Search

In people living with HIV, Kaposi Sarcoma (KS), a vascular neoplasm caused by KS herpesvirus (KSHV/HHV-8), remains one of the most common malignancies worldwide. Individuals living with HIV, receiving otherwise effective antiretroviral therapy, may present with extensive disease requiring chemotherapy. Hence, new therapeutic approaches are needed. The Wilms' tumor 1 (WT1) protein is overexpressed and associated with poor prognosis in several hematologic and solid malignancies and has shown promise as an immunotherapeutic target. We found that WT1 was overexpressed in >90% of a total 333 KS biopsies, as determined by immunohistochemistry and image analysis. Our largest cohort from ACTG, consisting of 294 cases was further analyzed demonstrating higher WT1 expression was associated with more advanced histopathologic subtypes. There was a positive correlation between the proportion of infected cells within KS tissues, assessed by expression of the KSHV-encoded latency-associated nuclear antigen (LANA), and WT1 positivity. Areas with high WT1 expression showed sparse T-cell infiltrates, consistent with an immune evasive tumor microenvironment. We show that major oncogenic isoforms of WT1 are overexpressed in primary KS tissue and observed WT1 upregulation upon de novo infection of endothelial cells with KSHV. KSHV latent viral FLICE-inhibitory protein (vFLIP) upregulated total and major isoforms of WT1, but upregulation was not seen after expression of mutant vFLIP that is unable to bind IKKƴ and induce NFκB. siRNA targeting of WT1 in latent KSHV infection resulted in decreased total cell number and pAKT, BCL2 and LANA protein expression. Finally, we show that ESK-1, a T cell receptor-like monoclonal antibody that recognizes WT1 peptides presented on MHC HLA-A0201, demonstrates increased binding to endothelial cells after KSHV infection or induction of vFLIP expression. We propose that oncogenic isoforms of WT1 are upregulated by KSHV to promote tumorigenesis and immunotherapy directed against WT1 may be an approach for KS treatment.

Rationale: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epidemiologic evidence supporting the importance of genetic factors influencing OSA but limited data implicating specific genes. Objectives: To search for rare variants contributing to OSA severity. Methods: Leveraging high-depth genomic sequencing data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the CFS (Cleveland Family Study), followed by multistage gene-based association analyses in independent cohorts for apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry. Measurements and Main Results: Linkage analysis in the CFS identified a suggestive linkage peak on chromosome 7q31 (LOD = 2.31). Gene-based analysis identified 21 noncoding rare variants in CAV1 (Caveolin-1) associated with lower AHI after accounting for multiple comparisons (P = 7.4 × 10-8). These noncoding variants together significantly contributed to the linkage evidence (P

Sleep duration, sleep efficiency, and sleep timing have been shown to have potential effects on metabolic functions relevant to circadian rhythms. It is not clear if the impact of sleep patterns on metabolic risk factors is through sociocultural and environmental factors or circadian misalignment. We investigated the associations of sleep patterns, chronotype, and social jet lag with metabolic syndrome among non-shift worker Hispanic/Latino adults. We used cross-sectional data from the Sueño Ancillary Study of The Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Data from a subsample of 2189 participants aged 18-64 years were used in the analysis. Mean nightly sleep duration, mean sleep onset time, mean sleep offset time, mean sleep midpoint time, sleep efficiency, sleep variability (standard deviation (SD) of sleep duration, and SD of sleep midpoint), and time spent above light exposure threshold (1000 lux) in a day were assessed by wrist actigraphy (Acti-watch Spectrum). Chronotype was determined by the reduced Morningness-Eveningness Questionnaire. Medical conditions including dyslipidemia, hypertension, and diabetes mellitus were determined from a fasting blood specimen and physical exam at the baseline visit. To determine whether sleep patterns, light levels, chronotype, and social jetlag are associated with metabolic syndrome, multivariable logistic regression models were fitted, including variables with P

BackgroundIdentifying Obstructive Sleep Apnea (OSA) phenotypes among middle-aged and older Hispanics/Latinos can facilitate personalized care, better inform treatment decisions, and could lead to improved clinical outcomes.MethodsWe focused on middle-aged and older adults (ages ≥45-74 years at baseline) with an apnea-hypopnea index (AHI) ≥5 from the HCHS/SOL (2008-2011) (unweighted n = 3,545). We used latent class analyses (LCA) to identify empirical and clinically meaningful OSA phenotypes. Sleep variables included AHI, percent sleep time SpO2

Study objectivesRecent work on US Whites from clinical samples used obstructive sleep apnea (OSA) symptoms to generate phenotypes for individuals with moderate-severe OSA which suggested 3 to 5 symptom classes. However, it is unknown whether similar classes generalize to diverse Hispanics/Latino adults. Therefore, we sought to fill this gap by empirically deriving sleep phenotypes among a large sample of diverse Hispanics/Latinos.MethodsWe used data from The Hispanic Community Health Study/Study of Latinos (HCHS/SOL; 2008-2011), a prospective cohort study designed using a multisite multistage probability sample of adults 18-74 years old. The subpopulation of interest included participants with moderate-severe OSA symptoms (≥15 respiratory event index (REI) events per hour; n = 1,605). We performed latent class analysis for complex survey data using 15 common OSA symptoms (e.g. Epworth Sleepiness Scale) and 4 comorbidities to identify phenotype classes.ResultsAverage age was 52.4 ± 13.9 years and 34.0% were female. Mean REI was 33.8 ± 22.5 events per hour. Fit statistics and clinical significance suggested that a three-class solution provided the best fit to the data. The three phenotypes were: (1) Minimally Symptomatic (47.7%), (2) Excessive sleepiness (37.1%), and (3) Disturbed Sleep (15.2%). Sensitivity models were consistent with the main proposed solution.ConclusionsDerived sleep phenotypes among diverse Hispanic/Latinos were consistent with recent findings from the Sleep Apnea Global Interdisciplinary Consortium, but we found notable differences in class prevalence relative to Whites. Further research is needed to link derived sleep phenotypes to health comorbidities in diverse populations.

BackgroundSleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.MethodsThe study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation

IntroductionWe determined if actigraphy-derived sleep patterns led to 7-year cognitive decline in middle-aged to older Hispanic/Latino adults.MethodsWe examined 1035 adults, 45 to 64 years of age, from the Hispanic Community Health Study/Study of Latinos. Participants had repeated measures of cognitive function 7 years apart, home sleep apnea studies, and 1 week of actigraphy. Survey linear regression evaluated prospective associations between sleep and cognitive change, adjusting for main covariates.ResultsLonger sleep-onset latency was associated with declines in global cognitive function, verbal learning, and verbal memory. Longer sleep-onset latency was also cross-sectionally associated with verbal learning, verbal memory, and word fluency. Sleep fragmentation was not associated with cognitive change.ConclusionIn a cohort of mostly middle-aged Hispanic/Latinos, actigraphy-derived sleep-onset latency predicted 7-year cognitive change. These findings may serve as targets for sleep interventions of cognitive decline.

BACKGROUND: Relationships between dyslipidaemia and leukocyte counts have been investigated in several studies, demonstrating limited evidence of associations in humans. As such, studying a diverse range of cohorts will ensure evidence is robust. This study focused on investigating cross-sectional and longitudinal relationships in three large-scale cohorts. METHODS: The cross-sectional analysis included a total of 27,566 participants with valid data on lipid measures and leukocyte counts from three study cohorts: National Health and Nutrition Survey (NHANES), Korean National Health and Nutrition Survey (KNHANES) and Treating to New Targets (TNT) trial. The longitudinal analysis included 9323 participants with valid data on lipid measures and leukocyte counts at baseline and one year with statin treatment. Associations between lipid levels and leukocyte counts were analysed by multivariable linear regression and adjusted for basic demographic and cardiovascular risk factors. RESULTS: Cross-sectional data from NHANES demonstrated the association of lower high-density lipoprotein (HDL) cholesterol and higher triglycerides with higher leukocyte count (0.9% lower and 0.3% higher count per 10 mg/dL increase in HDL cholesterol and triglycerides respectively, both p

BackgroundData on the prevalence and correlates of restless legs syndrome (RLS) in people with HIV are limited. This study sought to determine the prevalence of RLS, associated clinical correlates, and characterize sleep-related differences in men with and without HIV.MethodsSleep-related data were collected in men who have sex with men participating in the Multicenter AIDS Cohort Study (MACS). Demographic, health behaviors, HIV status, comorbidities, and serological data were obtained from the MACS visit coinciding with sleep assessments. Participants completed questionnaires, home polysomnography, and wrist actigraphy. RLS status was determined with the Cambridge-Hopkins RLS questionnaire. RLS prevalence was compared in men with and without HIV. Multinomial logistic regression was used to examine correlates of RLS among all participants and men with HIV alone. Sleep-related differences were examined in men with and without HIV by RLS status.ResultsThe sample consisted of 942 men (56% HIV+; mean age 57 years; 69% white). The prevalence of definite RLS was comparable in men with and without HIV (9.1% vs 8.7%). In multinomial regression, HIV status was not associated with RLS prevalence. However, white race, anemia, depression, and antidepressant use were each independently associated with RLS. HIV disease duration was also associated with RLS. Men with HIV and RLS reported poorer sleep quality, greater sleepiness, and had worse objective sleep efficiency/fragmentation than men without HIV/RLS.ConclusionsThe prevalence of RLS in men with and without HIV was similar. Screening for RLS may be considered among people with HIV with insomnia and with long-standing disease.

This paper explores the potential of Twitter, a popular social media platform, as a tool for predicting election outcomes. Sentiment analysis has emerged as a powerful tool for predicting election outcomes, with numerous studies showcasing its effectiveness in various countries. For instance, research has utilized sentiment analysis to forecast election results in nations like the USA, India, Pakistan and other countries, demonstrating the utility of social media data in gauging public opinion and predicting electoral results [1]. Elections in India are always considered important events that most people look forward to the rapid growth of social media in the past has provided end users with powerful tools to share their ideas. Twitter, which is one such platform, provides daily updates on political events through various hashtags and trends. People react to political events and give their opinions. Our approach is to collect tweets from top political parties contesting the Gujarat Assembly Elections 2022, and then calculate sentiment scores. The database includes a variety of recent and well-liked tweets about a specific political party. Party tweets are generated with specific keywords like “BJP”, “AAP”,“Congress” and so on. In the context of India, Twitter sentiment analysis tools and classification have been used to predict the outcomes of state assembly elections, underscoring the potential of social media data in forecasting electoral results within the country [2]. We used standard machine learning algorithms like VADER sentiment analyzer on Random Forest and Decision Tree for our classification and testing data to classify tweets as positive and negative. As a result, this work uses sentiment analysis to evaluate tweets gathered from Twitter and forecast election outcomes. This work shows the growing influence of social media on politics and the feasibility of using such platforms for predictive analysis. The findings of this study could provide valuable insights for political parties, policymakers, and researchers interested in the intersection of social media and politics. Random Forest and Decision Tree models performed well in predicting election outcomes based on sentiment analysis on Twitter data with 89% and 86% respectively.

BackgroundSleep Disordered Breathing (SDB) is associated with a wide range of pathophysiological changes due, in part, to hypoxemia during sleep. We sought to identify gene transcription associations with measures of SDB and hypoxemia during sleep, and study their response to treatment.MethodsIn two discovery cohorts, Framingham Offspring Study (FOS; N = 571) and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 580), we studied gene expression in peripheral blood mononuclear cells in association with three measures of SDB: Apnea Hypopnea Index (AHI); average oxyhemoglobin saturation (avgO2) during sleep; and minimum oxyhemoglobin saturation (minO2) during sleep. Associated genes were used for analysis of gene expression in the blood of 15 participants with moderate or severe obstructive sleep apnea (OSA) from the Heart Biomarkers In Apnea Treatment (HeartBEAT) trial. These genes were studied pre- and post-treatment (three months) with continuous positive airway pressure (CPAP). We also performed Gene Set Enrichment Analysis (GSEA) on all traits and cohort analyses.FindingsTwenty-two genes were associated with SDB traits in both MESA and FOS. Of these, lower expression of CD1D and RAB20 was associated with lower avgO2 in MESA and FOS. CPAP treatment increased the expression of these genes in HeartBEAT participants. Immunity and inflammation pathways were up-regulated in subjects with lower avgO2; i.e., in those with a more severe SDB phenotype (MESA), whereas immuno-inflammatory processes were down-regulated following CPAP treatment (HeartBEAT).InterpretationLow oxygen saturation during sleep is associated with alterations in gene expression and transcriptional programs that are partially reversed by CPAP treatment.

Rationale: Although both type 2 diabetes mellitus (T2DM) and obstructive sleep apnea (OSA) are independently recognized as risk factors for cardiovascular disease, little is known about their interaction.Objectives: We hypothesized that T2DM and OSA act synergistically to increase vascular risk, and that treatment of OSA would improve vascular reactivity in patients with T2DM plus OSA.Methods: Cross-sectional study of 141 adults with T2DM, OSA, T2DM plus OSA, and control subjects, followed by a 3-month, parallel-arm, randomized, placebo-controlled trial comparing active and sham continuous positive airway pressure (CPAP) in 53 adults with T2DM plus OSA. Endothelium-dependent macro- and microvascular reactivity (flow-mediated dilation [FMD] of the brachial artery and acetylcholine-induced dilation of forearm microvasculature, respectively) and cardiovascular magnetic resonance to assess left- and right-ventricular mass/volume.Results: Mean (±SD) FMD was 6.1 (±4.0)%, 7.3 (±3.6)%, 6.8 (±4.5)%, and 4.8 (±2.9)% in control subjects, T2DM only, OSA only, and T2DM plus OSA, respectively. We observed a significant T2DM × OSA interaction on FMD, such that the mean effect of OSA in those with T2DM was 3.1% (95% confidence interval [CI], 0.6 to 5.6) greater than the effect of OSA in those without T2DM. A total of 3 months of CPAP resulted in a mean absolute increase in FMD of 0.3% (95% CI, -1.9 to 2.5; primary endpoint), with a net improvement of 1.1% (95% CI, -1.4 to 3.6) among those with adherence of 4 h/night or greater. A significant T2DM × OSA interaction was found for both left ventricular (LV) and right ventricular end-diastolic volume, such that OSA was associated with a 22.4 ml (95% CI, 3.2 to 41.6) greater LV end-diastolic volume and 23.2 ml (95% CI, 2.6 to 43.8) greater right ventricular end-diastolic volume in those with T2DM compared with the impact of OSA in those without T2DM. We observed a net improvement in LV end-diastolic volume of 8.7 ml (95% CI, -7.0 to 24.4).Conclusions: The combination of T2DM plus OSA is associated with macrovascular endothelial dysfunction beyond that observed with either disease alone. CPAP for 3 months did not significantly improve macrovascular endothelial function in the intent-to-treat analysis; however, cardiovascular magnetic resonance results suggest that there may be a beneficial effect of CPAP on LV diastolic volume.Clinical trial registered with www.clinicaltrials.gov (NCT01629862).

BackgroundThere is a scarcity of published data on the global prevalence of obstructive sleep apnoea, a disorder associated with major neurocognitive and cardiovascular sequelae. We used publicly available data and contacted key opinion leaders to estimate the global prevalence of obstructive sleep apnoea.MethodsWe searched PubMed and Embase to identify published studies reporting the prevalence of obstructive sleep apnoea based on objective testing methods. A conversion algorithm was created for studies that did not use the American Academy of Sleep Medicine (AASM) 2012 scoring criteria to identify obstructive sleep apnoea, allowing determination of an equivalent apnoea-hypopnoea index (AHI) for publications that used different criteria. The presence of symptoms was not specifically analysed because of scarce information about symptoms in the reference studies and population data. Prevalence estimates for obstructive sleep apnoea across studies using different diagnostic criteria were standardised with a newly developed algorithm. Countries without obstructive sleep apnoea prevalence data were matched to a similar country with available prevalence data; population similarity was based on the population body-mass index, race, and geographical proximity. The primary outcome was prevalence of obstructive sleep apnoea based on AASM 2012 diagnostic criteria in individuals aged 30-69 years (as this age group generally had available data in the published studies and related to information from the UN for all countries).FindingsReliable prevalence data for obstructive sleep apnoea were available for 16 countries, from 17 studies. Using AASM 2012 diagnostic criteria and AHI threshold values of five or more events per h and 15 or more events per h, we estimated that 936 million (95% CI 903-970) adults aged 30-69 years (men and women) have mild to severe obstructive sleep apnoea and 425 million (399-450) adults aged 30-69 years have moderate to severe obstructive sleep apnoea globally. The number of affected individuals was highest in China, followed by the USA, Brazil, and India.InterpretationTo our knowledge, this is the first study to report global prevalence of obstructive sleep apnoea; with almost 1 billion people affected, and with prevalence exceeding 50% in some countries, effective diagnostic and treatment strategies are needed to minimise the negative health impacts and to maximise cost-effectiveness.FundingResMed.

Study objectivesDaytime sleepiness is a consequence of inadequate sleep, sleep-wake control disorder, or other medical conditions. Population variability in prevalence of daytime sleepiness is likely due to genetic and biological factors as well as social and environmental influences. DNA methylation (DNAm) potentially influences multiple health outcomes. Here, we explored the association between DNAm and daytime sleepiness quantified by the Epworth Sleepiness Scale (ESS).MethodsWe performed multi-ethnic and ethnic-specific epigenome-wide association studies for DNAm and ESS in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 619) and the Cardiovascular Health Study (n = 483), with cross-study replication and meta-analysis. Genetic variants near ESS-associated DNAm were analyzed for methylation quantitative trait loci and followed with replication of genotype-sleepiness associations in the UK Biobank.ResultsIn MESA only, we detected four DNAm-ESS associations: one across all race/ethnic groups; three in African-Americans (AA) only. Two of the MESA AA associations, in genes KCTD5 and RXRA, nominally replicated in CHS (p-value < 0.05). In the AA meta-analysis, we detected 14 DNAm-ESS associations (FDR q-value < 0.05, top association p-value = 4.26 × 10-8). Three DNAm sites mapped to genes (CPLX3, GFAP, and C7orf50) with biological relevance. We also found evidence for associations with DNAm sites in RAI1, a gene associated with sleep and circadian phenotypes. UK Biobank follow-up analyses detected SNPs in RAI1, RXRA, and CPLX3 with nominal sleepiness associations.ConclusionsWe identified methylation sites in multiple genes possibly implicated in daytime sleepiness. Most significant DNAm-ESS associations were specific to AA. Future work is needed to identify mechanisms driving ancestry-specific methylation effects.

Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Its prevalence and severity vary across ancestral background. Although OSA traits are heritable, few genetic associations have been identified. To identify genetic regions associated with OSA and improve statistical power, we applied admixture mapping on three primary OSA traits [the apnea hypopnea index (AHI), overnight average oxyhemoglobin saturation (SaO2) and percentage time SaO2

OBJECTIVE:Atherosclerosis is a major cause of cardiovascular disease. Monocyte-endothelial cell interactions are partly mediated by expression of monocyte CX3CR1 and endothelial cell fractalkine (CX3CL1). Interrupting the interaction between this ligand-receptor pair should reduce monocyte binding to the endothelial wall and reduce atherosclerosis. We sought to reduce atherosclerosis by preventing monocyte-endothelial cell interactions through use of a long-acting CX3CR1 agonist. METHODS:In this study, the chemokine domain of CX3CL1 was fused to the mouse Fc region to generate a long-acting soluble form of CX3CL1 suitable for chronic studies. CX3CL1-Fc or saline was injected twice a week (30 mg/kg) for 4 months into Ldlr knockout (KO) mice on an atherogenic western diet. RESULTS:CX3CL1-Fc-treated Ldlr KO mice showed decreased en face aortic lesion surface area and reduced aortic root lesion size with decreased necrotic core area. Flow cytometry analyses of CX3CL1-Fc-treated aortic wall cell digests revealed a decrease in M1-like polarized macrophages and T cells. Moreover, CX3CL1-Fc administration reduced diet-induced atherosclerosis after switching from an atherogenic to a normal chow diet. In vitro monocyte adhesion studies revealed that CX3CL1-Fc treatment caused fewer monocytes to adhere to a human umbilical vein endothelial cell monolayer. Furthermore, a dorsal window chamber model demonstrated that CX3CL1-Fc treatment decreased in vivo leukocyte adhesion and rolling in live capillaries after short-term ischemia-reperfusion. CONCLUSION:These results indicate that CX3CL1-Fc can inhibit monocyte/endothelial cell adhesion as well as reduce atherosclerosis.

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.

ObjectiveSleep disturbance is a known risk factor for depression, but it is not known whether sleep disturbance contributes to greater risk of depression in those infected with human immunodeficiency virus (HIV+) as compared to those uninfected with HIV (HIV-).MethodsUsing data from the Multicenter AIDS Cohort Study, a population-based prospective study of men who have sex with men (MSM), self-reported sleep disturbance (>2 weeks) and depressive symptoms (Clinical Epidemiologic Scale for Depression, CES-D) were assessed every 6 months over 12 years of follow-up. Adjusted mixed effects logistic regression analyses tested whether sleep disturbance predicted depression (CES-D ≥ 16) at the immediate subsequent visit, and so on over 12 years, in non-depressed HIV+(N = 1054; 9556 person-visits) and non-depressed HIV- (N = 1217; 12,680 person-visits). In HIV+ vs. HIV- MSM, linearly estimated average incidence of depression and normalized cumulative rate of depression over 12 years were compared.ResultsIn the HIV+ MSM, sleep disturbance was associated with a significant increase in depression 6 months later (OR = 1.6; 95% CI, 1.30, 1.96), which was significantly greater (P

BackgroundThe relationship between sleep disruption, independent of obstructive sleep apnea (OSA), and atrial fibrillation (AF) is unknown.ObjectiveThe purpose of this study was to determine whether poor sleep itself is a risk factor for AF.MethodsWe first performed an analysis of participants in the Health eHeart Study and validated those findings in the longitudinal Cardiovascular Health Study, including a subset of patients undergoing polysomnography. To determine whether the observed relationships readily translated to medical practice, we examined 2005-2009 data from the California Healthcare Cost and Utilization Project.ResultsAmong 4553 Health eHeart participants, the 526 with AF exhibited more frequent nighttime awakening (odd ratio [OR] 1.47; 95% confidence interval [CI] 1.14-1.89; P = .003). In 5703 Cardiovascular Health Study participants followed for a median 11.6 years, frequent nighttime awakening predicted a 33% greater risk of AF (hazard ratio [HR] 1.33; 95% CI 1.17-1.51; P