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For the hit on chromosome 17, CA10 is the only candidate and it also clearly linked to neurons and synapses. So if we focus on the close-by genes, the clearest hits seem to point to neurons/synapses. The exceptions are OLFM4 on chromosome 13, which has a clear immune connection (linked to...

PEBP1 seems like the second closest to the hit on chromosome 12, next to TAOK3, which seems very stretched out. EDIT: added the image below

Another gene that hasn't been discussed yet but that seems the closest to the hit on chromosome 6q is POU3F2 POU3F2 Gene - GeneCards | PO3F2 Protein | PO3F2 Antibody EDIT: added the image below

Highlighting gene UNC13C, which seems the closest to the hits on chromosome 15. The gene card reads as follows: UNC13C Gene - GeneCards | UN13C Protein | UN13C Antibody EDIT: added the image below

This lecture is interesting and relevant to our discussion: MPG Primer: Linking SNPs with genes in GWAS (2022) Don't understand everything, but there's some discussion that eQTL data and GWAS hits often do not match very well. Genes that are likely to be causally related to disease often do not...

If these experiments could show that the problems likely do not lie in the muscles itself (peripheral fatigue): wouldn't that affect theories about mitochondrial and endothelial dysfunction as being less likely causes of ME/CFS symptoms?

They did this in the intramural NIH study (some of the participants in this paper were healthy controls in the ME/CFS study). They reported that ME/CFS patients had faster declines in grip strength but that there were no signs of peripheral fatigue. This reported the slope of the Dimitrov...

This is fascinating @forestglip ! I'm quite a bit behind in my understanding of MAGMA and FUMA compared to you, but I will try to catch up. Based on what you posted, the evidence seems quite persuasive that the differences found in DecodeME (not just the 8 hits) point to something happening in...

Looks like the accuracy of imputation is usually > 95% in common variants in European populations (although I found it quite hard to find the numbers on this. I suppose it's easy to test: you could just deleted a portion of what you measured and then try to impute them.)...

Of the 8 hits, only 1 was measured, but the others have a high INFO_SCORE suggestion that their distributions follow Hardy-Weinberg Equilibrium. I suppose it's based on the strong correlations between SNPs that you only need to know a few to be pretty certain what the others are. But I was...

My understanding is that only ca. 820.000 SNPs were measured, and approximately half of these were discarded because of bad quality. The other 8 million were imputed. See Chris his response here...

Impressive! Is this with the dataset filtered for quality control or the full dataset?

Didn't feel like going deeper into the evidence because the included populations were so diverse and dissimilar to ME/CFS. Also got the impression that the reviewers didn't care much about quality of evidence. Only briefly scanned the studies but of the 25 included I don't think there's one...

Made this thread on the review: 1) A new review on Long Covid recommends 'exercise training' but it's based on low-quality trials with high risk of bias and problematic inclusion criteria. Some didn't even focus on Long Covid patients, just people who survived COVID-19. 2) The review included...

Not sure if that is the CFS prevalence or just the prevalence of 'four or more additional symptoms.'

In that case it might be quite important. I wonder if we should interpret the likelihood of possible genes in light of this MAGMA analysis: those that are not expressed in the brain might be less likely to be a relevant gene compared to those who are highly expressed in the brain (Figure 4 In...

I think in the DecodeME webinar just now Sonya said that they had 9 requests from other researchers to access the DecodeME data.

Thanks, will try to take a closer look at this. So it's like they used all possible genes but weighed them by how much the SNP signal from the GWAS points to them? That would make more sense and make there results more interesting.

I tend to agree. For most of the loci there are multiple potential genes implicated and each of the genes are involved in multiple pathways. You could perhaps argue that there are more genes involved in the immune and nervous system than expected. But it's hard to say how many immune-related...

Yes look like you're right. It seems that they highlight the GLMNET lasso model because it did well on the test set (while selection of the model should have happened before that).