Immune exhaustion in ME/CFS and long COVID, 2024, Eaton-Fitch et al.

[SNT Gatchaman]

Immune exhaustion in ME/CFS and long COVID
Natalie Eaton-Fitch; Penny Rudd; Teagan Er; Livia Hool; Lara Herrero; Sonya Marshall-Gradisnik

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID are debilitating multisystemic conditions sharing similarities in immune dysregulation and cellular signaling pathways contributing to the pathophysiology. In this study, immune exhaustion gene expression was investigated in participants with ME/CFS or long COVID concurrently.

RNA was extracted from peripheral blood mononuclear cells isolated from participants with ME/CFS (n = 14), participants with long COVID (n = 15), and healthy controls (n = 18). Participants with ME/CFS were included according to Canadian Consensus Criteria. Participants with long COVID were eligible according to the case definition for “Post COVID-19 Condition” published by the World Health Organization. RNA was analyzed using the NanoString nCounter Immune Exhaustion gene expression panel.

Differential gene expression analysis in ME/CFS revealed downregulated IFN signaling and immunoglobulin genes, and this suggested a state of immune suppression. Pathway analysis implicated dysregulated macrophage activation, cytokine production, and immunodeficiency signaling. Long COVID samples exhibited dysregulated expression of genes regarding antigen presentation, cytokine signaling, and immune activation. Differentially expressed genes were associated with antigen presentation, B cell development, macrophage activation, and cytokine signaling.

This investigation elucidates the intricate role of both adaptive and innate immune dysregulation underlying ME/CFS and long COVID, emphasizing the potential importance of immune exhaustion in disease progression.

Link | PDF (JCI Insight) [Open Access]

 

[SNT Gatchaman]

HLA-DQA1, HLA-DQB1, and IGHG1 were found to be pivotal in the top biological pathways and diseases in long COVID, which overlapped with ME/CFS with the addition of IGHG3, CCL2, CEACAM3, and IFNA6.

 

[SNT Gatchaman]

HLA-DQA1 and HLA-DQB1 have been highlighted previously, eg —

Immunometabolic changes and potential biomarkers in CFS peripheral immune cells revealed by single-cell RNA sequencing (2024, Journal of Translational Medicine)

‭Multi-ancestry GWAS of Long COVID identifies‬ ‭immune-related loci and etiological links to chronic fatigue‬ syndrome, fibromyalgia and depression‬ ‭ (2024, Preprint: MedRxiv)

A pilot study on the immune cell proteome of long COVID patients shows changes to physiological pathways similar to those in myalgic encephalomyelitis/chronic fatigue syndrome (2023, Nature Scientific Reports)

Fine mapping of the major histocompatibility complex MHC in myalgic encephalomyelitis/chronic fatigue syndrome ME/CFS suggests involvement of both HLA class I and class II loci (2021, Brain, Behavior, and Immunity)

Human Leukocyte Antigen alleles associated with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome ME/CFS (2020, Nature Scientific Reports)

Even DNA methylation signatures of functional somatic syndromes: Systematic review (2023, Psychosomatic Medicine)

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S4ME search links: HLA-DQA1, HLA-DQB1

 

[forestglip]

HLA-DQA1, HLA-DQB1, and IGHG1 were found to be pivotal in the top biological pathways and diseases in long COVID, which overlapped with ME/CFS

I'm a bit confused about whether the HLA genes are differentially expressed in ME/CFS. That statement seems to say so, but Figures 2 and 3 don't show those genes being significant.

 

[SNT Gatchaman]

Well, that's confusing. Looking at the raw data (normalised counts) from supp file 1 and reordering/transposing —

For HLA-DQA1
HC01 10.6659423
HC02 9.7885739
HC03 11.2015097
HC04 10.3171179
HC05 11.8322613
HC06 11.3585728
HC07 3.23962947
HC08 9.95662161
HC09 12.0608293
HC10 2.33747648
HC11 11.5315697
HC12 11.5688589
HC13 2.56401497
HC14 11.251918
HC15 10.2873327
HC16 10.3869218
HC17 11.1585409
HC18 10.8374035

LC01 9.55748782
LC02 10.3496759
LC03 1.82308287
LC04 11.540439
LC05 2.50327065
LC06 3.82728498
LC07 3.17607999
LC08 11.0519093
LC09 5.03855048
LC10 2.53558357
LC11 1.77570456
LC12 3.10386832
LC13 10.5981617
LC14 3.06462539
LC15 11.3712974

ME01 10.5853984
ME02 2.07604557
ME03 10.0873391
ME04 2.99365564
ME05 10.5596958
ME06 3.30327988
ME07 9.85769108
ME08 11.3484699
ME09 11.3198184
ME10 0.76455194
ME11 2.5244207
ME12 10.640375
ME13 2.76768527
ME14 2.69310125

For HLA-DQB1

HC01 10.6659423
HC02 9.7885739
HC03 11.2015097
HC04 10.3171179
HC05 11.8322613
HC06 11.3585728
HC07 3.23962947
HC08 9.95662161
HC09 12.0608293
HC10 2.33747648
HC11 11.5315697
HC12 11.5688589
HC13 2.56401497
HC14 11.251918
HC15 10.2873327
HC16 10.3869218
HC17 11.1585409
HC18 10.8374035

LC01 9.55748782
LC02 10.3496759
LC03 1.82308287
LC04 11.540439
LC05 2.50327065
LC06 3.82728498
LC07 3.17607999
LC08 11.0519093
LC09 5.03855048
LC10 2.53558357
LC11 1.77570456
LC12 3.10386832
LC13 10.5981617
LC14 3.06462539
LC15 11.3712974

ME01 10.5853984
ME02 2.07604557
ME03 10.0873391
ME04 2.99365564
ME05 10.5596958
ME06 3.30327988
ME07 9.85769108
ME08 11.3484699
ME09 11.3198184
ME10 0.76455194
ME11 2.5244207
ME12 10.640375
ME13 2.76768527
ME14 2.69310125

 

[forestglip]

My best guess is something like, by themselves, the HLA genes weren't significantly different, but when combined with the other genes that make up a pathway, the combination/pathway was significant: "overlapped with ME/CFS with the addition of IGHG3, CCL2, CEACAM3, and IFNA6."

 

[forestglip]

All participants with ME/CFS met the Canadian Consensus Criteria (CCC), excluding 1 participant who reported an improvement in cognitive disturbances since a prior appointment with the Neuroimmunology and Emerging Diseases (NCNED) and fulfilled Fukuda criteria, thus demonstrating the fluctuating nature of the illness.

Body mass index (BMI) differed significantly between cohorts (adjusted P value [Padj] = 0.021), whereby HC reported a significantly lower BMI compared with participants with long COVID (P = 0.016).

100% of ME/CFS and 73.3% of LC had PEM.

I think the genes/pathways most likely to be important would be the ones significant in both LC and ME/CFS, so here are the parts that they have in common:

Gene expression
Downregulated
IGHG1
IGHG2
IGHG3
IGHG4

Upregulated
CEACAM3
PIK3R1
TNFAIP3

Top 5 canonical pathways differed between long COVID and ME/CFS, excluding the macrophage alternative activation signaling pathway (P < 0.0001 and P < 0.0001, respectively). [...] HLA-DQA1, HLA-DQB1, and IGHG1 were found to be pivotal in the top biological pathways and diseases in long COVID, which overlapped with ME/CFS with the addition of IGHG3, CCL2, CEACAM3, and IFNA6.

Ingenuity Pathway Analysis (IPA) was used to determine the association of differentially expressed genes with biological functions and canonical pathways for both ME/CFS and long COVID cohorts when compared with HC (Table 6). [...] Only 2 of the abovementioned biological functions overlap with the ME/CFS cohort: the activation of leukocytes (P < 0.0001) and the activation of antigen-presenting cells (P < 0.0001).

GSA found similarities between participants with ME/CFS and long COVID, including chemokine signaling, type I and II IFN, IL signaling, CTLA4 signaling, DAP12 signaling, JAK/STAT signaling, and TNF signaling. Additionally, the identification of shared biological functions and canonical pathways between ME/CFS and long COVID, such as aberrant lymphocyte morphology and leukocyte activation, highlights commonalities in immune dysregulation across these conditions.

Some other interesting bits:

Downregulated IGHG genes reported in ME/CFS were also observed in long COVID. Frequency and function of IGHG genes are associated with infectious immunodeficiency, allergy, autoimmunity, and malignancy. Interestingly, an increase in IGHG-expressing cells was detected during disease progression in the bronchoalveolar lavage fluid of patients with COVID-19 (32). IgG has a central role in primary immunodeficiency disorders (33). Low serum IgG levels and low levels of IgG subclasses are correlated with diminished defense against pathogens. Various bacterial and viral antigens and allergens affect individuals with particular IGHG haplotypes (33). The investigation of alternative IGHG genes and allele genotypes may elucidate their role in ME/CFS and long COVID. The decreased expression of IGHG may indicate immunodeficiency in participants with ME/CFS or long COVID and may explain their susceptibility to secondary or prolonged infections. Previous investigations have reported that individuals with IgG deficiency often complain of fatigue and that this deficiency is associated with lower QoL (34). However, IgG levels were not investigated in this current investigation.

Previous NanoString technology employed in ME/CFS reported protein kinase gene expression in NK cells (35). This publication reported on 37 upregulated and 55 downregulated genes associated with JAK/STAT and NF-κB activity in a cohort of participants with severe ME/CFS compared with HC. This aligns with results of the present study reporting significantly altered expression of PI3KR1 in participants with ME/CFS or long COVID. However, other protein kinase genes included within the Immune Exhaustion panel did not significantly differ.

In ME/CFS, downregulation of IFN signaling (IFNA4/7/10/17/21 and IFNA6) pathways and immunoglobulin genes (IGHG) suggests a state of immune suppression. However, this may differ from previous research findings reporting elevated IFNA (17–19) and upregulated IGH variable region genes (20), contradicting the role of autoimmunity in the pathogenesis of ME/CFS in this cohort.

The abundance of cell populations was determined according to the expression of cell marker genes using Rosalind Bio. Hierarchical cluster analysis observations demonstrate heterogeneity within cohorts (Figure 4A). The abundance of exhausted CD8 cells was significantly lower in ME/CFS compared with HC (Padj = 0.0147). There were no significant differences in normal CD8 T cells reported.

In the present study, gene expression of TNFAIP3 was significantly upregulated in both ME/CFS and long COVID, presenting potential consistency with previous research.

 

[forestglip]

But, the report says that HLADQA1 and HLADQB1 were down regulated in Long Covid. and they are listed there in Table 3.

I mean significant by themselves in long COVID, but only significant in combination with other genes in ME/CFS, is my interpretation of that sentence.

Edit: I think those significant combinations in ME/CFS that include HLA are in Table 6: activation of leukocytes and activation of antigen presenting cells.

 

[Hutan]

I think the heat maps with their clustering of participants are interesting.

Fig 1: Long covid versus Healthy controls


Look how the HLA genes (in that dense horizontal band in the middle) really differentiate the long covid people from the controls (LC people mostly on the right side of the heat map, with down regulated HLA genes. But, the split between LC and healthy controls is messy, there are quite a few LC in clusters with healthy people on the right hand side of the diagram.

Within the predominately Long Covid side, there are two main clusters. In one the IGHG genes are upregulated; in the other they are downreglated.


Fig 2: ME/CFS versus healthy controls

In the ME/CFS heat map, the ME/CFS people are mostly on the left and they are more cleanly separated from the healthy control. There are also two main ME/CFS clusters. In one, the IGHG genes are down regulated, in the other, the IGHG genes are normal-ish.

In Figure 3, they compare the ME/CFS and LC groups, but just show the mean up or down regulation. I think that's a shame, it would have been good to see the results for each participant. With averaged results, there's not a lot of commonality between the groups, apart from the down-regulated IGHG genes.

I wonder about the HLA results in LC. It is such a clear finding and not replicated in the ME/CFS group. Could there have been a lab error of some sort, I wonder?

 

[forestglip]

I wonder about the HLA results in LC. It is such a clear finding and not replicated in the ME/CFS group. Could there have been a lab error of some sort, I wonder?

I wonder how much duration of illness has to do with differences between groups. Maybe HLA is much more pronounced in the early stages, and I assume LC had shorter durations here than ME/CFS, though I don't think they report that data.

 

[DMissa]

I wonder about the HLA results in LC. It is such a clear finding and not replicated in the ME/CFS group

probably time since infection/onset being much shorter in LC than ME? (I havent seen their cohort data or if they include duration of illness tho)

These necessarily rise post infection and wane gradually even in “normal” cases. If more pronounced in LC could be a feature of more severe infection than in recovered covid patients or could reflect pathology, don’t know the direction yet. Could be both at the same time

musing from my phone but seems likely and intuitive

edit: poster before me said the same thing. Haha

 

[Jonathan Edwards]

There seems to be the usual confusion here between genetic studies of HLA-DQ (which alleles you were born with) and gene expression studies in active cells - which are completely different issues. HLA-DQ is present on antigen presenting cells as just part of their make up. I cannot see any reason why shifts in expression rates as measured by mRNA should tell us anything at all. It is more likely to be telling us how old the cells are or some other irrelevance.

The abstract is nonsense as usual.

It is very disappointing that immunology isn't done at a basic level of competence.

 

[Dolphin]

Press release:
Immune exhaustion at the core of new ME/CFS and Long COVID research
https://news.griffith.edu.au/2024/1...e-core-of-new-me-cfs-and-long-covid-research/

https://twitter.com/user/status/1849431981437669811