Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

[Jonathan Edwards]

A question that remains is what exactly is causing the increased risk in women. Is it genetic variants on the X chromosome, hormonal or immune differences?

I don't think the 'increased risk in women' - i.e. why women have more ME/CFS than men - can be due to genetic variants of the X chromosomes because any variants will be shared out equally to both men and women. Genetic variants on the X chromosome may explain why women with ME/CFS have it and women without ME/CFS don't but that is a separate issue.

And we almost certainly cannot separate hormonal from immune issues because immune differences are very likely dependent on cumulative hormonal environment over many years, with changes at menarche and menopause. There might be a polymorphism in a gene for an immune receptor that is directly influenced in expression level by a single gene on the X chromosome with dosage effect (double for women). It that polymorphism was skewed differently in women with ME/CFS from women without ME/CFS we would have something meaty to work on but this may be wishful thinking.

 

[forestglip]

So the control data QA sweep used GnomAD (v2.1.1) which is an hg19 reference. But the DecodeME paper references hg38 locations?

As far as I understand, that shouldn't really change anything. h19 and hg38 are just different ways to refer to a SNP and can be converted between each other.

 

[wigglethemouse]

As far as I understand, that shouldn't really change anything. h19 and hg38 are just different ways to refer to a SNP and can be converted between each other.

I understand. I just expected to see something in the methods to explain what they did. I could find no mention of the remapping the genomic location from hg19 to hg38 in the text using a search and a quick read of the relevant sections in methods.The methods are very detailed. Perhaps I missed it.

I always get concerned when I spot check a main finding in the paper with available information and there is a mismatch. In this case one of the main findings is OLFM4 variant 13-53194927-GT-G rs35306732 in the paper but it does not exist in publicly available data on geneatlas for the UK Biobank axiom array data from which the control data was taken. LINK

@Chris Ponting would you be kind enough to explain why I can't find the OLFM4 variant from the paper in the data on the geneatlas tool?