ME/CFS Science

X marks the spot where ME/CFS biology can be discovered. The science behind the findings blog post.

'Each genetic signal is like an ‘X’ on a treasure map indicating roughly where the researchers should dig for treasure.'

Check out Simon McGrath’s blog to learn about the science behind the initial results: shorturl.at/hadjF

Is it that the SNP is likely just tagging a region on the genome that contains the causal variant, rather than directly influencing gene expression or disease itself?

So the measured SNP itself is likely not important, just pointing to a region of interest?

Thanks. The HLA-findings in DecodeME are a bit perplexing. Hope that further analysis will provide some clarity.

For those interested, there's a separate thread on S4ME to discuss the HLA findings:
www.s4me.info/threads/gene...

An excellent thread summarising and explaining the main results from DecodeME. With the promise of a blog to come.

Van hoop tot wanhoop: grote heibel over studies naar ziekte ME Het zag er zo mooi uit. Patiënten die lijden aan de chronische vermoeidheidsziekte ME kregen het na jarenlang duwen en trekken voor elkaar dat de overheid diep in de buidel tastte om grondig onderzoek...

Don't know the exact selection criteria for ME/CFS in the Lifelines cohort, only that it has been a source of controversy with criticism from patient organisations.

See for example this news article:
argos.vpro.nl/artikelen/va...

DecodeME supplementary material says:

In Lifelines, post-exertional malaise was defined when a participant answered one or more of questions 14-18, and 75-77 of the DePaul Symptom Questionnaire 2 (38), indicating at least "about half the time" with at least "moderate severity”.

Thanks but we don't have a scientific background. We're ME/CFS patients who have followed research for a long time.

Thanks for the clarification although I'm afraid I don't fully understand.

Another potential issue with the DecodeME replication attempts is that the cohorts where often quite small (for an overview see the image below).

The Lifelines cohort for example only included 3440 cases (compared to 15,579 for DecodeME).

Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome

24) Link to the preprint:

DecodeME collaboration 2025 'Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome'.
www.research.ed.ac.uk/en/publicati...

Discussion on S4ME:
www.s4me.info/threads/init...

23) There’s much more to say about this study, but we’ll wrap it up here and save the rest for an in-depth blog post on our website. A warmhearted thanks to the researchers and patients who made this landmark study possible!

SequenceME: first of a kind genetic study - Action for ME A groundbreaking partnership has launched today. The partners are working together to secure funding for a study which will analyse the entire...

22) The researchers hope to look at rare genetic variants in a follow-up study called SequenceME. This will get an even more detailed picture of the DNA differences associated with ME/CFS.

Rare variants might have bigger effect sizes.
www.actionforme.org.uk/sequenceme-f...

21) Lastly, these were the initial findings from DecodeME, which only looked at common DNA variants (where the least common version still occurs in more than 1% of the population).

20) DecodeME also did not diagnose ME/CFS using clinical examinations (which would not be possible for such a large sample size). It required a self-reported diagnosis and checked this with questionnaires based on the IOM and CCC criteria.

19) One possible exception is the Dutch Lifelines cohort, where cases were clinically diagnosed with ME/CFS and had PEM (although there are some doubts if the study did so reliably). Here, some associations were repeated but did not reach full significance.

18) A likely explanation was differences in case definitions. The other databases often did not select patients using modern case definitions that require the key symptom of post-exertional malaise (PEM).

17) DecodeME delivered, but we also have to highlight what is perhaps the main limitation of the DecodeME results: the authors tried to replicate their results in different cohorts, and this did not go very well.

16) A caveat is that these genes have other functions as well. Future research will need to figure out which ones are relevant to ME/CFS. We suspect that a lot of scientists will use these leads to start new research and get closer to the pathology of ME/CFS.

15) The HLA-region also got a significant result (HLA-DQA1*05:01). This region is important in differentiating your own body's cells from invaders like viruses or bacteria.

Many autoimmune diseases have abnormalities in the HLA region.

14) A third gene CA10 is involved in synaptic transmission and has previously been found in people experiencing chronic pain. It might explain why pain is such a common symptom in ME/CFS.

13) Another gene, Olfactomedin-4 (OLFM4), suppresses antibacterial and inflammatory responses by binding to neutrophil proteins and neutralizing their ability to kill.

12) Now it gets interesting because these suspect genes were often linked to the immune and nervous systems.

RABGAP1L for example promotes expulsion of the bacterium Streptococcus pyogenes and limits replication of multiple viruses.

11) The first region (chr1q25.1) for example is associated with 11 genes. Luckily there are databases with info about how SNPs affect the expression of nearby genes. This lets the researchers zoom in on the most likely suspects.

10) The 8 hits point to a specific region on our genome but a lot of DNA fragments (SNPs) are inherited together in what’s called linkage disequilibrium (LD). So, we’re not entirely sure which gene in the region is causally related to ME/CFS.

9) The 8 hits or DNA variants occur in 13%-60% of the general population. So it’s not that these determine if you have ME/CFS or not. Instead, they should be seen as clues or pointers to what's really going wrong.

8) The effect sizes are quite small (odds ratios below 1.1), but this is expected for genetic studies like this (it’s the same in other diseases).

To get a feel of how subtle this is, we recalculated the prevalence in ME/CFS and controls, which only differ by 1-2%.

7) So, what are the 8 results? Table 3 in the paper shows the main results: the location on the genome, the DNA letters that were different, how common these variants are and if the variant was increased or decreased in ME/CFS.

6) Six hits showed up in the main analysis (GWAS1), while another was found using only the ME/CFS patients who reported an infectious onset. The last one came up in GWAS2 which used a different subset of controls.

5) Let’s now move on to the key results.

Big genetic studies apply a strict significance threshold of 5*10^-8 (less than one in a million) to avoid differences between patients and controls being due to chance. In DecodeME there were 8 findings or hits above this threshold.

4) A second major finding: the genetic information could be used to estimate the heritability of ME/CFS: how much the illness is due to genetic differences in common DNA variants. The result was modest: 9.5%. This aligns with a previous estimate (8%) from the UK biobank.