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This might be a better comparison. Tried to convert the DecodeME data back to the GRCh37 positioning (28151 SNPs failed) and then used the same x-axis range. Insomnia GWAS 2019 DecodeME transferred to GRCh37 using

Here's how the signal looked like (notice that the X-axis is much shorter in DecodeME) EDIT: the graphs are misleading: the Insomnia GWAS uses GRCh37/hg19 positioning versus GRCh38/hg38 in the DecodeME graph. Insomnia GWAS 2019DecodeME data on ME/CFS 2025 The p-values for the insomnia...

On the GENE Atlas site you can click on PheWAS: https://atlas.ctglab.nl/PheWAS This allows you to search on geneID or rsID in the GWAS in their database.

Also noted that the Postuma received a large grant (BRAINSCAPES) of around 20 million euros to work out the biological mechanisms behind genetic results of brain disorders. Might be useful for DecodeME could make a connection to this group to see if ME/CFS could be included in their work...

Apparently CA10 was associated with morningness, in the same study. Suspect that this is something that would be useful: to systematically search if the DecodeME genes show up in other GWAS.

It also makes it possible to look if genes have been found in previous GWAS. For example it helped me find that OLFM4 was a hit in this GWAS on insomnia...

There's also this gene atlas which provides lots of data of previous gwas including manhatten and qqplots for comparison. Unfortunately, it looks like they stopped updating it since 2019. https://atlas.ctglab.nl/

I think it's very unlikely. The ancestry was controlled for by first choosing similar European ethnicity as the UK Biobank controls and then by adding the first 20 principal components as covariates in the regression analysis. These PCs showed no clear pattern anymore between patients and...

This paper gives some data and background on eQTL not being as useful in identifying relevant genes as many anticipated. The missing link between genetic association and regulatory function | eLife Using diseases and genes were the mechanisms are relatively well understood, they found that...

For those with strength, courage and coding skills: I've noticed that the Dutch authors of MAGMA have a new method called FLAME. It combines multiple approaches to finding the effector gene within a significant GWAS locus using a machine-learning framework. Prioritizing effector genes at...

Regarding neuronal damage, there's this paper from last year that reported (slightly) increased Neurofilament Light Chain. Trial Report - Plasma Neurofilament Light Chain: A Potential Biomarker for Neurological Dysfunction in ME/CFS, 2024, Azcue et al | Science for ME This has also been...

Thanks for delving into this! It looks so complicated. I expected that there would be nice packages in R and Python that wrap this into a handy user interface and provide the correct reference data (for LD, for example) automatically. Quite disappointing that the workflow mostly consists of...

I think it would only need to explain why nothing has been found yet on the brain scans (mostly MRI) that have been done. Based on @SNT Gatchaman interesting example of chronic traumatic encephalopathy and others' responses that neural damage would still be possible, I think brain banks and...

This looks like it could be quite important, a new target for pain treatment?

Looks like a labelling issue of the graph. Here's what I got trying to recreate it. The high p-values belong to the SNPs with high MAF values, showing that it was mostly this group that reached significant hits. @Chris Ponting

Tried to recreate the plot using the whole dataset: I thought it started to deviate from the red line (which has a slope of 1) quite soon already from an observed -log10 p-value of 3. But the graph is a bit misleading because it is logarithmic so the vast majority of points are in the region...

Anecdotally I heard that the problems are mostly with bacterial infections, not so much with viral infections in severe ME/CFS. But I don't know if that is a consistent pattern.

Ah apologies. I think I mostly meant brain damage or structural changes, things you can more clearly see on brain scans.

But isn't that a peripheral neuropathy, one that wouldn't explain any of the core ME/CFS symptoms? And why would a injury that is not severe cause much more debilitating fatigue symptoms than the severe CNS injuries that are already known? If it is possible, it will probably have this special...

I don't understand why the prevalence of ME/CFS was so high in no-LC and control cases: how could it be 6.7% in people without Long Covid symptoms and 10% in controls? That's 20 times higher than common estimates of ME/CFS prevalence.