Proteomic analysis of post-COVID condition: Insights from plasma and pellet blood fractions, 2024, Seco-González et al

Proteomic analysis of post-COVID condition: Insights from plasma and pellet blood fractions

Alejandro Seco-González, Paula Antelo-Riveiro, Susana B. Bravo, P.F. Garrido, M.J. Domínguez-Santalla, E. Rodríguez-Ruiz, Á. Piñeiro, R. Garcia-Fandino

Background
Persistent symptoms extending beyond the acute phase of SARS-CoV-2 infection, known as Post-COVID condition (PCC), continue to impact many individuals years after the COVID-19 pandemic began. This highlights an urgent need for a deeper understanding and effective treatments. While significant progress has been made in understanding the acute phase of COVID-19 through omics-based approaches, the proteomic alterations linked to the long-term effects of the infection remain underexplored. This study aims to investigate these proteomic changes and develop a method for stratifying disease severity.

Methods
Using Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) technology, we performed comprehensive proteomic profiling of blood samples from 65 PCC patients. Both plasma and pellet (cellular components) fractions were analyzed to capture a wide array of proteomic changes associated with PCC.

Results
Proteomic profiling revealed distinct differences between symptomatic and asymptomatic PCC patients. In the plasma fraction, symptomatic patients exhibited significant upregulation of proteins involved in coagulation, immune response, oxidative stress, and various metabolic processes, while certain immunoglobulins and proteins involved in cellular stress responses were downregulated. In the pellet fraction, symptomatic patients showed upregulation of proteins related to immune response, coagulation, oxidative stress, and metabolic enzymes, with downregulation observed in components of the complement system, glycolysis enzymes, and cytoskeletal proteins. A key outcome was the development of a novel severity scale based on the concentration of identified proteins, which correlated strongly with the clinical symptoms of PCC. This scale, derived from unsupervised clustering analysis, provides precise quantification of PCC severity, enabling effective patient stratification.

Conclusions
The identified proteomic alterations offer valuable insights into the molecular mechanisms underlying PCC, highlighting potential biomarkers and therapeutic targets. This research supports the development of tailored clinical interventions to alleviate persistent symptoms, ultimately enhancing patient outcomes and quality of life. The quantifiable measure of disease severity aids clinicians in understanding the condition in individual patients, facilitating personalized treatment plans and accurate monitoring of disease progression and response to therapy.

Link | PDF (Journal of Infection and Public Health) [Open Access]

 

Tying -omics to severity is a recent hope of mine. I have not read the paper yet so cannot be sure it does so properly, but the goal seems worthy.

 

I don't know what pellet is. There's not much information online. Maybe this paper has some information:

From this thread's paper. I think it says RBCs are overrepresented in pellet compared to plasma.

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"Volcano plot of differentially expressed proteins in cluster 2 (mostly symptomatic) versus cluster 1 (mostly asymptomatic), using the plasma fraction."


Upregulated proteins involved in coagulation:

Upregulated proteins involved in innate immune response:

Upregulated proteins involved in adaptive immune response:

Upregulated proteins involved in oxidative stress response:

Upregulated transport proteins

Upregulated proteins related to metabolic processes

Upregulated proteins involved in cytoskeletal integrity

Other significant upregulated proteins:

Downregulated proteins involved in adaptive immune response:

Other downregulated proteins:

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"Volcano plot of differentially expressed proteins in mild-PCC versus severe-PCC groups using the pellet blood fraction."

Much less skewed using pellet. There is more listing in the paper of proteins involved in various processes as above but for pellet, but I don't want this post to be extremely long.

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They made some kind of severity metric using protein levels. As far as I understand, it was made without referencing the group status, just an equation based on the unsupervised clustering results in plasma (A) and pellet (B). This is how the severity metric splits the groups:


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Was curious what the difference is between the two types of mannose binding lectin, MBL2 vs MBL1 (Link):

So I guess humans only have MBL2.

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First time I've seen that in a paper.

 

I think the volcano plots are comparing the two clusters from the unsupervised clustering, not symptomatic vs asymptomatic, which I don't really understand the reason for.

Edit: I guess maybe they're assuming the clustering reveals a subtype of LC?

 

I'm not quite sure how to interpret the volcano plot based on clustering. Whether it's possible the reason so many are upregulated and so few are downregulated is based on clustering, like the algorithm decided something like "all the people with low proteins go in cluster 1, all the high ones go in cluster 2". Maybe someone who understands this can explain.

In any case, I think it said there is 85% overlap between symptom status and clustering.

But anyway, the volcano plot again:

If this study is actually showing that expansive protein upregulation is a feature of long COVID, we've previously seen the same thing. David Price presented that at the PolyBio symposium:

I'm not sure if that has been published anywhere. Large numbers of proteins were mostly upregulated in each of four diverse body systems (inflammation, cardiometabolic, neurology, oncology).

He said "This really, I think, reinforces the fact that long COVID is a systemic disease". That doesn't explain why everything is upregulated. If half the significant proteins in neurology were downregulated, neurology could still be involved.

Is there some mechanism that can cause all protein expression to be increased, no matter what it is?

I asked the AI Claude that question. It gave this list. Some or all of this might be wrong, but maybe someone who knows more might see something in here that would fit:

 

Probably because ChatGPT partly wrote it, as they disclose.

I also was very confused. I just assumed they meant recovered, but I'm not sure. It might mean low number of symptoms.

Figure 3C has the reported symptoms of each patient:


Hard to read the symptoms, but there are some participants with no symptoms. (Edit: Though by my count there are only 5 participants with no symptoms out of 65.)

 

Proteomic and metabolomic profiling of plasma uncovers immune responses in patients with Long COVID-19, 2024, Wei et al

This preprint did untargeted proteomics as well.

Not as striking as the previous two studies I referenced, but still more proteins are upregulated than downregulated when comparing LC to never infected (56%) or LC to recovered (57%).

 

I haven't read this yet, but it may mean "not yet symptomatic" - ie like a cardiovascular or diabetic risk profile before angina/MI or DM declares months/years later.

Their previous paper is Lipidomics signature in post-COVID patient sera and its influence on the prolonged inflammatory response (2024, Journal of Infection and Public Health)

Edit: no this was a prospectively tracked cohort of 65 patients. They had blood samples taken at a single time-point (variable between the patients) following confirmed infection (non-hospitalised). The term "PCC" seems to be being used as the condition of being post-Covid, so some are symptomatic and some asymptomatic at the time of their blood sample. They do look at patient status: at 90 days, 9 months; and at sample collection. Some patients had no symptoms at 9 months.

 

This study did untargeted proteomics, but on extracellular vesicles not plasma:

Dysregulation of extracellular vesicle protein cargo in female ME/CFS cases & sedentary controls in response to maximal exercise, 2023 Giloteaux et al



Split evenly at baseline, most proteins downregulated at 15 minutes post-exercise, maybe slightly more upregulated at 24 hours post-exercise.

I found this interesting though:


These are separate volcano plots for ME/CFS and controls. Each one shows the level of proteins in the group 15 minutes after exercise compared to before exercise. In both groups there is widespread upregulation of proteins in EVs due to exercise.

 

Data-independent LC-MS/MS analysis of ME/CFS plasma reveals a dysregulated coagulation system, endothelial dysfunction, downregulation of complement machinery, 2024, Nunes, Kell, Pretorius et al

This one did proteomics on plasma, like the first three studies, but on ME/CFS. Slightly more proteins upregulated than downregulated in ME/CFS (53% vs 47%), but nothing special.

 

A multi-omics based anti-inflammatory immune signature characterizes long COVID-19 syndrome, 2022, Kovarik et al

And this one in LC, again on plasma, shows the opposite. More downregulated than upregulated. So maybe it's nothing.

 

Oh, one of the "symptoms" listed is "Symptomatic". There are 8 not filled in for this. None of them have any long COVID symptoms. 3 have boxes filled in for medications or unrelated symptoms like high cholesterol.

 

That's unbalanced enough that despite the label I'm wondering if they've actually remembered to log transform on the x-axis. (A protein can rise by more than 100% but not fall by more than 100%)?!