Integrated respiratory functions predict myelin status in the mouse brain

Demyelination is a common pathological feature of central nervous system (CNS) diseases, and its early detection is important for the diagnosis of neurological disorders; therefore, simple detection methods are in high demand. In this study, we found that both age-related myelin loss and demyelination in disease model mice can be predicted through integrative analysis of multiple respiratory parameters. Changes in some respiratory parameters correlated with myelin levels with aging; however, integrative analysis using conventional models further enabled the prediction of age-related myelin changes. In cuprizone-induced demyelination models, average respiratory values did not differ between demyelinated and control mice. However, the integrative analysis of the respiratory parameter set successfully distinguished demyelinated mice. Our study showed that respiratory function data may be used as a non-invasive method to predict brain conditions in mice, although translation to humans will require further validation. This approach shows promise as a potential method for early disease prediction and diagnostic support for CNS diseases.