Preprint Blood transcriptomics reveal persistent SARS-CoV-2 RNA and candidate biomarkers in Long COVID patients, 2024, Menezes et al.

Published as a preprint. See post #7
And now published in final form - link here
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This is an abstract from the Demystifying Long COVID International Conference 2023, converted from an image on Twitter, so it might be slightly wonky, but it looks intriguing.

Blood Transcriptomics Reveal Persistent SARS-COV-2 RNA And Candidate Clinical Biomarkers in A Belgian Long COVID Cohort
Menezes S, Jamoulle M, Carletto M, Van Holm B, Moens L, Meyts I, Maes P, Van Weyenbergh

Background: With millions of people currently suffering from Long COVID (LC), validated therapeutic options and biomarkers are direly needed to guide clinical management. In this study, we propose whole blood transcriptomics to identify non-invasive candidate biomarkers for viral persistence, disease severity and clinical evolution in a general practice-based cohort.

Materials and Methods: A cohort of LC patients (diagnosis according to WHO criteria) was followed up for 1-30 months after acute COVID. Complete clinical history and follow-up was obtained at a single general practice (MJ, Charleroi, Belgium) using electronic health records and several established clinical scales (DUSOI Duke Severity Overall Index, COOP Dartmouth Coop chart initiative) were used to quantify patient evolution. Severe neurocognitive deficits were confirmed by brain scintigraphy (SPECT), with 25/48 patients (52%) displaying vascular defects.

Whole blood samples were obtained from 48 LC patients and 12 controls (matched for age, sex, time since acute COVID-19, vaccination status and comorbidities) and analyzed by digital transcriptomic analysis (nCounter, Nanostring) to quantify a total of 800 RNAS (SARSCOV2 and innate/adaptive immunity), as previously established for critical COVID-19 (Menezes et al., Lancet Microbe 2021). Neutralizing antibodies against 10 different SARSCOV2 variants. were quantified using a sensitive electrochemoluminescent assay (MSD). Statistical analysis included non-parametric Mann- Whitney test, Spearman correlation and multivariable logistic regression.
Results: Digital transcriptomic analysis revealed a total of 212 differentially expressed genes between LC patients and matched controls.

Among 120 transcripts significantly increased in LC were several viral RNAs: Nucleocapsid, ORF7A, ORF3A, Mpro (target of Paxlovid) and antisense RNA, the latter suggesting ongoing viral replication, while Spike RNA was remarkably low/absent. In addition, several SARSCOV2-realted host genes were also increased in LC (ACE2/TMPRSS2 receptors and DPP4/FURIN proteases). Other upregulated RNAs were specific for memory B cells (CD27/IGHE/BMP8A), and platelets (CD99/PBX1/PDZK1IP1). Platelet transcripts were also positively corelated to viral load (p<10-7), providing a mechanistic link to the hypercoagulative state previously demonstrated in LC. Summarizing these 800 transcripts into biological pathways, we found significantly decreased TLR signaling (p=0.0039), lymphocyte activation (p=0.016) and immunometabolism (p=0.023) in LC patients. Moreover, immunometabolism was negatively correlated with blood viral load (R=-0.56, p<0.0001), suggesting an "exhausted" immune status in LC due to ongoing viral replication.

Using multivariable regression, we found that age and sex were not associated with "low" vs. "high" viral RNA status, whereas the number of comorbidities (1.61 95% CI [1.14-2.49], p=0.014) and the number of COVID vaccine doses (0.36 95% were CI [0.14-0.79], p=0.018) independent predictors of "low" vs. "high" status, confirming a protective role of vaccination. SPECT-positive patients could be discriminated from SPECT- negative by increased RNA levels of insulin receptor (INSR) and platelet P-selectin (SELP), further incriminating perturbated platelet
and (immuno)metabolism activation/coagulation in disease severity.

Conclusions: We used digital transcriptomics to identify non-invasive (blood) biomarkers for viral persistence, disease severity and clinical evolution, guided by SPECT imaging. Overall, increased platelet RNAs and decreased immunometabolism are significantly correlated to viral load, providing mechanistic links as well as therapeutic targets to tackle Long COVID.
Demystifying Long COVID International Conference 2023

 

A recording of the talk, as well as of every other talk can also be found on YouTube www.youtube.com/watch?v=gEsjR2y6fzs. When such "phenomenal" and very interesting preliminary results, which do significantly differ from previous results, are presented by a new team from a "smaller" lab I find it impossible to say whether it's mostly noise or indeed a groundbreaking finding. It certainly means that I'll be keeping an eye out for the paper.

 

Thanks @EndME! Here's a link to the start of this specific talk.

 

I've made a thread for this conference: day 1 here.

 

A small group of patients were followed before and after first and second line treatments. GP-based "real world" cohort. Observational not an interventional trial.

First line treatment is targeting platelets and the microcirculation: aspirin + clopidogrel + piracetam
Second line treatment is targeting viral persistence: paxlovid (off-label)

Transcriptomics (nanoString): viral RNA

The patients having paxlovid had samples at day 0 and day 15 of treatment. In the Q&A he said the patient reported outcomes showed symptom return following ceasing paxlovid.

In LC the volcano plot showed upregulation of viral, platelet and B cell (noting IgE heavy chain) transcripts.

Reducing the plot to a simplified diagram shows heterogeneity in patients. Eg for "immunometabolism" there is a homogeneous response in HCs but heterogenous in LC with both up and down on the pathway scores.

 

However that heterogeneity in the immunometabolism score correlated with viral RNA load.

 

Merged thread

Blood transcriptomics reveal persistent SARS-CoV-2 RNA and candidate biomarkers in Long COVID patients
Soraya Maria MENEZES; MARC JAMOULLE; Maria P Carletto; Bram Van Holm; Leen Moens; Isabelle Meyts; Piet Maes; Johan Van Weyenbergh

With an estimated 65 million individuals suffering from Long COVID, validated therapeutic strategies as well as non-invasive biomarkers are direly needed to guide clinical management.

We used blood digital transcriptomics in search of viral persistence and Long COVID diagnostic biomarkers in a real-world, general practice-based setting with a long clinical follow-up. We demonstrate systemic SARS-CoV-2 persistence for more than 2 years after acute COVID-19 infection. A 2-gene biomarker, including SARS-CoV-2 antisense RNA, correctly classifies Long COVID with 93.8% sensitivity and 91.7% specificity.

Specific immune transcripts and immunometabolism score correlate to systemic viral load and patient-reported anxiety/depression, providing mechanistic links as well as therapeutic targets to tackle Long COVID.


Link | PDF (Preprint: MedRxiv)

 

Details matter and I have not seen the paper, but if this pans out its potentially huge.

 

I've reformatted to add links to GeneCards. From supplementary materials, in order the 70 (FDR) DEGs are —

Spoiler: 70 DEGs

FYN
GATA3
BMP8A
PDZK1IP1
MAPK13
COASY
PTGS2
CD40LG
ETS1
CD99
IL28A
ORF7a
FGFR1
CD276
SOD1
CCL23
CSF3R
VSIR
MIF
IL1B
TLR9
TTK
CCR3
ADGRE1
IGHE
CX3CL1
CLEC7A
CDH4
IL3RA
Nucleocapsid
TMPRSS2
LGALS3
HIST1H1C
CDH1
PBX1
HOXD4
CLC
CCR4
CCR7
SERPINE3
TGM2
CCL18
ALOX15
ARF6
RAF1
TOP2A
FOSB
SARS-CoV-2_orf1ab_REV
BTG2
ITGAX
CSF2RA
CXCL13
ADGRE5
CCL24
ICOS
TLR6
CALR
IL5RA
MYC
PLAU
PTGDR2
DUSP1
CXCL14
TRAC
NFYC
CD28
MAP2K3
ELL2
ABCC8
S1PR1

 

For the top DEG, from GeneCards: FYN — "This gene is a member of the protein-tyrosine kinase oncogene family. It encodes a membrane-associated tyrosine kinase that has been implicated in the control of cell growth. The protein associates with the p85 subunit of phosphatidylinositol 3-kinase and interacts with the fyn-binding protein."

Note previous comments relating to WASF3 and metformin —

 

Now published
https://www.thelancet.com/journals/lanmic/article/PIIS2666-5247(24)00055-7/fulltext

 

See also ETS1-mRNA downregulation in Sex differences and immune correlates of Long COVID development, persistence, and resolution (2024, Preprint: BioRxiv)

 

GoFundMe: Your Support is Needed to Validate Long Covid Biomarkers

"Long COVID Foundation is organizing this fundraiser.

LCAP and Long COVID Foundation are excited to announce a chance for the community to fundraise and help validate a non-invasive Long Covid Biomarkers* test capable of FDA approval for clinical use and trials. With help from our grassroots activism, researchers in Belgium will be able to use donations gathered by this campaign to externally validate a set of universal Long Covid biomarkers for immune changes and SARS-CoV-2 viral persistence.

This research is nothing short of a miracle for those of us who’ve developed Long Covid and waited years for biomarkers.



Background

In 2024, Dr. Johan Van Weyenbergh, and his team of researchers, published a groundbreaking paper outlining results of a blood test that could identify Long Covid with 92% certainty using transcriptomic testing equipment that is widely available and can be FDA approved. The current test used in the study processes 800 genes to measure RNA viral load of SARS-CoV-2 and immune RNA at a cost that is roughly $400-$600 per sample. Your donations to this campaign will fund the second round of testing to validate the results discovered in Dr. Van Weyenbergh's research. This validation round will bring the research closer to FDA approval by funding over 100 additional tests from samples in the USA, UK, and France to be published in a new paper.

If our grassroots fundraising is successful, Dr. Van Weyenbergh believes the validated non-invasive biomarkers could be limited to a test of 50 genes, reducing the total cost of each sample in the future to $50-$100. This would radically change the ability of the NIH to run affordable validated biomarker tests in ongoing RECOVER trials and independent studies, as well as open access to more affordable Long Covid tests in clinical settings."

 

This sounds like a lot of parameters for one blood test. Is there a diagnostic test in clinical use that uses (if they get to this point) "a test of 50 genes"?

My gut says that having so many features plugged into a test is going to increase the chance of being nonspecific to clinically-similar conditions

 

From what I've heard they've already looked at this tests in independent cohorts and the success has been rather variable. Controlling for reinfections and quantifing data according to LC duration and date of last known infection will be key for any Long-Covid "viral-persistence markers".

 

is this a valuable thing to contribute money towards for those of us who might have some money to contribute and/or friends & family?

 

The LCAP has a very bad reputation and is extremely controversial. I'm also not sure what half of the stuff they are saying is supposed to mean for example "with help from out grassroots activism", does that just mean you're collecting money for this research project and giving it to these researchers? If they are just collecting money for one research group and project and giving it to that group, I can't see anything wrong with that at all. Of course one can also just donate to the researchers directly, which seems far more sensible for larger sums of money but for visibility donating smaller amounts might be beneficial in this campaign.

 

Notable that this is the bad LCAP group, the ones who constantly harass women and reject any and all notion that LC is not a completely unique precious little puppy that sprung into existence in 2020 and has zero overlap with any other chronic illness.