This application addresses broad Challenge Area (03) Biomarker Discovery and Validation, and specific Challenge Topic, 03-HL-101* Identify and validate clinically relevant, quantifiable biomarkers of diagnostic and therapeutic responses for blood, vascular, cardiac, and respiratory tract dysfunction. The traditional approach to quantifying sleep and sleep-respiration relies on manual or computer assisted scoring of 30 second epochs, tagging of discrete fast phasic electroencephalographic events as arousals, and thresholds to identify pathological breathing. The scoring rules are usually reliant on a single physiological stream to make a determination, such as arousals from the electroencephalogram. However, arousing stimuli reliably induce simultaneous transient changes in numerous physiological systems - electrocortical, respiratory, autonomic, hemodynamic, and motor. These multiple linked physiological systems seem to show important patterns of coupled activity that current staging / scoring systems do not recognize. The respiratory chemoreflexes track oxygen (O2) and carbon dioxide (CO2) levels in the blood. Disease states can alter the set-point or response slope of the respiratory chemoreflexes, such that they are less (e.g., obesity hypoventilation syndrome) or more (e.g., central sleep apnea) sensitive to O2 and CO2 fluctuations. An ability to quantify and track the respiratory chemoreflexes during sleep could have clinical use, as 1) In certain conditions like congestive heart failure, chemoreflex sensitivity is reliably increased, correlates with disease severity and outcomes, and contributes to the high prevalence of sleep-disordered breathing. 2) Heightened respiratory chemoreflexes may contribute to obstructive sleep apnea severity, be associated with induction of central apneas when continuous positive airway pressure (CPAP) is used for treatment, and possibly impair long term efficacy and tolerance. Patients with obstructive sleep apnea who fail CPAP therapy due to induction of central apneas and periodic breathing (called """"""""complex sleep apnea"""""""") are not otherwise distinguishable from CPAP-responsive patients. A biomarker that can track chemoreflex modulation of sleep respiration will provide a new view of short and long-term dynamic sleep physiology with important clinical implications. The approach proposed here is to analyze coupled sleep oscillations to mathematically extract state characteristics and modulatory influences. The fundamental idea is that mapping common themes encoded within multiple (2 or more) physiologically distinct but biologically linked signal streams (such as electrocortical, autonomic, respiratory and motor) yields evidence of deeper regulatory processes not evident by the current approach of scoring / staging sleep with electroencephalogram or airflow patterns alone. We have developed a method that needs only a single channel electrocardiogram (ECG), is automated, can have parametrically varied detection thresholds, and is readily repeatable. From the ECG, we extract heart rate variability (HRV) and ECG R-wave amplitude fluctuations associated with respiratory tidal volume changes (the ECG-derived respiration, EDR). The next step is to mathematically combine the HRV and EDR to generate the cross-product coherence of cardiopulmonary coupling, which yields the sleep spectrogram. The sleep spectrogram shows high (0.1-1 Hz, low (0.1-0.01) and very low (0.01-0 Hz) coupling spectra that show spontaneous shifts between states in health and disease. High frequency coupling (HFC) is the biomarker of stable and physiologically restful sleep, low frequency coupling (LFC) is unstable or physiologically aroused sleep, and very low frequency coupling (VLFC) is wake or REM sleep. Health is dominated by HFC, diseases such as sleep apnea by LFC. A subset of LFC that correlate with apneas and hypopneas is elevated LFC (e-LFC). The stronger the chemoreflex modulatory influence on e-LFC, the more likely the coupling spectral dispersion narrows, yielding narrow band e-LFC (i.e., metronomic oscillations with a relatively fixed frequency). Narrow band e-LFC is induced by high altitude, heart failure, and predicts central apnea induction during positive pressure titration. The development and progression of heart failure is associated with fragmented sleep and heightened chemoreflex sensitivity. We predict that HFC will decrease and narrow band e-LFC will emerge and increase with worsening heart failure. These spectral biomarkers should change dynamically with heart failure progression or regression - viewing cardiac function through the window of sleep. Our experiments will take the following approach. We will establish the hemodynamic correlates of spectrographic stable and unstable sleep and night-to-night stability / variability of the ECG-derived biomarkers in adults and children in health, and in those with sleep apnea. Next, we will use a model of altitude-induced periodic breathing, which is relatively pure chemoreflex-mediated sleep apnea, to adjust the spectrogram's parameters that allow the best sensitivity and specificity for detecting chemoreflex influences on sleep respiration. We will in parallel track the progress of heart failure patients from a hospitalization episode for 6 months, attempting to show that reductions of HFC and emergence or increases in narrow band e-LFC are sentinel biomarker events that predict worsening of heart failure (an early warning system). Finally, we will assess clinical outcomes based on spectral phenotyping of an archived data set, the Apnea Positive Pressure Long-term Efficacy Study. In the 2-year duration of the award, we will validate a unique biomarker of sleep, sleep-breathing, and cardiovascular biology that can be applied immediately to improve health outcomes.

Public Health Relevance

Simple measures of sleep, sleep-breathing and heart function that are cheap, readily repeatable, and which can track disease fluctuations would be useful, for clinical and research purposes. A new method based on a single channel of electrocardiogram (ECG) has been developed;it uses changes in the speed of the heart beat and breathing-related size modifications of the ECG, to create a """"""""picture of the """"""""music of sleep"""""""". We propose to show its usefulness as a monitor of sleep in health, in those with simple and complicated forms of sleep apnea, and in patients with heart failure.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
NIH Challenge Grants and Partnerships Program (RC1)
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Special Emphasis Panel (ZRG1-CVRS-B (58))
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Lewin, Daniel S
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Beth Israel Deaconess Medical Center
United States
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