Preclinical data suggest that hypoxia stimulates fibroblast growth factor 23 (FGF23) transcription and cleavage in osteocytes, resulting in elevated circulating c-terminal (cFGF23) levels but normal intact FGF23 (iFGF23) levels. We conducted a case-control study within the Hispanic Community Health Study/Study of Latinos to investigate whether sleep disordered breathing, as a model of hypoxemia, is independently associated with elevated cFGF23 levels in the general population and with elevated cFGF23 and iFGF23 levels in patients with chronic kidney disease (CKD), in whom FGF23 cleavage may be impaired. Cases (n = 602) had severe sleep disordered breathing defined as an apnea/hypopnea index (AHI) of ≥30. Controls without severe sleep disordered breathing (n = 602) were matched for sex and CKD stage. The median AHI in the cases was 45.8 (IQR 35.5-62.5) compared to 2.6 (IQR 0.6-8.2) in the controls. Cases had higher cFGF23 levels than controls (66.2 RU/mL, IQR 52.8-98.4 vs. 61.2 RU/mL, IQR 49.5-80.1, p value <0.001). There were no differences in iFGF23 levels between cases and controls. In adjusted linear regression and multinomial regression analyses, body mass index attenuated the relationship between severe sleep disordered breathing and cFGF23 levels. No significant relationships were seen in analyses of severe sleep disordered breathing and iFGF23 levels or in analyses of iFGF23 and cFGF23 stratified by CKD status. Additional studies using other models of intermittent and chronic hypoxia are needed to confirm whether hypoxia stimulates FGF23 transcription in humans and to determine the impact on iFGF23 levels in CKD.

Hypoxic burden (HB) has emerged as a strong predictor of cardiovascular risk in obstructive sleep apnoea (OSA). We aimed to assess the potential of HB to predict the cardiovascular benefit of treating OSA with continuous positive airway pressure (CPAP).

Although obstructive sleep apnea (OSA) is known to have a strong familial basis, no genetic polymorphisms influencing apnea risk have been identified in cross-cohort analyses. We utilized the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe) to identify sleep apnea susceptibility loci. Using a panel of 46,449 polymorphisms from roughly 2,100 candidate genes on a customized Illumina iSelect chip, we tested for association with the apnea hypopnea index (AHI) as well as moderate to severe OSA (AHI≥15) in 3,551 participants of the Cleveland Family Study and two cohorts participating in the Sleep Heart Health Study.Among 647 African-Americans, rs11126184 in the pleckstrin (PLEK) gene was associated with OSA while rs7030789 in the lysophosphatidic acid receptor 1 (LPAR1) gene was associated with AHI using a chip-wide significance threshold of p-value<2×10(-6). Among 2,904 individuals of European ancestry, rs1409986 in the prostaglandin E2 receptor (PTGER3) gene was significantly associated with OSA. Consistency of effects between rs7030789 and rs1409986 in LPAR1 and PTGER3 and apnea phenotypes were observed in independent clinic-based cohorts.Novel genetic loci for apnea phenotypes were identified through the use of customized gene chips and meta-analyses of cohort data with replication in clinic-based samples. The identified SNPs all lie in genes associated with inflammation suggesting inflammation may play a role in OSA pathogenesis.

Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p < 5 × 10-8; 43 loci at p < 6 × 10-9). Replication is observed for PAX8, VRK2, and FBXL12/UBL5/PIN1 loci in the CHARGE study (n = 47,180; p < 6.3 × 10-4), and 55 signals show sign-concordant effects. The 78 loci further associate with accelerometer-derived sleep duration, daytime inactivity, sleep efficiency and number of sleep bouts in secondary analysis (n = 85,499). Loci are enriched for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission and plasticity, among others. Genetic correlation indicates shared links with anthropometric, cognitive, metabolic, and psychiatric traits and two-sample Mendelian randomization highlights a bidirectional causal link with schizophrenia. This work provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways.

To use wrist-actrigrphy to collect objective measures of sleep and to characterise actigraphy-measured sleep patterns among children with disabilities. We also assessed the extent to which, if at all, caregivers' education is associated with children's sleep disturbances.

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

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.

Local ancestry, defined as the genetic ancestry at a genomic location of an admixed individual, is widely used as a genetic marker in genetic association and evolutionary genetics studies. Many methods have been developed to infer the local ancestries in a set of unrelated individuals, a few of them have been extended to small nuclear families, but none can be applied to large (e.g. three-generation) pedigrees. In this study, we developed a method, FamANC, that can improve the accuracy of local ancestry inference in large pedigrees by: (1) using an existing algorithm to infer local ancestries for all individuals in a family, assuming (contrary to fact) they are unrelated, and (2) improving its accuracy by correcting inference errors using pedigree structure. Applied on African-American pedigrees from the Cleveland Family Study, FamANC was able to correct all identified Mendelian errors and most of double crossovers.

Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with substantial functional deficits. Here, we identify 42 loci for self-reported daytime sleepiness in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirm the aggregate effect of a genetic risk score of 42 SNPs on daytime sleepiness in independent Scandinavian cohorts and on other sleep disorders (restless legs syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). However, individual daytime sleepiness signals vary in their associations with objective short vs long sleep, and with markers of sleep continuity. The 42 sleepiness variants primarily cluster into two predominant composite biological subtypes - sleep propensity and sleep fragmentation. Shared genetic links are also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing.

Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference.

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

Daytime 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).

The human microbiome is linked to multiple metabolic disorders such as obesity and diabetes. Obstructive sleep apnoea (OSA) is a common sleep disorder with several metabolic risk factors. We investigated the associations between the gut microbiome composition and function, and measures of OSA severity in participants from a prospective community-based cohort study: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

Our sleep timing preference, or chronotype, is a manifestation of our internal biological clock. Variation in chronotype has been linked to sleep disorders, cognitive and physical performance, and chronic disease. Here we perform a genome-wide association study of self-reported chronotype within the UK Biobank cohort (n=100,420). We identify 12 new genetic loci that implicate known components of the circadian clock machinery and point to previously unstudied genetic variants and candidate genes that might modulate core circadian rhythms or light-sensing pathways. Pathway analyses highlight central nervous and ocular systems and fear-response-related processes. Genetic correlation analysis suggests chronotype shares underlying genetic pathways with schizophrenia, educational attainment and possibly BMI. Further, Mendelian randomization suggests that evening chronotype relates to higher educational attainment. These results not only expand our knowledge of the circadian system in humans but also expose the influence of circadian characteristics over human health and life-history variables such as educational attainment.

Recently, multiple studies have performed whole-exome or whole-genome sequencing to identify groups of rare variants associated with complex traits and diseases. They have primarily utilized case-control study designs that often require thousands of individuals to reach acceptable statistical power. Family-based studies can be more powerful because a rare variant can be enriched in an extended pedigree and segregate with the phenotype. Although many methods have been proposed for using family data to discover rare variants involved in a disease, a majority of them focus on a specific pedigree structure and are designed to analyze either binary or continuously measured outcomes. In this article, we propose RareIBD, a general and powerful approach to identifying rare variants involved in disease susceptibility. Our method can be applied to large extended families of arbitrary structure, including pedigrees with only affected individuals. The method accommodates both binary and quantitative traits. A series of simulation experiments suggest that RareIBD is a powerful test that outperforms existing approaches. In addition, our method accounts for individuals in top generations, which are not usually genotyped in extended families. In contrast to available statistical tests, RareIBD generates accurate p values even when genetic data from these individuals are missing. We applied RareIBD, as well as other methods, to two extended family datasets generated by different genotyping technologies and representing different ethnicities. The analysis of real data confirmed that RareIBD is the only method that properly controls type I error.

Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population.

There has been sustained focus on the secondary prevention of coronary heart disease and heart failure; yet, apart from stroke prevention, the evidence base for the secondary prevention of atrial fibrillation (AF) recurrence, AF progression, and AF-related complications is modest. Although there are multiple observational studies, there are few large, robust, randomized trials providing definitive effective approaches for the secondary prevention of AF. Given the increasing incidence and prevalence of AF nationally and internationally, the AF field needs transformative research and a commitment to evidenced-based secondary prevention strategies. We report on a National Heart, Lung, and Blood Institute virtual workshop directed at identifying knowledge gaps and research opportunities in the secondary prevention of AF. Once AF has been detected, lifestyle changes and novel models of care delivery may contribute to the prevention of AF recurrence, AF progression, and AF-related complications. Although benefits seen in small subgroups, cohort studies, and selected randomized trials are impressive, the widespread effectiveness of AF secondary prevention strategies remains unknown, calling for development of scalable interventions suitable for diverse populations and for identification of subpopulations who may particularly benefit from intensive management. We identified critical research questions for 6 topics relevant to the secondary prevention of AF: (1) weight loss; (2) alcohol intake, smoking cessation, and diet; (3) cardiac rehabilitation; (4) approaches to sleep disorders; (5) integrated, team-based care; and (6) nonanticoagulant pharmacotherapy. Our goal is to stimulate innovative research that will accelerate the generation of the evidence to effectively pursue the secondary prevention of AF.

Background: Heart rate fragmentation (HRF), a new non-invasive metric quantifying cardiac neuroautonomic function, is associated with increasing age and cardiovascular disease. Since these are risk factors for cognitive decline and dementia, in the Multi-Ethnic Study of Atherosclerosis (MESA), we investigated whether disrupted cardiac neuroautonomic function, evidenced by increased HRF, would be associated with worse cognitive function assessed concurrently and at a later examination, and with greater cognitive decline. Methods: HRF was derived from the ECG channel of the polysomnographic recordings obtained in an ancillary study (n = 1,897) conducted in conjunction with MESA exam 5 (2010-2012). Cognitive function was assessed at exam 5 and 6.4 ± 0.5 years later at exam 6 (2016-2018) with tests of global cognitive performance (the Cognitive Abilities Screening Instrument, CASI), processing speed (Digit Symbol Coding, DSC) and working memory (Digit Span). Multivariable regression models were used to quantify the associations between HRF indices and cognitive scores. Results: The participants' mean age was 68 ± 9 years (54% female). Higher HRF at baseline was independently associated with lower cognitive scores at both exams 5 and 6. Specifically, in cross-sectional analyses, a one-standard deviation (SD) (13.7%) increase in HRF was associated with a 0.51 (95% CI: 0.17-0.86) points reduction in CASI and a 1.12 (0.34-1.90) points reduction in DSC. Quantitatively similar effects were obtained in longitudinal analyses. A one-SD increase in HRF was associated with a 0.44 (0.03-0.86) and a 1.04 (0.28-1.81) points reduction in CASI and DSC from exams 5 to 6, respectively. HRF added predictive value to the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE-APOE-ε4) risk score and to models adjusted for serum concentration of NT-proBNP, an analyte associated with cognitive impairment and dementia. Conclusion: Increased HRF assessed during sleep was independently associated with diminished cognitive performance (concurrent and future) and with greater cognitive decline. These findings lend support to the links between cardiac neuroautonomic regulation and cognitive function. As a non-invasive, repeatable and inexpensive probe, HRF technology may be useful in monitoring cognitive status, predicting risk of dementia and assessing therapeutic interventions.

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

Background: A major objective of precision medicine is the elucidation of non-invasive biomarkers of cardiovascular (CV) risk. Recently, we introduced a new dynamical marker of sino-atrial instability, termed heart rate fragmentation (HRF), which outperformed traditional and nonlinear heart rate variability metrics in separating ostensibly healthy subjects from patients with coronary artery disease. Accordingly, we hypothesized that HRF may be a dynamical biomarker of adverse cardiovascular events (CVEs). Methods: This study employed data from a cohort of participants in the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of sub-clinical heart disease. Interbeat interval time series (n = 1963), derived from the electrocardiographic channel of the polysomnogram study, were analyzed using the newly introduced metrics of fragmentation, as well as traditional heart rate variability (HRV) indices and the short-term detrended fluctuation analysis exponent. Cox regression analysis was used to assess the association between HR dynamic indices and CV outcomes in unadjusted and adjusted models. Results: The mean (± SD) follow-up time was 2.97 ± 0.63 years. In adjusted models, higher fragmentation was significantly associated with incident CVEs (number of events; hazard ratio [95% confidence interval]: n = 72, 1.43 [1.16-1.76]) and CV death (n = 21; 1.65 [1.15-2.36]). The traditional HRV and the fractal indices were not associated with CVEs or CV death. The most discriminatory fragmentation indices added significant value to Framingham and MESA CV risk indices in all analyses. Conclusion: Our findings show that HRF has promise as a non-invasive, automatable biomarker of CV risk. The basic mechanisms underlying fragmentation remain to be delineated. Its association with incident outcomes raises the possibility of connections to degenerative changes in the multisystem network controlling SAN function.