Preprint Role of the complement system in Long COVID, 2024, Farztdinov, Scheibenbogen et al.

Thanks for posting @SNT Gatchaman, looks interesting, and a lesson in the need to match cohorts.

 

Great that the investigators didn't stop at investigating the proteomics in the Zurich cohort after reassessing with the demographics properly taken into account, but also looked at two cohorts of their own: people post-severe Covid and people post-mild Covid.

Regarding that last cohort, the one likely to be most relevant to ME/CFS, the post-mild Covid:

This study is more evidence that CRP isn't relevant in PACS.

 

Has anyone looked at Supplementary Datafile 5? I don't know what the unit is for the proteins - all of the values seem to be in a very tight range, both between individuals and even between different proteins (ie approx 18 to 21). I assume the figures are the transformed outputs, log adjusted and probably also adjusted by the model that takes age and BMI into account?

There's also stuff about imputed values - from different visits? - in the methodology section.

I'm not up to working it all out, but if someone is across it, it could be interesting to hear about the process and understand it a bit more

 

As I said upthread, I think the post-mild Covid PACS fatigue+ cohort with some of the participants meeting ME/CFS criteria is the cohort of most interest to us.

While I love the overall approach of this paper, (i.e. attempting to account for the noise created by age and sex and BMI), I do think that they could have presented their results more clearly. I also wish that their post-mild Covid PACS cohort had all been compliant with the CCC (or another criteria with PEM). I hope the authors are as excited as I am by their results from the post-mild Covid PACS cohort and are continuing to work on getting some replicable proteomics for well characterised post-Covid ME/CFS.

Here's the volcano chart for the post-mild Covid cohort vs healthy controls, increased in size so the proteins can be read:

I don't know why the Supplementary Data tables don't give us the individual data with the same x axis unit.

Listing out the proteins of interest for the search engine:

Increased:
CFI, LRG1, APOB, IT1H3, CA1, SAA1, IGHV1-2

Decreased:
BTD, LTF, PON1, COMP, IGKVA-1, IGKV1-17, IGHV5-51, GP1BA, IGLV8-61, CFD, MMRN1, PTEN, PROZ, IGHV3-7, RBP4, IGLV1-51, LUM, FN1, PFN1, TAGLN2

That's a clear illustration of how important it is to use a well characterised disease sample. Rather than PON3 being increased, as found in the initial cohort with its mixture of post-Covid consequences, it appears that PON1 was decreased in PACS-ME/CFS patients.

Looking for significant proteins is complicated in that it's not just a matter of proteins being elevated or decreased in the plasma. For one thing, it could be the levels of the protein in a particular tissue in the body that makes a difference, and the levels in plasma may or may not reflect that, or might even show the opposite quantity. As @SNT Gatchaman notes, PON1 is part of the GWI story. With the GWI work, it was found that different versions of the PON1 gene made people more or less vulnerable to neurotoxic sarin gas exposure, because one version is less good at detoxifying sarin. So, the researchers wouldn't necessarily find lower levels of the PON1 protein as a whole in the GWI patient's blood. What I think they found was a correlation between [the number of versions of the PON1 gene that was less good at detoxifying sarin (0,1,2) in the person's DNA] and [likelihood of developing GWI], while taking into account frequency of exposure to sarin.

Still, it's intriguing that lower levels of PON1 is there in the PACS fatigue+ group, perhaps suggesting that something is suppressing the body's response to toxins?
(edit - sorry, fixed the last sentence)

 

Thanks SNT, very helpful links.

I know googling proteins can be like reading your horoscope in that there's usually something there that feels personally relevant. It's also fun.

Here's a few with high fold change and/or high p values but otherwise randomly chosen.

increased CA1 - from the Wikipedia entry:

decreased BTD - biotinidase (note, I don't think the results are suggesting a profound deficiency in the PACS cohort)
Biotinidase Deficiency

It's worth noting even as just another possible differential diagnosis for FMD and functional seizures - how many people with a functional diagnosis have been tested for BTD?


IG - immunoglobulin proteins
increased - IGHV1-2
decreased - IGKVA-1, IGKV1-17, IGHV5-51, IGLV8-61, IGHV3-7

The IGL stands for the lambda light chains
The IGK stands for the kappa light chains
The IGH stands for the heavy chains

That pattern of some IGH's being decreased and one increased is intriguing, is it just noise? The increased IGHV1-2 might well be, it's only just significant in the volcano plot F (shown above).

 

I agree that it's nice to see researchers critically looking at studies and having a go to demonstrate the problems. I hope what they have done isn't seen as impolite or fighting though. It's science at work, it's exactly what we need much more of.

Us complaining about cohort matching here on the forum doesn't achieve much. We get better at dismissing findings, but still the misleading papers come. Whereas papers like this, examining the consequences of ignoring cohort differences, will be remembered by young researchers for the rest of their careers, and will help improve their work.