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

[Jonathan Edwards]

From my understanding GWAS findings by themselves aren’t causal only correlative. You need to perform additional analyses to do casual inference. See for example an explanation here

I think you need to do other things to establish the precise nature of the causation and maybe the strength but if you correctly identify a gene polymorphism as linked to risk and have excluded linkage disequilibrium (assuming you can) then you have established a causal relation. That is the beauty of genetic studies.

 

[Hoopoe]

It's an interesting question but I am not sure it is obvious to look at the X and Y chromosomes. The reason why women are more likely to get ME/CFS than men is that they have two X chromosomes and men have one plus a Y. We know that already. We are not expecting women with ME/CFS to have any different gene variants from other women, or indeed X gene variants from men.

If that is the case, why did I have the impression that the result of finding no explanation for the increased risk in women was surprising?

 

[Jonathan Edwards]

If that is the case, why did I have the impression that the result of finding no explanation for the increased risk in women was surprising?

No idea, did someone say it was surprising?

 

[Hoopoe]

No idea, did someone say it was surprising?

It was mentioned in the abstract. To me that makes it seem that it was not something a person with basic knowledge would expect.

 

[Hutan]

The DecodeME participants were 85% females themselves.

We have discussed elsewhere about that not telling us much about sex ratios in ME/CFS though. There are too many confounders e.g. who gets diagnosed, who identifies with the ME/CFS community, who participates in unpaid research studies. What it does mean though is that there is a big female sample, so findings relating to the X chromosome could be quite robust. It is possible that the male sample was too small to produce good Y chromosome results I guess.

Thanks for the link, very interesting. It looks as though DecodeME is not alone in not reporting sex chromosome results. Hopefully in the case of DecodeME, the results are still coming.

 

[Jonathan Edwards]

We found no evidence of sex-bias among discovered associations

Were you meaning this?
I took this to mean that the risk gene profile looked the same in men and women. That would suggest that men's ME/CFS and women's ME/CFS are not two different diseases but I don't think it relates to the female predominance.

 

[Hoopoe]

Were you meaning this?

Yes.

I interpreted it differently, along the lines of "To our surprise, we were unable to explain why women are more likely to have ME/CFS". I was thinking of total risk.

What is actually meant is that the portion of risk that comes from the variants examined is insignificantly small.

It seems that a lack of sex-bias is actually a common finding in GWAS.

A question that remains is what exactly is causing the increased risk in women. Is it genetic variants on the X chromosome, hormonal or immune differences?

 

[Jonathan Edwards]

It seems that a lack of sex-bias is actually a common finding in GWAS.

I would have thought that for the non-sex chromosomes it was standard and in a sense almost a quality control exercise for the diagnostic category.

 

[Jonathan Edwards]

I think there have been several studies suggesting that phenotypic features of ME/CFS differ in men and women. The Beentjes study showed some features shared but not others. That raised a significant possibility that ME/CFS is mediated by different processes in the two sexes, just as arthritis is mediated differently in the two sexes (to a degree). The genetics did not provide evidence for that.

 

[Chris Ponting]

Sorry, can someone explain the "European ancestry" thing? I am not even sure what this means. Thank-you.

Hi. First, I should say that we didn't complete in time for the preprint a second DecodeME analysis that uses all cases passing quality control. We're going to keep going on this. But in answer to your question about "European ancestry", this is genetics short-hand for people whose DNA variation is very similar to the variation seen among people from Europe. We needed to do this to very accurately match the genetics of ME/CFS cases with our UK Biobank controls. If we hadn't done this accurately, then we could easily have wrongly found "ME/CFS associations" that would actually only reflect differences in ancestries between cases and controls. You can see from the preprint's Supplementary Figure S1 (https://www.pure.ed.ac.uk/ws/portalfiles/portal/533352490/Preprint.pdf) that we matched cases and controls really well: in each of 20 different dimensions genetic data from the ME/CFS cases (in green) fall on top of data from the UK Biobank controls (in black/grey). If there were cases from a non-European ancestry then these would fall outside of these "blobs". Hope that's OK.

 

[Deanne NZ]

Do we know the heritability and the explanatory power of genetics for other diseases that are believed to primarily have an infectious onset?

Type 1 Diabetes is believed to have an infectious onset - with genetic predisposition. In terms of heritability, off-spring of males with T1D are more likely to develop the disease, than off-spring of mothers with T1D. There is a greater ratio of males than females with T1D but more females are likely to have additional autoimmune conditions.
This paper has a good table (1) on the heritability ratios.

Risk Factors for Type 1 Diabetes - Diabetes in America - NCBI Bookshelf

 

[sb4]

I'm still trying to understand how confident we should be with these finding. I understand the difference in gene variants is very small between patients and controls but that's okay since large numbers were used. I also understand they failed to replicate the results using other databases.

Could somebody who understands this better say in laymen's terms how confident we should be that these findings are legit?

 

[Jonathan Edwards]

A question that remains is what exactly is causing the increased risk in women. Is it genetic variants on the X chromosome, hormonal or immune differences?

I don't think the 'increased risk in women' - i.e. why women have more ME/CFS than men - can be due to genetic variants of the X chromosomes because any variants will be shared out equally to both men and women. Genetic variants on the X chromosome may explain why women with ME/CFS have it and women without ME/CFS don't but that is a separate issue.

And we almost certainly cannot separate hormonal from immune issues because immune differences are very likely dependent on cumulative hormonal environment over many years, with changes at menarche and menopause. There might be a polymorphism in a gene for an immune receptor that is directly influenced in expression level by a single gene on the X chromosome with dosage effect (double for women). It that polymorphism was skewed differently in women with ME/CFS from women without ME/CFS we would have something meaty to work on but this may be wishful thinking.

 

[forestglip]

So the control data QA sweep used GnomAD (v2.1.1) which is an hg19 reference. But the DecodeME paper references hg38 locations?

As far as I understand, that shouldn't really change anything. h19 and hg38 are just different ways to refer to a SNP and can be converted between each other.

 

[wigglethemouse]

As far as I understand, that shouldn't really change anything. h19 and hg38 are just different ways to refer to a SNP and can be converted between each other.

I understand. I just expected to see something in the methods to explain what they did. I could find no mention of the remapping the genomic location from hg19 to hg38 in the text using a search and a quick read of the relevant sections in methods.The methods are very detailed. Perhaps I missed it.

I always get concerned when I spot check a main finding in the paper with available information and there is a mismatch. In this case one of the main findings is OLFM4 variant 13-53194927-GT-G rs35306732 in the paper but it does not exist in publicly available data on geneatlas for the UK Biobank axiom array data from which the control data was taken. LINK

@Chris Ponting would you be kind enough to explain why I can't find the OLFM4 variant from the paper in the data on the geneatlas tool?

 

[Ravn]

There’s considerable confusion in other patient groups about GWAS. Understandably so, it is all rather complicated. I see people interpreting the results as there definitely being something wrong with the 8 highlighted genes. Some who have dna data for themselves are finding they’re not having the snps listed and are wondering if that means they don’t have ME. So lots of misunderstandings

I think labelling the 8 regions with one particular gene each may be contributing to the confusion. I expect it’s standard procedure for this type of study but is there another way of handling this that’s clearer for lay people?

Like talking more prominently about risk-increasing/decreasing regions found, without attaching a specific gene’s name to them, maybe label the regions according to location or even just as risk regions 1 to 8. And then deeper in the guts of the paper explain that in those regions there are all these candidate genes - each of which may or may not increase or decrease risk, more research needed - and of those these 8 look especially interesting based on what we currently know but new knowledge from more research may shift the focus to one or more of the others

 

[Jonathan Edwards]

There’s considerable confusion in other patient groups about GWAS. Understandably so, it is all rather complicated. I see people interpreting the results as there definitely being something wrong with the 8 highlighted genes. Some who have dna data for themselves are finding they’re not having the snps listed and are wondering if that means they don’t have ME. So lots of misunderstandings

To be honest that sounds like an inevitable learning curve that will crop up if people do in for things like getting their DNA tested without understanding what the findings would mean. At least questions are being asked and they may learn.

I don't think it is the job of scientists writing papers using technical methodology to explain the basic biological principles behind how that methodology works. They should give enough detail for scientists not immediately in their field to see how the technique is being applied but not a lecture on the principles of genetic associations with disease.

 

[Chris Ponting]

I understand. I just expected to see something in the methods to explain what they did. I could find no mention of the remapping the genomic location from hg19 to hg38 in the text using a search and a quick read of the relevant sections in methods.The methods are very detailed. Perhaps I missed it.

I always get concerned when I spot check a main finding in the paper with available information and there is a mismatch. In this case one of the main findings is OLFM4 variant 13-53194927-GT-G rs35306732 in the paper but it does not exist in publicly available data on geneatlas for the UK Biobank axiom array data from which the control data was taken. LINK

@Chris Ponting would you be kind enough to explain why I can't find the OLFM4 variant from the paper in the data on the geneatlas tool?

My guess is that this variant is absent from the dbSNP Release used by GeneAtlas at the time, but present in the reference panel that we used for imputation (namely, UK Biobank Whole Genome Sequencing variants). Not all variants are listed in all resources unfortunately.

 

[Chris Ponting]

Hi. I've posted this elsewhere on Science for ME, but think it's important to leave here too.
About the "only a 1% difference between [the frequencies of] those with ME and controls". This small "effect size" does not matter if you're focused on drug discovery. This is because the success rate from clinical development to approval "is largely unaffected by genetic effect size", see https://www.nature.com/articles/s41586-024-07316-0. The reason for this is subtle but important. Even when DNA variation tweaks biology only slightly, this variation highlights what biological aspects need changing via drugs. And these drugs can be made to alter biology to a far, far greater extent than the genes can.

 

[Hoopoe]

Is it possible that we struggle to understand ME/CFS because we don't understand much about how the body returns to normal after an infection?

In the sense that we know a lot more about infection, inflammation, autoimmunity than about the restoration of homeostasis that follows that fighting phase. We try to build hypotheses with the knowledge that we have and the knowledge about the restoration phase is very limited. The research has failed to find a persistent pathogen, significant inflammation, autoantibodies, tissue damage. In ME/CFS it seems the body has returned to normal in many but not all ways... there must be some specific aspect that has not returned to normal which is causing a lot of problems in the long term.

Without a complete return to homeostasis, the body ends up being unable to tolerate the stress of ordinary daily activities and you get various responses like unrefreshing sleep, fatigue and postexertional malaise, avoidance and pacing behaviours that are psychologized.