What research do you want to see? (study ideas)

forestglip said:
Why not throw in an XXX as well? In theory, the risk of ME/CFS might be higher still if there is a triple dose. That's what seems to be the case in one of the SLE studies.
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Maybe, but one can argue that the situation for XXX raises a different question about repression - of a third X as well - that isn't strictly relevant to the difference between one (male) and two (female) in the way that the others are.
 
I imagine the simplest way to get this dosage data would be to compare the proportions of these with the various X-chromosome make-up spelled out above in the DecodeME cohort versus the general population. Although I don't know if DecodeME collected such data.
 
Simon M said:
Although I don't know if DecodeME collected such data.
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My worry would be that people with XO or XXY might be less likely to offer their DNA for studies, or conceivably more likely. There could be a major skew and the numbers would be quite small. On the other hand if there are any data they might just about be interpretable. Of course it is possible that people with unusual karyotypes were excluded?
 
Jonathan Edwards said:
Of course it is possible that people with unusual karyotypes were excluded?
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The data analysis plan for DecodeME says:
Sex of participants are inferred during the automated genotype calling process in AxAS based on X and Y linked variants. Samples failing this inference are flagged as “unknown” sex. This can reflect underlying sex-chromosome aneuploidy and mosaicism. Such conditions can be identified after conducting a Copy Number Variant (CNV) analysis using the AxAS. The probeset intensities across whole sex chromosomes of “unknown” sex samples are visualised and compared to those of male or female references (7). Samples with an “unknown” sex that remain unresolved or presenting sex-chromosome aneuploidy will be flagged and removed. Additionally, samples showing a discrepancy between the self- reported sex in questionnaire at recruitment and the genetically inferred sex are also removed as indicative of potential sample mix-ups.
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I would assume that whatever quality control tool they used would log the details of each sample that was removed. So maybe it would say "sample 123 was removed for having the XXY genotype". Thus maybe it would be as simple as counting how many XXY's were removed and dividing by the total case count to get prevalence.

Though I do agree there's a possibility of recruitment bias one way or the other with individuals that have these genotypes.
 
The best chance of a biomarker are the problematic antibodies as we saw in what Dara did to the antibodies of responders as measured by Tyler.

Problem is, we don’t know which antibody is the problem
 
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