Modeling the autonomic and metabolic effects of obstructive sleep apnea: a simulation study

A mathematical model to serve as a clinical tool for assessing obstructive sleep apnea severity

Obstructive sleep apnea (OSA) is a sleep disorder caused by periodic airway obstructions and has been associated with numerous health consequences, which are thought to result from tissue hypoxia. However, challenges in the direct measurement of tissue-level oxygenation make it difficult to analyze the hypoxia exposure pattern in patients. Furthermore, current clinical practice relies on the apnea-hypopnea index (AHI) and pulse oximetry to assess OSA severity, both of which have limitations. To overcome this, we developed a clinically deployable mathematical model, which outputs tissue-level oxygenation. The model incorporates spatial pulmonary oxygen uptake, considers dissolved oxygen, and can use time-dependent patient inputs. It was applied to explore a series of breathing patterns that are clinically differentiated. Supporting previous studies, the result of this analysis indicated that the AHI is an unreliable indicator of hypoxia burden. As a proof of principle, polysomnography data from two patients was analyzed with this model. The model showed greater sensitivity to breathing in comparison with pulse oximetry and provided systemic venous oxygenation, which is absent from clinical measurements. In addition, the dissolved oxygen output was used to calculate hypoxia burden scores for each patient and compared to the clinical assessment, highlighting the importance of event length and cumulative impact of obstructions. Furthermore, an intra-patient statistical analysis was used to underscore the significance of closely occurring obstructive events and to highlight the utility of the model for quantitative data processing. Looking ahead, our model can be used with polysomnography data to predict hypoxic burden on the tissues and help guide patient treatment decisions.

Path Topology in Molecular and Materials Sciences

The structures of molecules and materials determine their functions. Understanding the structure and function relationship is the holy grail of molecular and materials sciences. However, the rational design of molecules and materials with desirable functions remains a grand challenge despite decades of efforts. A major obstacle is the lack of an intrinsic mathematical characteristic that attributes to a specific function. This work introduces persistent path topology (PPT) to effectively characterize directed networks extracted from functional units, such as constitutional isomers, cis-trans isomers, chiral molecules, Jahn-Teller isomerism, and high-entropy alloy catalysts. Path homology (PH) theory is utilized to decipher the role of mirror-symmetric sublattices that hinder the formation of periodic unit cells in amorphous solids. Topological perturbation analysis (TPA) is proposed to reveal the critical target in the blood coagulation system. The proposed topological tools can be directly applied to systems biology, omics sciences, topological materials, and machine learning study of molecular and materials sciences.

Modeling patient-specific desaturation patterns in sleep apnea

OBJECTIVE

The physiological mechanisms involved in cardio-respiratory responses to sleep apnea events are not yet fully elucidated. A model-based approach is proposed to analyse the acute desaturation response to obstructive apneas.

METHODS

An integrated model of cardio-respiratory interactions was proposed and parameters were identified, using an evolutionary algorithm, on a database composed of 107 obstructive apneas acquired from 10 patients (HYPNOS clinical study). Unsupervised clustering was applied to the identified parameters in order to characterize the phenotype of each response to obstructive apneas.

RESULTS

A close match was observed between simulated oxygen saturation (SaO2) and experimental SaO2 in all identifications (median RMSE = 1.3892%). Two clusters of parameters, associated with different dynamics related to sleep apnea and periodic breathing were obtained.

CONCLUSION AND SIGNIFICANCE

The proposed patient and event-specific model-based analysis provides understanding on specific desaturation patterns, consequent to apnea events, with potential applications for personalized diagnosis and treatment.

Circadian Patterns of Patients with Type 2 Diabetes and Obstructive Sleep Apnea

Sleep apnea, a condition that modifies sleep and circadian rhythms, is highly prevalent in patients with diabetes. However, it is not known if there is an association between sleep apnea, circadian alterations and glycemic regulation in this type of patient. Here, a polysomnographic study was carried out on 21 women and 25 men (mean age = 64.3 ± 1.46 years) with diagnoses of type 2 diabetes to detect the presence of sleep apnea. Moreover, patients wore an actigraph and a temperature sensor on the wrist for one week, to study the manifestation of the circadian rhythms. The correlations of circadian and polysomnographic variables with the severity of apnea, measured by the apnea-hypopnea index, and with glycemic dysregulation, measured by the percentage of glycated hemoglobin, were analyzed. The mean apnea-hypoapnea index of all the participants was 39.6 ± 4.3. Apnea-hypoapnea index correlated with % N1, negatively with % N3, and also the stability of the active circadian rhythm. However, no significant correlation was found between the apnea-hypopnea index and wrist temperature rhythm and glycated hemoglobin. Glycated hemoglobin levels were negatively associated with the percentage of variance explained by the wrist temperature circadian rhythm (calculated via 24 and 12 h rhythms). This association was independent of body mass index and was strongest in patients with severe apnea. In conclusion, patients with diabetes showed altered circadian rhythms associated with a poor glycemic control and this association could partially be related to the coexistence of sleep apnea.

Review of quantitative systems pharmacological modeling in thrombosis

Hemostasis and thrombosis are often thought as two sides of the same clotting mechanism whereas hemostasis is a natural protective mechanism to prevent bleeding and thrombosis is a blood clot abnormally formulated inside a blood vessel, blocking the normal blood flow. The evidence to date suggests that at least arterial thrombosis results from the same critical pathways of hemostasis. Analysis of these complex processes and pathways using quantitative systems pharmacological model-based approach can facilitate the delineation of the causal pathways that lead to the emergence of thrombosis. In this paper, we provide an overview of the main molecular and physiological mechanisms associated with hemostasis and thrombosis, and review the models and quantitative system pharmacological modeling approaches that are relevant in characterizing the interplay among the multiple factors and pathways of thrombosis. An emphasis is given to computational models for drug development. Future trends are discussed.

An Improved Dynamic Model for the Respiratory Response to Exercise

Respiratory system modeling has been extensively studied in steady-state conditions to simulate sleep disorders, to predict its behavior under ventilatory diseases or stimuli and to simulate its interaction with mechanical ventilation. Nevertheless, the studies focused on the instantaneous response are limited, which restricts its application in clinical practice. The aim of this study is double: firstly, to analyze both dynamic and static responses of two known respiratory models under exercise stimuli by using an incremental exercise stimulus sequence (to analyze the model responses when step inputs are applied) and experimental data (to assess prediction capability of each model). Secondly, to propose changes in the models' structures to improve their transient and stationary responses. The versatility of the resulting model vs. the other two is shown according to the ability to simulate ventilatory stimuli, like exercise, with a proper regulation of the arterial blood gases, suitable constant times and a better adjustment to experimental data. The proposed model adjusts the breathing pattern every respiratory cycle using an optimization criterion based on minimization of work of breathing through regulation of respiratory frequency.

Characteristics of Obstructive Sleep Apnea Across the Spectrum of Glucose Tolerance in Obese Adolescents

BACKGROUND

It is not known if dysglycemia and sleep-disordered breathing are linked in adolescents, as in adults.

OBJECTIVE

To perform a pilot study evaluating measures of sleep-disordered breathing across the spectrum of glucose tolerance in obese adolescents. We hypothesized that dysglycemia would be associated with sleep-disordered breathing.

PARTICIPANTS/METHODS

This was a prospective, cross-sectional clinical pilot study that included 57 adolescents [body mass index (BMI) 38.9 ± 8.4 kg/m²] aged 12-18 years (14.5 ± 1.6) with normal glucose tolerance (NGT), or dysglycemia [impaired glucose tolerance (IGT) or type 2 diabetes (T2D)].

MEASURES

Anthropometrics, overnight polysomnogram, and oral glucose tolerance tests were performed. Participant characteristics and outcome measures were compared by glucose tolerance status. Correlational analyses were conducted to assess the associations between variables of interest.

RESULTS

Participants with dysglycemia (n = 21) were not different from those with NGT (n = 36) for BMI, waist circumference, body fat, or sleep characteristics. Nocturnal oxygen desaturation was associated with higher BMI (r = -0.334, p = 0.012). The apnea-hypopnea index (AHI) was not associated with physical and metabolic parameters. Although participants with dysglycemia tended to have higher AHIs (median 3.2, 2.2, and 1.6 events/h for T2D, IGT, and NGT, respectively), there was not a linear relationship between measures of glycemia and AHI.

CONCLUSION

Further study with a larger proportion of youth with prediabetes and T2D is necessary to determine whether evaluation for sleep-disordered breathing is uniformly warranted.

Pulmonary Function and Sleep Breathing: Two New Targets for Type 2 Diabetes Care

Population-based studies showing the negative impact of type 2 diabetes (T2D) on lung function are overviewed. Among the well-recognized pathophysiological mechanisms, the metabolic pathways related to insulin resistance (IR), low-grade chronic inflammation, leptin resistance, microvascular damage, and autonomic neuropathy are emphasized. Histopathological changes are exposed, and findings reported from experimental models are clearly differentiated from those described in humans. The accelerated decline in pulmonary function that appears in patients with cystic fibrosis (CF) with related abnormalities of glucose tolerance and diabetes is considered as an example to further investigate the relationship between T2D and the lung. Furthermore, a possible causal link between antihyperglycemic therapies and pulmonary function is examined. T2D similarly affects breathing during sleep, becoming an independent risk factor for higher rates of sleep apnea, leading to nocturnal hypoxemia and daytime sleepiness. Therefore, the impact of T2D on sleep breathing and its influence on sleep architecture is analyzed. Finally, the effect of improving some pathophysiological mechanisms, primarily IR and inflammation, as well as the optimization of blood glucose control on sleep breathing is evaluated. In summary, the lung should be considered by those providing care for people with diabetes and raise the central issue of whether the normalization of glucose levels can improve pulmonary function and ameliorate sleep-disordered breathing. Therefore, patients with T2D should be considered a vulnerable group for pulmonary dysfunction. However, further research aimed at elucidating how to screen for the lung impairment in the population with diabetes in a cost-effective manner is needed.

Chronic intermittent hypoxia and obstructive sleep apnea: an experimental and clinical approach

Obstructive sleep apnea (OSA) is a prevalent sleep disorder considered as an independent risk factor for cardiovascular consequences, such as systemic arterial hypertension, ischemic heart disease, cardiac arrhythmias, metabolic disorders, and cognitive dysfunction. The pathogenesis of OSA-related consequence is assumed to be chronic intermittent hypoxia (IH) inducing alterations at the molecular level, oxidative stress, persistent systemic inflammation, oxygen sensor activation, and increase of sympathetic activity. Overall, these mechanisms have an effect on vessel permeability and are considered to be important factors for explaining vascular, metabolic, and cognitive OSA-related consequences. The present review attempts to examine together the research paradigms and clinical studies on the effect of acute and chronic IH and the potential link with OSA. We firstly describe the literature data on the mechanisms activated by acute and chronic IH at the experimental level, which are very helpful and beneficial to explaining OSA consequences. Then, we describe in detail the effect of IH in patients with OSA that we can consider "the human model" of chronic IH. In this way, we can better understand the specific pathophysiological mechanisms proposed to explain the consequences of IH in OSA.

An integrated mathematical model of the human cardiopulmonary system: model development

Several cardiovascular and pulmonary models have been proposed in the last few decades. However, very few have addressed the interactions between these two systems. Our group has developed an integrated cardiopulmonary model (CP Model) that mathematically describes the interactions between the cardiovascular and respiratory systems, along with their main short-term control mechanisms. The model has been compared with human and animal data taken from published literature. Due to the volume of the work, the paper is divided in two parts. The present paper is on model development and normophysiology, whereas the second is on the model's validation on hypoxic and hypercapnic conditions. The CP Model incorporates cardiovascular circulation, respiratory mechanics, tissue and alveolar gas exchange, as well as short-term neural control mechanisms acting on both the cardiovascular and the respiratory functions. The model is able to simulate physiological variables typically observed in adult humans under normal and pathological conditions and to explain the underlying mechanisms and dynamics.

Understanding the metabolic syndrome: a modeling perspective

The prevalence of obesity is growing at an alarming rate, placing many at risk for developing diabetes, hypertension, sleep apnea, or a combination of disorders known as "metabolic syndrome". The evidence to date suggests that metabolic syndrome results from an imbalance in the mechanisms that link diet, physical activity, glucose-insulin control, and autonomic cardiovascular control. There is also growing recognition that sleep-disordered breathing and other forms of sleep disruption can contribute significantly to autonomic dysfunction and insulin resistance. Chronic sleep deprivation resulting from sleep-disordered breathing or behavioral causes can lead to excessive daytime sleepiness and lethargy, which in turn contribute to increasing obesity. Analysis of this complex dynamic system using a model-based approach can facilitate the delineation of the causal pathways that lead to the emergence of the metabolic syndrome. In this paper, we provide an overview of the main physiological mechanisms associated with obesity and sleep-disordered breathing that are believed to result in metabolic and autonomic dysfunction, and review the models and modeling approaches that are relevant in characterizing the interplay among the multiple factors that underlie the development of the metabolic syndrome.

A joint computational respiratory neural network-biomechanical model for breathing and airway defensive behaviors

Data-driven computational neural network models have been used to study mechanisms for generating the motor patterns for breathing and breathing related behaviors such as coughing. These models have commonly been evaluated in open loop conditions or with feedback of lung volume simply represented as a filtered version of phrenic motor output. Limitations of these approaches preclude assessment of the influence of mechanical properties of the musculoskeletal system and motivated development of a biomechanical model of the respiratory muscles, airway, and lungs using published measures from human subjects. Here we describe the model and some aspects of its behavior when linked to a computational brainstem respiratory network model for breathing and airway defensive behavior composed of discrete "integrate and fire" populations. The network incorporated multiple circuit paths and operations for tuning inspiratory drive suggested by prior work. Results from neuromechanical system simulations included generation of a eupneic-like breathing pattern and the observation that increased respiratory drive and operating volume result in higher peak flow rates during cough, even when the expiratory drive is unchanged, or when the expiratory abdominal pressure is unchanged. Sequential elimination of the model's sources of inspiratory drive during cough also suggested a role for disinhibitory regulation via tonic expiratory neurons, a result that was subsequently supported by an analysis of in vivo data. Comparisons with antecedent models, discrepancies with experimental results, and some model limitations are noted.