Columbia University: Insights from Metabolites Get Us Closer to a Test for Chronic Fatigue Syndrome

Hmm.

Going by this article (and what I may or may not have read from the actual paper, my memory is hazy), I think that they are saying that they can separate out the patients and the controls used in the microbiome study and this metabolic study (I think they were the same people used in both) quite well on the basis of some selected parameters identified as important from both studies. While that is interesting, I would not say that it's a predictive model yet or that it means that we are close to lab tests.

Given that they are applying a model developed from the results from one set of people to the same set of people and given they have lots of parameters to choose from, I would be very surprised if their model was not good at separating out patients and controls in that set of people.

I could be wrong (hopefully I am), but I don't see any mention of applying this model (which includes quite a large number of parameters) to a completely new set of patients and controls and finding that it successfully separates out the two groups. If indeed they have not done that, then they are doing what we have criticised others of doing, which is making their findings seem a lot more significant than they are at this stage.

This problem was discussed in detail in the thread
https://www.s4me.info/threads/treat...th-sodium-dichloroacetate-comhaire-2018.2885/
where Frank Comhaire was doing something similar in principle, and was rightly slammed for it.

Edit: I have re-read the CII study now. They definitely have not tested their model on an independent cohort. This is from their report:

It erodes trust when researchers make claims of biomarkers and lab tests being imminent on the basis of very preliminary data.

 

And this is a bit of a stretch too. The researchers could separate out patients from controls on the basis of the 10 metabolites showing the most difference - with a certainty of around 82.0%. By adding in the 8 most useful bacterial species in the trial participants' faecal samples, they increased the certainty to 83.6%. To say that the inclusion of the prevalence of the bacteria species improved the certainty of the model is true, but bearing in mind that this is an unverified predictive model, an improvement in certainty of 1.6% is pretty unexciting. Perhaps it just sounds more sexy to have a model based on microbiome and metabolome parameters?

I'm not criticising the paper so much as the unwarranted spin of this article.
Here's the thread on the paper itself:
https://www.s4me.info/threads/insig...ehensive-metabolomics-2018-lipkin-et-al.4873/

 

I have the same hesitation about the predictive modelling aspect of this research, especially if they haven't tested their predictions on a separate cohort. I've just been looking at some of the Workwell 2day CPET information, and they get 95% predictive accuracy from this testing. Not as useful, in the sense that you have to put people through the test that sets off PEM, but it would be interesting if they could test the metabolomic/microbiomic data on patients who have done 2 day CPET.

And I'm also left with the conundrum - If you diagnose people in two ways -
1. by a doctor interview and symptom questionnaire
2. by metabolomics
And you get an 85% overlap, which is the inaccurate one? Maybe the metabolomics are 100% accurate and the 15% who didn't show up on the metabolomics had been misdiagnosed by the doctor, or maybe the doctor was 100% accurate, but not everyone with ME has the same metabolic signature.

Or am I talking bollocks?

As for developing an animal model, I'm skeptical. Maybe give them an infection and while they have the infection, over-exercise them instead of letting them rest, then separate out the ones that fail a 2 day CPET, if you can do such a thing with mice.

 

I don't think it would be very hard. The number of metabolites they tested for was over 500. It's not that surprising that 10 of them were quite different in the patients compared to the controls. Even then, those 10 metabolites still only separated patients from controls with moderate certainty. And remember, it's not as if every patient had abnormal levels of all ten of those metabolites. A single patient might just have abnormal results for a few of those metabolites.

We have seen a number of metabolite studies now that tell some generally similar stories but the detail of the metabolites with the biggest differences between controls and patients I think varies quite a bit. This makes it quite unlikely that this study is the last word on the combination of metabolites that identifies ME.

I agree with others who suggest that more factors need to be standardised in these metabolite studies - e.g. all women, no medications or supplements, standard diet for a month before samples are taken, same time of menstrual cycle.

 

I think that's where the Ron Davis nanoneedle, or the Seahorse technology with blood cells comes in - finding that there's something wrong with the aerobic metabolism in our cells, rather than having to test our whole system's aerobic metabolism with exercise.

 

No, they have not. See this thread.

https://www.s4me.info/threads/colum...for-chronic-fatigue-syndrome.4947/#post-88857