Elevations of ventricular lactate levels occur in both chronic fatigue syndrome and fibromyalgia, 2017, Natelson et al

Andy

Andy

Senior Member (Voting rights)
ABSTRACT
Background: Chronic fatigue syndrome (CFS) and fibromyalgia (FM) frequently have overlapping symptoms, leading to the suggestion that the same disease processes may underpin the two disorders – the unitary hypothesis. However, studies investigating the two disorders have reported substantial clinical and/or biological differences between them, suggesting distinct pathophysiological underpinnings.

Purpose: The purpose of this study was to further add to the body of evidence favoring different disease processes in CFS and FM by comparing ventricular cerebrospinal fluid lactate levels among patients with CFS alone, FM alone, overlapping CFS and FM symptoms, and healthy control subjects.

Methods: Ventricular lactate was assessed in vivo with proton magnetic resonance spectroscopic imaging (1H MRSI) with the results normed across the two studies in which the data were collected.

Results: Mean CSF lactate levels in CFS, FM and CFS + FM did not differ among the three groups, but were all significantly higher than the mean values for control subjects.

Conclusion: While patients with CFS, FM and comorbid CFS and FM can be differentiated from healthy subjects based on measures of CFS lactate, this neuroimaging outcome measure is not a viable biomarker for differentiating CFS from FM or from patients in whom symptoms of the two disorders overlap.
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Paywalled at http://www.tandfonline.com/doi/abs/10.1080/21641846.2017.1280114?journalCode=rftg20

Study is from Feb 2017 but Solve have just posted a review of it:
The study was authored by Dr. Natelson, of the Pain & Fatigue Study Center at Beth Israel Medical Center, in conjunction with pain specialists, clinicians, and quantitative experts. The team used neuroimaging to measure ventricular lactate in subjects across three diagnostic groups – FM only, CFS only, or CFS plus FM – and compared to healthy controls. A modified version of the 1994 Fukuda (CDC) criteria was used to select CFS patients.

The group found that, relative to healthy controls, ventricular lactate was higher in all illness groups included in the study. Elevations in ventricular lactate suggests a shift to anaerobic processes and a problem with brain-related mitochondrial metabolism across the CFS-FM spectrum. The authors conclude that, while there is evidence that ventricular lactate measured by neuroimaging can be used as a biomarker of syndromes characterized by medically unexplained pain or fatigue, this result does not indicate it can be used to differentiate CFS from FM.
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http://solvecfs.org/elevations-of-v...th-chronic-fatigue-syndrome-and-fibromyalgia/
 
Fascinating. So if I understand it correctly, lactate is elevated in the brain in CFS and FM, but not in General Anxiety Disorder or in healthy controls.

And Solve think this could be caused by a problem with mitochondrial metabolism in the brain so it switches to relying more on anaerobic energy production, which produces lactate. Which fits neatly with other studies with white blood cells and muscles, I think.

And they suggest this as a biomarker for CFS and FM.
 
This seems to me exactly the sort of methodology people should be using. MRI spectroscopy is a hugely powerful tool for looking at in vivo metabolism in whole organs. It would be interesting to know what the levels were in the brain tissue itself.

I am surprised we have not had discussion of this before if it is from nearly a year ago. I don't remember it. It is a pity they do not give any figures. Why do papers not give numbers in the results section any more?
 
I'm glad it looks promising. I hope they will be able to do a bigger study that replicates the findings.

Can anyone tell me how much it costs per patient to do such a test? Not that I think they are saying it's a valid biomarker - yet!

Can anyone find access to the full paper - I've only seen the abstract.
 
Jonathan Edwards said:
It is a pity they do not give any figures. Why do papers not give numbers in the results section any more?
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Mostly to force people to buy access to the full paper I suppose :-P Though in this study they were combining results coming from different methods and using different scales. So instead of having numbers, we have z-scores.

More generally, they used Fukuda, and it looks like they combined data from an earlier study with new data. So some comparison groups had lactate measured via different methods. Some analyses were post-hoc.

I'd love to see this replicated with a criteria requiring PEM, and everyone having lactate measured in the same way in the same time frame, with the researchers being blinded.
 
What does that mean, elevated lactate levels in the brain (e.g. consequences, causes...)? How does that show on brain scans? Why is MRI spectroscopy such a good method? And how does this fit into other findings, like that by Fluge and Mella (-> pyruvate dehydrogenase)? How should it be used as a biomarker if the authors say it cannot, since they couldn't differentiate ME from FM? And why is this a good finding (compared to others)?
 
Inara said:
What does that mean, elevated lactate levels in the brain (e.g. consequences, causes...)? How does that show on brain scans? Why is MRI spectroscopy such a good method? And how does this fit into other findings, like that by Fluge and Mella (-> pyruvate dehydrogenase)? How should it be used as a biomarker if the authors say it cannot, since they couldn't differentiate ME from FM? And why is this a good finding (compared to others)?
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Elevated lactate either in brain tissue or CSF would indicate a metabolic shift actually happening all the time in the brain in ME. That may not be saying anything very specific about what the shift is due to or what its consequences are but it would be hugely important to understanding what sort of problem we are dealing with.

MR (without the I for imaging) spectroscopy is powerful because it gives direct evidence of altered metabolism in cells actually in real life circumstances. fMRI can do this for oxygen uptake in sufficient detail to give an image of variation from place to place within brain tissue but imaging only works for a very few metabolites. MR spectroscopy has been around much longer and allows you to pick up signals for a huge range of metabolites, but only if you sample quite large areas. So rather than getting picture you set your sensor to measure from an area you know to be ventricle fluid or brain and you get a single number out.

This sort of approach ugh to be particularly good for muscle, because it would allow you to measure levels of a series of metabolites in a whole muscle, like quadriceps and work out where any block metabolism was. This ought to be much better than taking muscle biopsies or measuring white cells in blood samples because it would be measuring the tissue functioning in real life. I think MR spectroscopy must have been done on muscle by people like David Jones and Richard Edwards in ME ten or twenty years ago but I have never been able to pin down exactly what was found.

Findings in brain would be of particular interest. Having read the full paper my impression is that this study was not done with the thoroughness one would like. As Valentijn says they seem to have cobbled together two lots of data on not that many cases and only reported one area. If brain was not metabolising properly I would expect the lactate in the brain itself to be abnormal. The ventricles are really the drains of the brain and might show 'waste levels' but I would like to know how that relates to brain itself.

Looking at the scatter plot against BMI one can see the spread of data. What becomes clear there is that the differences between individual ME subjects and controls for lactate are not big enough to allow this to be used as a clinical marker. There is huge overlap. The findings are purely statistical. It might be that there is an identifiable subset of people with ME who are consistently above normal but that would need further testing and analysis.
 
Jonathan Edwards said:
This sort of approach ugh to be particularly good for muscle, because it would allow you to measure levels of a series of metabolites in a whole muscle, like quadriceps and work out where any block metabolism was.
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Should 'ugh' be 'ought'? :)
 
Thank you, @Jonathan Edwards!

Why is it a problem to use data at different points of time (they used data from a previous study and added new data and compared that again) if they are normalized/standardized?

Jonathan Edwards said:
Looking at the scatter plot against BMI one can see the spread of data. What becomes clear there is that the differences between individual ME subjects and controls for lactate are not big enough to allow this to be used as a clinical marker.
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That was my impression, too. Good to have that confirmed.
 
Inara said:
Why is it a problem to use data at different points of time (they used data from a previous study and added new data and compared that again) if they are normalized/standardized?
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It weakens the controlled aspect, since having controls tested at the same time and in the same manner can indicate if there was a problem or major difference due to the specific equipment or procedures used.
 
But in this case, there were no major differences between CFS, FM and CFS+FM (which reproduces the previous finding), and the differences between CFS/FM and the healthy controls seem to be comparable (i.e. coharent with the previous study). Right? Would this be an indicator that the different points of time of data collection aren't a big problem?
In which way does this affect the quality of the study?
 
Inara said:
But in this case, there were no major differences between CFS, FM and CFS+FM (which reproduces the previous finding), and the differences between CFS/FM and the healthy controls seem to be comparable (i.e. coharent with the previous study). Right? Would this be an indicator that the different points of time of data collection aren't a big problem?
In which way does this affect the quality of the study?
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The real problem with combining sets of results taken at different times rather than asa single prospective study protocols that it is much more likely to lead to cherry-picking. It is very easy to forget that a first study showed an interesting result, a second study showed nothing (and was forgotten about) and then third study showed the samosa the first.Add the first and third results and you can get 'statistical significance' when neither orbits own would give you that. I amanita suggesting this was done but it is all too easy to cherry pick in science and the way to stop oneself from doing that is to make sure studies are done prospectively and systematically.
 
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