Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID, 2023, Woodruff et al

Discussion in 'Long Covid research' started by EndME, Jul 14, 2023.

  1. EndME

    EndME Senior Member (Voting Rights)

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    Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID

    Abstract

    While immunologic correlates of COVID-19 have been widely reported, their associations with post-acute sequelae of COVID-19 (PASC) remain less clear. Due to the wide array of PASC presentations, understanding if specific disease features associate with discrete immune processes and therapeutic opportunities is important.

    Here we profile patients in the recovery phase of COVID-19 via proteomics screening and machine learning to find signatures of ongoing antiviral B cell development, immune-mediated fibrosis, and markers of cell death in PASC patients but not in controls with uncomplicated recovery. Plasma and immune cell profiling further allow the stratification of PASC into inflammatory and non-inflammatory types. Inflammatory PASC, identifiable through a refined set of 12 blood markers, displays evidence of ongoing neutrophil activity, B cell memory alterations, and building autoreactivity more than a year post COVID-19.

    Our work thus helps refine PASC categorization to aid in both therapeutic targeting and epidemiological investigation of PASC.

    https://www.nature.com/articles/s41467-023-40012-7#article-info
     
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  2. Jonathan Edwards

    Jonathan Edwards Senior Member (Voting Rights)

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    I am afraid that any abstract that contains an instruction to the reader as to the value of the work described is a clear signal to stop bothering to read anything further.
    Conclusions should be factual. Whether the work is useful is up to the reader.
    And there are no data - so presumably there isn't anything important found.
     
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  3. EndME

    EndME Senior Member (Voting Rights)

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    As far as I can see there's a ton of data and it seems every bit of data is easily accessible open source.
     
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  4. SNT Gatchaman

    SNT Gatchaman Senior Member (Voting Rights)

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    Matching was good in terms of time points, a little less well matched for initial disease severity. Doesn't look that well matched in terms of basic demographics. I also couldn't see inclusion dates for SARS2 variant discrimination, or mention of vaccination status. Perhaps that doesn't matter in terms of the analysis they are reporting on.


    Screenshot 2023-07-15 at 1.17.36 PM Medium.jpeg
     
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  5. SNT Gatchaman

    SNT Gatchaman Senior Member (Voting Rights)

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    On initial read-through their findings seem to match some from Persistent serum protein signatures define an inflammatory subcategory of long COVID (2023).

    That paper's abstract said —

    This paper said —

    Screenshot 2023-07-15 at 2.15.39 PM Large.jpeg

    (IFNG looks to be just below threshold on the inflPASC subset volcano plot.)

    Screenshot 2023-07-15 at 2.14.07 PM Large.jpeg
     
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  6. Hutan

    Hutan Moderator Staff Member

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    Indeed, that's really disappointing. To not be anywhere matched on sex or age surely is a problem in proteomics?

    The PCA (Figure 1a) describes relatively little of the variance (PC1 explains 21% of the variance; PC2 explains 6% of the variance), and there's no clear separation of people with Long covid and controls. I so wish Long Covid researchers would select their samples more. Only 64% reported fatigue. Why mix cohorts that were hospitalised with severe Covid-19 with people who had it only mildly? Only 59% of the patient cohort were not hospitalised.

    If they can't select more tightly, it would be good to see more Principle Components Analyses done on homogeneous subsets - e.g. everyone who had mild Covid-19 and with just the people with Long Covid reporting fatigue.
     
  7. Hutan

    Hutan Moderator Staff Member

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    Further on the heterogeneity of the sample, they found that the Long Covid sample divided into two clusters, one of which looked like the healthy controls (on the left in the Fig 3a chart below) and one that was almost completely different (on the right). Pink is PASC, grey is healthy controls.
    Screen Shot 2023-07-15 at 4.09.29 pm.png
    Fig 3b is unsupervised sorting of the PASC sample, with the division into the two groups (blue and red).
    Screen Shot 2023-07-15 at 4.09.50 pm.png

    The researchers have termed these inflammatory and non-inflammatory PASC, and, if I'm assuming right, the non-inflammatory PASC looks most similar to the controls on inflammatory markers.

    Fig 3e and 3f show that the differences between the two subgroups aren't just related to the severity of the acute infection. The pattern shows in non-hospitalised patients.

    (At this point, I note that the authors clearly have tried to dig into the data to find subgroups in the PASC sample.)
     
  8. Hutan

    Hutan Moderator Staff Member

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    I'm not up to much this afternoon, and have run out of steam to copy charts. But there do look to be some interesting findings. Have a look at the Figure 3 charts.

    On symptom differences:
     
    Last edited: Jul 15, 2023
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  9. Hutan

    Hutan Moderator Staff Member

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    They note that the non-inflammatory PASC group still had proteomic differences compared to the controls
    Despite what they noted about some symptom differences earlier, in the discussion they comment about how symptoms aren't good at discriminating between people in the two groups they identified. They suggest that it will be important to move beyond symptomatic presentation when selecting people for therapy trials.
    They go on to suggest that the inflammatory group might actually be an expression of a phase in the illness, an illness flare, for example, as might be the case if the cause is reactivation of a viral reservoir.
     
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