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.
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.
Authors: Lyle J Palmer; Sarah G Buxbaum; Emma K Larkin; Sanjay R Patel; Robert C Elston; Peter V Tishler; Susan Redline Journal: Am J Respir Crit Care Med Date: 2004-04-07 Impact factor: 21.405
Authors: S Redline; P V Tishler; T D Tosteson; J Williamson; K Kump; I Browner; V Ferrette; P Krejci Journal: Am J Respir Crit Care Med Date: 1995-03 Impact factor: 21.405
Authors: S R Patel; T Blackwell; S Redline; S Ancoli-Israel; J A Cauley; T A Hillier; C E Lewis; E S Orwoll; M L Stefanick; B C Taylor; K Yaffe; K L Stone Journal: Int J Obes (Lond) Date: 2008-10-21 Impact factor: 5.095
Authors: Dennis A Dean; Ary L Goldberger; Remo Mueller; Matthew Kim; Michael Rueschman; Daniel Mobley; Satya S Sahoo; Catherine P Jayapandian; Licong Cui; Michael G Morrical; Susan Surovec; Guo-Qiang Zhang; Susan Redline Journal: Sleep Date: 2016-05-01 Impact factor: 5.849