Publications by Year: 2021

Rationale: Symptoms and morbidities associated with obstructive sleep apnea (OSA) vary across individuals and are not predicted by the apnea-hypopnea index (AHI). Respiratory event duration is a heritable trait associated with mortality that may further characterize OSA.Objectives: We evaluated how hypopnea and apnea durations in non-REM (NREM) sleep vary across demographic groups and quantified their associations with physiological traits (loop gain, arousal threshold, circulatory delay, and pharyngeal collapsibility).Methods: Data were analyzed from 1,546 participants from the Multi-Ethnic Study of Atherosclerosis with an AHI ≥5. Physiological traits were derived using a validated model fit to the polysomnographic airflow signal. Multiple linear regression models were used to evaluate associations of event duration with demographic and physiological factors.Measurements and Main Results: Participants had a mean age ± SD of 68.9 ± 9.2 years, mean NREM hypopnea duration of 21.73 ± 5.60, and mean NREM apnea duration of 23.87 ± 7.44 seconds. In adjusted analyses, shorter events were associated with younger age, female sex, higher body mass index (P < 0.01, all), and Black race (P < 0.05). Longer events were associated with Asian race (P < 0.01). Shorter event durations were associated with lower circulatory delay (2.53 ± 0.13 s, P < 0.01), lower arousal threshold (1.39 ± 0.15 s, P < 0.01), reduced collapsibility (-0.71 ± 0.16 s, P < 0.01), and higher loop gain (-0.27 ± 0.11 s, P < 0.05) per SD change. Adjustment for physiological traits attenuated age, sex, and obesity associations and eliminated racial differences in event duration.Conclusions: Average event duration varies across population groups and provides information on ventilatory features and airway collapsibility not captured by the AHI.

Rationale: Randomized controlled trials have been unable to detect a cardiovascular benefit of continuous positive airway pressure in unselected patients with obstructive sleep apnea (OSA). We hypothesize that deleterious cardiovascular outcomes are concentrated in a subgroup of patients with a heightened pulse-rate response to apneas and hypopneas (ΔHR). Methods: We measured the ΔHR in the MESA (Multi-Ethnic Study of Atherosclerosis) (N = 1,395) and the SHHS (Sleep Heart Health Study) (N = 4,575). MESA data were used to determine the functional form of the association between the ΔHR and subclinical cardiovascular biomarkers, whereas primary analyses tested the association of the ΔHR with nonfatal or fatal cardiovascular disease (CVD) and all-cause mortality in longitudinal data from the SHHS. Measurements and Main Results: In the MESA, U-shaped relationships were observed between subclinical CVD biomarkers (coronary artery calcium, NT-proBNP [N-terminal prohormone BNP], and Framingham risk score) and the ΔHR; notably, a high ΔHR (upper quartile) was associated with elevated biomarker scores compared with a midrange ΔHR (25th-75th centiles). In the SHHS, individuals with a high ΔHR compared with a midrange ΔHR were at increased risk of nonfatal or fatal CVD and all-cause mortality (nonfatal adjusted hazard ratio [95% confidence interval (CI)], 1.60 [1.28-2.00]; fatal adjusted hazard ratio [95% CI], 1.68 [1.22-2.30]; all-cause adjusted hazard ratio [95% CI], 1.29 [1.07-1.55]). The risk associated with a high ΔHR was particularly high in those with a substantial hypoxic burden (nonfatal, 1.93 [1.36-2.73]; fatal, 3.50 [2.15-5.71]; all-cause, 1.84 [1.40-2.40]) and was exclusively observed in nonsleepy individuals. Conclusions: Individuals with OSA who demonstrate an elevated ΔHR are at increased risk of cardiovascular morbidity and mortality. This study identifies a prognostic biomarker for OSA that appears useful for risk stratification and patient selection for future clinical trials.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

Rationale: Symptoms and morbidities associated with obstructive sleep apnea (OSA) vary across individuals and are not predicted by the apnea-hypopnea index (AHI). Respiratory event duration is a heritable trait associated with mortality that may further characterize OSA.Objectives: We evaluated how hypopnea and apnea durations in non-REM (NREM) sleep vary across demographic groups and quantified their associations with physiological traits (loop gain, arousal threshold, circulatory delay, and pharyngeal collapsibility).Methods: Data were analyzed from 1,546 participants from the Multi-Ethnic Study of Atherosclerosis with an AHI ≥5. Physiological traits were derived using a validated model fit to the polysomnographic airflow signal. Multiple linear regression models were used to evaluate associations of event duration with demographic and physiological factors.Measurements and Main Results: Participants had a mean age ± SD of 68.9 ± 9.2 years, mean NREM hypopnea duration of 21.73 ± 5.60, and mean NREM apnea duration of 23.87 ± 7.44 seconds. In adjusted analyses, shorter events were associated with younger age, female sex, higher body mass index (P < 0.01, all), and Black race (P < 0.05). Longer events were associated with Asian race (P < 0.01). Shorter event durations were associated with lower circulatory delay (2.53 ± 0.13 s, P < 0.01), lower arousal threshold (1.39 ± 0.15 s, P < 0.01), reduced collapsibility (-0.71 ± 0.16 s, P < 0.01), and higher loop gain (-0.27 ± 0.11 s, P < 0.05) per SD change. Adjustment for physiological traits attenuated age, sex, and obesity associations and eliminated racial differences in event duration.Conclusions: Average event duration varies across population groups and provides information on ventilatory features and airway collapsibility not captured by the AHI.

Rationale: Randomized controlled trials have been unable to detect a cardiovascular benefit of continuous positive airway pressure in unselected patients with obstructive sleep apnea (OSA). We hypothesize that deleterious cardiovascular outcomes are concentrated in a subgroup of patients with a heightened pulse-rate response to apneas and hypopneas (ΔHR). Methods: We measured the ΔHR in the MESA (Multi-Ethnic Study of Atherosclerosis) (N = 1,395) and the SHHS (Sleep Heart Health Study) (N = 4,575). MESA data were used to determine the functional form of the association between the ΔHR and subclinical cardiovascular biomarkers, whereas primary analyses tested the association of the ΔHR with nonfatal or fatal cardiovascular disease (CVD) and all-cause mortality in longitudinal data from the SHHS. Measurements and Main Results: In the MESA, U-shaped relationships were observed between subclinical CVD biomarkers (coronary artery calcium, NT-proBNP [N-terminal prohormone BNP], and Framingham risk score) and the ΔHR; notably, a high ΔHR (upper quartile) was associated with elevated biomarker scores compared with a midrange ΔHR (25th-75th centiles). In the SHHS, individuals with a high ΔHR compared with a midrange ΔHR were at increased risk of nonfatal or fatal CVD and all-cause mortality (nonfatal adjusted hazard ratio [95% confidence interval (CI)], 1.60 [1.28-2.00]; fatal adjusted hazard ratio [95% CI], 1.68 [1.22-2.30]; all-cause adjusted hazard ratio [95% CI], 1.29 [1.07-1.55]). The risk associated with a high ΔHR was particularly high in those with a substantial hypoxic burden (nonfatal, 1.93 [1.36-2.73]; fatal, 3.50 [2.15-5.71]; all-cause, 1.84 [1.40-2.40]) and was exclusively observed in nonsleepy individuals. Conclusions: Individuals with OSA who demonstrate an elevated ΔHR are at increased risk of cardiovascular morbidity and mortality. This study identifies a prognostic biomarker for OSA that appears useful for risk stratification and patient selection for future clinical trials.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

Epidemiological sleep research strives to identify the interactions and causal mechanisms by which sleep affects human health, and to design intervention strategies for improving sleep throughout the lifespan. These goals can be advanced by further focusing on the environmental and genetic etiology of sleep disorders, and by development of risk stratification algorithms, to identify people who are at risk or are affected by, sleep disorders. These studies rely on comprehensive sleep-related data which often contains complex multi-dimensional physiological and molecular measurements across multiple timepoints. Thus, sleep research is well-suited for the application of computational approaches that can handle high-dimensional data. Here, we survey recent advances in machine and deep learning together with the availability of large human cohort studies with sleep data that can jointly drive the next breakthroughs in the sleep-research field. We describe sleep-related data types and datasets, and present some of the tasks in the field that can be targets for algorithmic approaches, as well as the challenges and opportunities in pursuing them.

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint < 5 × 10-8), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (Pint < 5 × 10-8). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (Pint = 2 × 10-6). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (Pint < 10-3). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.