Persistent fatigue (PF) is a common symptom across countries and cultures, and an important cause of disability and reduced quality of life. Acute infection is a common trigger of PF, as exemplified by the 'Long COVID' phenomenon. Despite substantial burden for the suffering individuals as well as their next-of-kins, the healthcare systems and the economy, PF is an under-researched field, with scarce knowledge of disease mechanisms as well as treatment and preventive measures.

Existing knowledge on PF suggests complex interactions between functional brain processes (as opposed to permanent brain damage), aberrations of the immune system (that normally protects against infection) and the autonomic (or non-voluntary) part of the nervous system (that monitors the internal state of the body and adjusts the function of internal organs). Previous findings have been interpreted in light of two alternative models: A body-to-brain mechanism where disturbances of the immune system are thought to impact on brain functions, and a brain-to-body mechanism where functional brain alteration is regarded the central element whereas aberration of the immune system is seen as a consequence (rather than a cause) mediated through altered activity of the autonomic nervous system.

The multinational and collaborative Mechanism of Persistent Fatigue (MAP-FAT) project is determined to scrutinize both these potential brain-body interactions in PF. The main objectives are: a) To determine the relationship between PF, activities in certain brain areas, activity in a certain part of the autonomic nervous system (the sympathetic branch), and immunological alterations; b) To determine whether PF is primarily dependent upon the brain's automatic predictions rather than the continuous sensory information mediated to the brain. To achieve these objectives, MAP-FAT will exploit an existing health registry on post-infective fatigue (preparatory part) and conduct a new post-infective cohort study (main part) in which a total of 150 individuals with "kissing disease" and 150 healthy controls are followed for six months. Investigations include: a) Clinical and demographic assessment; b) Questionnaire charting; c) Functional and structural imaging of the brain (multimodal brain MRI); d) Assessment of autonomic nervous system activity; e) Deep immunological profiling; and f) Behavioral experiments. The latter are specifically designed to disentangle the relative contributions of the brain's automatic predictions and sensory input for the experience of PF. In addition, one of the experiments includes concurrent functional brain imaging, autonomic nervous system assessment, and immunological profiling during experimental injections of drugs that impact on autonomic activity; this experiment is key for addressing the causal association between brain functions, autonomic activity and immunological disturbance.

Inclusion Criteria (pertaining to EBV group only):

• EBV infection, laboratory confirmed.
• First symptoms > 3 and < 6 weeks away

Exclusion Criteria (pertaining to both groups)

• Co-morbidity, including mental illness (seasonal allergy/asthma is accepted if no signs/symptoms)
• Usage of pharmaceuticals (hormonal contraception and paracetamol/ibuprofen is accepted)
• Concurrent demanding life event causing fatigue.
• Disability impacting on daily living.
• Regular smoking
• Usage of illicit drugs
• Pregnancy

The population served by the South-Eastern Norway Regional Health Authority (approximately 3.1M)

Anonymized IPD from all elements of MAP-FAT will be shared at a trusted, public repository such as ZENODO. We will adhere to the FAIR (findable, accessible, interoperable, reusable) principles:

• A unique and persistent Digital Object Identifier (DOI) will be assigned to each item in the public repository, thus making them easily findable.
• MAP-FAT (meta)data will be retrievable by its identifier; all beneficiaries will ensure open access to the deposited data, following the principle 'as open as possible as closed as necessary'.
• MAP-FAT (meta)data will use a formal, accessible, shared, and broadly applicable language for knowledge representation. Interoperability resources such as FAIRsharing will be applied.
• The conditions under which the data can be used will be made transparent through easy-to-use copyright licenses, such as Creative Commons (Creative Commons Attribution International Public License, CC BY) or Creative Commons Public Domain Dedication (CC 0).

Start date: six monhts after last patient to follow-up (anticipated Oct 2027) End date: After five years

Cf. above. Anonymized data will be shared at a public repository. Data will be made available for scientific purposes upon request.