Sleep and circadian biomarkers of postoperative delirium (SLEEP-POD): protocol for a prospective and observational cohort study

INTRODUCTION

Surgical patients over 70 experience postoperative delirium (POD) complications in up to 50% of procedures. Sleep/circadian disruption has emerged as a potential risk factor for POD in epidemiological studies. This protocol presents a single-site, prospective observational study designed to examine the relationship between sleep/circadian regulation and POD and how this association could be moderated or mediated by Alzheimer's disease (AD) pathology and genetic risk for AD.

METHODS AND ANALYSIS

Study staff members will screen for eligible patients (age ≥70) seeking joint replacement or spinal surgery at Massachusetts General Hospital (MGH). At the inclusion visit, patients will be asked a series of questionnaires related to sleep and cognition, conduct a four-lead ECG recording and be fitted for an actigraphy watch to wear for 7 days before surgery. Blood samples will be collected preoperatively and postoperatively and will be used to gather information about AD variant genes (APOE-ε4) and AD-related pathology (total and phosphorylated tau). Confusion Assessment Method-Scale and Montreal Cognitive Assessment will be completed twice daily for 3 days after surgery. Seven-day actigraphy assessments and Patient-Reported Outcomes Measurement Information System questionnaires will be performed 1, 3 and 12 months after surgery. Relevant patient clinical data will be monitored and recorded throughout the study.

ETHICS AND DISSEMINATION

This study is approved by the IRB at MGH, Boston, and it is registered with the US National Institutes of Health on ClinicalTrials.gov (NCT06052397). Plans for dissemination include conference presentations at a variety of scientific institutions. Results from this study are intended to be published in peer-reviewed journals. Relevant updates will be made available on ClinicalTrials.gov.

TRIAL REGISTRATION NUMBER

NCT06052397.

Comparison between self-reported and actigraphy-derived sleep measures in patients receiving home parenteral nutrition: Secondary analysis of observational data

BACKGROUND

Patients receiving home parenteral nutrition (HPN) frequently report disrupted sleep. However, there are often inconsistencies between objectively measured and questionnaire-derived sleep measures. We compared sleep measures estimated from wrist actigraphy and self-report in adults receiving HPN.

METHODS

In this secondary analysis, we pooled data from two sleep-related studies enrolling adults receiving habitual HPN. We compared measures from 7-day averages of wrist actigraphy against comparable responses to a sleep questionnaire. Sleep measures included bedtime, wake time, time in bed, total sleep time, and sleep onset latency (SOL). Spearman correlation coefficients, Bland-Altman plots, and linear regression models for each set of sleep measures provided estimates of agreement.

RESULTS

Participants (N = 35) had a mean age of 52 years, body mass index of 21.6 kg/m2 , and 77% identified as female. Correlation coefficients ranged from 0.35 to 0.90, were highest for wake time (r = 0.90) and bedtime (r = 0.74), and lowest for total sleep time (r = 0.35). Actigraphy overestimated self-reported bedtime, wake time, and total sleep time and underestimated self-reported time in bed and SOL. Regression coefficients indicated the highest calibration for bedtime and wake time and lower calibration for time in bed, total sleep time, and SOL.

CONCLUSION

We observed strong-to-moderate agreement between sleep measures derived from wrist actigraphy and self-report in adults receiving HPN. Weaker correlations for total sleep time and SOL may indicate low wrist actigraphy sensitivity. Low-quality sleep resulting from sleep disruptions may have also contributed to an underreporting of perceived sleep quantity and lower concordance.

Nightmares share genetic risk factors with sleep and psychiatric traits

Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e-06), depressive (rg = 0.562, p = 1.282e-07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e-07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual's liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.

Genetics of sleep medication purchases suggests causality from sleep problems to psychiatric traits

STUDY OBJECTIVES

Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems.

METHODS

We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation.

RESULTS

In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12).

CONCLUSIONS

These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

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, and together may provide a more complete picture of sleep health, while also 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 to behavioral, psychological, and cardiometabolic traits.

Preeclampsia Prediction Using Machine Learning and Polygenic Risk Scores From Clinical and Genetic Risk Factors in Early and Late Pregnancies

BACKGROUND

Preeclampsia, a pregnancy-specific condition associated with new-onset hypertension after 20-weeks gestation, is a leading cause of maternal and neonatal morbidity and mortality. Predictive tools to understand which individuals are most at risk are needed.

METHODS

We identified a cohort of N=1125 pregnant individuals who delivered between May 2015 and May 2022 at Mass General Brigham Hospitals with available electronic health record data and linked genetic data. Using clinical electronic health record data and systolic blood pressure polygenic risk scores derived from a large genome-wide association study, we developed machine learning (XGBoost) and logistic regression models to predict preeclampsia risk.

RESULTS

Pregnant individuals with a systolic blood pressure polygenic risk score in the top quartile had higher blood pressures throughout pregnancy compared with patients within the lowest quartile systolic blood pressure polygenic risk score. In the first trimester, the most predictive model was XGBoost, with an area under the curve of 0.74. In late pregnancy, with data obtained up to the delivery admission, the best-performing model was XGBoost using clinical variables, which achieved an area under the curve of 0.91. Adding the systolic blood pressure polygenic risk score to the models did not improve the performance significantly based on De Long test comparing the area under the curve of models with and without the polygenic score.

CONCLUSIONS

Integrating clinical factors into predictive models can inform personalized preeclampsia risk and achieve higher predictive power than the current practice. In the future, personalized tools can be implemented to identify high-risk patients for preventative therapies and timely intervention to improve adverse maternal and neonatal outcomes.

Glycemic and sleep effects of daytime compared with those of overnight infusions of home parenteral nutrition in adults with short bowel syndrome: A quasi-experimental pilot trial

BACKGROUND

Patients with short bowel syndrome (SBS) dependent on home parenteral nutrition (HPN) commonly cycle infusions overnight, likely contributing to circadian misalignment and sleep disruption.

METHODS

The objective of this quasi-experimental, single-arm, controlled, pilot trial was to examine the feasibility, safety, and efficacy of daytime infusions of HPN in adults with SBS without diabetes. Enrolled patients were fitted with a continuous glucose monitor and wrist actigraph and were instructed to cycle their infusions overnight for 1 wk, followed by daytime for another week. The 24-h average blood glucose, the time spent >140 mg/dL or <70 mg/dL, and sleep fragmentation were derived for each week and compared using Wilcoxon signed-rank test. Patient-reported quality-of-life outcomes were also compared between the weeks.

RESULTS

Twenty patients (mean age, 51.7 y; 75% female; mean body mass index, 21.5 kg/m2) completed the trial. Overnight infusions started at 21:00 and daytime infusions at 09:00. No serious adverse events were noted. There were no differences in 24-h glycemia (daytime-median: 93.00 mg/dL; 95% CI: 87.7-99.9 mg/dL, compared with overnight-median: 91.1 mg/dL; 95% CI: 89.6-99.0 mg/dL; P = 0.922). During the day hours (09:00-21:00), the mean glucose concentrations were 13.5 (5.7-22.0) mg/dL higher, and the time spent <70 mg/dL was 15.0 (-170.0, 22.5) min lower with daytime than with overnight HPN. Conversely, during the night hours (21:00-09:00), the glucose concentrations were 16.6 (-23.1, -2.2) mg/dL lower with daytime than with overnight HPN. There were no differences in actigraphy-derived measures of sleep and activity rhythms; however, sleep timing was later, and light at night exposure was lower with daytime than with overnight HPN. Patients reported less sleep disruptions due to urination and fewer episodes of uncontrollable diarrhea or ostomy output with daytime HPN.

CONCLUSIONS

Daytime HPN was feasible and safe in adults with SBS and, compared with overnight HPN, improved subjective sleep without increasing 24-h glucose concentrations. This trial was registered at clinicaltrials.gov as NCT04743960 (https://classic.

CLINICALTRIALS

gov/ct2/show/NCT04743960).

DeepFocus: fast focus and astigmatism correction for electron microscopy

High-throughput 2D and 3D scanning electron microscopy, which relies on automation and dependable control algorithms, requires high image quality with minimal human intervention. Classical focus and astigmatism correction algorithms attempt to explicitly model image formation and subsequently aberration correction. Such models often require parameter adjustments by experts when deployed to new microscopes, challenging samples, or imaging conditions to prevent unstable convergence, making them hard to use in practice or unreliable. Here, we introduce DeepFocus, a purely data-driven method for aberration correction in scanning electron microscopy. DeepFocus works under very low signal-to-noise ratio conditions, reduces processing times by more than an order of magnitude compared to the state-of-the-art method, rapidly converges within a large aberration range, and is easily recalibrated to different microscopes or challenging samples.

Impact of polygenic score for BMI on weight loss effectiveness and genome-wide association analysis

BACKGROUND

While environmental factors play an important role in weight loss effectiveness, genetics may also influence its success. We examined whether a genome-wide polygenic score for BMI was associated with weight loss effectiveness and aimed to identify common genetic variants associated with weight loss.

METHODS

Participants in the ONTIME study (n = 1210) followed a uniform, multimodal behavioral weight-loss intervention. We first tested associations between a genome-wide polygenic score for higher BMI and weight loss effectiveness (total weight loss, rate of weight loss, and attrition). We then conducted a genome-wide association study (GWAS) for weight loss in the ONTIME study and performed the largest weight loss meta-analysis with earlier studies (n = 3056). Lastly, we ran exploratory GWAS in the ONTIME study for other weight loss outcomes and related factors.

RESULTS

We found that each standard deviation increment in the polygenic score was associated with a decrease in the rate of weight loss (Beta (95% CI) = -0.04 kg per week (-0.06, -0.01); P = 3.7 × 10-03) and with higher attrition after adjusting by treatment duration. No associations reached genome-wide significance in meta-analysis with previous GWAS studies for weight loss. However, associations in the ONTIME study showed effects consistent with published studies for rs545936 (MIR486/NKX6.3/ANK1), a previously noted weight loss locus. In the meta-analysis, each copy of the minor A allele was associated with 0.12 (0.03) kg/m2 higher BMI at week five of treatment (P = 3.9 × 10-06). In the ONTIME study, we also identified two genome-wide significant (P < 5×10-08) loci for the rate of weight loss near genes implicated in lipolysis, body weight, and metabolic regulation: rs146905606 near NFIP1/SPRY4/FGF1; and rs151313458 near LSAMP.

CONCLUSION

Our findings are expected to help in developing personalized weight loss approaches based on genetics.

CLINICAL TRIAL REGISTRATION

Obesity, Nutrigenetics, Timing, and Mediterranean (ONTIME; clinicaltrials.gov: NCT02829619) study.

Sleep regularity is a stronger predictor of mortality risk than sleep duration: A prospective cohort study

Abnormally short and long sleep are associated with premature mortality, and achieving optimal sleep duration has been the focus of sleep health guidelines. Emerging research demonstrates that sleep regularity, the day-to-day consistency of sleep-wake timing, can be a stronger predictor for some health outcomes than sleep duration. The role of sleep regularity in mortality, however, has not been investigated in a large cohort with objective data. We therefore aimed to compare how sleep regularity and duration predicted risk for all-cause and cause-specific mortality. We calculated Sleep Regularity Index (SRI) scores from > 10 million hours of accelerometer data in 60 977 UK Biobank participants (62.8 ± 7.8 years, 55.0% female, median[IQR] SRI: 81.0[73.8-86.3]). Mortality was reported up to 7.8 years after accelerometer recording in 1859 participants (4.84 deaths per 1000 person-years, mean (±SD) follow-up of 6.30 ± 0.83 years). Higher sleep regularity was associated with a 20%-48% lower risk of all-cause mortality (p < .001 to p = 0.004), a 16%-39% lower risk of cancer mortality (p < 0.001 to p = 0.017), and a 22%-57% lower risk of cardiometabolic mortality (p < 0.001 to p = 0.048), across the top four SRI quintiles compared to the least regular quintile. Results were adjusted for age, sex, ethnicity, and sociodemographic, lifestyle, and health factors. Sleep regularity was a stronger predictor of all-cause mortality than sleep duration, by comparing equivalent mortality models, and by comparing nested SRI-mortality models with and without sleep duration (p = 0.14-0.20). These findings indicate that sleep regularity is an important predictor of mortality risk and is a stronger predictor than sleep duration. Sleep regularity may be a simple, effective target for improving general health and survival.

The Role of Circadian Rhythms and Sleep in Anorexia Nervosa

Importance

Observational studies have associated anorexia nervosa with circadian rhythms and sleep traits. However, the direction of causality and the extent of confounding by psychosocial comorbidities in these associations are unknown.

Objectives

To investigate the association between anorexia nervosa and circadian and sleep traits through mendelian randomization and to test the associations between a polygenic risk score (PRS) for anorexia nervosa and sleep disorders in a clinical biobank.

Design, Setting, and Participants

This genetic association study used bidirectional 2-sample mendelian randomization with summary-level genetic associations between anorexia nervosa (from the Psychiatric Genomics Consortium) and chronotype and sleep traits (primarily from the UK Biobank). The inverse-variance weighted method, in addition to other sensitivity approaches, was used. From the clinical Mass General Brigham (MGB) Biobank (n = 47 082), a PRS for anorexia nervosa was calculated for each patient and associations were tested with prevalent sleep disorders derived from electronic health records. Patients were of European ancestry. All analyses were performed between February and August 2023.

Exposures

Genetic instruments for anorexia nervosa, chronotype, daytime napping, daytime sleepiness, insomnia, and sleep duration.

Main Outcomes and Measures

Chronotype, sleep traits, risk of anorexia nervosa, and sleep disorders derived from a clinical biobank.

Results

The anorexia nervosa genome-wide association study included 16 992 cases (87.7%-97.4% female) and 55 525 controls (49.6%-63.4% female). Genetic liability for anorexia nervosa was associated with a more morning chronotype (β = 0.039; 95% CI, 0.006-0.072), and conversely, genetic liability for morning chronotype was associated with increased risk of anorexia nervosa (β = 0.178; 95% CI, 0.042-0.315). Associations were robust in sensitivity and secondary analyses. Genetic liability for insomnia was associated with increased risk of anorexia nervosa (β = 0.369; 95% CI, 0.073-0.666); however, sensitivity analyses indicated bias due to horizontal pleiotropy. The MGB Biobank analysis included 47 082 participants with a mean (SD) age of 60.4 (17.0) years and 25 318 (53.8%) were female. A PRS for anorexia nervosa was associated with organic or persistent insomnia in the MGB Biobank (odds ratio, 1.10; 95% CI, 1.03-1.17). No associations were evident for anorexia nervosa with other sleep traits.

Conclusions and Relevance

The results of this study suggest that in contrast to other metabo-psychiatric diseases, anorexia nervosa is a morningness eating disorder and further corroborate findings implicating insomnia in anorexia nervosa. Future studies in diverse populations and with subtypes of anorexia nervosa are warranted.

Causal Association Between Subtypes of Excessive Daytime Sleepiness and Risk of Cardiovascular Diseases

BACKGROUND

Excessive daytime sleepiness (EDS), experienced in 10% to 20% of the population, has been associated with cardiovascular disease and death. However, the condition is heterogeneous and is prevalent in individuals having short and long sleep duration. We sought to clarify the relationship between sleep duration subtypes of EDS with cardiovascular outcomes, accounting for these subtypes.

METHODS AND RESULTS

We defined 3 sleep duration subtypes of excessive daytime sleepiness: normal (6-9 hours), short (<6 hours), and long (>9 hours), and compared these with a nonsleepy, normal-sleep-duration reference group. We analyzed their associations with incident myocardial infarction (MI) and stroke using medical records of 355 901 UK Biobank participants and performed 2-sample Mendelian randomization for each outcome. Compared with healthy sleep, long-sleep EDS was associated with an 83% increased rate of MI (hazard ratio, 1.83 [95% CI, 1.21-2.77]) during 8.2-year median follow-up, adjusting for multiple health and sociodemographic factors. Mendelian randomization analysis provided supporting evidence of a causal role for a genetic long-sleep EDS subtype in MI (inverse-variance weighted β=1.995, P=0.001). In contrast, we did not find evidence that other subtypes of EDS were associated with incident MI or any associations with stroke (P>0.05).

CONCLUSIONS

Our study suggests the previous evidence linking EDS with increased cardiovascular disease risk may be primarily driven by the effect of its long-sleep subtype on higher risk of MI. Underlying mechanisms remain to be investigated but may involve sleep irregularity and circadian disruption, suggesting a need for novel interventions in this population.

Comparison of the diagnostic yield of transbronchial lung biopsies by forceps and cryoprobe in diffuse parenchymal lung disease

Background

Transbronchial lung cryobiopsy (TBLC) in the diagnosis of diffuse parenchymal lung disease (DPLD) has shown a promising yield in recent times, with low post-procedural mortality and morbidity.

Objectives

To compare the yield of TBLC and conventional transbronchial forceps lung biopsy (TBLB).

Methods

A prospective study was carried out in patients with DPLD over a period of 1 year in a tertiary respiratory care institute in New Delhi, India. All 87 patients enrolled underwent both TBLB and TBLC. The procedures were performed in the bronchoscopy suite under conscious sedation and local anaesthesia, with an attempt to take a minimum of three biopsy specimens by conventional TBLB followed by TBLC. A 1.9 mm cryoprobe with a freezing time of 4 - 5 seconds was used. An Arndt endobronchial blocker was used to control bleeding along with locally administered medications.

Results

TBLB and TBLC led to a definitive diagnosis in 27 (31.0%) and 69 (79.3%) cases, respectively. The commonest diagnoses were hypersensitivity pneumonitis, sarcoidosis and pulmonary tuberculosis. TBLC led to additional diagnoses in 42 cases (48.3%). Pneumothorax was observed in 12 cases (13.8%), and moderate bleeding occurred in 63 (72.4%). There were no procedure-related deaths.

Conclusion

TBLC had a better diagnostic yield than conventional TBLB in DPLD. It has the potential to become a safe day-care procedure in a resource-limited setting, if certain precautions are taken.

Study synopsis

What the study adds. Compared with transbronchial forceps lung biopsy, transbronchial lung cryobiopsy (TBLC) led to additional diagnoses in 42 (48.3%) of 87 patients with clinicoradiological features of diffuse parenchymal lung disease. Pneumothorax was observed in 12 cases (13.8%) and moderate bleeding in 63 (72.4%). TBLC without rigid bronchoscopy or advanced airway devices under conscious sedation had a good diagnostic yield with an acceptable adverse events profile.Implications of the findings. TBLC under conscious sedation is not resource intensive and can be carried out in settings with limited resources.

Multi-ancestry genome-wide analysis identifies shared genetic effects and common genetic variants for self-reported sleep duration

Both short (≤6 h per night) and long sleep duration (≥9 h per night) are associated with increased risk of chronic diseases. Despite evidence linking habitual sleep duration and risk of disease, the genetic determinants of sleep duration in the general population are poorly understood, especially outside of European (EUR) populations. Here, we report that a polygenic score of 78 European ancestry sleep duration single-nucleotide polymorphisms (SNPs) is associated with sleep duration in an African (n = 7288; P = 0.003), an East Asian (n = 13 618; P = 6 × 10-4) and a South Asian (n = 7485; P = 0.025) genetic ancestry cohort, but not in a Hispanic/Latino cohort (n = 8726; P = 0.71). Furthermore, in a pan-ancestry (N = 483 235) meta-analysis of genome-wide association studies (GWAS) for habitual sleep duration, 73 loci are associated with genome-wide statistical significance. Follow-up of five loci (near HACD2, COG5, PRR12, SH3RF1 and KCNQ5) identified expression-quantitative trait loci for PRR12 and COG5 in brain tissues and pleiotropic associations with cardiovascular and neuropsychiatric traits. Overall, our results suggest that the genetic basis of sleep duration is at least partially shared across diverse ancestry groups.

Evaluating the association between genetically proxied ACE inhibition and dementias

INTRODUCTION

Angiotensin-converting enzyme (ACE) has been implicated in the metabolism of amyloid beta; however, the causal effect of ACE inhibition on risk of Alzheimer's disease (AD) dementia and other common dementias is largely unknown.

METHODS

We examined the causal association of genetically proxied ACE inhibition with four types of dementias using a two-sample Mendelian randomization (MR) approach.

RESULTS

Genetically proxied ACE inhibition was associated with increased risk of AD dementia (odds ratio per one standard deviation reduction in serum ACE [95% confidence interval]; 1.07 [1.04-1.10], P = 5 × 10-07 ) and frontotemporal dementia (1.16 [1.04-1.29], P = 0.01) but not with Lewy body dementia or vascular dementia (P > 0.05). These findings were independently replicated and remained consistent in sensitivity analyses.

DISCUSSION

This comprehensive MR study provided genetic evidence for an association between ACE inhibition and the risk for AD and frontotemporal dementias. These results should encourage further studies of the neurocognitive effects of ACE inhibition.

HIGHLIGHTS

This study evaluated genetically proxied angiotensin-converting enzyme (ACE) inhibition association with dementias. The results suggest an association between ACE inhibition and Alzheimer's disease. The results suggest an association between ACE inhibition and frontotemporal dementia. Those associations can be interpreted as potentially causal.

CIRCUST: A novel methodology for temporal order reconstruction of molecular rhythms; validation and application towards a daily rhythm gene expression atlas in humans

The circadian system drives near-24-h oscillations in behaviors and biological processes. The underlying core molecular clock regulates the expression of other genes, and it has been shown that the expression of more than 50 percent of genes in mammals displays 24-h rhythmic patterns, with the specific genes that cycle varying from one tissue to another. Determining rhythmic gene expression patterns in human tissues sampled as single timepoints has several challenges, including the reconstruction of temporal order of highly noisy data. Previous methodologies have attempted to address these challenges in one or a small number of tissues for which rhythmic gene evolutionary conservation is assumed to be preserved. Here we introduce CIRCUST, a novel CIRCular-robUST methodology for analyzing molecular rhythms, that relies on circular statistics, is robust against noise, and requires fewer assumptions than existing methodologies. Next, we validated the method against four controlled experiments in which sampling times were known, and finally, CIRCUST was applied to 34 tissues from the Genotype-Tissue Expression (GTEx) dataset with the aim towards building a comprehensive daily rhythm gene expression atlas in humans. The validation and application shown here indicate that CIRCUST provides a flexible framework to formulate and solve the issues related to the analysis of molecular rhythms in human tissues. CIRCUST methodology is publicly available at https://github.com/yolandalago/CIRCUST/.

A Novel Home-Based Study of Circadian Rhythms: Design, Rationale, and Methods for the Circadia Study

The Circadia Study (Circadia) is a novel "direct-to-participant" research study investigating the genetics of circadian rhythm disorders of advanced and delayed sleep phase and non-24 hour rhythms. The goals of the Circadia Study are twofold: (i) to create an easy-to-use toolkit for at-home circadian phase assessment for patients with circadian rhythm disorders through the use of novel in-home based surveys, tests, and collection kits; and (ii) create a richly phenotyped patient resource for genetic studies that will lead to new genetic loci associated with circadian rhythm disorders revealing possible loci of interest to target in the development of therapeutics for circadian rhythm disorders. Through these goals, we aim to broaden our understanding and elucidate the genetics of circadian rhythm disorders across a diverse patient population while increasing accessibility to circadian rhythm disorder diagnostics reducing health disparities through self-directed at-home dim light melatonin onset (DLMO) collections.

Associations between sleep health and grey matter volume in the UK Biobank cohort (n = 33 356)

As suggested by previous research, sleep health is assumed to be a key determinant of future morbidity and mortality. In line with this, recent studies have found that poor sleep is associated with impaired cognitive function. However, to date, little is known about brain structural abnormalities underlying this association. Although recent findings link sleep health deficits to specific alterations in grey matter volume, evidence remains inconsistent and reliant on small sample sizes. Addressing this problem, the current preregistered study investigated associations between sleep health and grey matter volume (139 imaging-derived phenotypes) in the UK Biobank cohort (33 356 participants). Drawing on a large sample size and consistent data acquisition, sleep duration, insomnia symptoms, daytime sleepiness, chronotype, sleep medication and sleep apnoea were examined. Our main analyses revealed that long sleep duration was systematically associated with larger grey matter volume of basal ganglia substructures. Insomnia symptoms, sleep medication and sleep apnoea were not associated with any of the 139 imaging-derived phenotypes. Short sleep duration, daytime sleepiness as well as late and early chronotype were associated with solitary imaging-derived phenotypes (no recognizable pattern, small effect sizes). To our knowledge, this is the largest study to test associations between sleep health and grey matter volume. Clinical implications of the association between long sleep duration and larger grey matter volume of basal ganglia are discussed. Insomnia symptoms as operationalized in the UK Biobank do not translate into grey matter volume findings.

The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections

BACKGROUND

Poor sleep is associated with an increased risk of infections and all-cause mortality but the causal direction between poor sleep and respiratory infections has remained unclear. We examined if poor sleep contributes as a causal risk factor to respiratory infections.

METHODS

We used data on insomnia, influenza and upper respiratory infections (URIs) from primary care and hospital records in the UK Biobank (N ≈ 231,000) and FinnGen (N ≈ 392,000). We computed logistic regression to assess association between poor sleep and infections, disease free survival hazard ratios, and performed Mendelian randomization analyses to assess causality.

FINDINGS

Utilizing 23 years of registry data and follow-up, we discovered that insomnia diagnosis associated with increased risk for infections (FinnGen influenza Cox's proportional hazard (CPH) HR = 4.34 [3.90, 4.83], P = 4.16 × 10-159, UK Biobank influenza CPH HR = 1.54 [1.37, 1.73], P = 2.49 × 10-13). Mendelian randomization indicated that insomnia causally predisposed to influenza (inverse-variance weighted (IVW) OR = 1.65, P = 5.86 × 10-7), URI (IVW OR = 1.94, P = 8.14 × 10-31), COVID-19 infection (IVW OR = 1.08, P = 0.037) and risk of hospitalization from COVID-19 (IVW OR = 1.47, P = 4.96 × 10-5).

INTERPRETATION

Our findings indicate that chronic poor sleep is a causal risk factor for contracting respiratory infections, and in addition contributes to the severity of respiratory infections. These findings highlight the role of sleep in maintaining sufficient immune response against pathogens.

FUNDING

Instrumentarium Science Foundation, Academy of Finland, Signe and Ane Gyllenberg Foundation, National Institutes of Health.

Sound and light levels in intensive care units in a large urban hospital in the United States

Intensive care units (ICUs) may disrupt sleep. Quantitative ICU studies of concurrent and continuous sound and light levels and timings remain sparse in part due to the lack of ICU equipment that monitors sound and light. Here, we describe sound and light levels across three adult ICUs in a large urban United States tertiary care hospital using a novel sensor. The novel sound and light sensor is composed of a Gravity Sound Level Meter for sound level measurements and an Adafruit TSL2561 digital luminosity sensor for light levels. Sound and light levels were continuously monitored in the room of 136 patients (mean age = 67.0 (8.7) years, 44.9% female) enrolled in the Investigation of Sleep in the Intensive Care Unit study (ICU-SLEEP; Clinicaltrials.gov: #NCT03355053), at the Massachusetts General Hospital. The hours of available sound and light data ranged from 24.0 to 72.2 hours. Average sound and light levels oscillated throughout the day and night. On average, the loudest hour was 17:00 and the quietest hour was 02:00. Average light levels were brightest at 09:00 and dimmest at 04:00. For all participants, average nightly sound levels exceeded the WHO guideline of < 35 decibels. Similarly, mean nightly light levels varied across participants (minimum: 1.00 lux, maximum: 577.05 lux). Sound and light events were more frequent between 08:00 and 20:00 than between 20:00 and 08:00 and were largely similar on weekdays and weekend days. Peaks in distinct alarm frequencies (Alarm 1) occurred at 01:00, 06:00, and at 20:00. Alarms at other frequencies (Alarm 2) were relatively consistent throughout the day and night, with a small peak at 20:00. In conclusion, we present a sound and light data collection method and results from a cohort of critically ill patients, demonstrating excess sound and light levels across multiple ICUs in a large tertiary care hospital in the United States. ClinicalTrials.gov, #NCT03355053. Registered 28 November 2017, https://clinicaltrials.gov/ct2/show/NCT03355053.

Polygenic prediction of preeclampsia and gestational hypertension

Preeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis. Altogether, we identified 18 independent loci associated with preeclampsia/eclampsia and/or gestational hypertension, 12 of which are new (for example, MTHFR-CLCN6, WNT3A, NPR3, PGR and RGL3), including two loci (PLCE1 and FURIN) identified in the multitrait analysis. Identified loci highlight the role of natriuretic peptide signaling, angiogenesis, renal glomerular function, trophoblast development and immune dysregulation. We derived genome-wide polygenic risk scores that predicted preeclampsia/eclampsia and gestational hypertension in external cohorts, independent of clinical risk factors, and reclassified eligibility for low-dose aspirin to prevent preeclampsia. Collectively, these findings provide mechanistic insights into the hypertensive disorders of pregnancy and have the potential to advance pregnancy risk stratification.

Genetic predisposition to macronutrient preference and workplace food choices

Prior research identified genetic variants influencing macronutrient preference, but whether genetic differences underlying nutrient preference affect long-term food choices is unknown. Here we examined the associations of polygenic scores for carbohydrate, fat, and protein preference with 12 months' workplace food purchases among 397 hospital employees from the ChooseWell 365 study. Food purchases were obtained retrospectively from the hospital's cafeteria sales data for the 12 months before participants were enrolled in the ChooseWell 365 study. Traffic light labels, visible to employees when making purchases, measured the quality of workplace purchases. During the 12-month study period, there were 215,692 cafeteria purchases. Each SD increase in the polygenic score for carbohydrate preference was associated with 2.3 additional purchases/month (95%CI, 0.2 to 4.3; p = 0.03) and a higher number of green-labeled purchases (β = 1.9, 95%CI, 0.5-3.3; p = 0.01). These associations were consistent in subgroup and sensitivity analyses accounting for additional sources of bias. There was no evidence of associations between fat and protein polygenic scores and cafeteria purchases. Findings from this study suggest that genetic differences in carbohydrate preference could influence long-term workplace food purchases and may inform follow-up experiments to enhance our understanding of the molecular mechanisms underlying food choice behavior.

AI-Driven sleep staging from actigraphy and heart rate

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold standard for sleep assessment and the clinical diagnosis of sleep disorders is polysomnography (PSG). However, PSG requires an overnight clinic visit and trained technicians to score the obtained multimodality data. Wrist-worn consumer devices, such as smartwatches, are a promising alternative to PSG because of their small form factor, continuous monitoring capability, and popularity. Unlike PSG, however, wearables-derived data are noisier and far less information-rich because of the fewer number of modalities and less accurate measurements due to their small form factor. Given these challenges, most consumer devices perform two-stage (i.e., sleep-wake) classification, which is inadequate for deep insights into a person's sleep health. The challenging multi-class (three, four, or five-class) staging of sleep using data from wrist-worn wearables remains unresolved. The difference in the data quality between consumer-grade wearables and lab-grade clinical equipment is the motivation behind this study. In this paper, we present an artificial intelligence (AI) technique termed sequence-to-sequence LSTM for automated mobile sleep staging (SLAMSS), which can perform three-class (wake, NREM, REM) and four-class (wake, light, deep, REM) sleep classification from activity (i.e., wrist-accelerometry-derived locomotion) and two coarse heart rate measures-both of which can be reliably obtained from a consumer-grade wrist-wearable device. Our method relies on raw time-series datasets and obviates the need for manual feature selection. We validated our model using actigraphy and coarse heart rate data from two independent study populations: the Multi-Ethnic Study of Atherosclerosis (MESA; N = 808) cohort and the Osteoporotic Fractures in Men (MrOS; N = 817) cohort. SLAMSS achieves an overall accuracy of 79%, weighted F1 score of 0.80, 77% sensitivity, and 89% specificity for three-class sleep staging and an overall accuracy of 70-72%, weighted F1 score of 0.72-0.73, 64-66% sensitivity, and 89-90% specificity for four-class sleep staging in the MESA cohort. It yielded an overall accuracy of 77%, weighted F1 score of 0.77, 74% sensitivity, and 88% specificity for three-class sleep staging and an overall accuracy of 68-69%, weighted F1 score of 0.68-0.69, 60-63% sensitivity, and 88-89% specificity for four-class sleep staging in the MrOS cohort. These results were achieved with feature-poor inputs with a low temporal resolution. In addition, we extended our three-class staging model to an unrelated Apple Watch dataset. Importantly, SLAMSS predicts the duration of each sleep stage with high accuracy. This is especially significant for four-class sleep staging, where deep sleep is severely underrepresented. We show that, by appropriately choosing the loss function to address the inherent class imbalance, our method can accurately estimate deep sleep time (SLAMSS/MESA: 0.61±0.69 hours, PSG/MESA ground truth: 0.60±0.60 hours; SLAMSS/MrOS: 0.53±0.66 hours, PSG/MrOS ground truth: 0.55±0.57 hours;). Deep sleep quality and quantity are vital metrics and early indicators for a number of diseases. Our method, which enables accurate deep sleep estimation from wearables-derived data, is therefore promising for a variety of clinical applications requiring long-term deep sleep monitoring.

Evening types as determined by subjective and objective measures are more emotional eaters

OBJECTIVE

This study aimed to determine the association between being an evening type (ET; defined subjectively by the Morning-Evening Questionnaire or objectively by the dim-light melatonin onset [DLMO] timing) and reporting emotional eating (EE) behaviors.

METHODS

Cross-sectional analyses were conducted in 3964 participants (four international cohorts: ONTIME and ONTIME-MT [both Spain], SHIFT [the US], and DICACEM [Mexico]), in which chronotype (Morning-Evening Questionnaire), EE behaviors (Emotional Eating Questionnaire), and dietary habits (dietary records or food-frequency questionnaire) were assessed. Among 162 participants (ONTIME-MT subsample), additional measures of DLMO (physiological gold standard of circadian phase) were available.

RESULTS

In three populations, ETs presented with a higher EE score than morning types (p < 0.02); and they made up a higher proportion of emotional eaters (p < 0.01). ETs presented with higher scores on disinhibition/overeating as well as food craving factors and experienced these behaviors more frequently than morning types (p < 0.05). Furthermore, a meta-analysis showed that being an ET was associated with a higher EE score by 1.52 points of a total of 30 points (95% CI: 0.89-2.14). The timing of DLMO in the early, intermediate, and late objective chronotypes occurred at 21:02 h, 22:12 h, and 23:37 h, with late types showing a higher EE score (p = 0.043).

CONCLUSIONS

Eveningness associated with EE in populations with different cultural, environmental, and genetic backgrounds. Individuals with late DLMO also showed more EE.

Heart rate response and recovery during exercise predict future delirium risk-A prospective cohort study in middle- to older-aged adults

BACKGROUND

Delirium is a neurocognitive disorder characterized by an abrupt decline in attention, awareness, and cognition after surgical/illness-induced stressors on the brain. There is now an increasing focus on how cardiovascular health interacts with neurocognitive disorders given their overlapping risk factors and links to subsequent dementia and mortality. One common indicator for cardiovascular health is the heart rate response/recovery (HRR) to exercise, but how this relates to future delirium is unknown.

METHODS

Electrocardiogram data were examined in 38,740 middle- to older-aged UK Biobank participants (mean age = 58.1 years, range: 40-72 years; 47.3% males) who completed a standardized submaximal exercise stress test (15-s baseline, 6-min exercise, and 1-min recovery) and required hospitalization during follow-up. An HRR index was derived as the product of the heart rate (HR) responses during exercise (peak/resting HRs) and recovery (peak/recovery HRs) and categorized into low/average/high groups as the bottom quartile/middle 2 quartiles/top quartile, respectively. Associations between 3 HRR groups and new-onset delirium were investigated using Cox proportional hazards models and a 2-year landmark analysis to minimize reverse causation. Sociodemographic factors, lifestyle factors/physical activity, cardiovascular risk, comorbidities, cognition, and maximal workload achieved were included as covariates.

RESULTS

During a median follow-up period of 11 years, 348 participants (9/1000) newly developed delirium. Compared with the high HRR group (16/1000), the risk for delirium was almost doubled in those with low HRR (hazard ratio = 1.90, 95% confidence interval (95%CI): 1.30-2.79, p = 0.001) and average HRR (hazard ratio = 1.54, 95%CI: 1.07-2.22, p = 0.020)). Low HRR was equivalent to being 6 years older, a current smoker, or ≥3 additional cardiovascular disease risks. Results were robust in sensitivity analysis, but the risk appeared larger in those with better cognition and when only postoperative delirium was considered (n = 147; hazard ratio = 2.66, 95%CI: 1.46-4.85, p = 0.001).

CONCLUSION

HRR during submaximal exercise is associated with future risk for delirium. Given that HRR is potentially modifiable, it may prove useful for neurological risk stratification alongside traditional cardiovascular risk factors.

Genome-wide gene by environment study of time spent in daylight and chronotype identifies emerging genetic architecture underlying light sensitivity

STUDY OBJECTIVES

Light is the primary stimulus for synchronizing the circadian clock in humans. There are very large interindividual differences in the sensitivity of the circadian clock to light. Little is currently known about the genetic basis for these interindividual differences.

METHODS

We performed a genome-wide gene-by-environment interaction study (GWIS) in 280 897 individuals from the UK Biobank cohort to identify genetic variants that moderate the effect of daytime light exposure on chronotype (individual time of day preference), acting as "light sensitivity" variants for the impact of daylight on the circadian system.

RESULTS

We identified a genome-wide significant SNP mapped to the ARL14EP gene (rs3847634; p < 5 × 10-8), where additional minor alleles were found to enhance the morningness effect of daytime light exposure (βGxE = -.03, SE = 0.005) and were associated with increased gene ARL14EP expression in brain and retinal tissues. Gene-property analysis showed light sensitivity loci were enriched for genes in the G protein-coupled glutamate receptor signaling pathway and genes expressed in Per2+ hypothalamic neurons. Linkage disequilibrium score regression identified Bonferroni significant genetic correlations of greater light sensitivity GWIS with later chronotype and shorter sleep duration. Greater light sensitivity was nominally genetically correlated with insomnia symptoms and risk for post-traumatic stress disorder (PTSD).

CONCLUSIONS

This study is the first to assess light as an important exposure in the genomics of chronotype and is a critical first step in uncovering the genetic architecture of human circadian light sensitivity and its links to sleep and mental health.

Chronotype Polygenic Score and the Timing and Quality of Workplace Cafeteria Purchases: Secondary Analysis of the ChooseWell 365 Randomized Controlled Trial

Background

Studies on the link between chronotype (i.e., propensity for morning or evening preference) and dietary intake have relied on self-reported data, estimating consumption, and chronotype from questionnaires.

Objectives

This study examined the associations between genetically proxied evening chronotype, objectively estimated workplace dietary choices, and the effectiveness of a behavioral intervention in hospital employees enrolled in the ChooseWell 365 study.

Methods

ChooseWell 365 was a randomized trial of a 12-mo automated, personalized intervention to prevent weight gain and improve diet. Cafeteria sales data were used to measure the timing and healthfulness of workplace food purchases of employees during the 12-mo-long baseline, intervention, and postintervention follow-up periods. A genome-wide polygenic score for evening chronotype was calculated for all participants and the population was divided into quartiles; the highest quartile indicated the most evening chronotype. Associations between polygenic score quartiles and workplace purchases at baseline, 12 mo, and 24 mo and changes from baseline at 12 and 24 mo were tested using adjusted multivariable linear regression models.

Results

At baseline, the highest chronotype quartile was associated with self-reported breakfast skipping. Over the 24-mo study, the highest quartile was associated with later timing of the first workplace purchase, but not with the healthfulness of purchases. There were no differences by the chronotype quartile in the effectiveness of the ChooseWell 365 intervention in improving employees' healthy food choices at work.

Conclusions

A chronotype polygenic score was associated with breakfast skipping and later workplace mealtimes of hospital employees, but not with the nutritional quality of objectively measured workplace food purchases. In addition, employees across the chronotype spectrum benefited from the workplace healthy eating intervention.This trial was registered at clinicaltrials.gov as NCT02660086 (https://clinicaltrials.gov/ct2/show/NCT02660086?cond=NCT02660086&draw=2&rank=1).

Circadian Rest-Activity Rhythms, Delirium Risk, and Progression to Dementia

OBJECTIVE

Delirium is a complex neurocognitive syndrome suspected to be bidirectionally linked to dementia. Circadian rhythm disturbances likely contribute to dementia pathogenesis, but whether these disturbances are related to delirium risk and progression to all-cause dementia is unknown.

METHODS

We analyzed continuous actigraphy data from 53,417 middle-aged or older UK Biobank participants during a median 5 years of follow-up. Four measures were used to characterize the 24-hour daily rest-activity rhythms (RARs): normalized amplitude, acrophase representing the peak activity time, interdaily stability, and intradaily variability (IV) for fragmentation of the rhythm. Cox proportional hazards models examined whether RARs predicted incident delirium (n = 551) and progression to dementia (n = 61).

RESULTS

Suppressed 24-hour amplitude, lowest (Q1) versus highest (Q4) quartile (hazard ratio [HR]_{Q1 vs Q4} = 1.94, 95% confidence interval [CI] = 1.53-2.46, p < 0.001), and more fragmented (higher IV: HR_{Q4 vs Q1} = 1.49, 95% CI = 1.18-1.88, p < 0.001) rhythms predicted higher delirium risk, after adjusting for age, sex, education, cognitive performance, sleep duration/disturbances, and comorbidities. In those free from dementia, each hour of delayed acrophase was associated with delirium risk (HR = 1.13, 95% CI = 1.04-1.23, p = 0.003). Suppressed 24-hour amplitude was associated with increased risk of progression from delirium to new onset dementia (HR = 1.31, 95% CI = 1.03-1.67, p = 0.03 for each 1-standard deviation decrease).

INTERPRETATION

Twenty-four-hour daily RAR suppression, fragmentation, and potentially delayed acrophase were associated with delirium risk. Subsequent progression to dementia was more likely in delirium cases with suppressed rhythms. The presence of RAR disturbances before delirium and prior to progression to dementia suggests that these disturbances may predict higher risk and be involved in early disease pathogenesis. ANN NEUROL 2023.

Prediction of Preeclampsia from Clinical and Genetic Risk Factors in Early and Late Pregnancy Using Machine Learning and Polygenic Risk Scores

Background

Preeclampsia, a pregnancy-specific condition associated with new-onset hypertension after 20 weeks gestation, is a leading cause of maternal and neonatal morbidity and mortality. Predictive tools to understand which individuals are most at risk are needed.

Methods

We identified a cohort of N=1,125 pregnant individuals who delivered between 05/2015-05/2022 at Mass General Brigham hospitals with available electronic health record (EHR) data and linked genetic data. Using clinical EHR data and systolic blood pressure polygenic risk scores (SBP PRS) derived from a large genome-wide association study, we developed machine learning (xgboost) and linear regression models to predict preeclampsia risk.

Results

Pregnant individuals with an SBP PRS in the top quartile had higher blood pressures throughout pregnancy compared to patients within the lowest quartile SBP PRS. In the first trimester, the most predictive model was xgboost, with an area under the curve (AUC) of 0.73. Adding the SBP PRS to the models improved the performance only of the linear regression model from AUC 0.70 to 0.71; the predictive power of other models remained unchanged. In late pregnancy, with data obtained up to the delivery admission, the best performing model was xgboost using clinical variables, which achieved an AUC of 0.91.

Conclusions

Integrating clinical and genetic factors into predictive models can inform personalized preeclampsia risk and achieve higher predictive power than the current practice. In the future, personalized tools can be implemented in clinical practice to identify high-risk patients for preventative therapies and timely intervention to improve adverse maternal and neonatal outcomes.

[Pharmacological importance of novel spiro derivatives against human pathogenic fungi]

Human mycoses have become a threat to health world-wide. Unfortunately there are only a limited number of antimycotic drugs in use. In the present study, antifungal activity of earlier synthesized spiro-1,4-dihydropyridines (1,4-DHPs) was investigated. The antifungal activity of spiro-1,4-DHPs compounds were screened against Aspergillus flavus, A. fumigatus, and Candida albicans by using Disc Diffusion and Modified Microdilution method. Among six spiro-1,4-DHPs compounds tested all of them showed stronger antifungal activity possibly through inhibiting the synthesis of chitin in cell wall against A. flavus, A. fumigatus, and C. albicans as compared to fluconazole, a standard antifungal drug. The combination of compounds showed that the synthesized compounds had synergistic, additive effects as compared to currently used drugs as an antifungal agent. These results indicated that these designed compounds were potential chitin synthase inhibitors and had excellent antimycotic activity for the treatment of fungal infections.

Genetics of circadian rhythms and sleep in human health and disease

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

Infusion timing and sleep habits of adults receiving home parenteral and enteral nutrition: A patient-oriented survey study

BACKGROUND

The emerging field of chrononutrition investigates the effects of the timing of nutritional intake on human physiology and disease pathology. It remains largely unknown when patients receiving home nutrition support routinely administer home parenteral nutrition (HPN) and/or home enteral nutrition (HEN).

METHODS

The present descriptive study included data collected from a patient-oriented survey designed to assess the timing of infusions and sleep habits of patients receiving HPN and HEN in the United States.

RESULTS

A total of 100 patients were included. Patients had a mean age of 44.1 years and 81% were female. Among 73 patients supported with HPN and 27 patients supported with HEN, 86% and 44% reported overnight infusions, respectively. The median start and end times of overnight infusions were 2100 (interquartile range [IQR] = 1900-2200) and 0800 (IQR = 0700-1000), respectively, for HPN and 2000 (IQR = 1845-2137) and 0845 (IQR = 0723-1000), respectively, for HEN. Overnight infusions started 2.0 h (IQR = 1.1-3.0) and 2.0 h (IQR = 0.6-3.3) before bedtime for HPN and HEN, respectively, and stopped 12.9 min (IQR = -21.3 to 29.1) and 30.0 min (IQR = -17.1 to 79.3) after wake time for HPN and HEN, respectively. Sleep disruption because of nutrition support or urination was most common among patients receiving infusions overnight compared with those receiving infusions continuously or during the daytime.

CONCLUSIONS

Our survey study focusing on a novel and medically relevant dimension of nutrition found that most HPN-dependent and HEN-dependent patients receive infusions overnight while asleep. Our findings suggest that overnight infusions coinciding with sleep may result in sleep and circadian disruption.

Faculty-or senior resident-led SNAPPS for postgraduate teaching in pediatrics

This was an educational intervention on postgraduates using SNAPPS (Summarize narrow, analyze, probe, plan, self-directed learning) showing comparable median (interquartile range) satisfaction scores with faculty or senior residents as 4 (3,5) and 4 (4, 4.25); respectively, P = 0.79. Further training of senior residents in medical education will enable them to participate efficiently and actively in postgraduate teaching.

Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea

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 < 10-3). Follow-up analysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (P = 0.024) and higher minimum overnight oxygen saturation (P = 0.007). Conclusions: Rare variants in CAV1, a membrane-scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.

Digital Pathology, A Cognitively Efficient Teaching Strategy: Current Application and a Glimpse into Future

Introduction/Objective

If pathology education is to be efficacious, it must embrace the ramifications of cognitive load of the learners, to optimize the capacity of the working memory. When undergraduate students commence their learning of pathology, they encounter a heap of new data and classifications. Simplifying these intricate systems into assimilable subschemas and items is key for effective transfer of knowledge. The minimization of the profundity of intrinsic cognitive load is essential, considering that its impact on pathology beginners is often left unaccounted, both in active learning as well as in traditional methods of instruction. In today’s digital generation, digital pathology plays a key role by intertwining disease morphology with clinical presentation and fortifying its pathophysiologic basis. We designed a teaching methodology utilizing digital pathology to evaluate its effect on cognitive load.

Methods/Case Report

Active learning was implemented online using digital pathology, molecular pathology, and laboratory data in case-based setting with question-answer sessions. In small groups, students were encouraged to analyze digital pathology slides with the help of annotations and identify areas of histopathological significance. They utilized this information further to make an accurate diagnosis and answer corresponding questions, with access to answers available later, complemented with algorithms and concept maps. A 14-item structured questionnaire was delivered afterwards to evaluate the efficacy and popularity of the exercise.

Results (if a Case Study enter NA)

End-of-term examination results showed that learners developed higher-order comprehension skills along with a greater potential in interpreting histopathological data towards solving case studies. Feedback revealed a higher degree of overall satisfaction and increased ability to retain information.

Conclusion

Digital transformation of pathology education provides the kind of framework where learning happens naturally - developing in small boosts of progress until expertise is achieved, and students appreciate the value of the ‘learned thing’ along with the real utility of that knowledge. The innovative approach utilizing digitization and integration offers the opportunity of decrement in intrinsic cognitive load by invoking students to build better, reliable, long-lasting, supportable and inclusive schemata while correlating the relevant incoming information with previously stabilized knowledge and consolidating the entirety of understanding.

Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis

Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Pathway-Specific Polygenic Risk Scores Identify Obstructive Sleep Apnea-Related Pathways Differentially Moderating Genetic Susceptibility to Coronary Artery Disease

BACKGROUND

Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia, may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (eg, inflammatory) and protective (eg, increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner.

METHODS

We selected a cross-sectional sample of 471 877 participants from the UK Biobank, with 4974 ascertained to have OSA, 25 988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics), annotated to specific genes and pathways using functional genomics databases. Based on prior evidence of involvement with intermittent hypoxia and CAD, we tested pathway-specific polygenic risk scores for the HIF1 (hypoxia-inducible factor 1), VEGF (vascular endothelial growth factor), NFκB (nuclear factor kappa-light-chain-enhancer of activated B cells) and TNF (tumor necrosis factor) signaling pathways.

RESULTS

In a multivariable-adjusted logistic generalized additive model, elevated pathway-specific polygenic risk scores for the Kyoto Encyclopedia of Genes and Genomes VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, P=6×10-4). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA.

CONCLUSIONS

We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. This invites further study of how OSA interacts with genetic risk at the molecular level and suggests eventual personalization of OSA treatment to reduce CAD risk according to individual pathway-specific genetic risk profiles.

The impact of Mendelian sleep and circadian genetic variants in a population setting

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.

Sleep patterns of patients receiving home parenteral nutrition: A home-based observational study

BACKGROUND

Patients supported with home parenteral nutrition (HPN) often report poor sleep; however, limited research has been conducted to objectively measure sleep patterns of HPN-dependent patients.

METHODS

We aimed to characterize the sleep patterns of patients receiving HPN through 7-day actigraphy in a home-based observational study. Sleep measures of clinical importance were derived from actigraphy, including sleep duration, sleep efficiency, sleep onset latency, and wake after sleep onset. Participants also completed validated sleep surveys.

RESULTS

Twenty participants completed all study procedures (mean [SD]: age = 51.6 [13.9] years, body mass index = 21.4  [4.6], and 80% female). The population median (IQR) for sleep duration, sleep efficiency, sleep onset latency, and wake after sleep onset was 6.9 (1.1) h, 83.3% (7.8%), 11.8 (7.1) min, and 57.2 (39.9) min, respectively, and 55%, 60%, 35%, and 100% of participants did not meet the recommendations for these measures from the National Sleep Foundation. Sixty-five percent of participants reported napping at least once during the 7-day period. Based on the Insomnia Severity Index, 70% of participants were classified as having subthreshold or more severe insomnia. Based on the Pittsburgh Sleep Quality Index, 85% were classified as having significant sleep disturbance.

CONCLUSION

Most HPN-dependent patients likely have disrupted sleep largely driven by difficulty maintaining sleep. The extent to which HPN contributed to poor sleep cannot be elucidated from this observational study. Addressing known factors that contribute to sleep disruption and considering sleep interventions may improve the overall quality of life of patients receiving HPN.

Updated variant curation expert panel criteria and pathogenicity classifications for 251 variants for RYR1-related malignant hyperthermia susceptibility

The ClinGen malignant hyperthermia susceptibility (MHS) variant curation expert panel specified the American College of Medical Genetics and Genomics/Association of Molecular Pathologists (ACMG/AMP) criteria for RYR1-related MHS and a pilot analysis of 84 variants was published. We have now classified an additional 251 variants for RYR1-related MHS according to current ClinGen standards and updated the criteria where necessary. Criterion PS4 was modified such that individuals with multiple RYR1 variants classified as pathogenic (P), likely pathogenic (LP), or variant of uncertain significance (VUS) were not considered as providing evidence for pathogenicity. Criteria PS1 and PM5 were revised to consider LP variants at the same amino-acid residue as providing evidence for pathogenicity at reduced strength. Finally, PM1 was revised such that if PS1 or PM5 are used PM1, if applicable, should be downgraded to supporting. Of the 251 RYR1 variants, 42 were classified as P/LP, 16 as B/LB, and 193 as VUS. The primary driver of 175 VUS classifications was insufficient evidence supporting pathogenicity, rather than evidence against pathogenicity. Functional data supporting PS3/BS3 was identified for only 13 variants. Based on the posterior probabilities of pathogenicity and variant frequencies in gnomAD, we estimated the prevalence of individuals with RYR1-related MHS pathogenic variants to be between 1/300 and 1/1075, considerably higher than current estimates. We have updated ACMG/AMP criteria for RYR1-related MHS and classified 251 variants. We suggest that prioritization of functional studies is needed to resolve the large number of VUS classifications and allow for appropriate risk assessment. RYR1-related MHS pathogenic variants are likely to be more common than currently appreciated.

Development of a patient decision aid for discharge planning of hospitalized patients with stroke

Background

Patient involvement in discharge planning of patients with stroke can be accomplished by providing personalized outcome information and promoting shared decision-making. The aim of this study was to develop a patient decision aid (PtDA) for discharge planning of hospitalized patients with stroke.

Methods

A convergent mixed methods design was used, starting with needs assessments among patients with stroke and health care professionals (HCPs). Results of these assessments were used to develop the PtDA with integrated outcome information in several co-creation sessions. Subsequently, acceptability and usability were tested to optimize the PtDA. Development was guided by the International Patient Decision Aids Standards (IPDAS) criteria.

Results

In total, 74 patients and 111 HCPs participated in this study. A three-component PtDA was developed, consisting of:

1) a printed consultation sheet to introduce the options for discharge destinations, containing information that can be specified for each individual patient;

2) an online information and deliberation tool to support patient education and clarification of patient values, containing an integrated “patients-like-me” model with outcome information about discharge destinations;

3) a summary sheet to support actual decision-making during consultation, containing the patient’s values and preferences concerning discharge planning.

In the acceptability test, all qualifying and certifying IPDAS criteria were fulfilled. The usability test showed that patients and HCPs highly appreciated the PtDA with integrated outcome information.

Conclusions

The developed PtDA was found acceptable and usable by patients and HCPs and is currently under investigation in a clinical trial to determine its effectiveness.

0285 Excessive daytime sleepiness with long sleep duration increases myocardial infarction risk

Introduction

Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with cardiovascular diseases (CVD) and mortality. However, EDS is heterogeneous, associated with both short and long sleep duration. It is unclear whether each subtype is related to CVD.

Methods

To understand the association of EDS subtypes (stratified by sleep duration) with incident myocardial infarction (MI), we perform multivariable Cox proportional hazards regression on MI using longitudinal medical record data of 471,991 individuals free of CVD at baseline from the UK Biobank. Baseline EDS and sleep duration were assessed by self-reported questionnaires.

Results

After adjusting for multiple social-demographic and behavioral factors, EDS with long sleep (³9 hours) was associated with a 91% increased incidence of MI (HR=1.91, 95% CI 1.34-2.71) compared to healthy sleep pattern (sleeping 6-9 hours without sleepiness), while EDS with normal (6-9 hours) or short sleep (≤6 hours) was not associated with incident MI. Long sleep without sleepiness was associated with a 39% increase in incident MI (HR=1.39, 95% CI 1.14-1.71). The association of EDS with long sleep was not explained by chronotype, insomnia, sleep apnea, depression, hypertension, or type 2 diabetes, but was confounded with self-reported overall health conditions (HR=1.46, 95% CI 1.02-2.08 after adjustment).

Conclusion

Our study suggests the previous association evidence of EDS increasing risk of MI may be primarily driven by its long sleep subtype (high “sleep propensity”), but the underlying mechanisms are unclear. Future work is needed to understand whether there are targetable interventions for this novel sleep phenotype that may improve cardiovascular health.

Support (If Any)

This research has been conducted using the UK Biobank Resource under Application Number 6818. Funding supports: NHLBI R35HL135818 and R01HL153814.

0698 Genetic susceptibility to elevated C-reactive protein and risk of obstructive sleep apnea in US men and women

Introduction

Obstructive sleep apnea (OSA) may trigger inflammation. However, growing evidence suggests a role for inflammation in predisposing OSA through increased upper airway size/collapsibility and altered ventilatory control. Inflammation also promotes sleep disturbance and excessive daytime sleepiness (EDS). Genetic analysis may provide further insights into the causal relationship between chronic inflammation and OSA incidence.

Methods

In 33,171 participants of European ancestry from the Nurses’ Health Study (NHS), NHS2 and the Health Professionals Follow-up Study, we quantified genetic predisposition to inflammation using a weighted polygenic risk score (PRS) based on 51 loci identified for C-reactive protein (CRP) in a recent genome-wide association meta-analysis. OSA was determined using self-reported diagnoses, which were demonstrated to reliably indicate moderate-to-severe OSA in these cohorts. EDS was defined based on self-reports of disrupted daily activities due to sleepiness ≥4 days/week. Multivariable logistic regression was used to estimate the odds ratio (OR) for OSA risk according to the number of risk alleles, adjusted for age, sex, BMI, genotyping platforms and 10 genetic principal components. Mendelian randomization using individual-level participant data was performed to evaluate the association between genetically determined CRP levels and OSA risk.

Results

A total of 3,163 participants (9.5%) had clinically diagnosed OSA (575 with EDS). While the CRP PRS (explained 5.0% variance in circulating levels) was not associated with OSA risk overall (OR per increment of 5 risk alleles: 1.00; 95% CI: 0.96, 1.04; p=0.96), a significant positive association was observed for OSA with concurrent EDS (Comparable OR: 1.13; 95% CI: 1.04, 1.23; p=0.003). In contrast, among participants without clinically diagnosed OSA, there was no association between the PRS and EDS (Comparable OR for EDS: 1.02; 95% CI: 0.98, 1.06; p=0.28). In Mendelian randomization, each doubling of genetically elevated CRP was associated with 44% higher odds of OSA with EDS (95% CI: 1.13, 1.82).

Conclusion

Chronic inflammation (characterized by elevated CRP levels) may be casually associated with risk of developing symptomatic OSA with EDS, but not OSA or EDS alone. To confirm our findings, future investigations are needed to evaluate the genetic associations with objective measures of OSA severity across diverse populations and elucidate mechanisms driven by specific inflammatory mediators.

Support (If Any)

NIH grants UM1CA186107, U01CA176726, U01CA167552, K01HL143034, R35HL135818

0224 The implication of the understudied druggable orphan GPCRs in sleep and cardiometabolic traits

Introduction

G-protein coupled receptors (GPCRs) are the largest class of membrane receptors. They are involved in various sleep and cardiometabolic disorders; however, 150 out of 900 GPCRs remain orphans (oGPCRs) with unknown endogenous ligands; thereby, limiting our understanding of their biological function. GPCRs are targeted by 36 % of FDA-approved drugs; thus, the understudied oGPCRs are druggable and have a high potential to impact human health once disease associations are made.

Methods

This study aimed to use a genomic approach from a large dataset to deorphanize oGPCRs whose genetic variations significantly impact sleep and cardiometabolic disorders. First, we used the UK Biobank study summary statistics to identify oGPCRs loci where multiple sleep and cardiometabolic traits colocalized at a false discovery rate &lt; 5%. Next, in the metabolic disease knowledge portal, we performed PheWAS analysis of the variants to identify new phenotypic traits in other datasets of European ancestry. We then used GTex to identify quantitative trait loci to highlight variants that affect gene expression.

Results

Our study identified variants in oGPCRs GPR61, GPR146, and GPRC5B that have a pleiotropic effect in sleep and cardiometabolic traits in the UK Biobank cohort. The variant rs12044778 is an intronic variant in GPR61 associated with ease of waking up and morningness chronotype. GPR146's intronic variant rs1997243 showed an association with cholesterol level (HDL and LDL) and blood pressure; additionally, rs1997243 significantly increased the expression of GPR146 in adipose tissues. Finally, the intronic variant rs11639988 is associated with a decrease in BMI, and that it significantly decreased GPRC5B gene expression in the nucleus accumbens and adipose tissues.

Conclusion

Overall, our study provides new insight into the functions of oGPCRs genetic variants in sleep and cardiometabolic processes.

Support (If Any)

5T32HL007609-35