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Something that hasn't been discussed much is the low heritability estimate This was estimated using linkage disequilibrium score regression ( LDSC). If I understand correctly the method is relatively simple: it does a regression analysis of linkage disequilibrium (how much SNPs correlate with...

In an interview with David Tuller, Ponting also said something interesting (starting at minute 21:23):

Yes it seems that figuring out where the signal comes from is quite difficult. The MAGMA gene-tissue analysis for example, used a different approach than FUMA + coloc and suggested different genes (given in supplementary table S4). Interestingly it suggests LRRC7 for the location on chromosome...

In the data analysis plan there was the suggestion of combining the DecodeME and UKB ME/CFS cases to get more power. Was this done or was the idea that the UKB ME/CFS cases are too unreliable?

Thanks, and big thanks to the DecodeME team for uploading all this info! This is all quite new to me so apologies for any errors or dumb questions. I think the INFO score give an indication if the imputation went well by comparing the variance of the dosage (expected number of alternative...

That's probably because 90% of texts and papers on ME/CFS talk about weak data and all these possible connections that have no sound basis. I wonder if you would get better results if you call it illnessX and describe it yourself with what are considered the most robust findings. You could also...

Most (around 90%) of the SNP results are imputed if I understand correctly, not just the HLA region. I'm trying to find info that says which ones were actually measured and which ones imputed.

Anyone who can point me to this study? Seem to have missed it.

Not sure, was thinking there might be a higher risk of selection bias and not getting a representative sample of the ME/CFS population.

The replication with existing databases does not seem to go very well: there's likely too much uncertainty about the case definition used. So I suspect that another project with the same approach as DecodeME might be needed to confirm the results. It will need to be in an area were ME/CFS is...

Apologies if this is a stupid question but how do you know which SNPs are measured and which ones are imputed? Do they mention this somewhere in the text or is it somewhere in the data?

EDIT: these probably reflect artefacts that were excluded in the main analysis? I'm looking at the DecodeME summary data, namely the file: gwas_1.regenie.gz taken from here: https://osf.io/rgqs3/files/osfstorage When I arrange by lowest p-value however, I get 8320 rows with a p-value lower...

Yes strange. Perhaps the overall frequency was taken from another database and does not reflect the data in DecodeME?

Here's an overview of the replication cohorts' sample sizes (taken from the supplementary material): Replication Cohort Cases Controls R1 Lifelines 3,440 17,080 R1 UK Biobank 10,327 195,103 R2 Estonian Biobank 1,926 195,103 R2 FinnGen 283 463,029 R2 Michigan Genomics Initiative...

I noticed that the HLA-region also got a significant finding (HLA-DQA1*05:01 at p = 1.4 x 10-10 but that it somehow reported separately form the other 8 hits. It seems to be a different SNP than what the Norwegians found but perhaps this is due to HLA being difficult to sequence?

The failed replications are disappointing but I suspect that next too broad case definitions for ME/CFS in the other databases, the sample size might also have been too small. In the supplementary material it says that the Lifelines cohort only had 3,440 cases and 17,080 controls (compared to...

Made a brief summary of the results here (EDIT: added full text and Bluesky link) Link to Bluesky: 1) The DecodeME study compared DNA of ca. 15,000 ME/CFS patients and 250,000 controls and found significant differences in 8 regions of our genome. The Manhattan plot below shows the genes and...

I think this is normal for GWAS, they provide clues or pointers to what's going wrong rather than the gene being the culprit behind ME/CFS.

To get a feel of the effect size, I've made an overview of the prevalence of these SNPs in patients versus controls. I couldn't find this in the paper or supplementary material so I've tried to calculate them using R (trying out different guesses until the combined prevalence and odds ratio...

No email yet but seeing some articles being published: Key genetic differences found in people with chronic fatigue syndrome | New Scientist