Disorders of autonomic functions are typically characterized by disturbances in multiple organ systems. These disturbances are often comorbidities of common and rare diseases, such as epilepsy, sleep apnea, Rett syndrome, congenital heart disease or mitochondrial diseases. Characteristic of many autonomic disorders is the association with intermittent hypoxia and oxidative stress, which can cause or exaggerate a variety of other autonomic dysfunctions, making the treatment and management of these syndromes very complex. In this review we discuss the cellular mechanisms by which intermittent hypoxia can trigger a cascade of molecular, cellular and network events that result in the dysregulation of multiple organ systems. We also describe the importance of computational approaches, artificial intelligence and the analysis of big data to better characterize and recognize the interconnectedness of the various autonomic and non-autonomic symptoms. These techniques can lead to a better understanding of the progression of autonomic disorders, ultimately resulting in better care and management.
Keywords: Artificial intelligence; Autonomic dysregulation; Intermittent hypoxia; Machine learning.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.