Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

[jnmaciuch]

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.

Ancestry is inferred by genetic similarity to reference populations—it wouldn’t have been decided by questionnaire

 

[EndME]

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.

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.

 

[Simon M]

Previously I wondered if the “Chronic pain gene“ (CA10 I think?), might actually be associated with ME not chronic pain. But since ME is commonly undiagnosed and has chronic pain for many, a lot of pwME may have ended up in a chronic pain GWAS and with large sample sizes it might show an effect.

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]

In the data analysis plan there was the suggestion of combining the DecodeME and UKB ME/CFS cases to get more power.

5.2.4 Combined analysisAs previously mentioned, DecodeME participants will have their DNA genotyped and imputed following the UK Biobank’s standard procedure. This give us the possibility to combine into a single set DecodeME cases with UKB participants with evidence of a ME/CFS diagnosis. We will perform analysis with this combined set (against UKB controls; Fig. 5) which would boost the power of discovery for variants enriched in both sets.

Was this done or was the idea that the UKB ME/CFS cases are too unreliable?

 

[Yann04]

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?

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]

The trouble is figuring out which gene associated with a given location is the troublemaker in ME/CFS.

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.

 

[Trish]

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?

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.

 

[ryanc97]

Call my cynical but I don't see how this would lead to better understanding the underlying cause of this disease.

 

[Ariel]

Call my cynical but I don't see how this would lead to better understanding the underlying cause of this disease.

Why do you say that in particular? The team have laid out what they hope to achieve and why.

 

[ryanc97]

I think the from the genes to the mechanism of the disease is too far away and the focus should be on experimental trials on treatments, that if they work, will then let us work backwards to figure out what went wrong.

 

[Hoopoe]

I think the from the genes to the mechanism of the disease is too far away and the focus should be on experimental trials on treatments, that if they work, will then let us work backwards to figure out what went wrong.

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.

 

[Trish]

I think the from the genes to the mechanism of the disease is too far away and the focus should be on experimental trials on treatments, that if they work, will then let us work backwards to figure out what went wrong.

I think this research is useful because it provides clues for future research. I understand GWAS study results for other diseases have led to significantly useful new research.
There are other threads for discussing the value or otherwise of other approaches which may also be useful.

 

[Ariel]

I think the from the genes to the mechanism of the disease is too far away and the focus should be on experimental trials on treatments, that if they work, will then let us work backwards to figure out what went wrong.

Even if this approach was followed (and someone has pointed out that this has been happening with no success), why not do both?

Additionally, seems unwise not to do our best to uncover the mechanism of the disease to narrow down what treatments to trial?

 

[ryanc97]

Well I hope they collab with good old Ron Davis since Davis is actually a world class geneticist for most of his career. He worked under the guy who discovered DNA, James Watson , ffs.

 

[Utsikt]

I think the from the genes to the mechanism of the disease is too far away and the focus should be on experimental trials on treatments, that if they work, will then let us work backwards to figure out what went wrong.

We’ve had extensive discussions elsewhere about trialing treatments vs looking for the mechanisms first. Feel free to read those for why your proposal isn’t the way to go, e.g. starting here.

 

[Utsikt]

Well I hope they collab with good old Ron Davis since Davis is actually a world class geneticist for most of his career.

Didn’t he primarily work on the technology behind genome sequencing?

The team is already working with Oxford Nanopore Technologies for SequenceME.

 

[Ariel]

Well I hope they collab with good old Ron Davis since Davis is actually a world class geneticist for most of his career. He worked under the guy who discovered DNA, ffs.

The team are making their data available for further study to other teams who would like to use it (this may already be happening, I don't know)

 

[V.R.T.]

Even if this approach was followed (and someone has pointed out that this has been happening with no success), why not do both?

Additionally, seems unwise not to do our best to uncover the mechanism of the disease to narrow down what treatments to trial?

Exactly! I get really frustrated when people talk about this like it's a binary thing.

 

[Andy]

For those interested in seeing some background on Chris, the Wikipedia article on him is here, and his research output from 1989 onwards can be seen here.

 

[Andy]

A select number of answers from the FAQs that might address recent discussion points.

Q. Do these results mean everyone with ME/CFS has one or all of these genetic differences?

A. No, these findings are based on large-scale patterns across the thousands of people with ME/CFS that we studied. They show that, on average, people with ME/CFS are more likely to have these differences than people without ME/CFS. These signals are about what we can see across populations, not individuals.


Q. Are these findings unique to ME or have they been found in other illnesses?

A. The signals we have found are different from those found in other illnesses to date, except for the one on chromosome 17 that was previously found in people experiencing chronic pain.


Q. Can these results lead to treatments for ME/CFS being developed?

A. DecodeME’s purpose was to gain an understanding of the biological roots of ME/CFS and how genetics could contribute to developing the condition. By identifying genes linked to the immune system and the nervous system, the study opens the door for scientists to explore what’s going wrong in ME/CFS at a molecular level. This deeper understanding could, in time, lead to treatments that target the root causes of the illness.


Q. What happens next with the study?

A. Although the initial results of DecodeME are now available, we are not finished. We’ll continue to analyse the genetic data, and we will update our scientific paper as needed before it is peer reviewed and published. We also have a detailed and valuable dataset from the second questionnaire that focused on symptoms, quality of life, treatments and therapies. We will be analysing and reporting on this in due course.

Our work doesn’t end there. Approved researchers will be able to use the data of those who consented through our data access process, helping to catalyse new studies and discoveries.


Q. What happens next for ME/CFS research?

A. The DecodeME findings are a springboard for future ME/CFS research. Now that we’ve identified genetic signals linked to ME/CFS, researchers can start investigating exactly what’s happening in the body – for example, by specialist scientists delving deeper into each genetic region found. These discoveries open new avenues for research, potential drug development or repurposing, and targeted treatments. DecodeME’s findings have laid the groundwork for a new era of ME/CFS research, and our rich dataset is available for data access applications and is already driving new discoveries forward.