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Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explicable by inactivity, 2024, Beentjes, Ponting et al In that study, both of these were significant in the BMI adjusted results for the combined cohort (from Dataset EV13). IGF-1 was decreased in ME/CFS. SHBG was increased in...

Good chance you know this since your first sentence where you posted figure 4 above was right, but I wanted to correct the wording here. The variant isn't overexpressed anywhere. The variant is just a different letter at a particular point in the DNA, and all cells in the body have the same...

That seems pretty much right, but I'm no expert, so I wanted to find a more reputable source to back it up (these correspond to ChatGPT's points 1 and 2): Prioritization of causal genes from genome-wide association studies by Bayesian data integration across loci (2025, PLOS Computational Biology)

The database (and figure 4 above) are about how the DecodeME's (and other) specific mutations affect the amount of CA10 produced, not how much CA10 there is in general. So it's saying that having this ME/CFS mutation leads to more CA10 in the prostate. Maybe it's possible the effect in other...

My understanding is that it's based on a project (GTEx) that tested expression of all genes in 54 different tissues to see where mutations affect expression. So I think they would have looked at CA10 in all tissues. Paper about GTEx

That's my view. Just a slight bias in how many infections people with ME/CFS get versus healthy people that isn't large enough to be obvious, but might become apparent in the genes in an enormous sample like we have here. With ME/CFS often following an infection being one of the few things we...

So the study found significant locations in the DNA, not necessarily significant specific genes. The trouble is figuring out which gene associated with a given location is the troublemaker in ME/CFS. For some of these locations, there are many possible genes. For example, for the chr1q25.1...

Sorry, my brain is too mushy to follow this very well. If they didn't confirm it's not the same cells, then how can you know it's EBV-infected cells reacting to EBV? And for the "strategy EBV uses" part, it sounds like you're saying it's settled then that they can make EBV antibodies?

That's interesting. The story from the other study is so nice though. Plenty of antibodies to other pathogens in CSF, but barely any to EBV, might suggest that primarily EBV-infected cells (that can't make EBV antibodies) are getting in. (Also Jonathan said B cells that make EBV antibodies...

Madelleine Müller - I Cant Run When I'm Dreaming (lyric video)

Could you quote the relevant part? I can only see the abstract.

Very cool, thanks.

Ok thanks that makes sense. Maybe still tough to squeeze through the tiles, but with millions of problematic B cells stopping, a few might make it through by chance. Five times bigger! I was imagining like 20% bigger.

Oh I was talking about MS where there's more reason to believe we'd actually find these B cells. Maybe something to look at in ME/CFS too though just in case.

I'm having trouble picturing how being bigger could make it easier to cross the BBB. Yep, that's the thread I linked.

I remember another thread with discussion about it being EBV infected B cells going into the brain and causing trouble. Would it not be trivial to look at the brain B cells post mortem to see if they all have EBV inside? Is it harder than I'm thinking to even find the B cells?

The main SNP here doesn't appear to be significant in the DecodeME data unfortunately. Data from DecodeME summary statistics. Converted rsID from this study to chromosome position ID using gnomAD. All DecodeME cases (p=.257) Females only, the way it was significant in this study (p=.428):

You got it. If they are hypothesizing about specific genes, they only have to adjust the p-value threshold for as many of these that they are interested in. They can even do a full GWAS on everything, strictly adjusting based on trying to find associations anywhere in the genome, and also do a...

I don't see any individual level data for illness duration in the study. Just a mean and range in Table 1. And I don't see anything about NK relationship to duration. Maybe it's from a talk?

It's a risk though. There might only have been significant hits just on the cusp of the threshold with the full sample. Reducing the sample size could lead to losing those findings. It might be better to put all the power possible in it while we've got it, and let the replication happen later.