Sleep Duration and Stroke: A Mendelian Randomization Study

2024 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 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

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.

Exploring the Causality of Type 1 Diabetes and Stroke Risk: A Mendelian Randomization Study and Meta-analysis

Type II diabetes was causally related to stroke, which is a risk factor for stroke. However, the causal relationship between type I diabetes(T1D) and stroke, especially its subtypes, remains unclear. To determine whether T1D has a genetic causal link to stroke and its subtypes, we undertook this mendelian randomization (MR) study. The genome-wide association studies (GWAS) of T1D was the source of exposure. The outcomes were strokes and their subtypes, including ischemic stroke (IS), small vessel stroke (SVS), cardioembolic stroke (CES), large artery atherosclerosis stroke (LAS), intracerebral hemorrhage (ICH), lobar intracerebral hemorrhage (LICH), and non-lobar intracerebral hemorrhage (NLICH). We used outcome GWAS conducted by ISGC consortium for the initial phase and GWAS from MEGASTROKE consortium as the data for the replication phase to confirm the causal association. Besides, we conducted a meta-analysis of the causal association from ISGC and MEGASTROKE databases to confirm robust causality. Inverse-variance weighting (IVW) was utilized as the primary method to estimate the causality between T1D and stroke. The Cochran's Q test and the MR-PRESSO global test were used to examine the sensitivity. We discovered the causal relationship between T1D and SVS (OR = 1.17, 95% CI: 1.07-1.28, p = 6.0 × 10- 4), CES (OR = 1.11, 95%CI: 1.03-1.21, p = 0.0080) in initial stage. The replication phase validated T1D has a causal relationship with SVS (OR = 1.12, 95% CI: 1.06-1.18, p = 4.0 × 10- 5), but not with stroke and other subtypes. The meta-analysis of initial and replication stage again supported the causal link between T1D and SVS (OR = 1.13, 95% CI: 1.08-1.18, p < 0.05). However, no causal relationship was found between T1D and other stroke subtypes. The sensitivity analysis also supported the robust of these results. In conclusion, T1D was causally associated with SVS, but not with other subtypes of stroke. More investigation is needed to understand the underlying biology mechanism.

Long Sleep Duration and Stroke-Highly Linked, Poorly Understood

Stroke is one of the leading causes of disability and mortality. Both short and long sleep durations are associated with adverse health outcomes. Cross-sectional studies have shown an increased prevalence of stroke in long sleepers. Long sleep duration increases stroke incidence and mortality in prospective epidemiological studies. Accumulating evidence suggests that the magnitude of the association between sleep and stroke appears to be stronger for longer sleep than shorter sleep, yielding a J-shaped curve. Potential links between long sleep duration and stroke include increased incidence of diabetes and atrial fibrillation, elevated levels of inflammation, arterial stiffness, and blood pressure variability. Long sleep duration is a strong marker and a plausible risk factor for stroke and should be considered in future scoring for risk stratification and stroke prevention.

The independent and combined association of napping and night sleep duration with stroke in Chinese rural adults

BACKGROUND

Inappropriate sleep duration is a potential cause of stroke. But the effect of napping on stroke risk remains controversial and the interaction between night sleep and napping duration remains unclear. The objective of this study was to examine the independent and combined effects of napping and nocturnal sleep duration on stroke.

METHODS

Subjects were derived from a rural cohort study in Henan. The Pittsburgh Sleep Quality Index (PSQI) was applied to identify nap duration and nocturnal sleep duration. Binary logistic regression was employed to indicate the dose-response relationships between naps, nocturnal sleep, total 24-h sleep duration, and stroke.

RESULTS

Among the 37,341 participants (14,485 men), 2600 suffered from a stroke. The odds ratios (ORs) and 95% confidence level (CI) for stroke in the fully adjusted model were 1.37 (1.13-1.65) for men nappers compared to non-nappers. Compared to 7-8 h of sleep per day, night sleep durations < 6 h and ≥ 9 h and 24-h sleep duration ≥ 10 h were linked to increased odds of stroke in men. The ORs (95%CI) were 1.34 (1.06-1.69) in nocturnal sleep duration < 6 h, 1.30 (1.06-1.59) in nocturnal sleep duration ≥ 9 h, and 1.40 (1.15-1.71) in 24-h sleep duration ≥ 10 h in men. In addition, long naps and prolonged nocturnal sleep duration have a joint effect on stroke in the fully adjusted model.

CONCLUSION

The napping duration and nocturnal sleep duration have independently and jointly effects on stroke in rural populations. More research is required to explore the underlying mechanisms for this relationship.

CLINICAL TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered on the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) ( http://www.chictr.org.cn/showproj.aspx?proj=11375 ).

Heart Disease and Stroke Statistics-2023 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 Epidemiology and Prevention 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 with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

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.

Association of sleep duration and napping with stroke mortality in older Chinese: A 14-year prospective cohort study of the Guangzhou Biobank Cohort study

STUDY OBJECTIVE

Evidence regarding the association of short sleep duration and napping with stroke remains limited and controversial. We examined the association of sleep duration and napping with risk of stroke mortality in an older Chinese cohort.

METHODS

Sleep duration and daytime napping were assessed by face-to-face interview during 2003-2008. Information of causes of death until April 30, 2021 was collected via record linkage with the Death Registry. Cox regression was used to calculate the hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

Of 27,254 participants aged average 62.0 (standard deviation = 7.1) years, 818 stroke deaths occurred within 388,798 person-years (mean = 14.3 years) of follow-up. A U-shaped relation between sleep duration and risk of stroke mortality was observed. Participants with short (≤5 h/day) or long sleep duration (≥9 h/day) showed higher risks of total stroke mortality, with adjusted HRs (95% CIs) being 1.27 (1.01-1.59) and 1.37 (1.07-1.75), respectively. However, non-significant association of short or long sleep duration with hemorrhagic or ischemic stroke mortality was found. The associations of short and long sleep duration with total stroke mortality were more pronounced in those with hypertension (P for interaction with hypertension = 0.01), with HRs (95% CIs) being 1.37 (1.04-1.82) and 1.77 (1.33-2.36), respectively. No association between napping and risk of stroke mortality was found.

CONCLUSIONS

Both short and long sleep duration, but not daytime napping, were associated with higher risk of stroke mortality. Public health messages to encourage good sleep hygiene may be important, especially for people with hypertension.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

Associations between sleep duration and cardiovascular diseases: A meta-review and meta-analysis of observational and Mendelian randomization studies

The associations between sleep duration and cardiovascular diseases (CVDs) have been explored in many observational studies. However, the causality of sleep duration and many CVDs, such as coronary artery disease (CAD), heart failure (HF), and stroke, remains unclear. In this study, we conducted a systematic meta-review and meta-analysis of the results of observational and Mendelian randomization (MR) studies to examine how sleep duration impacts the risk of CVDs. We searched articles published in English and before 10 September 2021 in PubMed, Web of Science, and Embase. The articles were screened independently by two reviewers to minimize potential bias. We combined the meta-analyses of observational studies and 11 MR studies and summarized evidence of the effect of sleep duration on the risk of CAD, HF, stroke, and cardiovascular and all-cause mortality. Results showed that (a) evidence is accumulating that short sleep duration is a causal risk factor for CAD and HF; (b) abundant evidence from observational studies supports that long sleep duration is associated with the risk of CAD, stroke, and mortality, and long sleep duration has no causal associations with stroke and CAD in the MR studies; the causation of long sleep duration and other CVDs should be further studied; and (c) emerging evidence indicates that an increase in hours of sleep is associated with a decreased risk of CAD. Finally, we discussed the underlying pathophysiological mechanisms underlying short sleep duration and CVDs and suggested that increasing sleep duration benefits cardiovascular health.

Genome-Wide Studies in Ischaemic Stroke: Are Genetics Only Useful for Finding Genes?

Ischaemic stroke is a complex disease with some degree of heritability. This means that heritability factors, such as genetics, could be risk factors for ischaemic stroke. The era of genome-wide studies has revealed some of these heritable risk factors, although the data generated by these studies may also be useful in other disciplines. Analysis of these data can be used to understand the biological mechanisms associated with stroke risk and stroke outcome, to determine the causality between stroke and other diseases without the need for expensive clinical trials, or to find potential drug targets with higher success rates than other strategies. In this review we will discuss several of the most relevant studies regarding the genetics of ischaemic stroke and the potential use of the data generated.

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.

Genetics of common cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.

The Role of Amyloid, Tau, and APOE Genotype on the Relationship Between Informant-Reported Sleep Disturbance and Alzheimer's Disease Risks

BACKGROUND

The association between sleep and Alzheimer's disease (AD) biomarkers are well-established, but little is known about how they interact to change the course of AD.

OBJECTIVE

To determine the potential interaction between sleep disturbance and Aβ, tau, and APOE4 on brain atrophy and cognitive decline.

METHODS

Sample included 351 participants (mean age 72.01 ± 6.67, 50.4%female) who were followed for approximately 5 years as part of the Alzheimer's Disease Neuroimaging Initiative. Informant-reported sleep disturbance (IRSD) was measured using the Neuropsychiatric Inventory (NPI). Changes in magnetic resonance imaging (MRI)-measured AD signature brain regions and cognitive performance and IRSD's interaction with cerebrospinal fluid amyloid-β (Aβ42) and p-Tau depositions and APOE4 status were examined using the linear mixed models.

RESULTS

Baseline IRSD was not significantly associated with the rate of atrophy after adjusting for covariates (age, sex, education, total NPI severity score, and sleep medications). However, there was a significant interaction between IRSD and AD biomarkers on faster atrophy rates in multiple brain regions, including the cortical and middle temporal volumes. Post-hoc analyses indicated that Aβ and p-Tau/Aβ predicted a faster decline in these regions/domains in IRSD, compared with biomarker-negative individuals with IRSD (ps≤0.001). There was a significant IRSD*APOE4 interaction for brain atrophy rate (ps≤0.02) but not for cognition.

CONCLUSION

IRSD may increase the future risk of AD by contributing to faster brain atrophy and cognitive decline when combined with the presence of AD biomarkers and APOE4. Early intervention for sleep disturbance could help reduce the risk of developing AD.

Sleep and Stroke: Opening Our Eyes to Current Knowledge of a Key Relationship

PURPOSE OF REVIEW

To elucidate the interconnection between sleep and stroke.

RECENT FINDINGS

Growing data support a bidirectional relationship between stroke and sleep. In particular, there is strong evidence that sleep-disordered breathing plays a pivotal role as risk factor and concur to worsening functional outcome. Conversely, for others sleep disorders (e.g., insomnia, restless legs syndrome, periodic limb movements of sleep, REM sleep behavior disorder), the evidence is weak. Moreover, sleep disturbances are highly prevalent also in chronic stroke and concur to worsening quality of life of patients. Promising novel technologies will probably allow, in a near future, to guarantee a screening of commonest sleep disturbances in a larger proportion of patients with stroke. Sleep assessment and management should enter in the routinary evaluation of stroke patients, of both acute and chronic phase. Future research should focus on the efficacy of specific sleep intervention as a therapeutic option for stroke patients.

Ischemic Stroke and Sleep: The Linking Genetic Factors

This review summarizes the available data about genetic factors which can link ischemic stroke and sleep. Sleep patterns (subjective and objective measures) are characterized by heritability and comprise up to 38-46%. According to Mendelian randomization analysis, genetic liability for short sleep duration and frequent insomnia symptoms is associated with ischemic stroke (predominantly of large artery subtype). The potential genetic links include variants of circadian genes, genes encoding components of neurotransmitter systems, common cardiovascular risk factors, as well as specific genetic factors related to certain sleep disorders.

Mendelian Randomization Studies in Stroke: Exploration of Risk Factors and Drug Targets With Human Genetic Data

Elucidating the causes of stroke is key to developing effective preventive strategies. The Mendelian randomization approach leverages genetic variants related to an exposure of interest to investigate the effects of varying that exposure on disease risk. The random allocation of genetic variants at conception reduces confounding from environmental factors and thus strengthens causal inference, analogous to treatment allocation in a randomized controlled trial. With the recent explosion in the availability of human genetic data, Mendelian randomization has proven a valuable tool for studying risk factors for stroke. In this review, we provide an overview of recent developments in the application of Mendelian randomization to unravel the pathophysiology of stroke subtypes and identify therapeutic targets for clinical translation. The approach has offered novel insight into the differential effects of risk factors and antihypertensive, lipid-lowering, and anticoagulant drug classes on risk of stroke subtypes. Analyses have further facilitated the prioritization of novel drug targets, such as for inflammatory pathways underlying large artery atherosclerotic stroke and for the coagulation cascade that contributes to cardioembolic stroke. With continued methodological advances coupled with the rapidly increasing availability of genetic data related to a broad range of stroke phenotypes, the potential for Mendelian randomization in this context is expanding exponentially.

Mendelian Randomization in Stroke: A Powerful Approach to Causal Inference and Drug Target Validation

Stroke is a leading cause of death and disability worldwide. However, our understanding of its underlying biology and the number of available treatment options remain limited. Mendelian randomization (MR) offers a powerful approach to identify novel biological pathways and therapeutic targets for this disease. Around ~100 MR studies have been conducted so far to explore, confirm, and quantify causal relationships between several exposures and risk of stroke. In this review, we summarize the current evidence arising from these studies, including those investigating ischemic stroke, hemorrhagic stroke, or both. We highlight the different types of exposures that are currently under study, ranging from well-known cardiovascular risk factors to less established inflammation-related mechanisms. Finally, we provide an overview of future avenues of research and novel approaches, including drug target validation MR, which is poised to have a substantial impact on drug development and drug repurposing.

Association between daytime napping and stroke: A dose-response meta-analysis

Daytime napping is common in many regions around the world and has been an important part of people's daily life. Daytime napping has attracted increasing attention in recent years. Thus, we conducted a meta-analysis to evaluate the relationship between daytime napping and stroke, and help reduce the risk of stroke by improving living habits. The Embase, PubMed, Web of Science and PsycINFO databases were searched for cohort studies published before October 2020 and eight eligible studies with 524,408 participants and 5,875 stroke cases were included in the final analysis. The pooled relative risk (RR) of stroke was 1.47 (95% confidence interval [CI]: 1.24-1.74; p < .001) with significant heterogeneity (I²  = 58%, p for heterogeneity = 0.02). However, the heterogeneity decreased when the study in which adjusting for sleep duration and stratifying the results based on sleep duration was not performed was excluded (RR: 1.38; 95% CI: 1.19-1.60, I²  = 44%, p for heterogeneity = 0.10). In dose-response analysis, the linear trend indicated that for every 10-min increase in daytime napping, the risk of stroke increased by 3%. Further well-designed large studies are needed to explore the effects of daytime napping on stroke and the underlying biological mechanisms.