Heritability of abnormalities in cardiopulmonary coupling in sleep apnea: use of an electrocardiogram-based technique.

RATIONALE: Studies of the genetics of obstructive sleep apnea may be facilitated by identifying intermediate traits with high heritability that quantify etiological pathways, such as those related to respiratory control. Electrocardiogram (ECG)-based sleep spectrograms, measuring the coupling between respiratory modulation of ECG QRS-wave amplitude and heart rate variability, may provide measures of sleep state and ventilatory dynamics during sleep. We evaluated the familial aggregation of distinctive spectrographic biomarkers of unstable sleep, related to elevated-low frequency cardiopulmonary coupling (e-LFC), to assess their utility in genetic studies. METHODS: 622 participants from 137 families from the Cleveland Family Study underwent standardized polysomnography (PSG). From the ECG signal on the PSG, the interbeat interval time series and the corresponding ECG-derived respiratory signal were extracted, and the low frequency (0.01-0.1 Hz) component of their coupling was computed using a fully automated method. Narrow sense heritability of e-LFC was calculated using variance component methods. RESULTS: A spectral marker of abnormal low frequency cardiopulmonary coupling (e-LFC) demonstrated moderate correlation with apnea hypopnea index (AHI; r = 0.35, P < 0.0001). The heritability estimate for e-LFC, after adjusting for age and sex was 0.32 (P < 10-5) and remained unchanged after additionally adjusting for body mass index or AHI. In biological relatives of those with sleep apnea, a related marker of e-LFC was more prevalent than in controls (P = 0.05). CONCLUSIONS: Approximately 30% of the variability of e-LFC, measured from a continuous ECG during sleep, is explained by familial factors other than BMI. ECG-based spectrographic measures of cardiopulmonary coupling may provide novel phenotypes for characterizing subgroups of individuals with different propensities and genetic etiologies for sleep apnea or for other conditions associated with sleep fragmentation.

A measure of ventilatory variability at wake-sleep transition predicts sleep apnea severity.

RATIONALE: Increased variability in ventilation may contribute to the pathogenesis of obstructive sleep apnea (OSA) by promoting ventilatory instability, fluctuations of neuromuscular output to the upper airway, and pharyngeal collapsibility. We assessed the association of a measure of ventilatory variability measured at the wake-sleep transition with OSA and associated covariates. METHODS: Four hundred eighty-five participants in the Cleveland Family Study underwent overnight polysomnography with independent derivation of the ventilatory variability index (VVI) and the apnea-hypopnea index (AHI). The VVI was calculated from the variability in the power spectrum of the abdominal inductance signal over a 2-min period beginning at sleep onset. RESULTS: The VVI was strongly correlated with the AHI (r=0.43; p<0.001). After adjusting for age, body mass index, sex, and race, the VVI remained significantly associated with AHI (p<0.001). The adjusted odds ratio for OSA (AHI, >or=15) with each half SD increase in VVI was 1.41 (range, 1.25 to 1.59). In a subgroup analysis of obese snorers, to limit analyses to those with a presumed anatomic predisposition for apnea, VVI remained associated with an elevated AHI. CONCLUSIONS: Increased ventilatory variability may be a useful phenotype in characterizing OSA.