Sex-related Differences in Loop Gain during High-Altitude Sleep-disordered Breathing.

Rationale: Central sleep apnea (CSA) is pervasive during sleep at high altitude, disproportionately impacting men and associated with increased peripheral chemosensitivity. Objectives: We aimed to assess whether biological sex affects loop gain (LGn) and CSA severity during sleep over 9-10 days of acclimatization to 3,800 m. We hypothesized that CSA severity would worsen with acclimatization in men but not in women because of greater increases in LGn in men. Methods: Sleep studies were collected from 20 (12 male) healthy participants at low altitude (1,130 m, baseline) and after ascent to (nights 2/3, acute) and residence at high altitude (nights 9/10, prolonged). CSA severity was quantified as the respiratory event index (REI) as a surrogate of the apnea-hypopnea index. LGn, a measure of ventilatory control instability, was quantified using a ventilatory control model fit to nasal flow. Linear mixed models evaluated effects of time at altitude and sex on respiratory event index and LGn. Data are presented as contrast means with 95% confidence intervals. Results: REI was comparable between men and women at acute altitude (4.1 [-9.3, 17.5] events/h; P = 0.54) but significantly greater in men at prolonged altitude (23.7 [10.3, 37.1] events/h; P = 0.0008). Men had greater LGn than did women for acute (0.08 [0.001, 0.15]; P = 0.047) and prolonged (0.17 [0.10, 0.25]; P < 0.0001) altitude. The change in REI per change in LGn was significantly greater in men than in women (107 ± 46 events/h/LGn; P = 0.02). Conclusions: The LGn response to high altitude differed between sexes and contributed to worsening of CSA over time in men but not in women. This sex difference in acclimatization appears to protect females from high altitude-related CSA. These data provide fundamental sex-specific physiological insight into high-altitude acclimatization in healthy individuals and may help to inform sex differences in sleep-disordered breathing pathogenesis in patients with cardiorespiratory disease.

An open-source application for the standardized burst identification from the integrated muscle sympathetic neurogram.

Muscle sympathetic nerve activity (MSNA) can be acquired from humans using the technique of microneurography. The resulting integrated neurogram displays pulse-synchronous bursts of sympathetic activity, which undergoes processing for standard MSNA metrics including burst frequency, height, area, incidence, total activity, and latency. The procedure for detecting bursts of MSNA and calculating burst metrics is tedious and differs widely among laboratories worldwide. We sought to develop an open-source, cross-platform web application that provides a standardized approach for burst identification and a tool to increase research reproducibility for those measuring MSNA. We compared the performance of this web application against a manual scoring approach under conditions of rest, chemoreflex activation (n = 9, 20-min isocapnic hypoxia), and metaboreflex activation (n = 13, 2-min isometric handgrip exercise and 4-min postexercise circulatory occlusion). The intraclass correlation coefficient (ICC) indicated good to strong agreement between scoring approaches for burst frequency (ICC = 0.92-0.99), incidence (ICC = 0.94-0.99), height (ICC = 0.76-0.88), total activity (ICC = 0.85-0.99), and latency (ICC = 0.97-0.99). Agreement with burst area was poor to moderate (ICC = 0.04-0.67) but changes in burst area were similar with chemoreflex and metaboreflex activation. Scoring using the web application was highly efficient and provided data visualization tools that expedited data processing and the analysis of MSNA. We recommend the open-source web application be adopted by the community for the analysis of MSNA.NEW & NOTEWORTHY The basic analysis of muscle sympathetic nerve activity (MSNA) requires the identification of pulse-synchronous bursts from the integrated neurogram before standard MSNA metrics can be quantified. This process is a time-consuming task requiring an experienced microneurographer to visually identify and manually label bursts. We developed an open-source, cross-platform application permitting a standardized approach for sympathetic burst identification and present the performance of this application against a manual scorer under basal conditions and during sympathoexcitatory stresses.