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I suspect these evolutionary pressures long predate the time of arrows. And because hEDS is said to be a disabling disease appearing in adolescence it would in many cases have reduced fitness. So the idea is that strong effects like the one found here would normally have been filtered away if...

I think that the effect sizes seen in DecodeME are the norm in GWAS. There's also an evolutionary theory behind this stating that if a common SNP was more strongly associated with disease, it would have been deleted. So the strong effect (OR = 1.66) found here is a bit curious and unusual...

@Jonathan Edwards how would you explain SLC39A13 showing up in this meta-analysis? Doesn't it seem to suggest a relationship between hEDS and EDS?

Yes not sure if that statement holds up, hadn't seen it. Thanks for highlighting it.

Not sure I would agree with that either: some of the genetic correlations we calculated with LDSC were quite high.

I am not sure this statement is correct by the way - regardless of the debate about hEDS in this thread. All human traits have heritability. My guess would be that if you take people with severe fatigue you might also find significant hits in a GWAS the size of DecodeME.

My own argument has been that the hEDS diagnosis likely captures a lot of people who do not have a connective tissue disorder but some other disease. Think the genetic data of this study is still consistent with that. The two hits show strong effects but it isn't very clear what they mean. They...

None of the regions found here came close to genome-wide significance the DecodeME dataset. ChromosomersIDp-value in DecodeME 2 rs2708184 0.637 8rs16880769 0.0672

The effect sizes are much larger (OR of 1.29 and 1.66) than in DecodeME.

I'm always a bit skeptical about medical succes stories based on individual cases and n = 1 trials. But the idea of repurposing drugs and testing it for many (often rare) diseases that don't have treatments have yet, seem to make sense.

It used to exist.

Not that I can remember but it's quite possible that I overlooked.

Yeah good point, it's a bit arbitrary. Selected the ones with the most associations (those that you see if you click on 'Traits'). Those are mostly quantitative traits like height or intelligence that have been tested a lot and have big sample sizes. So I also looked at traits with a reported...

Searched for genes, like CA10. Then you get a list of other traits and GWAS where the gene has been implicated. Selected the DecodeME genes mainly based on proximity to the SNP with the lowest p-value in the region. The bottom of the table is from regions that only reached a p value of 10^-7.

Coming back to @Woolie 's argument that the SNPs might reflect differences in non-ME/CFS factors such as ancestry, socio-economic status etc. I think that big genetic differences due to ancestry are controlled for by adding the 20 principal components to the regression. But what I said about...

See quite some similarity between this GWAS on multisite chronic pain. Genome-wide association study of multisite chronic pain in UK Biobank | PLOS Genetics Heritability around 10%, MAGMA only points to brain regions, DCC, CA10 and SOX6 as significant hits, genetic correlation with depression...

As the DecodeME preprint highlights, DCC has repeatedly been associated with chronic pain including in this GWAS of Analgesic Use https://www.medrxiv.org/content/10.1101/2024.12.02.24318312v1.supplementary-material

The source data about immune cells can be downloaded here: https://www.ebi.ac.uk/gwas/publications/32929287 But it seems like quite a lot of work to download and filter all of these (suspect the authors had automated scripts for this).

Interesting that elevated TNF levels were inversely related to ME /CFS risk. The effect size, however, were small and as @forestglip mentioned it doesn't look like they correct for multiple comparisons. So the significant results the paper highlights may simply be false positives. I wonder if...

Don't want to beat the same drum but these secondary hits also point to neuronal development, synapses, synaptic transmission etc.