS

This study identified three rs-fMRI phenotypes linked to increased sleep apnoea risk and one associated with decreased snoring risk, providing an important target for the treatment of sleep disorders at the level of brain functional networks.

Exploration oxidative stress underlying gastroesophageal reflux disease and therapeutic targets identification: a multi-omics Mendelian randomization study

INTRODUCTION

Gastroesophageal reflux disease (GERD) is a chronic inflammatory gastrointestinal disease, which has no thoroughly effective or safe treatment. Elevated oxidative stress is a common consequence of chronic inflammatory conditions.

METHODS

We employed Summary-data based MR (SMR) analysis to assess the associations between gene molecular characteristics and GERD. Exposure data were the summary-level data on the levels of DNA methylation, gene expression, and protein expression, which obtained from related methylation, expression, and protein quantitative trait loci investigations (mQTL, eQTL, and pQTL). Outcome data, Genome-wide association study (GWAS) summary statistics of GERD, were extracted from the Ong's study (discovery), the Dönertaş's study (replication), and the FinnGen study (replication). Colocalization analysis was performed to determine if the detected signal pairs shared a causative genetic mutation. Oxidative stress related genes and druggable genes were imported to explore oxidative stress mechanism underlying GERD and therapeutic targets of GERD. The Drugbank database was utilized to conduct druggability evaluation.

RESULTS

After multi-omics SMR analysis and colocalization analysis, we identified seven key genes for GERD, which were SUOX and SERPING1, DUSP13, SULT1A1, LMOD1, UBE2L6, and PSCA. SUOX was screened out to be the mediator, which suggest that GERD is related to oxidative stress. SERPING1, SULT1A1, and PSCA were selected to be the druggable genes.

CONCLUSIONS

These findings offered strong support for the identification of GERD treatment targets in the future as well as for the study of the oxidative stress mechanism underlying GERD.

Multi-omics identify ribosome related causal genes methylation, splicing, and expression in prostate cancer

BACKGROUND

Understanding the molecular underpinnings of prostate cancer remains a critical challenge in oncology. Ribosomes, essential cellular organelles responsible for protein synthesis, have emerged as potential regulators in cancer development. Previous studies suggest that dysfunction in ribosomal processes may contribute significantly to prostate cancer progression. We used summary-data-based Mendelian randomization (SMR) and colocalization analysis, as well as single-cell analysis, to investigate the association between ribosome-related genes and prostate cancer by integrating multi-omics.

METHOD

In this study, we employed a multi-omics approach integrating genomics and transcriptomics data to investigate the role of ribosome-related genes in prostate cancer. Summary-level data for prostate cancer were obtained from The Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome and FinnGen studies. SMR analyses were performed to assess the relevance of ribosomal gene-related molecular signatures to prostate cancer. We further performed colocalization analysis to assess whether the identified signal pairs shared causal genetic variants. Genes were then validated with single-cell sequencing analysis.

RESULTS

We identified significant causal effects of ribosome gene methylation on prostate cancer. After integrating the multi-omics data of mQTL, sQTL and eQTL, we identified two ribosomal genes, NSUN4 and MPHOSPH6. Methylation and splicing at different sites on the NSUN4 gene showed increased and decreased risks for prostate cancer, indicating complex gene regulation mechanisms. For instance, NSUN4 methylation site of cg10215817 was genetically associated with the increased prostate cancer risk (OR 1.20, 95% CI 1.10,1.30), while NSUN4 methylation site of cg00937489 was genetically associated with the decreased prostate cancer risk (OR 0.84, 95% CI 0.74,0.94); NSUN4 chr1:46341497:46344801 splicing (OR 1.11, 95% CI 1.05-1.17) were positively associated with prostate cancer risk, while NSUN4 chr1:46340919:46344801 splicing (OR 0.95, 95% CI 0.92-0.97) were negatively associated with prostate cancer risk. Expression analysis indicated significant associations between prostate cancer risk and increased expression levels of NSUN4 (OR 1.06, 95% CI 1.03-1.09; PPH4 = 0.79) and MPHOSPH6 (OR 1.07, 95% CI 1.04-1.10; PPH4 = 0.70). In-depth single-cell analysis showed that NSUN4 highly expresses in epithelial cells, while MPHOSPH6 highly expresses in myeloid cells.

CONCLUSION

The study found that ribosome NSUN4 and MPHOSPH6 genes were associated with prostate cancer risk. This integrative multi-omics study underscores the significance of ribosome-related genes in prostate cancer etiology. By elucidating the molecular mechanisms underlying ribosome dysfunction, our research identifies potential therapeutic targets for mitigating disease progression. These findings not only enhance our understanding of prostate cancer biology but also pave the way for personalized therapeutic strategies targeting ribosomal pathways to improve clinical outcomes.

Mitochondrial-related genome-wide Mendelian randomization identifies putatively causal genes in the pathogenesis of sepsis

BACKGROUND

The dysfunction of mitochondria has been associated with the development of sepsis, but the specific mitochondrial-related genes and their roles in sepsis have not been fully elucidated. We employed Mendelian randomization and colocalization analysis to investigate the association between mitochondrial-related genes and sepsis by integrating multi-omics data.

METHODS

Summary-level data on mitochondrial gene methylation, expression, and protein abundance levels were obtained from corresponding studies on methylation, expression, and protein quantitative trait loci, respectively. Genetic associations with sepsis were obtained from the genome-wide association studies catalog database. We used the MitoCarta3.0 database, which contains an updated list of 1,136 human mitochondrial genes, to identify mitochondrial genes. To assess the associations between mitochondrial gene-related molecular features and sepsis, we conducted summary data-based Mendelian randomization analysis. In addition, we performed colocalization analysis to determine whether the identified signal pairs shared a causal genetic variant.

RESULTS

After integrating the multi-omics data between methylation quantitative trait loci- expression quantitative trait loci and expression quantitative trait loci-protein quantitative trait loci, we identified FIS1 as having tier 1 evidence for its association with sepsis. Methylation of cg01299997 in FIS1 was found to be associated with lower expression of FIS1, an increased risk of sepsis, and a positive role in cg01299997 methylation. Furthermore, NUDT2, IMMP2L, LYRM4, MRPL10, MRPL17, MTIF3, and TFAM genes were associated with sepsis risk with tier 2 evidence. Both gene expression and protein abundance levels of NUDT2 were observed to be associated with an increased risk of sepsis. In addition, the ATP5MC1 and VWA8 genes were associated with sepsis risk with tier 3 evidence. Among these tertiary genes, ATP5MC1 gene expression level showed a negative correlation (posterior probability of H4 = 0.9242), whereas the gene expression level of VWA8 exhibited a positive correlation (posterior probability of H4 = 0.7270).

CONCLUSION

We found that the mitochondrial FIS1, NUDT2, IMMP2L, LYRM4, MRPL10, MRPL17, MTIF3, TFAM, ATP5MC1, and VWA8 genes were putatively associated with sepsis risk with evidence from multi-omics levels. This study identified mitochondrial genes in relation to sepsis, which may enhance the understanding of the pathogenic mechanisms of sepsis development.

Poor sleep and high rheumatoid arthritis risk: Evidence from large UK Biobank cohort

OBJECTIVE

To evaluate the relationship between sleep behaviors and rheumatoid arthritis (RA) risk.

METHODS

First, based on large-scale data from the UK Biobank, we analyzed the associations between multiple sleep factors and RA risk and calculated a poor sleep score (PSS) to assess their combined effect. Then we constructed genetic risk scores (GRS) based on a large genome-wide association study and assessed the interaction or combined effect of sleep and genetic factors on RA risk. Finally, we conducted a case-control study to explore the effect of RA on sleep.

RESULTS

Sleep duration, getting up, napping during the day, insomnia, and daytime dozing were associated with the risk of RA, but no associations were observed for chronotype and snoring with RA. Participants in the high genetic risk and high PSS group had a 363.1% higher risk of developing RA compared to those with low genetic risk and low PSS. We also found that women were more likely than men to be affected by the combined effects of PSS and GRS. In the case-control study, there were statistically significant associations of RA with getting up, PSS grade and PSS.

CONCLUSIONS

Unhealthy sleep patterns were associated with increasing risk of RA among participants with low, intermediate, or high genetic risk.

Bidirectional relationship between afternoon naps and depressive symptoms in Chinese middle-aged and older adults: Evidence from a nationally representative cohort study

BACKGROUND

Limited studies have investigated the association between depressive symptoms and napping habits. In this study, nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS) were employed to conduct cross-sectional and longitudinal analyses to investigate their associations among Chinese middle-aged and older adults.

METHODS

The study included 12,208 participants from the 2015 CHARLS. Depressive symptoms were measured using the Depression Scale. Napping duration was categorized into four groups: no napping (0 min), short (<30 min), moderate (30-89 min), and prolonged (≥90 min). Logistic regression analysis was used to assess bidirectional relationships, and dose-response patterns were analyzed via restricted cubic splines (RCS).

RESULTS

A total of 2487 participants (32.0 %) developed new-onset depressive symptoms, and moderate napping group exhibited the lowest incidence rate. Statistical analysis revealed that moderate napping was a protective factor for the depressive symptoms (OR, 95 % CI, 0.689, 0.567-0.843). A total of 1742 participants (42.3 %) newly experienced poor napping, and the incidence of poor napping gradually rose by the increase of the CES-D-10 score quartiles. Moreover, depressive symptoms were also found to be a risk factor for poor napping (OR, 95 % CI, 1.149, 1.004-1.314). The RCS model revealed that there was an approximately U-shaped association between nap duration and depressive symptoms, and there was a negative linear association between CES-D-10 scores and nap duration.

LIMITATION

The observational design limits ruling out unobserved confounding factors.

CONCLUSION

There was a significant bidirectional relationship and a dose-response association between napping and depressive symptoms in middle-aged and older adults.

Polygenic overlap between subjective well-being and psychiatric disorders and cross-ancestry validation

Subjective well-being (SWB) is important for understanding human behaviour and health. Although the connection between SWB and psychiatric disorders has been studied, common genetic mechanisms remain unclear. This study aimed to explore the genetic relationship between SWB and psychiatric disorders. Bivariate causal mixture modelling (MiXeR), polygenic risk score (PRS) and Mendelian randomization (MR) analyses showed substantial polygenic overlap and associations between SWB and the psychiatric disorders. Subsequent replication studies in East Asian populations confirmed the polygenic overlap between schizophrenia and SWB. The conditional and conjunctional false discovery rate analyses identified additional or shared genetic loci associated with SWB or psychiatric disorders. Functional annotation revealed enrichment of specific brain tissues and genes associated with SWB. The identified genetic loci showed cross-ancestry transferability between the European and Korean populations. Our findings provide valuable insights into the common genetic mechanisms underlying SWB and psychiatric disorders.

The role of sleep traits in prostate, endometrial, and epithelial ovarian cancers: An observational and Mendelian randomisation study

Background

Sleep traits may influence cancer risk; however, their associations with prostate (PCa), endometrial (ECa), and epithelial ovarian (EOCa) cancer remain unclear.

Methods

We conducted an observational analysis using the UK Biobank cohort and a two-sample Mendelian randomisation (MR) analysis to investigate the association of six sleep traits-duration, chronotype, insomnia, daytime napping, daytime sleepiness, and snoring-with PCa, ECa, and EOCa risk. Cox proportional hazards models were used for the observational analysis, while the inverse variance-weighted (IVW) method was applied in MR, with multiple sensitivity analyses. A Bonferroni correction accounted for multiple testing.

Results

Among 8,608 PCa, 1,079 ECa, and 680 EOCa incident diagnoses (median follow-up: 6.9 years), snoring was associated with reduced EOCa risk (HR=0.78, 95%CI: 0.62-0.98), while daytime sleepiness was associated with increased EOCa risk (HR=1.23, 95%CI: 1.03-1.47). However, these associations were not confirmed in MR. MR suggested higher odds of PCa (OR IVW =1.05, 95%CI: 1.01-1.11) and aggressive PCa (OR IVW =1.10, 95%CI: 1.02-1.19) for evening compared to morning chronotype. None of the findings survived multiple testing correction.

Conclusion

Sleep traits were not associated with PCa, ECa, or EOCa risk, but evening chronotype may increase PCa risk. Further research is needed to verify this association and investigate potential underlying mechanisms.

Impact

The proposed results have potential utility in reproductive cancer prevention.

What is already known on this topic

Sleep traits have been implicated in cancer risk, but their associations with prostate, endometrial, and epithelial ovarian cancer remain unclear.

What this study adds

This study found suggestive evidence that an evening chronotype may be associated with an increased risk of overall and aggressive prostate cancer.

How this study might affect research practice or policy

Further research is needed to confirm the potential association between chronotype and prostate cancer risk, which could inform personalised cancer prevention strategies.

Drosophila Modeling Identifies Increased Sleep as a Link Between Insomnia and Cardiovascular Disease

Insomnia is a common sleep disorder associated with negative long-term health outcomes. Mendelian randomization studies have found that insomnia significantly increases the risk of cardiovascular disease (CVD). To better understand the link between sleep and heart health, we identify genes associated with both insomnia and CVD. We model the disruption of the Drosophila melanogaster orthologs in neurons and cardiac tissue to characterize their cell-autonomous and non-cell-autonomous role in regulating sleep and cardiac physiology. We identify three genes that function in neurons and the heart to cell-autonomously regulate the function of each tissue. We find that the disruption of insomnia- and CVD-associated Drosophila orthologs in the heart most often lead to increased nighttime sleep. Inversely, disruptions in neurons that lead to increased sleep most often result in an elevated heart rate. To confirm the association between increased sleep and cardiac function, we performed a genetic correlation analysis from human data between long sleep-related traits and adverse cardiac outcomes. Significant correlations were found between most long sleep traits and heart failure, coronary artery disease, or myocardial infarction, reinforcing our findings in the fly linking increased or excessive sleep and altered cardiac health.

Development and validation of a risk prediction model for frailty in older nappers

BACKGROUND

Frailty among older adults has received widespread attention from society, especially among nappers. The objective of this study was to develop a frailty prediction model for nappers.

METHODS

The data source was the China Health and Retirement Longitudinal Study, with a cohort of 1830 older nappers. We used the least absolute shrinkage and selection operator to screen the best predictors from multiple factors, logistic regression analysis to explore the best predictors of frailty in older nappers, and nomogram to establish a prediction model. A calibration curve was used to evaluate the precision of the model, and the predictive performance was assessed by analyzing the area under the characteristic and decision curves.

RESULTS

The prevalence of frailty among older nappers was 28.9 % (528/1830). Chronic diseases, physical activity, sleep quality, pain, fatigue, depression, nap duration, and nighttime sleep duration were the best predictive factors for frailty in older nappers. The area under the curve (AUC) in the training set was 0.751 (95 % confidence interval [CI] = 0.724-0.779) with a specificity of 0.662 and sensitivity of 0.711. The AUC in the validation set was 0.781 (95 % CI = 0.749-0.812) with a specificity of 0.730 and sensitivity of 0.714. The Hosmer-Lemeshow test values were both p > 0.05. The nomogram model showed good concordance and accuracy.

CONCLUSION

We constructed a nomogram that serves as a valuable and convenient instrument for assessing the prevalence of frailty among older nappers.

The relationships between sleep and adiposity amongst multi-ethnic Asian populations: a cross-sectional analysis of the Health for Life in Singapore (HELIOS) study

BACKGROUND

Short sleep duration and poor sleep quality have been associated with obesity. Asian populations report shorter sleep duration compared to other groups. We therefore aimed to explore the relationships between sleep duration, sleep quality, dozing, daytime napping, snoring, insomnia and adiposity in a multi-ethnic Asian population, and investigate the potential contribution of disturbed sleep to the risk of obesity amongst Asian populations.

METHODS

We studied 8876 participants of the HELIOS study, a multi-ethnic population-based cohort comprising Chinese, Malay, and Indian Asian men and women living in Singapore. Sleep traits and psychological symptoms were assessed using validated tools which included the Pittsburg Sleep Quality Index, Generalised Anxiety Disorder-7, and Patient Health Questionnaire-9. We employed multivariable regression models to examine the associations between sleep and adiposity, while also conducting sub-group and sensitivity analyses to strengthen the reliability of our results.

RESULTS

The 8876 participants were 69.3% Chinese, 12.5% Malays, and 18.2% Indians, with mean age: 51.7 ± 11.8 years (standard deviation). Malays had the shortest sleep duration, while Chinese had the best sleep quality. Short sleep duration, poor sleep quality, and snoring were associated with higher BMI and waist circumference, independent of age, sex, ethnicity, and various confounding factors (education, household income, current smoking, regular alcohol drinking status, presence of diabetes and hypertension, and markers for anxiety and depression; P < 0.005). The estimated population attributable fraction for short sleep and snoring as contributors to obesity were 6.6% (95% CI: 2.5-10.6%) and 18.6% (95% CI: 17.0-20.2%), respectively.

CONCLUSION

Sleep duration, sleep quality, and snoring are associated with adiposity in a multi-ethnic Asian population of Chinese, Malays, and Indians. Our findings suggest that a substantial portion of obesity in Asian populations could be averted through public health interventions aimed at improving sleep duration and quality.

Lifetime depression, sleep disruption and brain structure in the UK Biobank cohort

Whether depression and poor sleep interact or have statistically independent associations with brain structure and its change over time is not known. Within a subset of UK Biobank participants with neuroimaging and subjective and/or objective sleep data (n = 28,351), we examined associations between lifetime depression and sleep disruption, and their interaction with structural neuroimaging measures, both cross-sectionally and longitudinally. Sleep variables were: self-reported insomnia and difficulty getting up; actigraphy-derived short sleep (<7 h); sustained inactivity bouts during daytime (SIBD); and sleep efficiency. Imaging measures were white matter microstructure, subcortical volumes, cortical thickness and surface area of 24 cortical regions of interest. Individuals with lifetime depression (self-reported, mental health questionnaire or health records) were contrasted with healthy controls. Interactions between depression and difficulty getting up for i) right nucleus accumbens volume and ii) mean diffusivity of forceps minor, reflected a larger negative association of poor sleep in the presence vs. absence of depression. Depression was associated with widespread reductions in white matter integrity. Depression, higher SIBD and difficulty getting up were individually associated with smaller cortical volumes and surface area, particularly in the frontal and parietal lobes. Many regions showed age-related decline, but this was not exacerbated by either depression or sleep disturbance. Overall, we identified widespread cross-sectional associations of both lifetime depression and sleep measures with brain structure. Findings were more consistent with additive rather than synergistic effects - although in some regions we observed greater magnitude of deleterious associations from poor sleep phenotypes in the presence of depression.

Multi-omics insight into the molecular networks of mental disorder related genetic pathways in the pathogenesis of inflammatory bowel disease

Mental disorders are associated with inflammatory bowel disease (IBD), but the genetic pathophysiology is not fully understood. We obtained data on mental disorder-related gene methylation, expression, protein levels, and summary statistics of IBD, and performed Summary data-based Mendelian randomization and colocalization analyses to explore the causal associations and shared causal genetic variants between multiple molecular traits and IBD. Integrating multi-omics data, we found QDPR, DBI and MAX are associated with ulcerative colitis (UC) risk, while HP is linked to IBD risk. Inverse associations between gene methylation (cg0880851 and cg26689483) and expression are observed in QDPR, consistent with their detrimental role in UC. Methylation of DBI (cg11066750) protects against UC by enhancing expression. Higher levels of DBI (OR = 0.79, 95%CI = 0.69-0.90) and MAX (OR = 0.74, 95%CI = 0.62-0.90) encoded proteins are inversely associated with UC risk, while higher QDPR (OR = 1.17, 95%CI = 1.07-1.28) and HP (OR = 1.09, 95%CI = 1.04-1.14) levels increase UC and IBD risk. Our findings advance the understanding of IBD's pathogenic mechanisms and gut-brain interaction.

Investigating the impact of multidimensional sleep traits on cardiovascular diseases and the mediating role of depression

BACKGROUND

Observational studies have reported that sleep is associated with the risk of major depressive disorder (MDD) and cardiovascular diseases (CVDs). However, the causal relationships among various sleep traits remain contentious, and whether MDD mediates the impact of specific sleep traits on CVDs is unclear.

METHODS

We performed two-sample Mendelian randomisation analyses to explore whether insomnia, sleep time, daytime napping, daytime sleepiness, chronotype, snoring or obstructive sleep apnoea were causally associated with the risk of five CVDs, including coronary artery disease (CAD), myocardial infarction (MI), heart failure (HF), atrial fibrillation and stroke. Mediation analyses were performed to assess the proportion mediated by MDD.

RESULTS

Genetically predicted insomnia, short sleep, daytime napping and daytime sleepiness increased the risk of CVDs, with the OR ranging from 1.24 (95% CI 1.06 to 1.45) for insomnia on stroke to 1.55 (95% CI 1.28 to 1.89) for insomnia on MI. In contrast to short sleep, genetically predicted sleep duration decreased the risk of CAD (OR 0.88 (95% CI 0.80 to 0.97)), MI (OR 0.89 (95% CI 0.80 to 0.99)) and HF (OR 0.90 (95% CI 0.83 to 0.98)). However, we found no significant associations of long sleep, chronotype, snoring and obstructive sleep apnoea with increased risk for any CVD subtype. Additionally, the effect of insomnia was partially mediated by MDD for the risk of CAD (proportion mediated: 8.81% (95% CI 1.20% to 16.43%)), MI (9.17% (95% CI 1.71% to 16.63%)) and HF (14.46% (95% CI 3.48% to 25.45%)). Similarly, the effect of short sleep was partially mediated by MDD for the risk of CAD (8.92% (95% CI 0.87% to 16.97%)), MI (11.43% (95% CI 0.28% to 22.57%)) and HF (12.65% (95% CI 1.35% to 23.96%)). MDD also partially mediated the causal effects of insomnia on stroke, sleep duration on CAD, MI and HF, daytime napping on HF and daytime sleepiness on CAD.

CONCLUSIONS

Our study provides evidence that genetically predicted insomnia, short sleep, frequent daytime napping and sleepiness are associated with a higher risk of certain CVD subtypes, partly mediated by MDD.

Sleep traits causally affect epigenetic age acceleration: a Mendelian randomization study

Sleep disorders (SDs) are a common issue in the elderly. Epigenetic clocks based on DNA methylation (DNAm) are now considered highly accurate predictors of the aging process and are associated with age-related diseases. This study aimed to investigate the causal relationship between sleep traits and the epigenetic clock using Mendelian randomization (MR) analysis. The genome-wide association study (GWAS) statistics for epigenetic clocks (HannumAge, intrinsic epigenetic age acceleration [IEAA], PhenoAge, and GrimAge) and sleep traits were obtained from the UK Biobank (UKB), 23andMe and Finngen. Moreover, crucial instrumental variables (IVs) were evaluated. Inverse variance weighted (IVW), MR-Egger, weighted median (WM), weighted mode, and simple mode methods were employed to assess the causal relationship between them. Multiple analyses were performed for quality control evaluation. Our study showed that self-reported insomnia may speed up the aging process by GrimAge clock, while GrimAge acceleration could faintly reduce self-reported insomnia. Epigenetic clocks mainly influence sleep traits by PhenoAge and GrimAge with weak effects. This may indicate that early interventions of SDs could be a breaking point for aging and age-related diseases. Further studies are required to elucidate the potential mechanisms involved.

The impact of sleep on breast cancer-specific mortality: a Mendelian randomisation study

BACKGROUND

The relationship between sleep traits and survival in breast cancer is uncertain and complex. There are multiple biological, psychological and treatment-related factors that could link sleep and cancer outcomes. Previous studies could be biased due to methodological limitations such as reverse causation and confounding. Here, we used two-sample mendelian randomisation (MR) to investigate the causal relationship between sleep and breast cancer mortality.

METHODS

Publicly available genetic summary data from females of European ancestry from UK Biobank and 23andme and the Breast Cancer Association Consortium were used to generate instrumental variables for sleep traits (chronotype, insomnia symptoms, sleep duration, napping, daytime-sleepiness, and ease of getting up (N = 446,118-1,409,137)) and breast cancer outcomes (15 years post-diagnosis, stratified by tumour subtype and treatment (N = 91,686 and Ndeaths = 7,531 over a median follow-up of 8.1 years)). Sensitivity analyses were used to assess the robustness of analyses to MR assumptions.

RESULTS

Initial results found some evidence for a per category increase in daytime-sleepiness reducing overall breast cancer mortality (HR = 0.34, 95% CI = 0.14, 0.80), and for insomnia symptoms reducing odds of mortality in oestrogen receptor positive breast cancers not receiving chemotherapy (HR = 0.18, 95% CI = 0.05, 0.68) and in patients receiving aromatase inhibitors (HR = 0.23, 95% CI = 0.07, 0.78). Importantly, these relationships were not robust following sensitivity analyses meaning we could not demonstrate any causal relationships.

CONCLUSIONS

This study did not provide evidence that sleep traits have a causal role in breast cancer mortality. Further work characterising disruption to normal sleep behaviours and its effects on tumour biology, treatment compliance and quality of life are needed.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), 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, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

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.

Associations between sleep traits and colorectal cancer: a mendelian randomization analysis

Background

Although many researches have shown a relationship between sleeping habits and the risk of developing colorectal cancer (CRC), there is a lack of data from randomized controlled trials (RCTs) to support this point. Hence, this study used Mendelian randomization (MR) to robustly assess whether five primary sleep characteristics are directly linked with the risk of CRC occurrence.

Methods

In the performed study, the main Mendelian randomization analysis was conducted using approaches such as Inverse Variance Weighting (IVW), MR Egger, and weighted median method. To this end, five genetically independent variants associated with the sleep-related characteristics (chronotype, sleep duration, insomnia, daytime napping, and daytime fatigue) were identified and used as instrumental variables. Publicly accessible GWAS (Genome-Wide Association Study) data were used to identify these variants to investigate the putative causal relationships between sleep traits and CRC. Additionally, we conducted sensitivity analyses to minimize possible biases and verify the consistency of our results.

Results

Mendelian randomization analyses showed that an morning chronotype reduces the risk of CRC with the IVW method, hence, odds ratio (OR) of 1.21 and 95% confidence interval (CI) of 0.67-0.93, which is statistically significant at P = 5.74E-03. Conversely, no significant evidence was found to suggest that sleep duration, insomnia, daytime napping, or daytime sleepiness have a direct causal impact on CRC risk according to the IVW analysis.

Conclusions

Findings from our Mendelian randomization analyses suggest that an individual's chronotype may contribute to an increased risk of CRC. It is advisable for individuals to adjust their sleep patterns as a preventative measure against CRC.

Rural-urban differences in the association between afternoon napping and depressive symptoms among middle-aged and older adults in China

OBJECTIVE

This study aimed to examine the association between afternoon napping and depressive symptoms among Chinese middle-aged and older adults and to evaluate the rural-urban differences.

METHODS

A total of 11,056 participants, aged≥45, 5646 rural and 5410 urban, were included using data from CFPS. Each participant provided data on afternoon napping through field interviews. CESD8 was used to measure depressive symptoms. Multivariable logistic regressions were used to investigate the association.

RESULTS

2654 (24.01 %) participants had depressive symptoms and 7239 (65.48 %) napped. Nappers were likely to have a lower risk of depressive symptoms (OR = 0.899; 95%CI =0.816-0.991). A significantly lower risk of depressive symptoms was found in the moderate-duration afternoon napping groups (31-60 min/day) compared with non-nappers (OR = 0.816; 95%CI =0.727-0.917). In terms of rural-urban differences, rural participants had a lower risk of depressive symptoms compared with non-nappers (OR = 0.813; 95%CI =0.716-0.926). A significant association was also found between age groups. Participants aged 65-74 years old had a lower risk of depressive symptoms compared with non-nappers (OR = 0.776; 95%CI = 0.627-0.959).

LIMITATIONS

First, the cross-sectional study may limit the ability to infer causality. Second, only those who responded to the questionnaire were included; selection bias was unavoidable. Finally, answers were retrospective self-reported, which may cause recall bias and social desirability bias.

CONCLUSIONS

Afternoon napping was associated with a lower risk of depressive symptoms among Chinese middle-aged and older adults. The associations varied between rural-urban and age groups. We recommend taking a moderate-duration afternoon napping every day to prevent the risk of potential depression.

Causal Association of Sleep Traits with All-Cause and Cause-Specific Mortality: A Prospective Cohort and Mendelian Randomization Study

The study aimed to explore the association between different sleep traits and all-cause mortality as well as to validate causality in the association through mendelian randomization (MR). We analyzed 451,420 European ancestry participants from the UK Biobank. Multivariable-adjusted Cox proportional hazards model was conducted to evaluate the association between sleep traits and all-cause mortality. In MR analysis, the inverse variance weighting (IVW) method was applied as the primary analysis to investigate the causal association between sleep traits and mortality. During a median follow-up period of 12.68 years, 34,397 individuals died. Observational analyses showed the multivariate-adjusted hazard ratio (HR) and 95% confidence intervals (CIs) for short sleep, long sleep, early chronotype, daytime sleepiness, daytime napping, and insomnia with mortality, 1.246 (1.195, 1.298), 1.735 (1.643, 1.831), 0.931 (0.909, 0.953), 1.276 (1.212, 1.344), 1.299 (1.254, 1.346), and 1.117 (1.091, 1.142) (All p < 0.0001). Based on UK Biobank, MR analysis indicated the association between daytime napping and an increased risk of all-cause mortality (odd ratio [OR]: 1.219, 95% CI: 1.071-1.387, p = 0.003), which may be largely attributable to cancer disease mortality (OR: 1.188, 95% CI: 1.009-1.399, p = 0.039). We found no causal association between sleep duration, short sleep, long sleep, chronotype, daytime sleepiness, insomnia, and mortality risk. The causal associations between sleep traits and all-cause mortality risk were directionally replicated in FinnGen. Our findings suggest a potential causal association between daytime napping and increased risk of all-cause mortality in middle-aged and older persons. The finding could have important implications for evaluating daytime napping habits to decrease the risk of mortality.

Genome-wide association analysis of composite sleep health scores in 413,904 individuals

Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, so together may provide a more complete picture of sleep health, while illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches. GWASs of these six SHSs identify 28 significant novel loci adjusting for multiple testing on six traits (p < 8.3e-9), along with 341 previously reported loci (p < 5e-08). The heritability of the first three SHS-PCs equals or exceeds that of SHS-ADD (SNP-h2 = 0.094), while revealing sleep-domain-specific genetic discoveries. Significant loci enrich in multiple brain tissues and in metabolic and neuronal pathways. Post-GWAS analyses uncover novel genetic mechanisms underlying sleep health and reveal connections (including potential causal links) to behavioral, psychological, and cardiometabolic traits.

Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis

BACKGROUND

To elucidate the genetic and molecular mechanisms underlying psoriasis by employing an integrative multi-omics approach, using summary-data-based Mendelian randomization (SMR) to infer causal relationships among DNA methylation, gene expression, and protein levels in relation to psoriasis risk.

METHODS

We conducted SMR analyses integrating genome-wide association study (GWAS) summary statistics with methylation quantitative trait loci (mQTL), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data. Publicly available datasets were utilized, including psoriasis GWAS data from the European Molecular Biology Laboratory-European Bioinformatics Institute and the UK Biobank. Heterogeneity in dependent instruments (HEIDI) test and colocalization analyses were performed to identify shared causal variants, and multi-omics integration was employed to construct potential regulatory pathways.

RESULTS

Our analyses identified significant causal associations between DNA methylation, gene expression, protein abundance, and psoriasis risk. We discovered two pathways involving the long non-coding RNA RP11-977G19.11 and apolipoprotein F (APOF). Methylation at sites cg26804944 and cg02705573 was negatively associated with RP11-977G19.11 expression. Reduced expression of RP11-977G19.11 was linked to increased APOF levels, which were positively associated with a higher risk of psoriasis. Methylation at sites cg00172967, cg00294382, and cg24773560 was positively associated with RP11-977G19.11 expression. Elevated expression of RP11-977G19.11 was associated with decreased APOF levels, reducing the risk of psoriasis. Colocalization analysis highlighted APOF as a key protein in psoriasis pathogenesis. Validation using skin tissue, EBV-transformed lymphocytes data and inflammation-related protein panels confirmed the associations of RP11-977G19.11 and APOF with psoriasis.

CONCLUSIONS

Our multi-omics analysis provides preliminary evidence for potential molecular mechanisms in psoriasis pathogenesis. Through the integration of GWAS and molecular QTL data, we identify candidate pathways that may be relevant to disease biology. While these findings require extensive experimental validation, they offer a framework for future investigations into the molecular basis of psoriasis.

From single nucleotide variations to genes: identifying the genetic links between sleep and psychiatric disorders

STUDY OBJECTIVES

Sleep disorders and psychiatric disorders frequently coexist and interact, yet the shared genetic basis linking these two domains remains poorly understood.

METHODS

We investigated the genetic correlation and overlap between seven sleep/circadian traits and three psychiatric disorders at the level of genome-wide association studies (GWAS), utilizing LDSC, HDL, and GPA. To identify potential polygenic single nucleotide variations (SNVs) within each trait pair, we used PLACO, while gene-level analyses were performed using MAGMA and POPS. Furthermore, the functions and biological mechanisms, enriched phenotypes, tissues, cellular features, and pathways were thoroughly investigated using FUMA, deTS, and enrichment analyses at the biological pathway level.

RESULTS

Our study revealed extensive genetic associations and overlaps in all 21 trait pairs. We identified 18 494 SNVs and 543 independent genomic risk loci, with 113 confirmed as causative through colocalization analysis. These loci collectively spanned 196 unique chromosomal regions. We pinpointed 43 distinct pleiotropic genes exhibiting significant enrichment in behavioral/physiological phenotypes, nervous system phenotypes, and brain tissue. Aberrations in synaptic structure and function, neurogenesis and development, as well as immune responses, particularly involving the MAPK pathway, emerged as potential underpinnings of the biology of sleep/circadian traits and psychiatric disorders.

CONCLUSIONS

We identified shared loci and specific sets of genes between sleep/circadian traits and psychiatric disorders, shedding light on the genetic etiology. These discoveries hold promise as potential targets for novel drug interventions, providing valuable insights for the development of therapeutic strategies for these disorders.

Siesta behavior and genetics interact to influence obesity risk

OBJECTIVE

In this cross-sectional study, we aim to investigate the interactions between obesity, siesta behavior, and the genetic propensity for siesta in a Mediterranean population, in whom siesta is deeply rooted.

METHODS

We applied a previously generated Siesta-Polygenic Score (PGS) in the ONTIME study (n = 1278). Siesta and other Mediterranean lifestyle behaviors were characterized using questionnaires. We further determined obesity grade. Secondarily, we measured weight loss during treatment as well as long-term weight-loss maintenance. Logistic regression analyses were performed to address our aim.

RESULTS

A total of 42.4% of the population usually took siesta. A significant genetic influence on siesta propensity was found, with a higher genetic predisposition linked to taking siesta more frequently (odds ratio [OR] = 1.17, 95% CI: 1.03-1.32; p = 0.015). Participants with a higher genetic propensity for siesta showed poorer dietary habits (p < 0.05). Among individuals with a high genetic propensity for siesta, we found that those who usually take siesta have lower odds of having obesity (p = 0.038) compared with those who do not. Similarly, in exploratory analysis, among individuals with a high genetic propensity for siesta, we found that those who usually take siesta have higher odds of weight-loss success (p = 0.007) compared with those who do not.    CONCLUSIONS: Considering the ongoing debate regarding whether siesta is beneficial or detrimental, our findings suggest that individual genetic predisposition to siesta might influence the association between siesta and health.

Unraveling the causal role of sleep traits in development of diabetic retinopathy: A UK Biobank observational study and Mendelian randomization

AIMS

To evaluate the potential causal role of sleep traits (STs) on diabetic retinopathy (DR).

METHODS

The cross-sectional study included 23,851 patients with type 2 diabetes from the UK Biobank and used multivariate logistic models to investigate the observational association between STs and DR. Genetic correlation analysis and two-sample Mendelian randomization (MR) were conducted using ST data from the UK Biobank and DR data from the FinnGen consortium to investigate the genetic and causal associations between STs and DR.

RESULTS

Patients who experienced daytime sleepiness often/all of the time had a higher risk for DR (OR: 1.40; 95% CI, 1.09-1.79; p = .008) compared with those who sometimes/never/rarely experienced daytime sleepiness. Genetic correlations between several STs and DR were detected by cross-trait linkage disequilibrium score regression. MR suggested a causal effect of self-reported daytime sleepiness (OR: 4.08; 95% CI, 1.44-11.61; p = .008), and accelerator-derived sleep duration (OR: 0.73; 95% CI, 0.54-0.98; p = .036) and sleep efficiency (OR: 0.54; 95% CI, 0.36-0.80; p = .002) on DR.

CONCLUSIONS

STs may have a potential causal role for DR. Attention should be paid to the STs of patients for better prevention and treatment of DR.

Relationships between orofacial pain and sleep: Analysis of UK biobank and genome-wide association studies data

Background/purpose

Orofacial pain is common in dental practices. This study aimed to explore relationships between orofacial pain and sleep using the UK Biobank dataset and, based on epidemiological associations, to investigate the causal association using genome-wide association studies data.

Materials and methods

First, a cross-sectional study was conducted with 196,490 participants from UK Biobank. Information on pain conditions and sleep traits was collected. Multivariable models were used to explore the relationships with odds ratio (OR). Second, Mendelian randomization analyses were conducted using data for orofacial pain, including temporomandibular joint disorders-related pain (n = 377,277) and atypical facial pain (n = 331,749), and sleep traits, including sleep duration (n = 446,118), short sleep (n = 411,934), long sleep (n = 339,926), snoring (n = 359,916), ease of getting up (n = 385,949), insomnia (n = 453,379), daytime dozing (n = 452,071), daytime napping (n = 452,633), and chronotype (n = 403,195).

Results

The cross-sectional study confirmed the bidirectionality between pain and sleep. Participants experiencing pain all over the body showed a significant association with an unhealthy sleep pattern (OR = 1.18, P < 0.001) and other sleep traits (P < 0.05). Risks of chronic orofacial pain were associated with sleep duration in a non-linear relationship (P = 0.032). The Mendelian randomization analyses indicated that long sleep was causally associated with temporomandibular joint disorders-related pain (OR = 6.77, P = 0.006).

Conclusion

The relationship between pain and sleep is bidirectional. Long sleep is found to be causally associated with chronic orofacial pain.

Causal Associations Between Sleep Traits and Delirium: A Bidirectional Two-Sample Mendelian Randomization Study

Purpose

Numerous studies have identified a correlation between sleep and delirium; however, the causal relationship remains ambiguous. This bidirectional two-sample Mendelian randomization (MR) study was conducted to examine the possible causal relationships between sleep traits and delirium.

Patients and Methods

Utilizing genome-wide association studies (GWAS), we identified ten sleep traits: chronotype, sleep duration, short sleep duration, long sleep duration, daytime napping, daytime sleepiness, insomnia, number of sleep episodes (NSE), sleep efficiency, and rapid eye movement sleep behavior disorder (RBD). In this MR study, genetic variants independently associated with exposures were selected as instrumental variables (IVs). To establish causal inferences, three regression models were employed-inverse variance weighted (IVW), MR Egger, and weighted median (WM) -and conducted sensitivity analyses to assess the robustness of our findings.

Results

Our results suggest no significant causal association between the ten sleep traits and the risk of delirium. The reverse MR analysis revealed that delirium is associated with an increased propensity for morning chronotype [ORIVW, 1.025; 95% CI, 1.012-1.036; p = 1.50E-05; adjusted p values (padjusted)= 1.35E-04] and a decreased risk of long sleep duration [ORIVW, 0.996; 95% CI, 0.993-0.999; p = 0.013; padjusted= 0.059]. However, no robust evidence currently exists to substantiate a causal relationship between delirium and other sleep traits.

Conclusion

Our bidirectional, two-sample MR analysis study did not provide definitive evidence that sleep traits may augment the susceptibility to delirium. However, the reverse MR results indicate that delirium may predispose patients to an earlier sleep-wake cycle. Additional large-scale investigations are necessary to examine the bidirectional causality between delirium and sleep traits.

Sleep quality and incident hypertension

INTRODUCTION AND OBJECTIVES

Poor sleep quality poses significant public health challenges worldwide. This study aimed to investigate the association between sleep quality and the risk of hypertension.

METHODS

The study analyzed 284 250 adults from the UK Biobank (UKB) and 6104 participants from the English Longitudinal Study of Ageing (ELSA) without hypertension at baseline. The exposure of interest was sleep quality, which was evaluated based on questionnaires. Participants were divided into 3 groups based on the assessment of sleep quality. Sleep duration was assessed by self-reported sleep hours by each participant. The primary endpoint was new onset hypertension.

RESULTS

In the UKB cohort, participants with poor sleep quality showed a significantly higher risk of hypertension than those with healthy sleep quality (HR, 1.277; 95%CI, 1.21-1.346]. The results from the ELSA cohort effectively validated those from the UKB cohort; participants with poor sleep quality had a notably heightened risk of hypertension (HR, 1.264; 95%CI, 1.02-1.566). Prolonging sleep duration was associated with a decrease in the risk of hypertension in individuals with intermediate or healthy sleep quality. Although several factors were independently associated with a lower risk of hypertension (P<.001), the association between sleep quality and an increased risk of hypertension remained significant regardless of genetic susceptibility to hypertension (P for interaction=.067).

CONCLUSIONS

Considering the genetic predisposition to hypertension, poor sleep quality is associated with an elevated risk of hypertension. In intermediate or healthy levels of sleep quality, prolonging sleep duration is linked to a reduced risk of hypertension.

A conserved role for ALG10/ALG10B and the N -glycosylation pathway in the sleep-epilepsy axis

Congenital disorders of glycosylation (CDG) comprise a class of inborn errors of metabolism resulting from pathogenic variants in genes coding for enzymes involved in the asparagine-linked glycosylation of proteins. Unexpectedly to date, no CDG has been described for ALG10 , encoding the alpha-1,2-glucosyltransferase catalyzing the final step of lipid-linked oligosaccharide biosynthesis. Genome-wide association studies (GWAS) of human traits in the UK Biobank revealed significant SNP associations with short sleep duration, reduced napping frequency, later sleep timing and evening diurnal preference as well as cardiac traits at a genomic locus containing a pair of paralogous enzymes ALG10 and ALG10B . Modeling Alg10 loss in Drosophila, we identify an essential role for the N -glycosylation pathway in maintaining appropriate neuronal firing activity, healthy sleep, preventing seizures, and cardiovascular homeostasis. We further confirm the broader relevance of neurological findings associated with Alg10 from humans and flies using zebrafish and nematodes and demonstrate conserved biochemical roles for N -glycosylation in Arabidopsis . We report a human subject homozygous for variants in both ALG10 and ALG10B arising from a consanguineous marriage, with epilepsy, brain atrophy, and sleep abnormalities as predicted by the fly phenotype. Quantitative glycoproteomic analysis in our Drosophila model identifies potential key molecular targets for neurological symptoms of CDGs.

Integrative multiomic analysis unveils the molecular nexus of mitochondrial dysfunction in the pathogenesis of age-related macular degeneration

Mitochondrial dysfunction is linked to age-related macular degeneration (AMD), but its mechanisms and related molecular networks remain unclear. We explored the association between mitochondrial-related genes and AMD by integrating multiomic data. We acquired summary-level data on mitochondrial-related protein abundance, gene expression, and gene methylation from quantitative trait locus studies. Genetic associations with AMD were sourced from the International Age-related Macular Degeneration Genomics Consortium (discovery), FinnGen (replication), and UK Biobank (replication) studies. We used summary-data-based Mendelian randomization to assess the correlations between mitochondrial-related gene molecular characteristics and AMD. Furthermore, colocalization analysis was performed to ascertain if the detected signal pairings had a common causative genetic variation. Mitochondrial-related gene NFKB1 demonstrated a protective role in AMD (tier 1 evidence), whereas HSPA1A and HSPA1B genes were also associated with decreased AMD risk (tier 2 evidence). The methylation of cg09390974 and cg15409712 in NFKB1 was associated with increased NFKB1 expression, consistent with the protective effect on AMD risk, whereas inverse associations were observed between gene methylation and gene expression for HSPA1B (cg04835051 and cg16372051), supporting the risk roles of methylation in AMD. At circulating protein level, genetically predicted higher levels of HSPA1A (odds ratio [OR] 0.28, 95% confidence interval [CI] 0.19-0.41, P < 0.001), HSPA1B (OR 0.13, 95% CI 0.06-0.27, P < 0.001), and NFKB1 (OR 0.43, 95% CI 0.27-0.68, P < 0.001) were inversely associated with AMD risk. These associations were corroborated in the colocalization analysis. We identified AMD-linked mitochondrial-related genes, potentially improving the understanding of its pathophysiological mechanisms and aiding the identification of novel pharmaceutical targets.

To nap or not? Evidence from a meta-analysis of cohort studies of habitual daytime napping and health outcomes

Habitual daytime napping is a common behavioral and lifestyle practice in particular countries and is often considered part of a normal daily routine. However, recent evidence suggests that the health effects of habitual daytime napping are controversial. We systematically searched PubMed, Web of Science, Embase, and Cochrane Library databases from inception to March 9, 2024, to synthesize cohort studies of napping and health outcome risk. A total of 44 cohort studies with 1,864,274 subjects aged 20-86 years (mean age 56.4 years) were included. Overall, habitual napping increased the risk of several adverse health outcomes, including all-cause mortality, cardiovascular disease, metabolic disease, and cancer, and decreased the risk of cognitive impairment and sarcopenia. Individuals with a napping duration of 30 min or longer exhibited a higher risk of all-cause mortality, cardiovascular disease, and metabolic disease, whereas those with napping durations less than 30 min had no significant risks. No significant differences in napping and health risks were observed for napping frequency, percentage of nappers, sample size, sex, age, body mass index, follow-up years, or comorbidity status. These findings indicate that individuals with a long napping duration should consider shortening their daily nap duration to 30 min or less.

Navigating Mendelian Randomization in Sleep Medicine: Challenges, Opportunities, and Best Practices

Mendelian randomization (MR) has become an influential method for elucidating causal links between sleep traits and disorders, and health outcomes. This article provides sleep medicine specialists with an overview of MR, emphasizing its applications and limitations in health research, particularly in the context of sleep research. The article addresses key challenges in conducting and interpreting MR studies on sleep, focusing on the core assumptions of relevance, exchangeability, and exclusion restriction. The importance of proper genetic instrument selection, bias mitigation, and cautious result interpretation is emphasized. Strategies are recommended to enhance the quality of MR studies in sleep medicine, including collaborations between MR experts and sleep specialists. The paper also explores sleep medicine-specific issues like analyzing binary traits and addressing heterogeneity in pooled analyses. Guidance is provided on transparent reporting of MR findings, stressing the need for comprehensive effect estimates, confidence intervals, and p-values. We conclude by advocating for rigorous MR implementation in sleep research to deepen our understanding of sleep-health relationships. By following best practices in study design, analysis, and reporting, researchers can reinforce the credibility and impact of MR findings in sleep medicine, ultimately improving patient care and public health strategies.

Mendelian randomization of individual sleep traits associated with major depressive disorder

BACKGROUND

Observational studies have shown that individual sleep traits habits are potential risk factors for major depression. However, it is not known whether there is a causal relationship between individual sleep traits habits such as continuous sleep duration, short sleep duration, short sleep duration, insomnia, nap during the day, snoring, and major depression. In this study, Mendelian randomization (MR) was used to predict major depressive disorder (MDD) in individuals sleep traits habits.

METHODS

Data were obtained from the genome-wide association study (GWAS). Nine MR analysis methods were used: Inverse Variance Weighted (IVW) [fixed effects/multiplicative random effects], simple mode, simple mode, weighted mode, simple median, weighted median, penalised weighted median, and MR-Egger, MR Egger (bootstrap). IVW was used as the main analysis method for the MR analysis of two samples, and the other methods were used as supplements.

RESULTS

The results obtained through the IVW method supported a causal relationship between sleep duration and decreased risk of MDD (odds ratio, ORivw: 0.998; 95 % CI: 0.996-0.999, P<0.001). Two-Sample MR, results showed that short sleep duration has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.179; 95 % CI: 1.108-1.255, P<0.001). However, there were no sufficient evidence supported that long sleep duration has a causal effect on the decreased risk of MDD (odds ratio, ORivw: 0.991; 95 % CI: 0.924-1.062, P = 0.793). A significant causal relationship between insomnia and increased risk of MDD was observed (OR: 1.233; 95 % CI: 1.214-1.253, P<0.001). Interestingly, our study also found that daytime napping has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.519; 95 % CI: 1.376-1.678, P<0.001). The present results did not show a significant causal relationship between snoring and the risk of MDD (ORivw: 1.000; 95 % CI: 0.998-1.002, P = 0.906). Obstructive sleep apnea (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) and morning person (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) have no causal effect on the increased risk of MDD.

LIMITATIONS

The study could not ascertain whether there were genetic differences among different ethnicities, nations, and regions, as it only included participants of European ancestry.

CONCLUSIONS

In summary, our research provides genetic evidence for the relationship between individual sleep traits (short sleep duration, insomnia, daytime napping) and the increased risk of MDD. Interventions targeting lifestyle factors may reduce the risk of MDD.

Circadian transcriptome oscillations in human adipose tissue depend on napping status and link to metabolic and inflammatory pathways

STUDY OBJECTIVES

Napping is a common habit in many countries. Nevertheless, studies about the chronic effects of napping on obesity are contradictory, and the molecular link between napping and metabolic alterations has yet to be studied. We aim to identify molecular mechanisms in adipose tissue (AT) that may connect napping and abdominal obesity.

METHODS

In this cross-sectional study, we extracted the RNA repeatedly across 24 hours from cultured AT explants and performed RNA sequencing. Circadian rhythms were analyzed using six consecutive time points across 24 hours. We also assessed global gene expression in each group (nappers vs. non-nappers).

RESULTS

With napping, there was an 88% decrease in the number of rhythmic genes compared to that in non-nappers, a reduction in rhythm amplitudes of 29%, and significant phase changes from a coherent unimodal acrophase in non-nappers, towards a scattered and bimodal acrophase in nappers. Those genes that lost rhythmicity with napping were mainly involved in pathways of glucose and lipid metabolism, and of the circadian clock. Additionally, we found differential global gene expression between nappers and non-nappers with 34 genes down- and 32 genes upregulated in nappers. The top upregulated gene (IER3) and top down-regulated pseudogene (VDAC2P2) in nappers have been previously shown to be involved in inflammation.

CONCLUSIONS

These new findings have implications for our understanding of napping's relationship with obesity and metabolic disorders.

Napping and Obesity in Adults - What do we Know?

PURPOSE OF REVIEW

To review the evidence on the relationship between daytime napping and obesity.

RECENT FINDINGS

There is concern that napping may be harmful to metabolic health. Prospective studies have shown long time daytime napping (> 1 h) is associated with increased diabetes risk which may be partly associated with obesity. Evidence from numerous cross-sectional studies and meta-analyses of cross-sectional studies have shown that long time napping (> 1 h) but not short time napping is associated with increased risk of obesity, and this is seen worldwide. Inference regarding the nature of association from cross-sectional studies is limited; it is suggested the association is bidirectional. Prospective studies on the association between daytime napping and obesity are few and results unclear. Large longitudinal studies integrating daytime napping duration and night-time sleep behaviour and detailed information on lifestyle influences is needed to help elucidate further the associations of long time napping with obesity.

Day napping and metabolic-associated fatty liver disease: A systematic review and meta-analysis of observational studies

BACKGROUND

Napping inevitably affects human health, and the association between napping and metabolism-related diseases is being more seriously considered. However, the conclusions of studies on the relationship between napping and fatty liver disease (NAFLD)/metabolic-associated fatty liver disease (MAFLD) remain controversial.

METHODS

We performed a systematical search to identify eligible studies up to July 31, 2024. The fixed effects model was used to calculate the pooled odds ratio (OR). Subgroup were performed. Sensitivity analyses and meta-regression analysis were carried to explore the heterogeneity. Publication bias was assessed by funnel plot and Egger's test.

RESULTS

48,248 participants from 13 studies were included in this meta-analysis. The pooled analysis found napping to have an association between the incidence of NAFLD/MAFLD (OR, 1.13; 95% confidence interval (CI), 1.08-1.19; P < .001). The robustness of this study was confirmed using a sensitivity analysis. No apparent heterogeneity or publication bias was observed. Further meta-analysis revealed that short nap duration did not greatly affect the incidence of the disease (OR, 1.01; 95% CI, 0.91-1.12; P = .80). However, long nap duration was significantly linked to high risk of the disease (OR, 1.21; 95% CI, 1.02-1.44; P = .03).

CONCLUSION

Patients with NAFLD/MAFLD may had higher prevalence of napping habit. Future research is warranted to conduct a dose-response analysis, measure the effects of confounding factors, and explore the causal relationships between NAFLD/MAFLD. The research protocol was registered and approved in PROSPERO (registration no: CRD42023439507).

Associations between daytime napping, sleep duration, and depression and 15 cardiovascular diseases: a Mendelian randomization study

Background

Numerous studies have documented the effects of daytime napping, sleep duration, and depression on cardiovascular diseases (CVDs). However, the evidence has been gleaned from observational studies that might be riddled with confounding variables and the possibility of reverse causation bias. Therefore, the present study employed a Mendelian randomization (MR) methodology to meticulously explore the relationships between daytime napping, sleep duration, and depression, and the risk profiles of CVDs.

Methods

Genome-wide significant genetic variants associated with daytime napping, sleep duration, and depression were used as the instrumental variables (IVs). Data on the genetic correlations between these IVs and 15 CVDs were derived from the United Kingdom (UK) Biobank, Finnish Genome Studies, and other large-scale collaborations. We conducted both univariate and multivariate MR analyses to assess the overall effects and mediated relationships after adjusting for potential confounders, including body mass index (BMI), smoking status, and type 2 diabetes. The effect sizes were estimated using inverse variance-weighted (IVW) regression.

Results

The MR analysis revealed that an increased risk of heart failure (HF) [odds ratio (OR): 1.366; 95% confidence interval (CI): 1.013-1.842; P=0.04], coronary atherosclerosis (OR: 1.918; 95% CI: 1.257-2.927; P=0.003), myocardial infarction (MI) (OR: 1.505; 95% CI: 1.025-2.211; P=0.04), and coronary artery disease (CAD) (OR: 1.519; 95% CI: 1.130-2.043; P=0.006) was significantly associated with genetically predicted daytime napping. Prolonged sleep duration was found to be related to a reduced risk of HF (OR: 0.995; 95% CI: 0.993-0.998; P=2.69E-04), peripheral vascular disease (PVD) (OR: 0.984; 95% CI: 0.971-0.997; P=0.02), and CAD (OR: 0.997; 95% CI: 0.994-0.999; P=0.006). Additionally, a statistically significant positive relationship was observed between depressive disorders and the occurrence of atrial fibrillation (AF) (OR: 1.298, 95% CI: 1.065-1.583, P=0.01), indicating a heightened susceptibility. The multivariable MR analyses substantiated the reliability of the observed associations between daytime napping and the incidence of HF and CAD, following adjustments for genetically predicted BMI and smoking. The sensitivity analysis did not reveal any evidence of horizontal pleiotropy or heterogeneity, thus supporting the validity of the study's results.

Conclusions

This MR investigation posits a potential causal nexus between daytime napping, sleep duration, and depression, and the genesis of CVDs, offering new perspectives on the prevention and management of CVDs.

Causal Associations Between Sleep Traits and Low Grip Strength: A Bidirectional Mendelian Randomization Study

Background

Sleep disorders and low grip strength often co-occur clinically and are geriatric symptoms that cause significant socioeconomic burden. Previous observational studies have found an association between sleep behaviors and grip strength, but the causal relationship remains unclear.

Purpose

With the Mendelian randomization (MR) approach, the study aimed to determine the causal association between sleep traits (sleep duration, insomnia, daytime napping, sleep-wake disorders, chronotype) and low grip strength.

Methods

The study used genetic variants from the genome-wide association study (GWAS) archived in UK Biobank and FinnGen. We assessed the potential causal relationship between sleep behaviors and grip strength using inverse variance weighting (IVW), weighted median (WM), and MR-Egger. Additionally, we performed sensitivity analyses using Cochran's Q test, MR Egger Intercept test, funnel plots, and leave-one-out method.

Results

We found that sleep duration is causally negatively associated with low grip strength (OR = 0.618, 95% CI = 0.424-0.900, P = 0.012). Sleep-wake disorders have a positive association with low grip strength (OR = 1.018, 95% CI = 1.002-1.034, P = 0.029). Reversely, high low grip strength risk was causally associated with increased daytime napping (OR = 1.018, 95% CI = 1.004-1.032, P = 0.011).

Conclusion

The study revealed causal associations between sleep duration, sleep-wake disorders, and low grip strength. Understanding their relationship helps in early clinical intervention to improve the life quality of the elderly.

Cross-species evidence for a developmental origin of adult hypersomnia with loss of synaptic adhesion molecules beat-Ia/CADM2

Idiopathic hypersomnia (IH) is a poorly-understood sleep disorder characterized by excessive daytime sleepiness despite normal nighttime sleep. Combining human genomics with behavioral and mechanistic studies in fish and flies, we uncover a role for beat-Ia/CADM2 , synaptic adhesion molecules of the immunoglobulin superfamily, in excessive sleepiness. Neuronal knockdown of Drosophila beat-Ia results in sleepy flies and loss of the vertebrate ortholog of beat-Ia , CADM2 , results in sleepy fish. We delineate a developmental function for beat-Ia in synaptic elaboration of neuropeptide F (NPF) neurites projecting to the suboesophageal zone (SEZ) of the fly brain. Brain connectome and experimental evidence demonstrate these NPF outputs synapse onto a subpopulation of SEZ GABAergic neurons to stabilize arousal. NPF is the Drosophila homolog of vertebrate neuropeptide Y (NPY), and an NPY receptor agonist restores sleep to normal levels in zebrafish lacking CADM2 . These findings point towards NPY modulation as a treatment target for human hypersomnia.

Genetically predicted effects of 10 sleep phenotypes on revision of knee arthroplasty: a mendelian randomization study

BACKGROUND

Accumulating evidence has suggested that sleep disturbances and disorders are common in patients who undergo knee arthroplasty. Revision surgery represents one of the most catastrophic outcomes of knee arthroplasty. However, it remains unclear whether sleep traits are the causes or consequences of knee arthroplasty revision. This study aimed to genetically examine the relationships between sleep traits and knee arthroplasty revision.

METHODS

To determine the causal relationship between sleep traits and knee arthroplasty revision, we employed two-sample Mendelian randomization (MR) using summary statistics from the largest publicly available genome-wide association studies (GWASs). The MR design uses genetic variants as instrumental variables to help separate causal relationships from non-causal associations. The main analyses included an inverse variance weighted (IVW) meta-analysis to obtain primary effect estimates. Sensitivity analyses involving the weighted median approach and MR-Egger regression were also conducted to check for potential pleiotropic biases. Numerous complementary sensitivity analyses were also performed to identify statistically significant causal correlations when there were horizontal pleiotropy and heterogeneity across variants. Finally, a reverse MR analysis was performed to evaluate the possibility of reverse causation.

RESULTS

In the absence of heterogeneity and horizontal pleiotropy, the IVW method revealed that genetically-predicted short sleep duration short sleep duration (average sleep duration of 24 h is 6 h or less) was positively correlated with the risk of knee arthroplasty revision (odds ratio = 1.03, 95% confidence interval = 1.01-1.05, and P = 0.003), while the association between genetically-predicted long sleep duration and knee arthroplasty was negative. The reverse MR analysis did not yield evidence supporting reverse causality relation between knee arthroplasty revision and sleep phenotypes.

CONCLUSION

This research indicated that, of the 10 sleep phenotypes we analyzed, only sleep duration was causally associated with knee arthroplasty revision. These discoveries added to the understanding of the role of sleep traits in the etiology of knee arthroplasty revision, which might further expand our insights into the prevention of knee arthroplasty revision.

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.

Association of sleep traits with risk of hypertensive disorders of pregnancy: a mendelian randomization study

BACKGROUND

Unhealthy sleep patterns are common during pregnancy and have been associated with an increased risk of developing hypertensive disorders of pregnancy (HDPs) in observational studies. However, the causality underlying these associations remains uncertain. This study aimed to evaluate the potential causal association between seven sleep traits and the risk of HDPs using a two-sample Mendelian randomization study.

METHODS

Genome-wide association study (GWAS) summary statistics were obtained from the FinnGen consortium, UK Biobank, and other prominent consortia, with a focus on individuals of European ancestry. The primary analysis utilized an inverse-variance-weighted MR approach supplemented by sensitivity analyses to mitigate potential biases introduced by pleiotropy. Furthermore, a two-step MR framework was employed for mediation analyses.

RESULTS

The data analyzed included 200 000-500 000 individuals for each sleep trait, along with approximately 15 000 cases of HDPs. Genetically predicted excessive daytime sleepiness (EDS) exhibited a significant association with an increased risk of HDPs [odds ratio (OR) 2.96, 95% confidence interval (95% CI) 1.40-6.26], and the specific subtype of preeclampsia/eclampsia (OR 2.97, 95% CI 1.06-8.3). Similarly, genetically predicted obstructive sleep apnea (OSA) was associated with a higher risk of HDPs (OR 1.27, 95% CI 1.09-1.47). Sensitivity analysis validated the robustness of these associations. Mediation analysis showed that BMI mediated approximately 25% of the association between EDS and HDPs, while mediating up to approximately 60% of the association between OSA and the outcomes. No statistically significant associations were observed between other genetically predicted sleep traits, such as chronotype, daytime napping, sleep duration, insomnia, snoring, and the risk of HDPs.

CONCLUSION

Our findings suggest a causal association between two sleep disorders, EDS and OSA, and the risk of HDPs, with BMI acting as a crucial mediator. EDS and OSA demonstrate promise as potentially preventable risk factors for HDPs, and targeting BMI may represent an alternative treatment strategy to mitigate the adverse impact of sleep disorders.

[Causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus: a two-sample bidirectional Mendelian randomization study]

OBJECTIVE

To explore the causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus (iNPH) using two-sample bidirectional Mendelian randomization.

METHODS

The exposure data including 8 sleep phenotypes used in this study were obtained from GWAS catalog, FinnGenR10 and MRCIEU GWAS. The outcome data for idiopathic normal-pressure hydrocephalus were obtained from FinnGen R10. We used the inverse-variance weighted (IVW) method to perform the principal analyses. Cochrane Q-statistics test was used to assess the heterogeneity and MR Egger‑intercept test performed to evaluate the pleiotropy for sensitivity analyses.

RESULTS

IVW result showed that frequent daytime nap was associated with higher odds of iNPH (OR=3.3393, 95 CI% : 1.0646-10.4742, P=0.0270). Cochrane Q-statistics test and MR Egger‑intercept test showed that the MR analysis had no pleiotropy or heterogeneity (P > 0.05). The external validation reproduced this result (OR=2.5660, 95 CI% : 1.1680-5.6373, P=0.0189; OR=4.0424, 95 CI% : 1.5709-10.4024, P=0.0038). Reverse Mendelian randomization suggested that iNPH did not have significant impact on sleep phenotype.

CONCLUSION

The frequency of daytime naps is causally associated with iNPH, and reducing the frequency of weekly daytime naps can reduce the risk of iNPH in the elderly population.

Daytime napping and the incidence of Parkinson's disease: a prospective cohort study with Mendelian randomization

BACKGROUND

The causal relationship between daytime napping and the risk of Parkinson's disease (PD) remains unclear, with prospective studies providing limited evidence. This study investigated the association between daytime napping frequency and duration and PD incidence and explored the causality relationship between this association by conducting Mendelian randomization (MR) analysis.

METHODS

This prospective cohort study included 393,302 participants, and accelerometer-measured daytime napping data were available only for 78,141 individuals. Cox proportional hazards regression was used to estimate the association between the daytime napping frequency and duration and the PD risk. The role of the systemic immune-inflammation index (SII) in the association between daytime napping frequency and PD risk was assessed through mediation analyses. Moreover, the causal association between the daytime napping frequency and the PD risk was preliminarily explored by conducting two-sample MR analyses.

RESULTS

The median follow-up duration was 12.18 years. The participants who reported napping sometimes or usually exhibited a significantly higher PD risk than those who never/rarely napped during the day [sometimes: hazard ratio (HR), 1.13; 95% confidence interval (CI), 1.03-1.23; usually: HR, 1.33; 95% CI, 1.14-1.55], and SII played a mediating role in this association. However, the MR analyses did not indicate that the daytime napping frequency and PD risk were significantly associated. The participants napping for over 1 h exhibited a significantly elevated PD risk (HR, 1.54; 95% CI, 1.11-2.16). Moreover, no significant interaction was identified between napping frequency or duration and genetic susceptibility to PD (P for interaction > 0.05).

CONCLUSIONS

In this study, increased daytime napping frequency and duration were associated with an increased PD risk, but no causal relationship was observed between napping frequency and PD risk in the MR analysis. Larger GWAS-based cohort studies and MR studies are warranted to explore potential causal relationships.

The Genetics of Human Sleep and Sleep Disorders

Healthy sleep is vital for humans to achieve optimal health and longevity. Poor sleep and sleep disorders are strongly associated with increased morbidity and mortality. However, the importance of good sleep continues to be underrecognized. Mechanisms regulating sleep and its functions in humans remain mostly unclear even after decades of dedicated research. Advancements in gene sequencing techniques and computational methodologies have paved the way for various genetic analysis approaches, which have provided some insights into human sleep genetics. This review summarizes our current knowledge of the genetic basis underlying human sleep traits and sleep disorders. We also highlight the use of animal models to validate genetic findings from human sleep studies and discuss potential molecular mechanisms and signaling pathways involved in the regulation of human sleep.

No genetic association between sleep traits and periodontitis: A bidirectional two-sample Mendelian randomization study

OBJECTIVE

This study aimed to investigate the potential genetic link between sleep traits and periodontitis.

METHODS

A two-sample bidirectional Mendelian randomization (MR) analysis was conducted using publicly available genome-wide association studies data on chronotype, daytime sleepiness, daytime napping frequency, insomnia, sleep duration, snoring, and the apnea-hypopnea index (AHI), along with a separate dataset on periodontitis.

RESULTS

Chronotype (OR = 0.929, 95% CI = 0.788-1.095), daytime sleepiness (OR = 0.492, 95% CI = 0.186-1.306), daytime napping frequency (OR = 1.178, 95% CI = 0.745-1.863), sleep duration (OR = 0.868, 95% CI = 0.644-1.169), AHI (OR = 1.124, 95% CI = 0.980-1.289), insomnia (OR = 0.832, 95% CI = 0.440-1.573), and snoring (OR = 0.641, 95% CI = 0.198-2.075) had no effect on periodontitis. Similarly, periodontitis demonstrated no significant effect on sleep traits.

CONCLUSIONS

There is no evidence of a bidirectional genetic relationship between sleep traits and the risk of periodontitis.

Excessive Daytime Napping Increases the Risk of Non-Alcoholic Fatty Liver Disease: A Meta-Analysis and a Mendelian Randomization Study

Background

Prior research based on observations has furnished evidence that supports a connection between daytime napping and the prevalence of non-alcoholic fatty liver disease (NAFLD). Nevertheless, the question of whether this correlation is indicative of a causal link has not been definitively answered.

Methods

We used meta-analysis and Mendelian randomization (MR) to synthesize genetic and observational data. A two-sample MR analysis was conducted, leveraging 105 single-nucleotide polymorphisms (SNPs) known to be associated with daytime napping patterns. Additionally, summary-level data pertaining to NAFLD outcomes were acquired from the comprehensive UK Biobank study. Network meta-analyses were employed to investigate the relationship between excessive daytime napping and NAFLD, while subgroup was also performed.

Results

Significant associations were observed between daytime napping and NAFLD. The systematic review/meta-analysis uncovered a heightened risk of NAFLD development among individuals who engaged in daytime naps exceeding 30 minutes, when compared to those who did not nap(odds ratio [OR] = 1.32, 95% confidence interval [CI]: 1.05 to 1.66). Furthermore, MR analysis indicated that a genetic propensity towards longer daytime napping was significantly linked to an increased likelihood of NAFLD (OR = 2.26, 95% CI: 1.38 to 3.73).

Conclusion

Daytime napping has been found to be causally related to a higher risk of NAFLD. Furthermore, across all participants, napping for an average duration over 30 minutes was linked to an elevated likelihood of NAFLD.

Genetic predisposition to type 2 diabetes mellitus and aortic dissection: a Mendelian randomisation study

Background

This Mendelian randomization (MR) study aimed to explore the causal relationship between the genetic predisposition to type 2 diabetes mellitus (T2DM) and aortic dissection (AD), and to assess associations with genetically predicted glycemic traits. The study sought to verify the inverse relationship between T2DM and AD using a more robust and unbiased method, building on the observational studies previously established.

Materials and methods

The study employed a two-sample and multivariable MR approach to analyze genetic data from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) with 74,124 cases and 824,006 controls, and the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) involving up to 196,991 individuals. For AD data, FinnGen Release 10 was used, including 967 cases and 381,977 controls. The research focused on three foundational MR assumptions and controlled for confounders like hypertension. Genetic instruments were selected for their genome-wide significance, and multiple MR methods and sensitivity analyses were conducted.

Results

The study revealed no significant effect of genetic predisposition to T2DM on the risk of AD. Even after adjusting for potential confounders, the results were consistent, indicating no causal relationship. Additionally, glycemic traits such as fasting glucose, fasting insulin, and HbA1c levels did not show a significant impact on AD susceptibility. The findings remained stable across various MR models and sensitivity analyses. In contrast, genetic liability to T2DM and glycemic traits showed a significant association with coronary artery disease (CAD), aligning with the established understanding.

Conclusion

Contrary to previous observational studies, this study concludes that genetic predisposition to T2DM does not confer protection against AD. These findings underscore the imperative for further research, particularly in exploring the preventative potential of T2DM treatments against AD and to facilitate the development of novel therapeutic interventions.