Abstract

Motivation: Some people exposed to SARS-CoV-2 experience persistent symptoms months after recovering from acute infection. These symptoms, grouped under the umbrella of “long-COVID”, include neurological and autonomic dysfunctions for which there is not yet a clear explanation. Goal(s): To identify biophysically meaningful features characterising long-COVID pathophysiology in the brain. Approach: A novel multimodal MRI protocol was developed to measure iron accumulation, myelin content, inflammation, microstructure alterations, atrophy, and cerebral blood flow changes. Machine learning was employed to discriminate long-COVID from controls and people who fully recovered. Results: Alterations in bound-pool fraction (myelin content) emerge in long-COVID. Impact: This study encourages investigating the neurological aspect of long-COVID and its interplay with conditions affecting myelin as it shows that long-COVID may cause myelin alterations or be more likely to occur in people with compromised myelin content in the brain.