ABSTRACT
Considering sex as a biological variable in modern digital health solutions, we investigated sex-specific differences in the trajectory of four physiological parameters across a COVID-19 infection. A wearable medical device measured breathing rate, heart rate, heart rate variability, and wrist skin temperature in 1163 participants (mean age = 44.1 years, standard deviation [SD]=5.6; 667 [57%] females). Participants reported daily symptoms and confounders in a complementary app. A machine learning algorithm retrospectively ingested daily biophysical parameters to detect COVID-19 infections. COVID-19 serology samples were collected from all participants at baseline and follow-up. We analysed potential sex-specific differences in physiology and antibody titres using multilevel modelling and t-tests. Over 1.5 million hours of physiological data were recorded. During the symptomatic period of infection, men demonstrated larger increases in skin temperature, breathing rate and heart rate as well as larger decreases in heart rate variability than women. The COVID-19 infection detection algorithm performed similarly well for men and women. Our study belongs to the first research to provide evidence for differential physiological responses to COVID-19 between females and males, highlighting the potential of wearable technology to inform future precision medicine approaches. This work has received support from the Princely House of the Principality of Liechtenstein, the government of the Principality of Liechtenstein, the Hanela Foundation in Switzerland, and the Innovative Medicines Initiative (IMI) 2 Joint Undertaking under grant agreement No 101005177. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.
Subject(s)
COVID-19 , Learning Disabilities , Severe Acute Respiratory SyndromeABSTRACT
Background: During and after mild (no hospitalization) or moderate (hospitalization without ICU) SARS-CoV-2 infections, a wide range of symptoms, including neurological disorders have been reported. It is, however, unknown if these neurological symptoms are associated with brain injury and whether brain injury and related symptoms also emerge in patients suffering from Long-COVID. Neuronal biomarkers such as serum neurofilament light chain and glial fibrillary acidic protein can be used to elucidate neuro-axonal and astroglial injuries. We therefore investigated whether these biomarkers are associated with the COVID-19 infection status (mild-to-moderate), the associated symptoms and Long-COVID. Methods: From 146 individuals of the general population with a post-acute, mild-to-moderate SARS-CoV-2 infection, serum neurofilament light chain (sNfL; marker of intra-axonal neuronal injury) and serum glial fibrillary acidic protein (sGFAP; marker of astrocytic activation/injury) were measured. Samples were taken before, during and after (five and ten months) a SARS-CoV-2 infection. Individual symptoms and Long-COVID status were assessed using questionnaires. Results: Neurological symptoms were described for individuals after a mild and moderate COVID-19 infection, however, serum markers of brain injury (sNfL/sGFAP) did not change after an infection (sNfL: P = 0.74; sGFAP: P = 0.24) and were not associated with headache (P = 0.51), fatigue (P = 0.93), anosmia (P = 0.77) and ageusia (P = 0.47). In participants with Long-COVID, sGFAP (P = 0.038), but not sNfL (P = 0.58) significantly increased but was not associated with neurological symptoms. Conclusion: Neurological symptoms in individuals after a mild-to-moderate SARS-CoV-2 infection with and without Long-COVID were not associated with brain injury, although there was some astroglial injury observed in Long-COVID patients. Funding: The COVI-GAPP study received grants from the Innovative Medicines Initiative (IMI grant agreement number 101005177), the Princely House of Liechtenstein, the government of the Principality of Liechtenstein, and the Hanela Foundation (Switzerland). None of the funders played a role in the study design, data collection, data analysis, data interpretation, writing of the report, or decision to publish.