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Mine is ME/CFS from hEDS made worse by the covid vaccine. Patient led 'research' I'm talking about is done off the books in private chat groups / discords / telegram - so nothing is published. That's a double edged sword - but given the slow pace of normal medical research we just couldn't wait. Given that it's grey / black market these groups, the ones that survive, are extremely private.

Those listed conditions are a set of overlapping clusters that have a lot in common. Some of the listed conditions do have distinguishing comorbidities. The things you listed does appear squarely in the shared comorbidities and not in any of the distinguishing comorbidities - so it could be any number of things. The Ulcerative Colitis does increases the likelihood that it's hEDS which is already the highest likely predisposition @ ~2% of general population and higher for the HN population and even higher again for physics people (not the published figures of 1/50K, 1/15K, or the 1/500 which I consider to be incorrect due to the incorrect assumptions for disease state thresholds in the diagnostic tests).

Probably the best lens to look at it would be through the lens of dysautonomia which is a balance of a not well understood by the vast majority of doctors yet reasonably well understood by a few doctors - enough to be able to find decent information in medical research. My preferred meds for treatment of dysautonomia are modafinil and amitriptyline and these meds also act as immunomodulators - the same thing the helminths are supposed to help with. Modafinil can exacerbate gastro issues so in my view people who have those issues should focus on amitriptyline first (at the sleep aid doses not the depression doses). And googling it now it does appear that amitriptyline is indeed a known treatment for Ulcerative Colitis.



Curious to know the origin of your likelihood calculation (HN & Physics).

Also very funny you inspect my account to figure out I'm a physicist.


That's how I get my data, well at least substantively check some of my data. Behavioral analytics a.k.a big anecdata. With great care and restraint it is possible to extract useful information from a large amount of biased sources - just can't publish it unless you want to spend the rest of your life arguing with people who argue for a living and do little else (academics).

With enough data it's possible to disambiguate between genetically linked behaviors and learned behaviors because of the different diffuse patterns through disparate populations. The summary is that behavior and intelligence is absolutely dominated by genes, there is really only a 13% residual - so on a nature vs nurture spectrum the nurture is less than 13%.

The stronger the selection criteria bias on intelligence the more likely a RCCX gene variant (SNPs) will be selected, specifically TNXB (burnout / ME/CFS), C4 (schizophrenia), and CYP21A2 (generalized anxiety disorder).

You may wonder why this doesn't come up in GWAS studies - usually there is an assumption of independence of SNPs due to the idea that most SNPs are very old and genetic drift has been sufficient to provide this independence. Since these individual SNPs are so behaviorally impactful there a strong sexual selection bias that takes place so those assumptions don't hold and thus the math is bunk. I could spend forever talking about the incompetence of medical research.

Dr Jessica Eccles is probably doing the best research where she talks about the shocking 'overrepresentation' of Generalized Hypermobility Disorders (GHD) in the Long Covid populations. In my view the only difference between GHD and hEDS is the number and severity of TNXB SNPs, so while 2% of the population are impacted most of those are only mildly impacted. The co-occurrence of multiple TNXB SNPs is much higher random chance - again from the aforementioned sexual selection biases. In general researchers into such conditions assume TNXB SNPs are far too common to cause such a rare disease, the thing is that it's not a rare disease - just rarely diagnosed and surfaces in a variety of complex ways that look completely different to the untrained eye.

You can get a Deep Whole Genome Sequence for ~ $280 from dantelabs and then you'll know for sure.




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