Preprint Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explicable by inactivity, 2024, Beentjes, Ponting et al

Some questions that were going around my head today.

What sort of sample size would be needed to replicate this do we think? This has ~1500 people with ME, could a study be done with this (or fewer) people with ME and compared to the healthy controls in the biobank data?

Would it be possible to do a study with say, a subset of the DecodeME cohert, to see what the results were in a more clearly defined group and across different severities?

What are the minimum blood tests needed to compare?

Given most of us in DecodeME will have had common blood test results done is there anything that can be analysed with access to our NHS records as a starting point?

Jonathan Edwards said:
For me the real prize would be if one or more of these proteins matched a signal on DecodeME in some way
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That would be nice! Presumably that would give people a clearer idea of what to focus on but also encourage and support research and funding?
 
hotblack said:
What sort of sample size would be needed to replicate this do we think? This has ~1500 people with ME, could a study be done with this (or fewer) people with ME and compared to the healthy controls in the biobank data?
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I think you could try to replicate findings for individual markers with quite a small sample of maybe just 100 people from DecodeME. But there are issues with controls. The UK Biobank is OK to use as a source of healthy controls in terms of genes. But I think the age window would be different from that for DecodeME. So you might well not be comparing like with like. Possibly you could look at DecodeME cases aged 40-70, but the population being drawn from may be different.

Individual results for any given person do not tell us much because all these values are probably within the normal range. The meaningful result is the difference across a population/cohort. Results from routine care are probably not useful because all these tests are likely to be calibrated slightly differently in different labs.

There are lots of test that one could compare. It is not clear which of these are truly related to ME/CFS and in what way.
 
I can’t remember what has been discussed on this thread already so I apologise if this is a repeat but a thought occurs to me: Samples were taken from the UK biobank. Given reported high rates of misdiagnosis by GPs, and the lack of requirement to have even been diagnosed by a doctor in order to be categorised as having ME/CFS for the biobank, it seems likely that there may be a high percentage of people in this study who are classed as having ME/CFS but do not meet any useful diagnostic criteria for the illness. What I’m wondering is whether a significant percentages of those cases may have the same undiagnosed conditions which are causing patients to wrongly think they have ME/CFS. Is it possible that it is the signals from conditions which are commonly misdiagnosed (and mis-self-diagnosed) as ME/CFS which are showing up in the data?

If it is possible, I hope* DecodeME may be able to tell us whether or not it is the case.

*Edit: changed wording.
 
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Robert 1973 said:
Is it possible that it is the signals from conditions which are commonly misdiagnosed (and mis-self-diagnosed) as ME/CFS which are showing up in the data?
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Yes, and I have discussed this with Chris in detail. There is actually a problem the other way around too. If ME/CFS is underdiagnosed the diagnosed Biobank cases may not be representative of people with ME/CFS because they may have got their diagnosis for confounding reasons. One simple scenario is that if they also have another problem, whether or not diagnosed, that takes them to doctors frequently they may see more doctors and since only a proportion of doctors use the ME or CFS labels they will be more likely to be (correctly) diagnosed with ME/CFS.

And with a large sample you are almost guaranteed to pick up confounding associations of that sort which, paradoxically, would not show up on smaller studies.

DecodeME should help because the cohort ascertainment was better. There is still the same risk to a degree but I think it will be less. Also the risk is likely to be much less for gene associations I think. And of course the causal analysis is much easier because genes have to be upstream. In a way I see this study as a reassurance that one can demarcate how big an influence confounding factors are likely to have under what circumstances.
 
The paper found high ALT/ALAT levels to be associated with ME. I looked through my blood tests and that doesn’t match my n=1 results. And I have a lot of blood tests done lol. For reference according to most websites a normal level is from around 7-50 U/l. These are my blood test results for ALT:


A month after getting COVID: 6 (ME/CFS like two month long “crash”)

Three months after: 7 (mostly recovered)

Six months after: 13 (mild ME)

1 year three months: 9 (severe ME)

1 year four months: 6 (severe ME)

2 years after: 12 (very severe ME)
 
Yann04 said:
The paper found high ALT/ALAT levels to be associated with ME. I looked through my blood tests and that doesn’t match my n=1 results. And I have a lot of blood tests done lol. For reference according to most websites a normal level is from around 7-50 U/l. These are my blood test results for ALT:


A month after getting COVID: 6 (ME/CFS like two month long “crash”)

Three months after: 7 (mostly recovered)

Six months after: 13 (mild ME)

1 year three months: 9 (severe ME)

1 year four months: 6 (severe ME)

2 years after: 12 (very severe ME)
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Mine are normal too, except for one time ALT was randomly high at 92. My doc immediately retested and got 20.

TIBC, AST were also higher than my normal values for this test. AST returned to normal as well for the followup, and she didn't retest TIBC.
 
Not really much going on for ALT in the deep phenotyping study.

There's one outlier with 548, so the second plot is just zoomed in to everyone else. No one else has abnormal values, and not much difference between groups except maybe 2 participants are a little higher and 1 is very high.
ALT (U_L)_box.png ALT (U_L)_box.png
 
Trying to have another look at this paper.

For the proteomics, the following seem to be the values that stand out most. I've extracted the following values from the data (Using direct effects).

Name(abbreviation), cohen_d_raw_data, z_value_modelled, corrected_p_value

Males
Butyrylcholinesterase (BCHE), 0.796, +5.3, 0.000313,
Apolipoprotein D (APOD), 0.427, -4.91, 0.00130
Leptin (LEP) - increased, 0.652, 4.81, 0.00142

Females
Neutral ceramidase (ASAH2), 0.315, +4.75, 0.00517
Inactive serine protease (PAMR1), 0.314, +4.59, 0.00517
Coiled-coil domain-containing protein 50 (CCDC50), 0.280, -4.55, 0.00517

Combined
Complement factor H (CFH), +0.694 male, +0.491 female, 5.85, 0.0000143
Extracellular superoxide dismutase (SOD3), -0.274 male, -0.21 female, -4.88, 0.00159
 
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ME/CFS Skeptic said:
Complement factor H (CFH), +0.694 male, +0.491 female, 5.85, 0.0000143
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Wikipedia
Due to the central role that factor H plays in the regulation of complement, there are a number of clinical implications arising from aberrant factor H activity. Overactive factor H may result in reduced complement activity on pathogenic cells – increasing susceptibility to microbial infections.
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ME/CFS and Long COVID

SARS-CoV-2 hijacks host CD55, CD59 and factor H to impair antibody- dependent complement-mediated lysis, 2024, Gebetsberger et al
Here, we demonstrate that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hijacks host cellular RCA members CD55 and CD59 and serum-derived Factor H (FH) to resist antibody-dependent complement-mediated lysis triggered by immunized human sera. Blockage of the biological functions of virion-associated CD55 and CD59 and competition of FH recruitment with functionally inactive recombinant FH-derived short consensus repeats SCR18-20 restore SARS-CoV-2 complement sensitivity in a synergistic manner. Moreover, complement-mediated virolysis is dependent on classical pathway activation and does not occur in the absence of virus-specific antibodies.

https://doi.org/10.1080/22221751.2024.2417868
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Preprint - Role of the complement system in Long COVID, 2024, Farztdinov, Scheibenbogen et al.
The statistical analysis of this cohort revealed among others the C-reactive protein (CRP), Apolipoprotein A-II (APOA2), Alpha-1-acid glycoprotein 2 (ORM2) and the CS regulator Complement factor H-related protein 5 (CFHR5) to be less abundant in PACS (Figure 1E). Only Properdin (CFP), a regulator of the alternative complement pathway, was significantly, albeit only slightly, upregulated in PACS patients.
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Persistent complement dysregulation with signs of thromboinflammation in active Long Covid, 2024, Boyman et al
In 6-month Long Covid patients, C5 was the only TCC component with significantly altered total levels (fig. S4H). Analysis of additional complement components showed increased complement regulatory proteins factor I, factor H, and C4-binding protein beta (C4BPB) and confirmed increased C2 in 6-month Long Covid patients (Fig. 4KOpens in image viewer).
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Pathway-focused genetic evaluation of immune and inflammation related genes with chronic fatigue syndrome, 2015, Rajeevan et al
For CFH, four SNPs, rs1061147 (G/T polymorphism), rs7529589 (C/T polymorphism), rs1061170 (T/C polymorphism) and rs10801555 (G/A polymorphism), were in high LD (Fig. 1B). Their respective major alleles G, C, T and G were associated with CFS in both allele (72–73% CFS vs 56% NF; p = 4.81–6.5 × 10−3) and haplotype analyses. Haplotype GCTG was 2 times more likely to be associated with CFS than NF (OR = 2.07; CI = 1.24–3.45; p = 4.8 × 10−3).
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Targeted proteomics identifies circulating biomarkers associated with active COVID-19 and post-COVID-19, 2022, Zoodsma et al
Hub proteins for post-COVID-19 individuals included cytastatin 3 (CST3), Notch homolog 1, translocation-associated (NOTCH1), complement factor H-related 5 (CFHR5), and ST6 beta-galactoside alpha-2,6-sialyltransferase 1 (ST6GAL1).
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Complement dysregulation is a predictive and therapeutically amenable feature of long COVID, 2023, Morgan et al
Moreover, we found that plasma concentrations of several complement regulators, namely C1INH, FD, properdin, FH, and clusterin, were relatively elevated in patients with long COVID.
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Other conditions

Increased plasma complement factor H is associated with geriatric depression, 2019, Shin et al

The human complement factor H: functional roles, genetic variations and disease associations, 2004, Rodrı́guez de Córdoba et al

The role of complement Factor H in age-related macular degeneration: a review, 2010, Donoso et al

Complement 3 and factor h in human cerebrospinal fluid in Parkinson's disease, Alzheimer's disease, and multiple-system atrophy, 2011, Wang et al
In contrast, FH concentration, although not altered significantly in patients with PD, tended to increase in both the MSA and AD groups compared with the control and PD groups, and statistical significance was achieved when differentiating AD from control (P < 0.0001) and from PD (P < 0.0001) after adjustment for age, sex, and Hb. Significant differences also were observed when data for male and female participants were analyzed separately (Figure 1B and Table 1). However, none of the ROC calculations yielded acceptable (<60%) sensitivity and/or specificity for classifying any diseases when C3 or FH was used alone (data not shown).
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Complement regulator factor H as a serum biomarker of multiple sclerosis disease state, 2010, Ingram et al
Multiple sclerosis has a variable phenotypic presentation and subsequent disease course that, although unpredictable at disease onset, is of crucial importance in guiding interventions. Effective and accessible biomarkers are required in order to stratify patients and inform treatment. We examined whether the complement regulator factor H and its Tyr402His polymorphism, recently implicated as biomarkers in other chronic inflammatory central nervous system conditions, might identify or predict specific pathological processes and outcomes in multiple sclerosis. Employing novel assays, we measured factor H and its His402 variant in serum from 350 patients with multiple sclerosis classified according to disease course and relapse status. Serum factor H levels were significantly higher in progressive disease (P < 0.001) compared to controls and relapsing patients, after controlling for variables including disease duration, age, gender, disability and treatment. Serum factor H levels were capable of distinguishing secondary progressive from relapsing remitting disease (excluding patients in clinical relapse) with a sensitivity of 89.41%, specificity of 69.47% and a positive predictive value of 72.38%. Acute relapse was also associated with transiently increased factor H levels (P = 0.009) compared to stable relapsing disease. In clinically stable patients, factor H levels remained constant over 1 year (coefficient of variation percentage = 6.8), however, in patients in transition from relapsing to progressive disease, factor H levels significantly increased over a period of 2 years (P = 0.007). Concentration of the His402 variant in heterozytgotes was significantly higher in secondary progressive (P < 0.01) and primary progressive (P < 0.05) disease, suggesting altered expression or consumption of variants when factor H is upregulated. Serum factor H may be an effective indicator of progression and a practical and accessible biomarker and stratifying tool in determining disease course, providing objective evidence to help guide therapeutic decisions.
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In the absence of clear evidence of inflammation I am doubtful that 'protection against damage' is likely to be what we are looking for, although it is conceivable.

What I find more interesting is the suggestion that complement may be involved in normal day to day neural plasticity (I don't have a citation at hand). If SOD3 and Factor H both have a moderating role in complement mediated events then that might be important.
 
Males
Cholinesterase (BCHE), 0.796, +5.3, 0.000313,
Apolipoprotein D (APOD), 0.427, -4.91, 0.00130
Leptin (LEP) - increased, 0.652, 4.81, 0.00142
Females
Neutral ceramidase (ASAH2), 0.315, +4.75, 0.00517
Inactive serine protease (PAMR1), 0.314, +4.59, 0.00517
Coiled-coil domain-containing protein 50 (CCDC50), 0.280, -4.55, 0.00517
Combined
Complement factor H (CFH), +0.694 male, +0.491 female, 5.85, 0.0000143
Extracellular superoxide dismutase (SOD3), -0.274 male, -0.21 female, -4.88, 0.00159
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Obviously BChE hydrolyses acetylcholine. ApoD has a role in cholesterol metabolism and transport of lipids; leptin obviously affects hunger, body weight, energy use & feeding. ASAH2 is involved in hydrolysing ceramides to sphingosine. I may be completely off-base with this (been a very long time) but something that strikes me is that sex hormones in some way regulate most of the things on that list - if I remember correctly levels of leptin are altered by androgens & oestrogen (?testosterone suppresses), BChE expression is partially regulated by androgens, I think, as is ApoD - not sure about ASAH2 but doesn't oestrogen have an effect on sphingolipid metabolism as well...? Something to look up.

Some papers discussing the role of complement in CNS that I've started to read through:

"The role of astrocytes and complement system in neural plasticity"

"Complement peptide C3a stimulates neural plasticity after experimental brain ischaemia"

"Complement in the Brain"

"Role of Complement in neurodegeneration and neuroinflammation"

"The complement cascade in the regulation of neuroinflammation, nociceptive sensitization, and pain"
 
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Jonathan Edwards said:
In the absence of clear evidence of inflammation I am doubtful that 'protection against damage' is likely to be what we are looking for, although it is conceivable.

What I find more interesting is the suggestion that complement may be involved in normal day to day neural plasticity (I don't have a citation at hand). If SOD3 and Factor H both have a moderating role in complement mediated events then that might be important.
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But aren't complement mediated events inflammatory?
 
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