Genetic similarities between ME/CFS and other diseases

I'm sorry, it was late for me eight hours ago.

I believe in the persistence theory.

I believe that's what makes us sick, fools us lab wise. A pathogen tandem abrogates our immune system, it snips the wiring so to muffle the alarms.

But I also think, paradoxically, our immune system is making us feel sick.

There has always been a contradiction of sorts here, but it is more stark now, harder to reconcile with these findings.

Never a dull moment.

ETA: Harder, but not impossible. :)
 
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Sean said:
Seriously complicated by it being unclear how 'recovered' those reporting recovery actually are, and if they are really completely free from the disease process.

We do indeed have a major data deficit on this question.


I have that. Consistently high ALP, every single time it has been measured since at least from when I was first diagnosed in 1989 (including standard annual bloods). Don't know about before then. It is the only consistently abnormal lab marker that has showed up in all that time, including other liver function tests.

What, if anything, it has to do with ME/CFS I have no idea. No doctors have thought it important enough to follow up. *shrugs*
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"The ALP isoforms were assayed by isoelectric focusing. Our data suggest that the increase in ALP and ALP-10 closely reflects the abnormal activation of T lymphocytes that is common in autoimmune diseases, and that the source of the ALP-10 is activated T lymphocytes."
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Sean said:
I have that. Consistently high ALP, every single time it has been measured since at least from when I was first diagnosed in 1989 (including standard annual bloods). Don't know about before then. It is the only consistently abnormal lab marker that has showed up in all that time, including other liver function tests.

What, if anything, it has to do with ME/CFS I have no idea. No doctors have thought it important enough to follow up. *shrugs*
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Probably because many people have elevated ALP but they do not have ME/CFS so elevated liver enzymes cannot possibly be responsible. Not my thoughts, obviously - since 2011.
 
Felis Catus said:
I think my most essential question is: was that procedure developed to be used on a dataset of different illnesses or a dataset of patients who all have the same illness? From little reading about SNF, I saw it could be used for the latter which doesn't mean that it couldn't be used for the former. I don't know enough myself to answer the question. I thought if it was developed specifically for the latter (i.e. trying to identify subgroups/subtypes) then it would probably need modifications. I understand it's a draft and I'm not judging your judgement. If it turns out that something we write here identifies what you could change, great.
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SNF takes as input N symmetric matrices (with same dimension) with elements between 0 and 1 (similarity scores) and generates a consensus matrix where similarity scores that are similar in different input matrices are increased while the others are decreased. From the manual of the R package I used to apply this method:

Similarity Network Fusion takes multiple views of a network and fuses them together to construct
an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances,
or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and
classification.
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paolo said:
At present, my idea is that it is a disease of the brain, it is not a psychiatric disease and it is not a neuroimmune condition. I am waiting for a clustering made by others, I think it may be really important at this point. I will revise mine in the meanwhile.
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I'm somewhat less confident about the genes selected for ME/CFS because of PrecisionLife's approach, and because Snyder's study had only around 200 participants and focused on rare mutations. Would it be an option to use a smaller selection of genes where we have some higher confidence? For example, the 2 closest to DecodeME hits defined by, for example, p < 10^-6? Or would that still result in too few genes to make such an analysis?

The LDSC comparisons did point to similarities to fatigue, IBS, but also neuropsychiatric conditions such as depression/anxiety, etc.
 
ME/CFS Science Blog said:
I'm somewhat less confident about the genes selected for ME/CFS because of PrecisionLife's approach, and because Snyder's study had only around 200 participants and focused on rare mutations. Would it be an option to use a smaller selection of genes where we have some higher confidence? For example, the 2 closest to DecodeME hits defined by, for example, p < 10^-6? Or would that still result in too few genes to make such an analysis?

The LDSC comparisons did point to similarities to fatigue, IBS, but also neuropsychiatric conditions such as depression/anxiety, etc.
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The method I am using needs dozens of genes. LDSC comparison is probably the canonical way to do this job, but I developed a fascination for gene networks and I want to pursue this avenue.
 
paolo said:
SNF takes as input N symmetric matrices (with same dimension) with elements between 0 and 1 (similarity scores) and generates a consensus matrix where similarity scores that are similar in different input matrices are increased while the others are decreased. From the manual of the R package I used to apply this method:
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Let's take a step back. What I've been asking from the beginning is not a technical detail. It's a more fundamental high level "I saw people applying this to the data coming from a set of patients who all have the same illness. Can the method be applied to a set of different illnesses and give a valid output?"

I'm interested if the data coming from different illnesses can be handled the way it was handled to get a dendrogram of illnesses that makes sense.

It's ok if you don't know the answer and just gave it a go anyway to see what happens. I was thinking that if you weren't sure, maybe that was the first question to get a clear answer to. Because if the answer was no, that's what had to be addressed first.

I won't pester you with this question any more.
 
Felis Catus said:
Let's take a step back. What I've been asking from the beginning is not a technical detail. It's a more fundamental high level "I saw people applying this to the data coming from a set of patients who all have the same illness. Can the method be applied to a set of different illnesses and give a valid output?"

I'm interested if the data coming from different illnesses can be handled the way it was handled to get a dendrogram of illnesses that makes sense.

It's ok if you don't know the answer and just gave it a go anyway to see what happens. I was thinking that if you weren't sure, maybe that was the first question to get a clear answer to. Because if the answer was no, that's what had to be addressed first.

I won't pester you with this question any more.
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I think that the technical detail is important: SNF is a method that works on symmetric matrices, as I wrote, and fuses them, building a consensus. It can be applied to a wide class of problems, wherever you are dealing with similarities or distances.
 
mariovitali said:
Probably because many people have elevated ALP but they do not have ME/CFS so elevated liver enzymes cannot possibly be responsible. Not my thoughts, obviously - since 2011.
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Not saying this analogy holds for elevated liver enzymes, imo chronically elevated liver enzymes (which I have too since ME) might be a side effect just like mildy elevated glucose found in ME

But almost everyone has EBV by the time they are adults and most do not have MS but the evidence is out there now that EBV is implicated in triggering and/or driving MS.
 
paolo said:
At present, my idea is that it is a disease of the brain, it is not a psychiatric disease and it is not a neuroimmune condition.
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Ciao, @paolo .Thanks much for your work on this.

If possible can you expand upon your statement that ME/CFS is a brain disease and not a neuroimmune disease?

If this is the case how would you explain that patients have likely responded to immunomodulatory treatments such as Daratumumab and cyclophosphamide?

Lastly, as others such as @leokitten have commented, if ME/CFS is a pure brain disease, the likelihood of finding a treatment is likely much lower than if it were an immune mediated disease.

Thanks.
 
Jaybee00 said:
Lastly, as others such as @leokitten have commented, if ME/CFS is a pure brain disease, the likelihood of finding a treatment is likely much lower than if it were an immune mediated disease.
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It’s my personal opinion because pure neurological disorders have historically had a very hard time getting at the pathophysiology and then finding targets and discovering and trialing new treatments

Not to mention getting consistently good funding and research interest for pure neurological disorders
 
On the topic of treating neurological disorders: this reddit thread in r/neurology offers me some hope.

Top comment says:
Since I graduated medical school [spinal muscular atrophy] has gone from meaning death before the age of 2 to what appears to be totally normal development and lives for these kids (obviously, can’t fully know what will happen in the next few decades as they grow). There is now also a gene therapy for Duchenne Muscular Dystrophy and another one for metachromatic leukodystrophy. Gene therapies and enzyme replacement for many other diseases are also in the works and studied are very promising.
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I doubt those particular 3 disorders will have much relevance to us, but it does sound like progress is happening. Also two diseases we have gotten better at treating recently are migraine and narcolepsy, which may have more in common with ME/CFS.
 
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