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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).

I think platelet-derived cfRNA was decreased in ME/CFS. EDIT: so that would mean that the platelets are less likely to rupture in ME/CFS?

The model that reached the best fit (in the 30% test samples) was GLMNET Lasso. It reached a maximum accuracy of 77% (84% sensitivity, and 68% specificity, testing AUC-ROC: 0.81 (95% CI: [0.694 to 0.926]). This is similar to BiomapAI which reported an accuracy of 72.5% and AUC of 0.82 (but...

They also found that in their machine learning models, the accuracy was highly variable depending on the predictors that were included. The main reason for this was thee fraction of platelet-derived cfRNA, which was apparently lower in ME/CFS patients compared to controls. Not sure what this...

They tested RNA outside of the cell which represents a mixture of RNA fragments released from many different cell types all over the body. Perhaps one of the more interesting findings is that they found no differences in Viral RNA Signatures between ME/CFS patients and controls. In the theory...

I suppose they did all that selecting in the 70% training set and then tested it in the 30% data that the model hadn't seen yet.