ATS Core Curriculum 2021. Adult Sleep Medicine: Sleep Apnea.

The American Thoracic Society Sleep Core Curriculum updates clinicians on important sleep topics, presented during the annual meeting, and appearing in summary here. This year's sleep core theme is sleep-disordered breathing and its management. Topics range from pathophysiological mechanisms for the association of obstructive sleep apnea (OSA) and metabolic syndrome, surgical modalities of OSA treatment, comorbid insomnia and OSA, central sleep apnea, and sleep practices during a pandemic. OSA has been associated with metabolic syndrome, independent of the role of obesity, and the pathophysiology suggests a role for sleep fragmentation and intermittent hypoxia in observed metabolic outcomes. In specific patient populations, surgical treatment modalities for OSA have demonstrated large reductions in objective disease severity compared with no treatment and may facilitate adherence to positive airway pressure treatment. Patient-centered approaches to comorbid insomnia and sleep apnea include evaluating for both OSA and insomnia simultaneously and using shared-decision making to determine the order and timing of positive airway pressure therapy and cognitive behavioral therapy for insomnia. The pathophysiology of central sleep apnea is complex and may be due to the loss of drive to breathe or instability in the regulatory pathways that control ventilation. Pandemic-era sleep practices have evolved rapidly to balance safety and sustainability of care for patients with sleep-disordered breathing.

ATS Core Curriculum 2020. Adult Sleep Medicine.

The American Thoracic Society Core Curriculum updates clinicians annually in adult and pediatric pulmonary disease, medical critical care, and sleep medicine, in a 3-4-year recurring cycle of topics. These topics will be presented at the 2020 Virtual Conference. Below is the adult sleep medicine core that includes topics pertinent to sleep-disordered breathing and insomnia.

Genetic variants associated with sleep disorders.

OBJECTIVE: The diagnostic boundaries of sleep disorders are under considerable debate. The main sleep disorders are partly heritable; therefore, defining heritable pathophysiologic mechanisms could delineate diagnoses and suggest treatment. We collected clinical data and DNA from consenting patients scheduled to undergo clinical polysomnograms, to expand our understanding of the polymorphisms associated with the phenotypes of particular sleep disorders. METHODS: Patients at least 21 years of age were recruited to contribute research questionnaires, and to provide access to their medical records, saliva for deoxyribonucleic acid (DNA), and polysomnographic data. From these complex data, 38 partly overlapping phenotypes were derived indicating complaints, subjective and objective sleep timing, and polysomnographic disturbances. A custom chip was used to genotype 768 single-nucleotide polymorphisms (SNPs). Additional assays derived ancestry-informative markers (eg, 751 participants of European ancestry). Linear regressions controlling for age, gender, and ancestry were used to assess the associations of each phenotype with each of the SNPs, highlighting those with Bonferroni-corrected significance. RESULTS: In peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1B), rs6888451 was associated with several markers of obstructive sleep apnea. In aryl hydrocarbon receptor nuclear translocator-like (ARNTL), rs10766071 was associated with decreased polysomnographic sleep duration. The association of rs3923809 in BTBD9 with periodic limb movements in sleep was confirmed. SNPs in casein kinase 1 delta (CSNK1D rs11552085), cryptochrome 1 (CRY1 rs4964515), and retinoic acid receptor-related orphan receptor A (RORA rs11071547) were less persuasively associated with sleep latency and time of falling asleep. CONCLUSIONS: SNPs associated with several sleep phenotypes were suggested, but due to risks of false discovery, independent replications are needed before the importance of these associations can be assessed, followed by investigation of molecular mechanisms.

Circadian polymorphisms in night owls, in bipolars, and in non-24-hour sleep cycles.

People called night owls habitually have late bedtimes and late times of arising, sometimes suffering a heritable circadian disturbance called delayed sleep phase syndrome (DSPS). Those with DSPS, those with more severe progressively-late non-24-hour sleep-wake cycles, and those with bipolar disorder may share genetic tendencies for slowed or delayed circadian cycles. We searched for polymorphisms associated with DSPS in a case-control study of DSPS research participants and a separate study of Sleep Center patients undergoing polysomnography. In 45 participants, we resequenced portions of 15 circadian genes to identify unknown polymorphisms that might be associated with DSPS, non-24-hour rhythms, or bipolar comorbidities. We then genotyped single nucleotide polymorphisms (SNPs) in both larger samples, using Illumina Golden Gate assays. Associations of SNPs with the DSPS phenotype and with the morningness-eveningness parametric phenotype were computed for both samples, then combined for meta-analyses. Delayed sleep and "eveningness" were inversely associated with loci in circadian genes NFIL3 (rs2482705) and RORC (rs3828057). A group of haplotypes overlapping BHLHE40 was associated with non-24-hour sleep-wake cycles, and less robustly, with delayed sleep and bipolar disorder (e.g., rs34883305, rs34870629, rs74439275, and rs3750275 were associated with n=37, p=4.58E-09, Bonferroni p=2.95E-06). Bright light and melatonin can palliate circadian disorders, and genetics may clarify the underlying circadian photoperiodic mechanisms. After further replication and identification of the causal polymorphisms, these findings may point to future treatments for DSPS, non-24-hour rhythms, and possibly bipolar disorder or depression.

Genotyping sleep disorders patients.

OBJECTIVE: The genetic susceptibility factors underlying sleep disorders might help us predict prognoses and responses to treatment. Several candidate polymorphisms for sleep disorders have been proposed, but there has as yet inadequate replication or validation that the candidates may be useful in the clinical setting. METHODS: To assess the validity of several candidate associations, we obtained saliva deoxyribonucleic acid (DNA) samples and clinical information from 360 consenting research participants who were undergoing clinical polysomnograms. Ten single nucleotide polymorphisms (SNPs) were genotyped. These were thought to be related to depression, circadian sleep disorders, sleep apnea, restless legs syndrome (RLS), excessive sleepiness, or to slow waves in sleep. RESULTS: With multivariate generalized linear models, the association of TEF rs738499 with depressive symptoms was confirmed. Equivocal statistical evidence of association of rs1801260 (the C3111T SNP in the CLOCK gene) with morningness/eveningness and an association of Apolipoprotein E (APOE) rs429358 with the Epworth Sleepiness Scale (ESS) were obtained, but these associations were not strong enough to be of clinical value by themselves. Predicted association of SNPs with sleep apnea, RLS, and slow wave sleep were not confirmed. CONCLUSION: The SNPs tested would not, by themselves, be of use for clinical genotyping in a sleep clinic.

Evaluation of immobility time for sleep latency in actigraphy.

BACKGROUND: Actigraphy has become an important tool in sleep research, however, most actigraphic models have had little evaluation of their sleep scoring software. Some reports have described poor agreement of actigraph and polysomnogram (PSG) results. In this study, we examined the accuracy of the Actiwatch-L instrument with Actiware((R)) software version 5.0 (Minimitter-Respironics, Bend, Oregon). METHODS: We analyzed the sleep latencies and total sleep times in 33 actigraph recordings and compared performance to simultaneous polysomnography. For scoring sleep latency, the default criterion for scoring sleep onset (10min of immobility) was compared with criteria of 4, 5, 6, and 15min of immobility, and low, middle, and high activity thresholds were compared. RESULTS: Of 4, 5, 6, 10 and 15min of actigraphic immobility, the 5min criterion yielded the most accurate sleep latencies. The 5min criterion also yielded near-optimal estimates for total sleep time and wake after sleep onset. CONCLUSIONS: We found that a default 10-min immobility parameter for sleep onset was not as accurate as 5min for scoring sleep latency and total sleep time in this clinical sample. There is a need for expanded samples to further evaluate algorithm scoring parameters and the search for superior alternatives.