Reactivated EBV, HHV6, HAdV in Sputum from ME/CFS Patients: Are autoAbs to IFN-I Impairing Antiviral Immunity?, 2025, Hannestad et al.

Now published. Minor changes to abstract wording. I haven't checked the differences in the full text. Though the inconsistency in the EBV chart is still there.

Prevalence of EBV, HHV6, HCMV, HAdV, SARS-CoV-2, and Autoantibodies to Type I Interferon in Sputum from Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Patients

Ulf Hannestad, Annika Allard, Kent Nilsson, Anders Rosén

[Line breaks added]


Abstract
An exhausted antiviral immune response is observed in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and post-SARS-CoV-2 syndrome, also termed long COVID. In this study, potential mechanisms behind this exhaustion were investigated.

First, the viral load of Epstein–Barr virus (EBV), human adenovirus (HAdV), human cytomegalovirus (HCMV), human herpesvirus 6 (HHV6), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was determined in sputum samples (n = 29) derived from ME/CFS patients (n = 13), healthy controls (n = 10), elderly healthy controls (n = 4), and immunosuppressed controls (n = 2). Secondly, autoantibodies (autoAbs) to type I interferon (IFN-I) in sputum were analyzed to possibly explain impaired viral immunity.

We found that ME/CFS patients released EBV at a significantly higher level compared to controls (p = 0.0256). HHV6 was present in ~50% of all participants at the same level. HAdV was detected in two cases with immunosuppression and severe ME/CFS, respectively. HCMV and SARS-CoV-2 were found only in immunosuppressed controls.

Notably, anti-IFN-I autoAbs in ME/CFS and controls did not differ, except in a severe ME/CFS case showing an increased level.

We conclude that ME/CFS patients, compared to controls, have a significantly higher load of EBV. IFN-I autoAbs cannot explain IFN-I dysfunction, with the possible exception of severe cases, also reported in severe SARS-CoV-2. We forward that additional mechanisms, such as the viral evasion of IFN-I effect via the degradation of IFN-receptors, may be present in ME/CFS, which demands further studies.

Link | PDF (Viruses) [Open Access]
 
High EBV but normal anti-IFN-1 autoAbs seems to support one pattern I keep coming back to:

Epoch1. Prior to infection
a) stress and “over-doing” things causes HPA activation to create sustained cortisol elevation
b) high cortisol (initially may enhance innate immunity) if sustained can inhibit T/NK cells, reducing immune surveillance

Epoch2. Infection by some virus/pathogen (which one may not matter)
a) contributes to immune exhaustion
b) enables reactivation of latent EBV

Epoch3. Post-infection ME/CFS
a) immune exhaustion + reactivated EBV means chronic EBV symptoms, especially PEM
 
I posted about the plot on Pubpeer and the author responded:
Thank you for pointing out this error. We have looked into the details and find the following: five healthy donors are negative for EBV and 5 positive in Fig. 2A. The top point appears as a duplet which is a misprint - only one donor had 882,000 EBV copies/mL. The error appeared during image copying from JMP statistical program into Powerpoint giving a duplex. The reason for this image reproduction /tranfer error is not known and the 'bug' will be reported to JMP Statistical Inc. The correct image will be inserted into the Viruses journal as soon as possible. Thanks again for alerting us on this issue. Best regards, Anders Rosén corresponding author
 
I posted about the plot on Pubpeer and the author responded:
So they are adamant that the underlying data has not been affected?

A duplicate in the plot could also indicate that the data had an error - how do we know if other analyses have been affected?

Surely they would have to rerun their calculations now - and I’m slightly concerned that they don’t mention doing it.
 
ME Research UK:

Prolonged exposure to viral infections, such as Epstein Barr Virus which causes glandular fever, could be linked to immune exhaustion in people with ME/CFS.

Therefore, a small study in Sweden looked to investigate whether higher numbers of cells from several different viruses could be identified in people with ME/CFS compared to those without the disease.

Read more about what the study found here: https://tinyurl.com/3d63zwwh
 
So they are adamant that the underlying data has not been affected?

A duplicate in the plot could also indicate that the data had an error - how do we know if other analyses have been affected?

Surely they would have to rerun their calculations now - and I’m slightly concerned that they don’t mention doing it.
From the comment it seems like the duplicate appeared after the image had already been generated in their statistical software and was a visual artifact of copying into PowerPoint.

So if the original image didn’t have the duplicate point, which seems to the be case, there’s no actual duplicate in the data and no need to rerun the tests.
 
From the comment it seems like the duplicate appeared after the image had already been generated in their statistical software and was a visual artifact of copying into PowerPoint.

So if the original image didn’t have the duplicate point, which seems to the be case, there’s no actual duplicate in the data and no need to rerun the tests.
I don’t have a computer science background, but I struggle to think of any process for storing or copying images that would result in duplication of only a few selected pixels in a limited area of the image, in a way that matches the visual characteristics of the same image.
 
Back
Top Bottom