Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank, 2024, Huang et al

Perhaps the OI/hypertension discussion might benefit from my experience. I am not alone, but I have BOTH hypertension and NMH, neurally mediated hypotension. My hypertension is constant, my OI is usually suppressed except when very tired, such as my two and a half days without sleep earlier this week. During my Tilt Table Test maybe twenty odd years ago, my blood pressure crashed to zero and my cardiologist was about to call the crash cart when his treatment restored my bp enough to regain consciousness.

Given that maybe most of us have a new type of OI (eighty percent if I recall correctly), if it can be called that, with hypoperfusion of the brain, that does not show up on conventional TTT, we still do not know nearly enough to answer these questions. This is the kind of complicated that makes it no surprise that researchers still have not figured it out.

To me, metabolomics data is critical in our path forward. Of course I am biased, my background is in biochemistry.

For the record I consider I have ME, if pacing well I have minimal fatigue (but it takes only tiny amounts over my limit to have it crash back), I have been diagnosed with CFS four times (ME was not being used much back then), and may have been sick 56 years now after measles encephalitis as a child, though it really kicked up several notches after a stomach flu in 1985, several years before I was diagnosed as having antibodies to a coxsackie virus (1989).
 
I developed OI after reactivation of both HHV6 and EBV 11 years after PVFS/ME onset. I'm referring it OI because it's the only term we have at this time. We don't have a proper term for what we're experiencing for that either. It certainly exacerbates the pathophysiology of delayed PEM and we don't understand that yet either.
 
horton6 said:
It matters to me insofar as:
1) More severely ill people may have more of whatever is wrong in their bodies, which may be important for detecting whatever it is
2) Most research up to this point has excluded us, and has found very little
3) researchers invent totally whackadoodle definitions of severity and publish misleading writing on it, like those ones that defined "severe" as people who would pass multiple sets of diagnostic criteria for ME/CFS
4) when researchers misunderstand severity as symptom burden/frequency, they haven't understood the condition or its classic defining feature (PEM), and that carries over into other assumptions they make, and doesn't bode well for them looking in the right direction.
Click to expand...

I understand what you're saying and wasn't trying to diminish anyone's experiences. The severity of the patient is very important. What I was trying to convey was that focusing more on the distinctive set of symptoms that we all share in common such as delayed PEM.

I think we'll find that there are different types of ME, like there are with MS, in which there are 4.
 
wigglethemouse said:
They found 1/4 of people with ME/CFS had hypertension as did 1/4 of the people in the Comparison group.
View attachment 24390

I've been led to believe for many years by the media, papers, and advocacy that people with ME/CFS have orthostatic intolerance and a major cause of that is hypotension. In fact it is my understanding that orthostatic intolerance has been thought to be almost universal in ME/CFS. If that is the case I would have thought this data would show that there was a significantly lower % of PwME with hypertension which is not the case.

That makes me wonder what is the reason for orthostatic intolerance for those with hypertension, and why have we not seen more research asking that question. I feel that could hold an important clue to this disease.

I don't think I mentioned POTS. By definition POTS has a definition of an increase in heart rate WITHOUT a drop in blood pressure. However it seems clinicians and patients use POTS as a name for any sort of increase in heart rate above 30ppm, regardless of blood pressure. That muddies the water.
Click to expand...

Hypertension is in reference to ongoing elevated blood pressure at rest.

Orthostatic hypotension is the dramatic drop and sustained drop of blood pressure upon standing outside of a normal range. POTS is the dramatic rise and sustained rise of heart rate upon standing outside of a normal range.

Hypertension had no significance to ME/CFS, this isn't related to orthostatic issues.
 
Mij said:
Does severity matter at this point when mildly and severely affected patients all experience severe delayed PEM when we go over our own personal energy threshold?

I didn't experience severe delayed PEM for 8 years until I started exercising again when I became very mild almost symptom- free. I didn't have OI during that time period.
Click to expand...
Depends on the study, certainly severity matters if you were to develop an objective marker for clinical trials. It remains an important need for this disease.

In terms of studying the pathology of the disease or developing a diagnostic. It may not matter but it also may matter, the cause of severity is unknown.

One might simply think a severe patient has a more severe pathology of ME/CFS, but that may not be the case. A severe patient may have an accumulation of undefined co-morbidities that exacerbate their physical condition and remain unaccounted for.
 
 
Last edited:
I was looking at this paper when I wanted to find out what we know about cholesterol in ME/CFS. This paper didn't get much attention from us in terms of its findings. I have my doubts about the quality of the UK Biobank ME/CFS characterisation, but there might be something worth looking at closer here.


Dolphin said:
https://pursuit.unimelb.edu.au/arti...atigue-syndrome,-but-were-improving-diagnosis

Health & Medicine
Research
We don’t yet know what causes chronic fatigue syndrome, but we’re improving diagnosis
Using health factors and blood markers, researchers can now distinguish Chronic Fatigue Syndrome from other conditions for the first time – a giant step closer to formal diagnosis
Click to expand...
I thought that article was bordering on irresponsible.

One of the most troubling aspects of ME/CFS is the lack of clear answers for patients. Treatment options are limited, and none are currently approved for use in Australia.
Click to expand...
That makes it sound as though there are useful treatments.


The complexity of the disease adds to the challenge – patients experience varied symptoms, triggers and comorbidities (the simultaneous presence of two or more diseases or medical conditions in one patient), resulting in diverse responses to medication. Our research published in the Nature journal Communications Medicine, is a large-scale data study that highlights the development of a differential diagnostic marker.
These markers help to distinguish one condition from others that share similar symptoms and, in this case, enable a faster diagnosis for ME/CFS patients.
Click to expand...
Our research identified a set of 19 basic health factors and nine blood markers that could differentiate ME/CFS from seven common comorbid conditions correctly 83 per cent of the time.
Click to expand...
The model only differentiated ME/CFS from seven common comorbid conditions 83% of the time in that particular (probably poorly characterised) sample. We don't know if that set of health factors and blood markers are useful for diagnosis generally.

The data revealed inflammation and abnormalities in cholesterol and triglycerides when comparing ME/CFS to other diseases. These findings could have significant implications for understanding the biological mechanisms underlying ME/CFS.
Click to expand...
While the accuracy of this marker set is not perfect, this result is better than we expected, given that none of the UK Biobank data we identified was collected with ME/CFS in mind. We are hopeful that this study provides a new path to being able to rapidly diagnose ME/CFS and to assess severity for treatment trial outcomes. The next challenge we are working on is to translate this research to clinical use in the community.
Click to expand...
They say the next challenge is to translate the research to clinical use. Surely the next step is to validate the findings in other samples of people with ME/CFS?
 
Last edited:
The largest drivers of biomarker variation were mostly consistent with established biological mechanisms including inflammation (C-reactive protein explaining 20.5% of biomarker variance; neutrophil count, 7.1%) via GlycA, kidney function (urate, 22.3%; cystatin C, 21.3%) via plasma creatinine, testosterone (16.2%) via plasma creatinine and serum urea (15.3%) via valine. These traditional blood biochemistry measurements similarly explained the same set of biomarkers in the entire study population (Supplementary Figs. 9 and 10 and Supplementary Data 12).
Click to expand...
These findings increase my suspicion about the accuracy of the ME/CFS characterisation in the UK biobank. Many ME/CFS studies have looked at C-reactive protein and not found it to be high.


The 28 selected features for the LightGBM model, which was selected as the optimum model
(from Fig 4) (negative or positive association, effect size, individual p value, vs healthy controls from Supp Data 14 )

Frequency of tiredness/lethargy (positive, 1.35, ***)
Sleep duration (positive, 0.47,***)
Whole body pain (positive, 3.82, ***)
Headache pain (positive, 0.96, ***)
Female (data not given for comparison with healthy controls)
Alcohol consumption (negative, -1.26, ***) (note: only options were 'never or previous' and 'current')
Smoker (negative association,-0.21, *)
IPAQ (Physical Activity) High (negative,-0.76, ***)
Nucleated Red Blood Cell % (positive, 0.01, NS)
Nucleated Red Blood Cell Count (negative, -0.01, NS)
Facial pain (positive, 1.82, ***)
Stomach/abdominal pain (positive, 1.37, ***)
Hip pain (positive, 1.05, ***)
PUFA% (negative, -0.16, ***)
Total P (negative, -0.28, ***)
Leucine (positive, 0.03, NS)
Age at recruitment (data not given for comparison with healthy controls)
Acetone (negative, -0.10, **)
S-LDL-P (positive, 0.16, ***)
S-LDL-TG (positive, 0.27, ***)
Systolic Blood Pressure (negative, -0.07, *)
Acetoacetate (negative, -0.03, NS)
Frequency of depressed moods (positive, 0.73, ***)
Nap during Day (positive, 1.01, ***)
L-VLDL-Free cholesterol Very Low Density Lipoproteins (positive, 0.14, ***)
Sleeplessness/Insomnia (positive, 0.78, ***)
Immature Reticulocyte Fraction (positive, 0.20, ***)
M-VLDL-P (positive, 0.20, ***)

I think applying the 'Age at recruitment to the UK Biobank' will be a particularly hard feature to translate to clinical use. It doesn't look as though any of the tested and selected blood biomarkers had much effect on whether a person was in the ME/CFS or non-diseased group; the presence of various sorts of pain were a lot more discriminating.

Only XXL-VLDL-TG % was uniquely associated with ME/CFS (Supplementary Fig. 6), with the remaining 196 associations also present in other conditions.
Click to expand...
TG is triglycerides. That feature was not selected to be one of the 28 features in the favoured model. The P value was not very significant at 0.037 (Supp material 6 Females only). I think that p value is comparing the ME/CFS group against the non-diseased group.

This metabolomics analysis presents a lipoprotein profile for ME/CFS, highlighting significant associations of the disease with VLDL subclasses and size. These findings pinpoint a triglyceride and cholesterol transport problem, potentially arising from enzyme dysregulation, such as lipoprotein lipase (LPL). Interestingly, our retrospective analysis connects a recent study revealing a 2-fold overexpression of microRNA-29a in ME/CFS, which may inhibit LPL translation. The resulting inhibition of LPL activity leads to decreased clearance of VLDL particles and reduced degradation of circulating triglycerides. Surface lipids including total cholines, phosphatidylcholines, sphingomyelins, and phosphoglycerides were significantly decreased in the UKB ME/CFS cohort. These results are consistent with prior research, suggesting potential membrane destabilisation, altered cell signalling and dysregulated immune cell function. Our study contributes further evidence with a TG/PG association showing increased core lipid content relative to surface area, which may reduce membrane fluidity.
Click to expand...
That's interesting.

Cholesterol handling is of particular importance to steroid hormones given that it serves as the exclusive precursor for all steroidogeneses. The steroid hormone cortisol is currently the most reliable biomarker in ME/CFS research, with lower levels in ME/CFS evidenced at the level of meta-analysis 59. This observation aligns with recent findings in Long Covid, a condition sharing similarities with ME/CFS, wherein reduced cortisol levels have also been identified as a major distinguishing feature, potentially contributing to the pathogenesis [61].
Click to expand...
But that's disappointingly very wrong. Reference 59 is a 2014 paper on Chronic Fatigue Syndrome by Nijhof et al.
Reference 61 is 'Protracted stress-induced hypocortisolemia may account for the clinical and immune manifestations of Long COVID. 2022'

This ME/CFS cohort reflected an older population, with an average age of 55, and the youngest participant was aged 40. ME/CFS can occur at any time across the lifespan, with two major onset peaks in adolescence and late 30s, which are not captured in this study
Click to expand...
That makes no sense. The age of the people in the UK Biobank cohort does not exclude the possibility that ME/CFS participants had ME/CFS onsets in adolescence and in their late 30s.
 
I found this a disappointing paper. There are clearly potentially good data analysis skills here and a lot of effort was made, but the presentation takes away from the useful information. I think too, that the authors are still floundering around a bit in the CFS and ME/CFS literature, not reading critically enough to discard claims that really don't hold up to scrutiny.

Potentially useful findings are somewhat hidden in a lot of other material.

I think researchers rush too often to make a diagnostic model (perhaps because that is what funders emphasise? perhaps it is seen as an appropriate doctorate level task?), when what we really need to know right now is what things are truly different. The models and all the analyses of how well they perform fill up papers, without increasing our understanding of useful things. As I noted before, I also think the UK Biobank data on ME/CFS is rather problematic, with a very large noise to signal ratio due to poor characterisation of the ME/CFS group.
 
Last edited:
Hand grip strength
ME/CFS had lower hand-grip strength, an indicator of muscle fatigue, compared to all cohorts except for hypothyroidism.
Click to expand...
I think I've raised similar issues with another paper by these authors. The groups that the ME/CFS cohort is compared to are very different, not just in the characteristic that is being varied. The percentage of females in the ME/CFS group is 73.9%, the percentage of females in the C2 (healthy) group is 53.5%.

It's not surprising then that the handgrip strength for the ME/CFS group is a median of 25, while for C2 it is 30. The percentage of females in the hypothyroidism group is 26, and it has 86.7% female. Hayfever, with lowest percentage of females (45.9%) has the highest hand grip strength (33). This isn't helpful. It leaves us guessing about how much of the differences are just attributable to different percentages of females (and differences in age). It opens the door to misinterpretation, with later studies potentially citing this as evidence that people with ME/CFS have lower hand-grip strength (due to their illness).

I've said all this before, but, why on earth did the authors not match the cohorts better? They had thousands of healthy controls to choose from, and they could have balanced the other disease cohorts by sex too. Or just analysed the female data.

Associations of lipo-molecules with ME/CFS
Figure 1 shows the associations of the non-derived lipoprotein measurements, lipids and LMWM in ME/CFS. The strongest biomarker association was total triglyceride to phosphoglyceride ratio (TG/PG), where a one standard deviation (SD) increase in the biomarker measurement was associated with 46% higher odds of having ME/CFS compared to the odds of not having ME/CFS (odds ratio (OR): 1.46, 95% confidence interval (CI): 1.38–1.56, P = 3.9510−33).
Click to expand...
The odds ratio calculations shown in Figure 1 are reported to have taken into account sex, age, cholesterol-lowering medication and fish oil use.
But, it is not clear to me what the comparison population is. What population is contributing to the odds of not having ME/CFS?

The study population included a heterogenous ME/CFS cohort, seven homogenous comorbid cohorts (hypertension, depression, asthma, IBS, hay fever, hypothyroidism and migraine) and a non-diseased or ‘healthy’ cohort (C2) (Supplementary Table 1). A heterogenous cohort was defined as the presentation of multiple, and different medical conditions and homogenous refers to the existence of one single condition.
Click to expand...
It looks as though the only population allowed to have a high cholesterol problem is the 'heterogeneous' ME/CFS cohort. The C2 healthy cohort are the super healthy people with no disease and basically no medication use. The disease cohorts are only allowed to consist of people with the one single disease, whether that be hay fever or hypothyroidism. As I said, I couldn't see where it is reported what the comparison population is.

If the comparison population was the C2 group, or indeed 'the study population', then the very large proportion of the population that has an issue with high cholesterol has been ignored. That will obviously make it seem that the heterogeneous ME/CFS population, which is the only group allowed to have multiple conditions, can be characterised by issues with cholesterol. If that is the case, then Figure 1 is creating a massively false impression, and potentially leading researchers to chase issues that aren't important.

@MelbME, can you tell us what the comparison population was for Figure 1?
 
Hutan said:
If the comparison population was the C2 group, or indeed 'the study population', then the very large proportion of the population that has an issue with high cholesterol has been ignored.
Click to expand...
Supplementary Data 4 said:
Logistics regression was performed using each diseased cohort against C2 (non-diseased cohort). Odds ratios (OR) were calculated using the formula: Condition ~ Biomarker + age at recruitment + sexFemale + cholesterol lowering medication + fish oil supplements and are shown per SD increment.
Click to expand...

Looking at Supplementary Data 4, it seems that the odds ratios are calculated for each disease cohort against the C2 group, the healthy controls. So the ME/CFS group includes people who have ME/CFS as well as whatever other illnesses they had. They are effectively compared to people who have no illnesses. The C2 group are quite unusually healthy people, for people in this age range.

That comparison is what produces those odds ratios reported in Figure 1.

The strongest biomarker association was total triglyceride to phosphoglyceride ratio (TG/PG), where a one standard deviation (SD) increase in the biomarker measurement was associated with 46% higher odds of having ME/CFS compared to the odds of not having ME/CFS (odds ratio (OR): 1.46, 95% confidence interval (CI): 1.38–1.56, P = 3.9510−33).
Click to expand...

Given people with ME/CFS and all the usual illnesses of people in their age range are being compared to super healthy people with no comorbidities, I'm actually surprised that the "strongest biomarker" had an odds ratio of only 1.46.

Here's part of Figure 1, where the ME/CFS people are compared with the super healthy C2 people.

Screenshot 2026-04-05 at 9.10.12 PM.png

I think it's reasonable to assume that actually most of these molecules in the people with ME/CFS are rather similar to the levels in the overall population in the UK Biobank, after taking into account things like age and sex.

In support of that is the fact that Table 1 tells us that 10.5% of the ME/CFS group have high cholesterol while 12.6% of the C1 group have high cholesterol. To be clear, the ME/CFS group has less people with high cholesterol than the overall population group in the biobank. That C1 group has more than 273,000 people. This is the more appropriate comparison group, not the C2 super healthy people.

It means that Figure 1 is indeed misleading. I think if the C1 general population group was compared with the C2 super healthy people, many of the same conclusions about the general UK biobank population could be made as have been made about the ME/CFS population. I don't think we have evidence here of broad-scale dyslipidemia in ME/CFS that is different to that of most people in the age range in the UK.

The wrong comparison group was used. I think this is a pretty major problem. It's leading to people thinking that problems specific to ME/CFS have been identified, when most, at least, are typical of older people in the UK.
 
Last edited:
What I have been going on about on this thread and on the thread for another similar paper by this team seems obvious to me. To summarise:

The wider population of older people in the UK has issues with cholesterol e.g. the Guardian in 2017 said that a UK study looking at who would be eligible to be prescribed statins to lower cholesterol found:
Among men, 33% of those aged 45 to 59 would be eligible according to the risk assessment tool. This increased to 95% of men aged 60 to 74 years and 100% of men aged 75 to 84.

One in 10 women aged 45 to 59 would be eligible, increasing to 66% of women aged 60 to 74 and 100% of women aged 75 to 84.
Click to expand...

The wider population of the members of the UK Biobank can therefore also be expected to have issues with cholesterol. The wider population of the members of the UK Biobank is named C1. We know from Table 1 in this paper that around 12% of C1 have high total cholesterol. We know that the members of the UK Biobank tend to be a bit healthier than the average UK person of their age, but, even so, a significant number have those issues with high cholesterol.

Therefore, the members of the ME/CFS group in the UK Biobank are likely to also present with issues with cholesterol. And they do. We know from Table 1 that around 10% of the ME/CFS group have high cholesterol. That seems about right, considering the percentages of women in ME/CFS group and the C1 group (more women in the ME/CFS group).

We know that the C2 population of the UK Biobank consists of people who are super healthy. They have no co-morbidities. They are not your typical UK older person, they are not even typical for the typical UK Biobank member who tends to be a bit healthier than normal. The C2 members presumably have far fewer problems with cholesterol and other lipids. Table 2 in this paper confirms that - while 15.7% of the ME/CFS group are on statins to lower cholesterol, only 0.8% of the C2 super healthy group are. All of the literature I can find suggests that that level of statin use in the ME/CFS group is normal, perhaps even low, for older people in western countries including the UK. The level of statin use in the C2 super healthy people is definitely not normal for people of their age.

If you compare the UK Biobank ME/CFS group with the UK Biobank C2 super healthy population, as the Supplementary Data 4 file tells us that Figure 1 does, you will find that the ME/CFS group have more issues with cholesterol. This is not the least bit surprising. This finding does not necessarily tell us anything about ME/CFS and it should not be presented as such. It is simply wrong, on the basis of comparing the ME/CFS group and the super healthy group to conclude, as this paper does,:
This metabolomics analysis presents a lipoprotein profile for ME/CFS, highlighting significant associations of the disease with VLDL subclasses and size. These findings pinpoint a triglyceride and cholesterol transport problem, potentially arising from enzyme dysregulation, such as lipoprotein lipase (LPL). Interestingly, our retrospective analysis connects a recent study revealing a 2-fold overexpression of microRNA-29a in ME/CFS, which may inhibit LPL translation. The resulting inhibition of LPL activity leads to decreased clearance of VLDL particles and reduced degradation of circulating triglycerides. Surface lipids including total cholines, phosphatidylcholines, sphingomyelins, and phosphoglycerides were significantly decreased in the UKB ME/CFS cohort. These results are consistent with prior research, suggesting potential membrane destabilisation, altered cell signalling and dysregulated immune cell function. Our study contributes further evidence with a TG/PG association showing increased core lipid content relative to surface area, which may reduce membrane fluidity.
Click to expand...

Some of that paragraph may be true, there may be some particular lipid issues in ME/CFS. But there needs to be a comparison of the ME/CFS group with the wider population group, C1, in order for us to know that. For people with access to the UK Biobank data, doing that comparison would be very easy. I think it is important for us to do that before a whole lot of research funding is directed to trying to explain issues that maybe have nothing to do with ME/CFS.

Perhaps I am wrong, after all, if there is a problem, it got past the authors and the peer reviewers and the editorial staff of this Nature journal, and that should be very unlikely. I communicated with Chris Armstrong at the end of last year about his team's other paper with the same problem and he didn't seem to see the problem. He seemed to think that a comparison with the super healthy group is appropriate.

But it seems pretty clear to me that the identification of issues with lipids in Figure 1 rests on an inappropriate comparison. I'm concerned that this incorrect information will lead researchers in a wrong direction and waste time and scarce funding.

Chris, @MelbME, can you please identify why my reasoning set out in this post is wrong, why Figure 1 and the conclusions drawn from it help us identify ME/CFS-specific pathology?
 
You must log in or register to reply here.
Back
Top Bottom