Emerging data suggest that determination of physiologic endotypic traits (eg, loop gain) may enable precision medicine in OSA. Does a single-night assessment of polysomnography-derived endotypic traits provide reliable estimates in moderate to severe OSA? Two consecutive in-lab polysomnography tests from a clinical trial (n = 67; male, 69%; mean ± SD age, 61 ± 10 years; apnea-hypopnea index [AHI] 53 ± 22 events/h) were used for the reliability analysis. Endotypic traits, reflecting upper airway collapsibility (ventilation at eupneic drive [V_passive]), upper airway dilator muscle tone (ventilation at the arousal threshold [V_active]), loop gain (stability of ventilatory control, LG1), and arousal threshold (ArTh) were determined. Reliability was expressed as an intraclass correlation coefficient (ICC). Minimal detectable differences (MDDs) were computed to provide an estimate of maximum spontaneous variability. Further assessment across four repeated polysomnography tests was performed in a subcohort (n = 22). Reliability of endotypic traits between the two consecutive nights was moderate to good (ICC: V_passive = 0.82, V_active = 0.76, LG1 = 0.72, ArTh = 0.83). Variability in AHI, but not in body position or in sleep stages, was associated with fluctuations in V_passive and V_active (r = –0.49 and r = –0.41, respectively; P < .001 for both). MDDs for single-night assessments were: V_passive = 22, V_active = 34, LG1 = 0.17, and ArTh = 21. Multiple assessments (mean of two nights, n = 22) further reduced MDDs by approximately 20% to 30%. Endotypic trait analysis using a single standard polysomnography shows acceptable reliability and reproducibility in patients with moderate to severe OSA. The reported MDDs of endotypic traits may facilitate the quantification of relevant changes and may guide future evaluation of interventions in OSA.

The carbonic anhydrase inhibitor sulthiame (STM) reduces obstructive sleep apnea (OSA) severity, increases overnight oxygenation and improves sleep quality. Insights into how STM modulates OSA pathophysiology (endotypic traits) adds to our understanding of the breathing disorder itself, as well as the effects of carbonic anhydrases in respiratory regulation. How does STM treatment modify endotypic traits in OSA? Per protocol tertiary analysis of a randomized controlled trial with the inclusion criteria: BMI ≥20 to ≤35 kg/m², age 18-75 years, apnea-hypopnea index (AHI) ≥15/h, Epworth sleepiness scale ≥6 as well as non-acceptance or non-tolerance of positive airway pressure treatment. Patients were randomized to receive placebo (n=22), STM 200 mg (n=12) or 400 mg (n=24) during four weeks of treatment. Polysomnography was applied twice at baseline and follow-up. Endotypic traits were determined from polysomnography tracings (PUPBeta, Terrill 2015). STM plasma concentration was analysed. Differences from baseline to follow-up (Δ) were analysed with ANCOVA/Kruskal-Wallis H-test and Pearson/Spearman correlation (r/r_s). STM (200 and 400 mg groups) consistently reduced loop gain (LG₁) (mean -0.16, [95% CI -0.18 to -0.13], p <0.05) in addition to increased ventilation at lowest decile of ventilatory drive (V_min, median +12 [4 to 20], p <0.05) and median ventilation at eupneic ventilatory drive (V_passive, median +4 [0 to 5], p <0.05). ΔLG₁ correlated with ΔAHI% (200 mg: r 0.65, p<0.05) and V_min/V_passive with ΔAHI (all STM: r_s -0.59 / r_s -0.65, all p<0.05). The reduction of LG₁ was seen already in the lower STM concentration range, while changes in V_min peaked in the higher range. The effect of STM in OSA may be explained by a reduction of ventilatory instability (LG₁) as well as upper airway collapsibility (V_min / V_passive).

Chronotype reflects individual preferences for timing activities throughout the day, determined by the circadian system, environment and behavior. The relationship between chronotype, physical activity, and cardiovascular health has not been established. We studied the association between chronotype, physical activity patterns, and an estimated 10-year risk of first-onset cardiovascular disease (CVD) in the Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot cohort. A cross-sectional analysis was performed in a middle-aged population (n = 812, 48% male). Self-assessed chronotype was classified as extreme morning, moderate morning, intermediate, moderate evening, or extreme evening. Time spent sedentary (SED) and in moderate to vigorous physical activity (MVPA) were derived from hip accelerometer. The newly introduced Systematic COronary Risk Evaluation 2 (SCORE2) model was used to estimate CVD risk based on gender, age, smoking status, systolic blood pressure, and non-HDL cholesterol. Extreme evening chronotypes exhibited the most sedentary lifestyle and least MVPA (55.3 ± 10.2 and 5.3 ± 2.9% of wear-time, respectively), with a dose-dependent relationship between chronotype and SED/MVPA (p < 0.001 and p = 0.001, respectively). In a multivariate generalized linear regression model, extreme evening chronotype was associated with increased SCORE2 risk compared to extreme morning type independent of confounders (β = 0.45, SE = 0.21, p = 0.031). Mediation analysis indicated SED was a significant mediator of the relationship between chronotype and SCORE2. Evening chronotype is associated with unhealthier physical activity patterns and poorer cardiovascular health compared to morning chronotype. Chronotype should be considered in lifestyle counseling and primary prevention programs as a potential modifiable risk factor.

Background The relationship between insomnia and cardiorespiratory fitness (CRF), a well-established risk factor for cardiovascular disease, has not been extensively studied. We aimed to assess the independent association between insomnia and CRF in a population-based cohort of subjects aged 50 to 64 years. Methods Subjects participating in the Swedish CArdioPulmonary bioImaging Study (SCAPIS) pilot cohort (n = 603, men 47.9%) underwent a submaximal cycle ergometer test for estimation of maximal oxygen consumption (VO₂max). Data on physical activity and sedentary time were collected via waist-worn accelerometers. An insomnia severity index score ≥ 10 was used to define insomnia. Results Insomnia was identified in 31.8% of the population. The VO₂max was significantly lower in insomnia subjects compared with the non-insomnia group (31.2 ± 6.3 vs. 32.4 ± 6.5 ml* kg⁻¹ *min⁻¹, p = 0.028). There was no difference in objectively assessed physical activity or time spent sedentary between the groups. In a multivariate generalized linear model adjusting for confounders, an independent association between insomnia status and lower VO₂max was found in men, but not in women (β = − 1.15 [95% CI − 2.23–− 0.06] and − 0.09 [− 1.09–0.92], p = 0.038 and 0.866, respectively). Conclusions We found a modest, but significant, association between insomnia and lower CRF in middle-aged men, but not in women. Our results suggest that insomnia may link to cardiovascular disease via reduced CRF. Insomnia may require a specific focus in the context of health campaigns addressing CRF.