Jonathan Edwards
Senior Member (Voting Rights)
it may also be worth remembering that 'MHC' originally refers to gene products that determine histocompatibility of allograft cells - which is not to do with their antigen presenting function.
Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration
V.R.T.
Senior Member (Voting Rights)
Would it be an idea to ask Chris if this is the case? It seems like a very important point to get clear on.
V.R.T.
Senior Member (Voting Rights)
Do they mention why they had reason to distrust it anywhere?
DCC is a netrin-1 receptor, and it seems to be relevant to the functioning of epithelial cells of various sorts.
What is Epithelial Cell Polarity?
- Asymmetrical Structure:
Epithelial cells are oriented with distinct "poles" – an apical surface that faces a lumen or the outside of the organism, and a basolateral surface that faces other cells or the underlying extracellular matrix (basement membrane).
- Structural Organization:
This orientation allows the cells to form organized sheets and maintain their position within tissues.
- Functional Barrier:
Polarity is vital for the selective transport of ions, water, and other molecules across the epithelial layer, ensuring a controlled passage between different compartments of the body.
If epithelial cell polarity was disrupted, that might make problems related to the absorption of molecules across epithelium. For example, vascular epithelial issues could cause faulty fluid and ion homeostasis, maybe accounting for muscle weakness and pain.
Maybe the flow of water and ions across the faulty vascular epithelium would be okay when the body is at rest. But when more demand is placed on the body, maybe when there are more activated T cells, that would result in a faulty vascular epithelium not delivering what is needed to tissues (or taking waste away).
jnmaciuch
Senior Member (Voting Rights)
Yes it was in the results section on HLA, had to do with lack of linkage disequilibrium where it was expected leading them to suspect an imputation issue, if my memory serves. I am on my phone so cannot quote the text
My layman understanding:
They caution that the results are based on imputed data. They want to repeat the analysis using directly imputed HLA alleles for both cases and controls together to confirm whether this association is real or not.
- One allele, HLA-DQA1*05:01, was significantly associated with ME/CFS.
- Its frequency was lower in cases (21.7%) compared to controls (23.2%) (the finding held even when they restricted analysis to a genetically more uniform group).
- The association was very statistically strong (p = 1.4 × 10^{-10}).
- They checked related alleles (HLA-DRB1*03:01 and HLA-DQB1*02:01) but didn’t find strong associations (p-values were not significant: 0.27 and 0.042).
- This was a bit surprising, since these alleles are often inherited together with HLA-DQA1*05:01.
They caution that the results are based on imputed data. They want to repeat the analysis using directly imputed HLA alleles for both cases and controls together to confirm whether this association is real or not.
jnmaciuch
Senior Member (Voting Rights)
Indeed. And the alleles that matter for compatibility are the ones in the actual HLA protein complexes.
The DCC gene is an netrin-1 receptor. LRRC4B is a netrin-G3 ligand (that is, it binds to a receptor).
There does seem to be the repeated themes in the DecodeME identified possible genes of endothelium and neural synapses.
This is a 2012 paper:
Netrin Ligands and Receptors: Lessons From Neurons to the Endothelium
and is paywalled. Possibly it makes for interesting reading, perhaps it has been cited by more up-to-date papers.
ME/CFS Science Blog
Senior Member (Voting Rights)
A gene that hasn't been disucssed much is TAOK3 on chromosome 12 (it wasn't a Tier 1 gene). It has been previously been associated with Lupus at around the same region as in DecodeME. The vertical dotted line in the graph below shows the location for the Lupus hit (12:118244946) with the SNP summary data from DecodeME.
The Lupus GWAS said this about it:
pubmed.ncbi.nlm.nih.gov
The Lupus GWAS said this about it:
Identification of Shared and Asian-Specific Loci for Systemic Lupus Erythematosus and Evidence for Roles of Type III Interferon Signaling and Lysosomal Function in the Disease: A Multi-Ancestral Genome-Wide Association Study - PubMed
In this study both shared and Asian-specific loci for SLE were identified, and functional annotation provided evidence of the involvement of increased type III IFN signaling and reduced lysosomal function in SLE.
pubmed.ncbi.nlm.nih.gov
Jonathan Edwards
Senior Member (Voting Rights)
"It enhances T cell receptor signaling by regulating its negative feedback by SH2domain–containing phosphatase 1 (44), and Taok3 deficiency in mice was found to cause defects in the development of marginalzone B cells but not follicular B cells (45)."
Intriguing. An influence on SHIP1 would make some sense. Marginal zone B cell behaviour is odd in lupus too.
Intriguing. An influence on SHIP1 would make some sense. Marginal zone B cell behaviour is odd in lupus too.
jnmaciuch
Senior Member (Voting Rights)
Is this for the same hit that was annotated to SUDS3 in DecodeME?A gene that hasn't been disucssed much is TAOK3 on chromosome 12 (it wasn't a Tier 1 gene). It has been previously been associated with Lupus at around the same region as in DecodeME. The vertical dotted line in the graph below shows the location for the Lupus hit (12:118244946) with the SNP summary data from DecodeME.
View attachment 28547
The Lupus GWAS said this about it:
Identification of Shared and Asian-Specific Loci for Systemic Lupus Erythematosus and Evidence for Roles of Type III Interferon Signaling and Lysosomal Function in the Disease: A Multi-Ancestral Genome-Wide Association Study - PubMed
In this study both shared and Asian-specific loci for SLE were identified, and functional annotation provided evidence of the involvement of increased type III IFN signaling and reduced lysosomal function in SLE.
ME/CFS Science Blog
Senior Member (Voting Rights)
Yes
jnmaciuch
Senior Member (Voting Rights)
Interesting, so it seems like this is another case where the final annotation for DecodeME was chosen based on high number of [edit: coloc] tissues. The top SNP is within an intronic region in DecodeME, and seems to be quite a long deletion. The mutation in the lupus paper you posted was in a protein-coding region which might explain stronger effect of the mutation.
Also, interesting that 3 proteins in that whole region that looks to be in LD have well-established links to MAPK signaling (SUDS3, TAOK3, and PEBP1)
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I've copied @ME/CFS Science Blog's chart and some discussion about TAOK3 to the discussion thread we had on SUDS3, renaming it Chromosome 12 SUDS3, TAOK3. Probably those discussion threads should have been titled about the identified regions of interest rather than individual genes.
Genetics: Chromosome 12: SUDS3, TAOK3
Those charts with the DecodeME results and gene positions are really useful, ME/CFS Science Blog.
Genetics: Chromosome 12: SUDS3, TAOK3
Those charts with the DecodeME results and gene positions are really useful, ME/CFS Science Blog.
ME/CFS Science Blog
Senior Member (Voting Rights)
Thanks I should probably mention that I zoom out a bit more (1Mb) than most tools like LocusZoom (around 250kb) to get an overview of the entire region around the hit. The implicated genes are probably closer to the top SNP then the region I show (so don't pay too much attention to the genes at the borders of my graphs).
ME/CFS Science Blog
Senior Member (Voting Rights)
Reading some GWAS in other illnesses made me appreciate DecodeME even more.
Other GWAS are usually based on (1) extracting data from big databases like the UK biobank, Finngen, AllofUS, 23andME etc. where the case definition was often poor or (2) on multiple cohorts that are combined into a single meta-analysis which likely has extra problems in terms of preventing confounding.
I haven't seen many GWAS where they collected the entire sample in one study like DecodeME did. This had the benefit that the case definition could be stricter defined using extra questionnaires and that the researchers could include various questions that might help their analysis. DecodeME was in contact with all its participants that donated DNA, which is often not the case for other GWAS.
I'm curious to see if some of the hits we see are due to a comorbidity such as depression or pain (if the signal is the same in ME/CFS patients without depression or without pain). Hoping that the questionnaire data will allow such an analysis.
Other GWAS are usually based on (1) extracting data from big databases like the UK biobank, Finngen, AllofUS, 23andME etc. where the case definition was often poor or (2) on multiple cohorts that are combined into a single meta-analysis which likely has extra problems in terms of preventing confounding.
I haven't seen many GWAS where they collected the entire sample in one study like DecodeME did. This had the benefit that the case definition could be stricter defined using extra questionnaires and that the researchers could include various questions that might help their analysis. DecodeME was in contact with all its participants that donated DNA, which is often not the case for other GWAS.
I'm curious to see if some of the hits we see are due to a comorbidity such as depression or pain (if the signal is the same in ME/CFS patients without depression or without pain). Hoping that the questionnaire data will allow such an analysis.