Stanford Community Symposium 2018: Phair, Metabolic traps, Tryptophan trap

Keela Too said:
Funnily enough I said that in a “slightly” more long-winded way here:

http://sallyjustme.blogspot.com/2017/02/get-out.html
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Really good to read that, because I have always maintained that my wife is best evidence against the deconditioning theory. I'm totally convinced she always does more than would be needed to work past any deconditoning; in your case (glad you have improved by the way), that proves it very nicely. I would tentatively suggest that that little snippet of your ME history alone is very good anecdotal evidence against the deconditioning theory, and that it might be worth citing this as an illustration to NICE.
 
Keela Too said:
@RDP

This is very interesting to me, because of how my level of functioning switched from an average of 500-600 steps per day (3 year duration) to my current 4000 - 4500 average steps in a short space of time in early 2016.

With a few minor waves up & down, I have maintained, but not been able to improve, that new level of activity to date. (I am still limited by PEM, by having to walk slowly, by struggling in busy environments and with standing or sitting upright for normal durations of time - but the improvements to my well-being have been life changing for me and my family.)

It is no secret now, that I took an ARV (anti-retroviral) drug for a year. The switch I experienced happened in a very short space of time about 4 months after starting the drug. It was like a brake had been released! My stamina improved dramatically over a two week period, but it took much longer for my strength to catch up to that improved stamina.

This seems to me to support the idea of a trap of some sort being reversed, allowing me to do more. My initial low strength I attribute to the deconditioning of being so physically inactive for 3+ years. (My strength is still not at pre-illness levels.)

It is also obvious to me, that deconditioning was not the limiting factor in my 500 steps days. Once that limit was lifted, I improved and so I did more, until I hit a new limit. Sadly it seems, I still have something else holding my physical abilities back.

So, I’m hoping that I can maintain this level, and that any further switch is not a backward one.

This post is not a recommendation for the ARV I took. I mention it only because of the “switch” I experienced, which I thought might be interesting in the context of this conversation.

PS I have Fitbit stepcount data for this period on file, so the numbers are not guesswork. ;-)
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Dear Keela, your improvement is really stunning, you know. Why did the doctor give you this drug? What was the thinking? Thank you.
 
Keela Too said:
This post is not a recommendation for the ARV I took. I mention it only because of the “switch” I experienced, which I thought might be interesting in the context of this conversation.
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I've experienced several 'switches' in my 28yrs of ME without taking any meds. As long as we stay within our 'energy envelop" , and avoid PEM, I don't feel that some of us will worsen over time.

BTW, my 'switches' occurred almost overnight.
 
It’s all interesting. My initial onset had a period of viruses and failing but functioning health. Then a general anaesthetic triggered a dramatic drop.

After that I had a year of ratcheting steeply downwards before I properly got the pacing concept, followed by a slower decline over another 3 years, which I still likened to ratcheting down, just slower. However, every slip on my part still involved losing some more ability, apparently permanently. It was a scary time, because by then I’d done enough reading to “know” what might happen on this trajectory. I felt powerless to stop the slow but relentless downward trend.

The decision to take the ARV, was because I was in the right place at the right time to hear about it, and so after much contemplation we (joint decision with my husband, you understand) decided to try it privately. Beyond that I’m not commenting further on reaching the decision.

It gave me a reprieve, and reset me back to probably about where I was just after the general anaesthetic. I remain eternally grateful for this second chance. . . . But am also aware that changes can happen spontaneously, and as such my anecdotal (n=1) experience may not mean much.
 
Keela Too said:
Then a general anaesthetic triggered a dramatic drop.
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Interesting. My wife developed ME whilst recovering from a fairly minor op, but under general anaesthetic, and getting a horrible flu bug at virtually the same time. Her ME became evident by way of not seeming to recover from the operation; turned out her ME was cutting in as her op recovery was progressing OK. (Unless of course history shows ME to sometimes be a post-op-recovery failure mode). Can't help wondering if this could be the kind of perfect storm of trigger events @RDP speaks of regarding the metabolic trap. Either way, it would seem a potential perfect storm that very possibly triggered something.
 
Chris Ponting said:
Thank you @RDP. This is very helpful indeed. I am only now left with a couple of questions: (1) What is the probability that your analysis would have alighted upon *any* gene with this burden of damaging mutations among all that you considered? (In other words, after correcting for multiple tests, what was the q-value from the Chi-squared test?) (2) Have you done, or are you planning, a replication test, using an independent cohort? (As you know, this requires only a single test, so the burden of multiple testing correction, is very small.)

(For others: In essence, my questions are all about whether a single gene, here IDO2, has been pinpointed merely by chance. There are 20,000 genes that could have been pinpointed. At a p-value threshold of 5%, 5% of these (i.e. 1000) would be highlighted by chance; at a threshold of 0.5%, 100 would be highlighted by chance, at p<0.05%, 10 would be highlighted, and so on.)

@RDP My MNV argument is not valid. I was previously put right on this! See previous posts. Thanks all.
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@Chris Ponting I've struggled with the statistical aspects of this, and I'll follow up on your suggestions. It has always seemed odd to me that the appropriate statistical test depends on how you came upon the observation you want to test for significance. As I've said elsewhere, I'm a classical (maybe dated) Popperian hypothesis tester. Like many biologists coming to ME/CFS, I started with the theory that the problem must be mitochondrial, but I also had this conviction based on the existence of outbreaks/epidemics/clusters that any predisposing mutation MUST be common, otherwise epidemics would be inexplicable. Just as I was beginning in ME/CFS, Ron Davis presented me with access to his Big Data study on severely ill ME/CFS patients. This was my very first opportunity to look at any sequencing data in the context of a real project, but the ready accessibility of genome browsers gave me hope that I could become sufficiently expert to test my own ideas. So I searched all the genes coding for proteins in all the complexes in the mitochondrial ETC. That's 70+ genes. You'll be aghast that I did all that by hand, displaying my 20 genomes for one gene at a time and looking for shared common (hopefully missense) mutations among the 20 severely ill patients. Took weeks, but I was a free-agent and I was learning new stuff. Bottom line, perhaps not surprising, there are no common shared missense mutations in the genes coding for components of the mitochondrial ETC. Still thinking it had to be energy metabolism, I turned to other aspects of central energy metabolism. I soon came to the kynurenine pathway because it's one of the sources of NAD+. There are no common damaging mutations in TDO2 or IDO1, but you can imagine what it felt like to type IDO2 into the IGV search bar and have multiple mutations line up for many of the 20 patients. The rest of the story is in the paper. The search of the entire dataset for common damaging mutations in enzymes or transporters came two years later when a student came to me who had those skills in abundance. IDO2 was the 82nd gene I looked at in this way. Does that mean my burden of multiple testing is 82 instead of 20,000? Moreover, with 74 patients, none of the 4 damaging SNPs in IDO2 is statistically more common in the patients than in healthy controls. My risk of false positives is high and it keeps me awake, but the IDO metabolic trap hypothesis is compelling on enough other grounds that, to me at least, it remains worth testing at the level of metabolic fluxes in CFS cells. So, as I've said before, your GWAS of the UK Biobank self-diagnosed patients failing to reach genome-wide significance seems to me correct. It's because we are focused on common mutations that we have the unusual situation of four different keys all capable of unlocking the same lock. Only in a case like this would it make sense to ask how many patients have zero damaging mutations, and how does that number compare to what is expected based on the population allele frequencies?

I will follow up on your ideas, and I'm sure I'll learn a lot. Thanks for sharing your thoughts. Rob
 
RDP said:
@Keela Too If you have those data on stepcounts vs. date in a spreadsheet or a text file, I would love to have a look. I'm always happiest when time is on the horizontal axis.
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I’m just on the iPad just now, but I’ll fire up the computer later and send you some stuff in a PM.

PS... Edited to add, @RDP I just watched your video at the top of this thread. :) Really that trap idea seems to make so much sense! I wonder can there be multiple traps? Given my n=1 observation that I seem to have climbed from one relatively steady state to another, but am not yet actually healthy.
 
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RDP said:
IDO2 was the 82nd gene I looked at in this way. Does that mean my burden of multiple testing is 82 instead of 20,000? Moreover, with 74 patients, none of the 4 damaging SNPs in IDO2 is statistically more common in the patients than in healthy controls.
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RDP said:
It's true that the original group of 20 in Ron Davis' OMF-funded big data study were identified as severely ill. But we now have sequence data for 66 ME/CFS patients covering the entire spectrum of disease severity, and every one of them has at least one damaging mutation in IDO2. The average is 1.8 damaging mutations in IDO2.
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If the original testing which identified damaging IDO2 mutations as a potentially predisposing factor was only done on the 20 severely affected patients, I assume that the remaining 46 samples were tested after the IDO2 hypothesis was generated. Does this not mean that, from a statistical point of view, the 46 should be treated separately from the original 20, without the need to adjust for multiple testing in the 46?

[edited for clarity]
 
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RDP said:
@Chris Ponting I've struggled with the statistical aspects of this, and I'll follow up on your suggestions. It has always seemed odd to me that the appropriate statistical test depends on how you came upon the observation you want to test for significance. As I've said elsewhere, I'm a classical (maybe dated) Popperian hypothesis tester. Like many biologists coming to ME/CFS, I started with the theory that the problem must be mitochondrial, but I also had this conviction based on the existence of outbreaks/epidemics/clusters that any predisposing mutation MUST be common, otherwise epidemics would be inexplicable. Just as I was beginning in ME/CFS, Ron Davis presented me with access to his Big Data study on severely ill ME/CFS patients. This was my very first opportunity to look at any sequencing data in the context of a real project, but the ready accessibility of genome browsers gave me hope that I could become sufficiently expert to test my own ideas. So I searched all the genes coding for proteins in all the complexes in the mitochondrial ETC. That's 70+ genes. You'll be aghast that I did all that by hand, displaying my 20 genomes for one gene at a time and looking for shared common (hopefully missense) mutations among the 20 severely ill patients. Took weeks, but I was a free-agent and I was learning new stuff. Bottom line, perhaps not surprising, there are no common shared missense mutations in the genes coding for components of the mitochondrial ETC. Still thinking it had to be energy metabolism, I turned to other aspects of central energy metabolism. I soon came to the kynurenine pathway because it's one of the sources of NAD+. There are no common damaging mutations in TDO2 or IDO1, but you can imagine what it felt like to type IDO2 into the IGV search bar and have multiple mutations line up for many of the 20 patients. The rest of the story is in the paper. The search of the entire dataset for common damaging mutations in enzymes or transporters came two years later when a student came to me who had those skills in abundance. IDO2 was the 82nd gene I looked at in this way. Does that mean my burden of multiple testing is 82 instead of 20,000? Moreover, with 74 patients, none of the 4 damaging SNPs in IDO2 is statistically more common in the patients than in healthy controls. My risk of false positives is high and it keeps me awake, but the IDO metabolic trap hypothesis is compelling on enough other grounds that, to me at least, it remains worth testing at the level of metabolic fluxes in CFS cells. So, as I've said before, your GWAS of the UK Biobank self-diagnosed patients failing to reach genome-wide significance seems to me correct. It's because we are focused on common mutations that we have the unusual situation of four different keys all capable of unlocking the same lock. Only in a case like this would it make sense to ask how many patients have zero damaging mutations, and how does that number compare to what is expected based on the population allele frequencies?

I will follow up on your ideas, and I'm sure I'll learn a lot. Thanks for sharing your thoughts. Rob
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EDIT: @Chris Ponting Reading your post for maybe the fifth time, I infer that the burden of multiple testing does not devolve from how many tests I DID, but rather how many tests I could have done. Is that inference correct?
 
Andy said:
Just wanted to highlight that, if you need to source samples for any replication test, then there is the UK ME/CFS Biobank, https://cureme.lshtm.ac.uk/researchers/ as a potential resource. As they are able to visit donors at home they have samples from severe patients, and they have experience in shipping samples internationally.
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@Andy That too is a great idea. Thanks!
 
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