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

wouldn't the fact that a fair number of the pw/oME also have these genetic traits mean that even if only 50% of the "ME cohort" actually had ME we'd still be likely to see this in the analysis?
It's a small correlation - someone calculated it earlier in this thread at an average of 1.2% per identified gene. And they had to pool all the ME patients in the other biobanks together to get similar number of people to the study's cohort. It would make sense that, if there were less actual ME sufferers in the other data, that the strength of association would be weaker and potentially get lost in the noise. Sure, it casts some doubt, but nothing is ever certain.

As they mentioned subsequently, they were able to obtain stronger associations with more rigours data, though not as strong as would be ideal.
 
Another thing on the potential mislabeling of pwME/healthy in the analysis is that we don’t know how common it is to have (very?) mild ME/CFS that’s not diagnosed.

Maybe some people just take longer to recover? Maybe they have sleep issues after having overdone it. Maybe this is temporary for them following an infection so it is never diagnosed as anything. But it could still be the same process as in us and require a similar genetic makeup.
 
It's a very good 'dumb question' that I too would like answered.

Here are the relevant bits of the preprint:
On the 8 GWAS associated genes/locations
Given ME/CFS’s female predominance and frequent infectious trigger, we also analysed females (those assigned female at birth) and males (those assigned male at birth) together and then separately and stratified by whether disease onset was infectious or not. These GWAS yielded eight genome-wide significant associations, which indicate a genetic contribution, and an immunological and neurological basis, to this poorly understood disease.


On the 29 candidate causal genes
Linking GWAS variants to causal genes that may provide biological insights and medical applications remains a challenge for the field (43). There were 43 protein-coding genes with at least one eQTL within an ME/CFS genome-wide significant interval, and we prioritised 29 ME/CFS candidate causal genes among them (Fig. 4; Table S5; Table S6; Fig. S6). These ‘Tier 1’ genes have a high (≥75%) posterior probability for colocalisation (H4) of a shared causal variant for their expression and ME/CFS risk in at least one of 50 tissues. We calculated this probability using coloc, a statistical method that predicts whether two traits are likely to be influenced by the same genetic variant in a specific chromosomal region (32). For this step, we disregarded the histone genes in the chr6p22.2 HIST1 cluster as candidates, as their sequences and functions are highly redundant (44).

AI "An expression quantitative trait locus (eQTL) is a genomic region where genetic variations are associated with differences in gene expression levels. Essentially, it identifies locations in the genome that influence how much of a particular gene is produced. This can help scientists understand how genetic variation affects gene regulation and potentially contributes to traits and diseases"

If I'm understanding things @Ravn, the eQTLs affect the operation of the 8 identified genes/location. So, they are either part of the identified genetic interval of interest, or are upstream in another gene, controlling the expression of the identified genetic interval.

I'm assuming that a vulnerability to ME/CFS could be partially caused either by an issue directly with the identified 8 genes, or something acting on the expression of those upstream genes that in turn influence the expression of the 8 genes.

AI "eQTL (expression quantitative trait loci) analysis can significantly enhance GWAS (genome-wide association studies) by helping to identify potential causal variants and understand the functional mechanisms underlying trait-associated SNPs . By integrating eQTL data with GWAS findings, researchers can pinpoint the specific genes and regulatory regions where disease-associated SNPs exert their effects, thus providing a more mechanistic interpretation of GWAS results."

Clarifications and corrections very welcome.
 
When attempting to replicate these findings in previously existing databases, given that the genetic differences identified "are also often found in people without ME/CFS" (p.2), wouldn't one still expect to see some reflection of this predominance even in a data set feature many unidentified individuals without ME? That is, wouldn't the fact that a fair number of the pw/oME also have these genetic traits mean that even if only 50% of the "ME cohort" actually had ME we'd still be likely to see this in the analysis?

If the data set featured many healthy individuals without ME, you'd expect the data to look more like the control cohort. The genes they identified are different from a random sample, so would be unlikely to occur if no one had a disease. If a handful of healthy controls were added into the ME/CFS group I think it would just reduce the strength of the results not produce any new differences.

Do we know what kind of impact a small portion of the cohort having another disease would have on the results? If for example 100 ME/CFS patients in this sample had a cancer all with the same genetic change could that be enough to reach significance? I went back and looked at the NIH paper Hutan mentioned and 4 out of the 27 patients that were given a diagnosis of ME/CFS by a panel of 'experts' were found to have another condition after rigorous testing. Do any of the statisticians know how many people with a genetic difference it would take to produce a 1% change between control and disease in a cohort of this size? Are any of the genes identified strongly associated with any relatively common conditions that can present as ME/CFS like and can be difficult to diagnose?
 
I strongly suspect that the undiagnosed or misdiagnosed rate, especially among the milder end of the spectrum, is going to be an important confounder in general.

Nor would I be surprised if a decent chunk of that 'misdiagnosis' in particular was from wiser and more compassionate clinicians deliberately giving patients a less prejudicial and problematic diagnosis, or hiding it behind an existing diagnosis like diabetes, hypertension, etc, in order to protect patients from the mistreatment and iatrogenic trauma that typically results from getting the formal ME/CFS label.
 
I'm assuming that a vulnerability to ME/CFS could be partially caused either by an issue directly with the identified 8 genes, or something acting on the expression of those upstream genes that in turn influence the expression of the 8 genes.
I’m too far removed from the field and never worked with GWAS to comment on the specifics, but wanted to say a regulatory sequence can be downstream of a gene too.
 
It's a very good 'dumb question' that I too would like answered.
Thanks for trying but it’s still gobbledegook to me. They all sound like candidate genes to me, not just the 8 highlighted, so what makes those 8 special? And how much attention should we pay the others on the list Chris shared? Maybe someone else can dumb it down further?

Mind you, my brain is mush. I let excitement win over self-discipline today and ended up reading a lot more than I should have. The consequences are starting to make themselves felt

While waiting for the fog to lift a huuuuge thanks to everyone who helped make DecodeME happen. Here’s hoping it’ll be an inspiration to many
 
Just had a quick look at if any of the top 25 significant genes from Table S3 were significant in a few other genetic studies. I only have the genes saved from a few of the genetic studies that have been done, so I hope to check others too at some point, but I found that DCC and CDK5RAP1 were significant in the following study (which had 77 total significant genes):
DCC is much more interesting gene than the others (as it is involved in peripheral nerve regeneration), but it was only found in the replication analysis "Lifelines and UKB Biobank cases" not the main study. I wonder why an association was found in other samples/studies but not the main one...
 
FBXL4 regulates mitophagy, which is a process where surplus, aged or damaged mitochondria are degraded.

When FBXL4 is absent, the levels of BNIP3 and NIX raise and hyperactive mitophagy results. Loss-of-function mutations in FBXL4 are known to cause mitochondrial DNA depletion syndrome 13.

In DecodeME, the FBXL4 variant that was associated with ME/CFS was rs97984426. I couldn't find information on whether it would lead to icreased or decreased mitophagy.

In this study of mitochondrial DNA it was reported that "ME/CFS patients had an excess of individuals without a mildly deleterious population variant".
https://www.nature.com/articles/s41598-019-39060-1

Fewer deleterious mtDNA variants would suggest higher mitophagy is occurring. The question is how could this contribute to ME/CFS?
 
Last edited:
Thanks for trying but it’s still gobbledegook to me. They all sound like candidate genes to me, not just the 8 highlighted, so what makes those 8 special? And how much attention should we pay the others on the list Chris shared? Maybe someone else can dumb it down further?

Mind you, my brain is mush. I let excitement win over self-discipline today and ended up reading a lot more than I should have. The consequences are starting to make themselves felt

While waiting for the fog to lift a huuuuge thanks to everyone who helped make DecodeME happen. Here’s hoping it’ll be an inspiration to many
The way I'm understanding this is that the 8 highlighted results are genomic loci / variants (SNPs). These point to a region in the DNA, not to one specific gene. These genomic loci are then named after the closest gene. Which is why they seem to appear as specifc genes. But it's not guaranteed that the closest gene is actually the gene that's involved in ME/CFS. It could be a more distant one or multiple genes. So these appear as genes but they're actually regions.

The researchers then attempt to locate specific genes in those regions that seem the most relevant to ME/CFS. These are the candidate genes.

From the lay summary:
We found that people with ME/CFS are more likely to carry certain DNA differences in eight regions of their genome.

Most of these regions contain several genes. Our methods did not allow us to conclusively locate the ones most relevant to ME/CFS in each region, but public data allowed us to pick out the most likely ones.
So basically the output of a GWAS isn't a list of specific genes but a list of DNA regions in which the associated genes must be. The candidate genes are an attempt at mapping those regions to specific genes.

Someone correct me if I'm wrong about any of this.
 
Last edited:
If I'm understanding things @Ravn, the eQTLs affect the operation of the 8 identified genes/location. So, they are either part of the identified genetic interval of interest, or are upstream in another gene, controlling the expression of the identified genetic interval.
I'm assuming that a vulnerability to ME/CFS could be partially caused either by an issue directly with the identified 8 genes, or something acting on the expression of those upstream genes that in turn influence the expression of the 8 genes.
Although I don't understand anything I feel like this is giving me a glimpse of something. I could be completely wrong in interpretation but if it is what I think it means it would fit my ME. Meaning I had something happen before my ME, a permanent change after a bacterial infection and I always thought this change had made me vulnerable to getting ME. Then along came a cold virus and something in the cold virus switched ME on.

Please ignore if this makes no sense.

Thanks so much to DecodeME and everyone who participated and made this happen.
 
I wonder if an FBXL4 mediated oversensitivity to removing slightly mutated mitochondria could explain that. It appears that FBXL4 loss is deleterious to mitochondrial function - from FBXL4's OMIM page:
Patient muscle homogenates or isolated mitochondria showed variably decreased activities of the mitochondrial respiratory chain complexes as well as decreased mtDNA content. Cultured skin fibroblasts had reduced maximal oxygen consumption rate and increased fragmentation of the mitochondrial network. At least 1 patient cell line studied showed a significant reduction of the mitochondrial membrane potential. These defects could be rescued by expression of wildtype FBXL4 in patient cells. The findings indicated that FBXL4 is necessary for the homeostasis of mitochondrial bioenergetics.

We are already looking at this stuff so whether this effect holds up or not (presumably more subtly than this, if so) it will actually come to light as a matter of time.

I was intending to vomit out my encyclopaedic knowledge of the hodgepodge of mitochondrial findings available to provide context to how we interpret this gene coming up (and expected effects of issues with it) but, really, since we have little that is consistent or replicated I actually think it wouldn't really be good to make any major predictions. tldr is some parts of the above cited phenotype have manifested in different studies but variably between sample types and usually with small effect sizes, hard to draw anything definitive. eg: membrane potential reduction.

What's probably more interesting than going back to what we "know" about mitochondrial studies in ME/CFS is the sort of orthogonal line of enquiry this invites. As far as I am aware mitophagy hasn't really been looked at in published work on ME/CFS. Instead much of the research involving mitochondria has focused on respiratory activity, sometimes on morphology. While morphology is tricky to interpret from particularly older literature where methods were more subjective, there have actually been generally striking differences reported, and in several tissues. It doesn't come up in the discussion often because of the difficulty of interpretation and age of some of the work. But changes in morphology are very clear, direct consequences of changes in how mitophagy is working so if there's anything to that, it's a point in favour.

Anyway. Looking forwards:

I am actually quite surprised that something like this came up (and pleasantly, because it's plausible and interesting). Mitophagy is an interesting angle and issues with it might make more sense in terms of how I imagine things actually happening. Issues with mitochondrial biogenesis, quality control, dynamics and whatever else can very easily elicit stress signalling responses that could plausibly drive many of the issues we have been recently suspecting here on s4me. A mitophagy issue would match the clinical picture much more than the commonly regurgitated blanket "energy production issue". You can have consequences for sensitivity and activation of immune cells, entanglement with ER issues more generally and the list goes on. It's very fertile ground. And to somebody else who I know will read this, wink wink nudge nudge, I won't steal your thunder.

Not as a plug but as a point of optimism and excitement, our lab is particularly well placed to look at many components of this. We are already doing complementary things and we have some unique means to study these processes that aren't commercially available. Hopefully we can add some clarity to whether there are functional consequences here that align with clinical presentation.

I'm starting to design some projects, not just specifically for this gene and mitochondria, but there's my 2c for anyone that wants the quick summary of where we can go with this particular gene.

Apologies if this isn't clear or organised, I'm unwell today but I couldn't just sleep on today's news.

The point is: mitophagy, and more generally the consequences for a cell should mitochondria be forming or breaking up, being cleaned up or talking to other organelles in a crappy way, is a plausible and compelling line of investigation (in my view moreso than a lot of the mitochondrial ideas that are typically memed to death, usually accompanying vague evocations of "energy" and/or "fatigue" - yes I have also been guilty of this).
 
Last edited:
DCC is much more interesting gene than the others (as it is involved in peripheral nerve regeneration), but it was only found in the replication analysis "Lifelines and UKB Biobank cases" not the main study. I wonder why an association was found in other samples/studies but not the main one...
Do we now have to say “noise”?

Is it now reasonable to say that if a DNA region hasn’t been identified by the DECODE ME main study as having an association, then the genes in that region probably aren’t usually associated with IOM/CCC-criteria ME/CFS?
 
I’m not up to reading this discussion or the paper but I put it through Google LM Notebook:
Video (language a bit exaggerated): https://notebooklm.google.com/noteb...tifactId=d7f17a74-9b5a-43f5-9770-425e0e2fe26f

Audio: https://notebooklm.google.com/noteb...tifactId=0b7b797e-c059-4ca8-a14a-8d67887f153d if you click interactive you can have a spoken conversation and ask your questions about the research.

Full notebook: https://notebooklm.google.com/notebook/1e5d9261-37bf-43da-b8a4-63c831980a14

NB AI does make errors (let me know if you hear any) but Google LM Notebook tends to be accurate to the source.
 
Mitophagy is an interesting angle and issues with it might make more sense in terms of how I imagine things actually happening. Issues with mitochondrial biogenesis, quality control, dynamics and whatever else can very easily elicit stress signalling responses that could plausibly drive many of the issues we have been recently suspecting here on s4me.
Sorry for the dumb question, but could phagocytes be implicated in PEM? Could a problem with mitophagy or other phagocytosis explain the delay? Exertion somehow decreases phagocyte functioning, and the result is felt hours or days later when a lot of impaired cells are hanging around?
 
Back
Top Bottom