Elevated ATG13 in serum of pwME stimulates oxidative stress response in microglial cells , 2022, Gottschalk et al

From the Simmaron Research blog: Cleaning Crisis? Is Defective Mitochondrial Cleanup Impairing Energy Production in ME/CFS? (Sep 2022).

Autophagy clears unused proteins and old and damaged mitochondria from the cells and is especially important during exercise. When autophagy breaks down it can impair oxygen consumption and mitochondrial activity, affect immune functioning, turn cells into pro-inflammatory generators, and lead to clumps of proteins that can damage all sorts of processes.
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A variety of tests found high levels of several autophagic factors - most particularly a protein called ATG13. High levels of ATG13 outside in the serum indicate that ATG13 has undergone phosphorylation and has aborted the autophagy process.

Applying serum from ME/CFS patients and healthy controls to the microglial cells caused the cells given the ME/CFS serum to begin spewing out pro-inflammatory substances.
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From the Simmaron Research blog: Cleaning Crisis? Is Defective Mitochondrial Cleanup Impairing Energy Production in ME/CFS? (Sep 2022):

Rapamycin Connection?
Health Rising recently presented the story of a physician who has recovered from ME/CFS using rapamycin - a longevity drug and MTOR inhibitor. That was an interesting report given that MTOR activation aborts the autophagy process. The fact that an MTOR inhibitor significantly helped at least one long-term ME/CFS patient suggests that an impaired autophagy process may be present in some people with ME/CFS.
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This is interesting but, after all the effort that has been put into highlighting the methodological problems and unscientific reasoning applied to BPS research, I wish people would be more careful in their reporting of recovery anecdotes. I’ve not read this story on HR, but it is misleading to say that “an MTOR inhibitor significantly helped at least one long-term ME/CFS patient”. All we can know is that one patient reported that they had recovered after taking rapamycin, an MTOR inhibitor. But without clinical trials we cannot know whether rapamycin helped.

Applying serum from ME/CFS patients and healthy controls to the microglial cells caused the cells given the ME/CFS serum to begin spewing out pro-inflammatory substances.
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Something to add to your Something in the Blood blog @Simon M?
 
I hope they have good reason to hype this up to this level.

"We’re onto something big: a treatable pathway for PEM. The implications are huge. Not only do we believe the chemical pathway involving the ATG-13 protein is a culprit in PEM, we believe it can be targeted for drugs. There is hope for treatment!"

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Andy said:
I hope they have good reason to hype this up to this level.

"We’re onto something big: a treatable pathway for PEM. The implications are huge. Not only do we believe the chemical pathway involving the ATG-13 protein is a culprit in PEM, we believe it can be targeted for drugs. There is hope for treatment!"
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They found something new in a small study...that a whopping two people with ME have elevated levels of ATG13 and that microglia don't like it. This is a brainstorm, not a real hope. While their research appears novel, all scientists should present their findings realistically, especially if they're a non-profit soliciting donations.

A reasonable threshold for a "real hope" of treating PEM would be a drug entering human trials.
 
Hutan said:
There's a sample size calculation to support the use of only 7 case-control pairs. I think it's a bit, I don't know, 'unreasonably applying precision to unknowable things'? to do a calculation like that. I think with preliminary studies, researchers should usually be using sample sizes of at least 20. It's a quibble, I know.
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This is the sample size determination as stated in the paper.

"For 99% confidence interval and 0.05 significance, our sample size calculation is n = z2×p (1− p) / ε2 = 1.282×0.99 (1− 0.99) / 0.05^ 2 = 7. Z is the z score, which is 1.28 for power 0.8; p is the population proportion. For 99% confidence interval, p will be 0.99; ε is the margin of error = 0.05. Therefore, throughout the study we selected at least n = 7 per group when comparing results between HC and ME groups."
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To me this does not make sense. A power calculation requires an effect size.

The author probably misinterpreted a formula he found online or in a textbook: p should be a proportion of the population, e.g how many people have a disease. Setting p to 99% because one wanted a confidence interval of 99% seems like a quite a big statistical misunderstanding.

If the authors conducted a proper power calculation, they would probably found that only incredibly large effects can be reliable detected with 7 participants per group.
 
ME/CFS Skeptic said:
Did anyone get a reply about this inconsistency?

Below is figure 3.A as used in the paper:
View attachment 18793

And this is my own plot of the data shown in table 1:
View attachment 18794
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To me it seems like outliers have been removed in their plot, while you've kept them in yours. If you filter out the top and bottom participants from both groups (and use geom_quasirandom/play around with how wide your groups can be, and change to theme_classic) I think they will look the same.

Edit: Agree the power calculation is off. Sure it's difficult with omics data when we know so little about what is "normal" of what we are measuring but to get a sample size then go with Hutans suggestion (though I've been taught at least 30, not 20).
 
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