How does that make sense? If these people with "the same ME/CFS as those in DecodeME" end up in chronic pain cohort then shouldn't the chronic pain study find also the other genes from DecodeME?
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Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration
Ariel
Senior Member (Voting Rights)
Anecdotally I know of more than one case where a person with ME/CFS partially "recovered" from that and their illness turned into fibromyalgia with a pain presentation basically. Interestingly the one case I am thinking of in particular involves a person where pain medication eg opiates, whatever they give you at the dentist (local anaesthetic), does not work on them - apparently this is very rare and for genetic reasons? I thought that was interesting that they have so much pain and can't really get pain relief that way. (They don't work at all seemingly for them). A fairly cruel coincidence?
MrMagoo
Senior Member (Voting Rights)
Yes I was wondering this, because I have inter generational mixed-race, it’s recent enough for me to have had a sickle cell test but I don’t recall what I was asked about on the DecodeME.Thanks; I would be curious about this because I am a participant and one of my parents did immigrate but one did not. Presumably this means I would be included but I cannot remember what questions I answered.I don't remember the questions being asked or what I wrote.
I am not sure in general though - how long does one's family have to be here to have not "immigrated"? I don't understand this criterion. I get it about comparing similar genes but it would be good to know if I was actually included in the GWAS portion of the study and what this means for others.
MrMagoo
Senior Member (Voting Rights)
Ah this is good to know
Yann04
Senior Member (Voting Rights)
Not necessarily. As we saw in decode the effects are quite marginal. Perhaps as @VRT suggests CA10 is associated with more Fibro adjacent presentations of ME, ie. more likely to end up in chronic pain cohorts.
I think we shouldn’t assume ME as “one illness”, yet.
Kiristar
Senior Member (Voting Rights)
I remember struggling a little with that question as on pain meds and I couldn't remember properly what drove me onto them in the first place. But I ticked yes in the end as I do get what probably are a muscular type aches in my legs, not exactly pain but that make me "squirm" and I have to contract the muscles to try and relieve the sensation. It's quite widespread so I hesitated at first to define it as muscular. I definitely don't have Fibromyalgia. I only get joint pain in my elbows in extreme pem, when not on meds worsened in winter.
But isn't this then just the argument that is already presented? That genes related to pain can be part of different illnesses associated to pain in various ways?
Kiristar
Senior Member (Voting Rights)
One thing as a non technical lay person I still don't understand as how the 8 signals work in an individual.
If you have ME do you only need one of them, so there are 8 phenotypes?
Or did you need two or three? Or all 8?
Thanks if someone who can explain how that bit works, I can't read the technical paper.
If you have ME do you only need one of them, so there are 8 phenotypes?
Or did you need two or three? Or all 8?
Thanks if someone who can explain how that bit works, I can't read the technical paper.
Kitty
Senior Member (Voting Rights)
This is why I don't lie down unless I absolutely have to. My quad muscles burn badly when they're relaxed, but as soon as I engage or stretch them most of that pain is relieved. Sitting on a sofa with my feet on the floor stretches them just enough to keep it at bay.
If I have to lie down and they're really painful, I can relieve it by lying on my front. I can't keep it up for more than two or three minutes because it hurts my neck, but at least I get a change.
jnmaciuch
Senior Member (Voting Rights)
Ancestry is inferred by genetic similarity to reference populations—it wouldn’t have been decided by questionnaire
I tend to think of it as a "group signal" vs an "individual signal". There will be people in the DecodeME's cohort that don't have any of the signals and there will be healthy people that have all of them. It is more so that on average people with ME/CFS status are as associated with these signals. That makes it likely that these things are somehow involved in tiping the balance to developing ME/CFS, but for some people that balance can tip with certain things and for others it needn't tip at all despite the genetic signature being there, but because these things are somehow involved it gives a first proxy of where things may be occuring.
So if some people think of something like Huntington's disease, where as I understand it you either have a gene or not which leads to disease development, things are very different here. But things are the same way here as they in most other illnesses, where genes have often provided important information to understand diseases.
DecodeME shows: If you recruit people by asking them whether they have (been diagnosed with) ME/CFS, then on average you can associate these people with some genes that differ from healthy people and other illnesses.
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Simon M
Senior Member (Voting Rights)
Lots of conditions have chronic pain, so I'm not sure there would be enough people with undiagnosed ME/CFS to make a difference. Particularly as those most likely to be under diagnosed have non- white ethnicities. And they are under diagnosed with most things (the situation is more extreme with.ME/CFS ). This is also a group who are under represented in research studies generally.
ME/CFS Science Blog
Senior Member (Voting Rights)
In the data analysis plan there was the suggestion of combining the DecodeME and UKB ME/CFS cases to get more power.
Was this done or was the idea that the UKB ME/CFS cases are too unreliable?
Yann04
Senior Member (Voting Rights)
How “hard” is doing something like this?
To my untrained eye it sounds like something you could do in 30 minutes with a python script? But I’m assuming that I’m wildly wrong because of things like imputation and the massive computational power required?
ME/CFS Science Blog
Senior Member (Voting Rights)
Yes it seems that figuring out where the signal comes from is quite difficult.
The MAGMA gene-tissue analysis for example, used a different approach than FUMA + coloc and suggested different genes (given in supplementary table S4). Interestingly it suggests LRRC7 for the location on chromosome 1, a gene that codes for a protein primarily found in the brain and is important in synaptic communication.
I'm also not sure how more likely a gene like RABGAP1L is compared to other genes around that position. It seems that RABGAP1L was highlighted because of its eQTLs colocalising with ME/CFS risk in 24 of the 50 tissue samples. But if other genes aren't expressed in many tissues or there is less eQTL data available for them, that wouldn't necessarily mean that they aren't excluded as the causal variant.
Ca10 is gene that is most likely relevant because it's the only one linked to that location on chromosome 17. But perhaps it's also not that interesting if it's linked to general pain.
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Chris Ponting explained it well in the interview with David Tuller. The data is about the slight variations across the population of people with ME/CFS in genetic signals compared with healthy people. It tells us nothing about individuals. It's about clues of where scientists should focus the next phase of research.
Ariel
Senior Member (Voting Rights)
Why do you say that in particular? The team have laid out what they hope to achieve and why.
Hoopoe
Senior Member (Voting Rights)
ME/CFS research has been conducted since around 1990, and there have been clinical trials of treatments. None of them have convincingly shown a benefit. Finding a working treatment with this approach is difficult and could take a very long time.
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