Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome, 2024, Walitt et al

[NelliePledge]

What PPI approach was taken by NIH? Because from this distance I find it difficult to envisage that anyone working in partnership with people with ME/CFS on all aspects of the project (rather than seeing us as researchees) would have produced this as the output.

 

[SNT Gatchaman]

Yep, if they were looking for adulation, they could have had it in spades. Will be interesting to see if, what, when and how subsequent papers will be published.

 

[forestglip]

I downloaded the raw data from mapmecfs to dig around in. First little thing I did was get the correlation of every molecule from the metabolomics dataset with the group. Used point biserial correlation and Benjamini–Hochberg correction.

Here are the top 40 out of 445 total molecules:



And the top five molecules:

 

[Hutan]

@forestglip, thank you. How does the correlation work? All the correlation signs are negative. Is there a way to tell if a metabolite is up or down in the ME/CFS people?

 

[forestglip]

@forestglip, thank you. How does the correlation work? All the correlation signs are negative. Is there a way to tell if a metabolite is up or down in the ME/CFS people?

I thought that was weird too, but the first 102 molecules are all lower in ME/CFS. Only 27/445 molecules are higher. Which seems fishy so I may have done something wrong, but I'll manually check some of these, probably tomorrow.

 

[forestglip]

Yes, I think these are correct. I just averaged the metabolites for each group directly in the raw data file and the mean levels in ME/CFS are lower than HC in the top five negative correlations and higher in the top five positive correlations. (ME/CFS is 1, HC is 0.)

Highest negative correlations:

phenyllactate (PLA) (-0.6419851379)
0 - 1.10
1 - 0.78

dimethyl sulfone (-0.6342549253)
0 - 1.68
1 - 0.60

2-hydroxy-3-methylvalerate (-0.5998691623)
0 - 1.27
1 - 0.85

orotidine (-0.5752991066)
0 - 1.20
1 - 0.84

5-methylcytidine (-0.5588008689)
0 - 1.10
1 - 0.87

Highest positive correlations

X-23195 (0.385856033)
0 - 0.95
1 - 1.03

ribitol (0.3602466004)
0 - 0.87
1 - 1.03

cysteine-glutathione disulfide (0.2767696195)
0 - 0.96
1 - 1.26

homostachydrine* (0.2683386352)
0 - 0.94
1 - 1.89

3-hydroxydecanoate (0.2647341082)
0 - 0.98
1 - 1.08

Maybe we're just generally metabolite deficient and that will be the answer.

 

[forestglip]

Also appears to match with the paper. I don't know if this heatmap is ordered by most correlated at the top, but the top four are the same as the top four in my list, although in a slightly different order. And it seems to also show that most of the metabolites they chose to illustrate are higher in HV.

Metabolomic analysis of cerebrospinal fluid also showed group differences (Fig. 6h). Tryptophan metabolites were among the top 15 differentially expressed and statistically significant after correction for multiple comparisons (Fig. 6i). Decreased glutamate, dopamine 3-O-sulfate, butyrate, polyamine, and tricarboxylic acid (TCA) pathway metabolites were noted in PI-ME/CFS participants (Supplementary Data S14A). Threonine and glutamine were decreased in males (Fig. 6j, Supplementary Fig. S13D, Supplementary Data S14C). Several tryptophan metabolites were decreased in females suggesting a decrease in serotonin signaling (Fig. 6k, Supplementary Fig. S13E, Supplementary Data S14D). This was irrespective of NSRI/SSRI use.

 

[chillier]

Also appears to match with the paper. I don't know if this heatmap is ordered by most correlated at the top, but the top four are the same as the top four in my list, although in a slightly different order. And it seems to also show that most of the metabolites they chose to illustrate are higher in HV.


View attachment 22997

This is the CSF data if I recall right? I believe from when I looked at this earlier in the year that the ones in that heatmap are the top results from a simple mann whitney u test between groups. They also analysed it using a more complicated (but probably more appropriate) glm model.

If it's not a pain, it would be cool to see strip plots like you've done for those metabolites for pyrroline-5-carboxylate and maybe also hypoxanthine. They've both come up in a few places before and I think I remember seeing them here too.

Also 1-steroyl-GPC (18:0) - from third to the bottom of that heatmap - is a phosphatidylcholine. Interesting that one of their top results here is again a phosphatidylcholine and is also low ( I don't think they do a broader lipidomics panel do they EDIT: They do).

 

[forestglip]

This is the CSF data if I recall right? I believe from when I looked at this earlier in the year that the ones in that heatmap are the top results from a simple mann whitney u test between groups. They also analysed it using a more complicated (but probably more appropriate) glm model.

Yes, this is CSF.

If it's not a pain, it would be cool to see strip plots like you've done for those metabolites for pyrroline-5-carboxylate and maybe also hypoxanthine. They've both come up in a few places before and I think I remember seeing them here too.

Also 1-steroyl-GPC (18:0) - from third to the bottom of that heatmap - is a phosphatidylcholine.

Sure here are those plots. Also box plots, with the white dot being mean and the yellow line being median.

Molecule | Correlation (point-biserial) | uncorrected p value | adjusted p (BH)
S-1-pyrroline-5-carboxylate | -0.3542989681 | 0.02907775564 | 0.08665556102


hypoxanthine | -0.2336116431 | 0.1580701679 | 0.247194837


1-stearoyl-GPC (18:0) | -0.4503725604 | 0.004548911271 | 0.0427324321

( I don't think they do a broader lipidomics panel do they EDIT: They do).

Yes, I'm hoping to look at that as well. You think Mann-Whitney would be more appropriate?

 

[chillier]

Yes, this is CSF.



Sure here are those plots. Also box plots, with the white dot being mean and the yellow line being median.

Molecule | Correlation (point-biserial) | uncorrected p value | adjusted p (BH)
S-1-pyrroline-5-carboxylate | -0.3542989681 | 0.02907775564 | 0.08665556102
View attachment 23003View attachment 23008

hypoxanthine | -0.2336116431 | 0.1580701679 | 0.247194837
View attachment 23004View attachment 23007

1-stearoyl-GPC (18:0) | -0.4503725604 | 0.004548911271 | 0.0427324321
View attachment 23005View attachment 23006


Yes, I'm hoping to look at that as well. You think Mann-Whitney would be more appropriate?

That's great thank you Mann whitney is a safe bet since it doesn't make any assumptions about distribution and simply asks the question of whether one group is higher or lower than another, so their p values are probably fine. Biserial correlation I think is ok too but assumes that the data is normally distributed, and sometimes metabolomics data needs a log transform first to better meet that assumption. A (generalized) linear model can also be nice because it can handle confounders like sex and age.

 

[forestglip]

That's great thank you Mann whitney is a safe bet since it doesn't make any assumptions about distribution and simply asks the question of whether one group is higher or lower than another, so their p values are probably fine. Biserial correlation I think is ok too but assumes that the data is normally distributed, and sometimes metabolomics data needs a log transform first to better meet that assumption. A (generalized) linear model can also be nice because it can handle confounders like sex and age.

Ok, much appreciated, thanks!

 

[forestglip]

Ok, I did Mann-Whitney on both the metabolomics and the lipidomics datasets, and the BH adjusted p-values are based on both datasets combined.

Metabolomics order changed a bit:


And here's lipidomics top 40:


Top 5:

 

[forestglip]

From study:

Lack of differences in lipidomics between PI-ME/CFS and healthy volunteers
Univariate analysis of the plasma lipidomic data did not identify statistically significant differences between HV and PI-ME/CFS groups (Supplementary Data S20). Multivariate analysis in all participants as well as in male and female cohorts separately identified several lipids as important variables in prediction (Supplementary Fig. S19A–C) and are consistent with a prior lipidomic analysis28.

 

[chillier]

Ok, I did Mann-Whitney on both the metabolomics and the lipidomics datasets, and the BH adjusted p-values are based on both datasets combined.

Metabolomics order changed a bit:
View attachment 23021

And here's lipidomics top 40:
View attachment 23015

Top 5:
View attachment 23016 View attachment 23017 View attachment 23018 View attachment 23019 View attachment 23020

This looks really interesting - no individual TAG passes adjusted p<0.05, but (like with Germain 2020) they all seem to be biased higher in ME. I'd quite like to repeat the analysis I did on that data (ie volcano plot and testing global TAG differences):

Thanks that's interesting. They don't report on triglycerides or phosphatidylcholine in Germain et al 2020 but they do mention they are detectable in their lipid panel so it follows they would probably be insignificant.

I wanted to check anyway so went into the supplementary and calculated the p values for the phosphatidycholines and triglycerides (I log2 transformed the data like they do in the paper I believe). Here's a volcano plot for the phosphatidylcholines (each dot is a unique phosphatidylcholine):
View attachment 22986
Sure enough nothing significant, and also no particular fold change bias either way.

Triglycerides also aren't mentioned and also aren't significant (besides one but it won't survive multiple test correction).

However, across ~500 unique triglycerides there is a global bias towards increased levels. Only a small handful are lower and they contain big outliers. in a linear model using all triglycerides as a random effect to test whether there are global differences in triglyceride levels, it comes out as highly significant <2e-16. I tried summing them together too to compare total triglyceride levels, and while this trended up it was not significant.
View attachment 22987

@forestglip how would you feel about sharing the lipidomics data with me? Is it in a convenient csv type format?

 

[forestglip]

@forestglip how would you feel about sharing the lipidomics data with me? Is it in a convenient csv type format?

It is, but it's against the terms of mapmecfs to share raw data:

3. I will not further disclose these data beyond the uses outlined in this agreement and my data use application and understand that redistribution of data in any manner is prohibited.
4. I will not share data with anyone on my team, at my institution, unless they have registered with mapMECFS and, by doing so, agreed to this agreement.

I did email to ask if sharing charts on this forum made from the data was allowed and they said yes to that. Can you make an account?

 

[Hutan]

Ok, I did Mann-Whitney on both the metabolomics and the lipidomics datasets, and the BH adjusted p-values are based on both datasets combined.

Thank you forestglip. From a quick google, those top metabolites (that were lower in the ME/CFS samples) all seem to be associated with defence against pathogens. Certainly worth having more of a look at them.

 

[chillier]

It is, but it's against the terms of mapmecfs to share raw data:



I did email to ask if sharing charts on this forum made from the data was allowed and they said yes to that. Can you make an account?

That's fair enough! I'll make an account in that case

 

[forestglip]

That's fair enough! I'll make an account in that case

Took about four days for them to approve my account, FYI.

 

[forestglip]

What could explain why almost all metabolites tested were lower in ME/CFS? Most of these aren't statistically significant on their own, but as @chillier was saying about triglycerides in the lipidomics study, there seems to be a general trend here too.

The comparisons are based on medians. The lists are in alphabetical order, this just says if the medians of one group of metabolite are at all higher than the other, and says nothing about significance.

Metabolites that were higher (n=36)

1-methylnicotinamide
2-hydroxybutyrate/2-hydroxyisobutyrate
3-hydroxydecanoate
3-hydroxyindolin-2-one
3-indoxyl sulfate
3-methylxanthine
4-acetamidophenol
4-acetamidophenylglucuronide
5-(galactosylhydroxy)-L-lysine
7-methylxanthine
caffeine
citramalate
cys-gly, oxidized
cysteine s-sulfate
cysteine-glutathione disulfide
cysteinylglycine
ethylmalonate
glycerophosphoethanolamine
homocarnosine
homostachydrine*
hypotaurine
methylsuccinoylcarnitine
N-acetyl-3-methylhistidine*
N-acetylleucine
N4-acetylcytidine
phenol sulfate
ribitol
sphingomyelin (d18:1/20:0, d16:1/22:0)*
tartarate
theobromine
theophylline
X-14056
X-15245
X-23195
X-24411
X-24520

Metabolites that were lower (n=409)

(N(1) + N(8))-acetylspermidine
1-(1-enyl-palmitoyl)-2-oleoyl-GPC (P-16:0/18:1)*
1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (P-18:0/20:4)*
1-methyl-4-imidazoleacetate
1-methyl-5-imidazoleacetate
1-methylxanthine
1-myristoyl-2-palmitoyl-GPC (14:0/16:0)
1-oleoyl-GPC (18:1)
1-palmitoyl-2-arachidonoyl-GPC (16:0/20:4n6)
1-palmitoyl-2-docosahexaenoyl-GPC (16:0/22:6)
1-palmitoyl-2-linoleoyl-GPC (16:0/18:2)
1-palmitoyl-2-oleoyl-GPC (16:0/18:1)
1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1)*
1-palmitoyl-2-stearoyl-GPC (16:0/18:0)
1-palmitoyl-GPC (16:0)
1-ribosyl-imidazoleacetate*
1-stearoyl-2-arachidonoyl-GPC (18:0/20:4)
1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)
1-stearoyl-2-arachidonoyl-GPI (18:0/20:4)
1-stearoyl-2-docosahexaenoyl-GPC (18:0/22:6)
1-stearoyl-2-docosahexaenoyl-GPE (18:0/22:6)*
1-stearoyl-2-oleoyl-GPC (18:0/18:1)
1-stearoyl-GPC (18:0)
1,2-dipalmitoyl-GPC (16:0/16:0)
1,3-propanediol
1,5-anhydroglucitol (1,5-AG)
2-aminoheptanoate
2-aminooctanoate
2-aminophenol sulfate
2-hydroxy-3-methylvalerate
2-hydroxyadipate
2-hydroxyglutarate
2-isopropylmalate
2-keto-3-deoxy-gluconate
2-methylcitrate
2-O-methylascorbic acid
2-oxoadipate
2-oxoarginine*
2-piperidinone
2,3-dihydroxy-5-methylthio-4-pentenoate (DMTPA)*
2,3-dihydroxyisovalerate
2,6-dihydroxybenzoic acid
2'-deoxycytidine
2'-deoxyuridine
2'-O-methylcytidine
2R,3R-dihydroxybutyrate
2S,3R-dihydroxybutyrate
3-(3-amino-3-carboxypropyl)uridine*
3-(4-hydroxyphenyl)lactate
3-amino-2-piperidone
3-carboxy-4-methyl-5-pentyl-2-furanpropionate (3-CMPFP)**
3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF)
3-hydroxy-2-ethylpropionate
3-hydroxy-3-methylglutarate
3-hydroxybutyrate (BHBA)
3-hydroxyhexanoate
3-hydroxyisobutyrate
3-hydroxyoctanoate
3-hydroxypyridine sulfate
3-hydroxystachydrine*
3-methoxytyramine sulfate
3-methoxytyrosine
3-methyl-2-oxobutyrate
3-methyl-2-oxovalerate
3-methylcytidine
3-methylglutaconate
3-methylglutarylcarnitine (2)
3-methylhistidine
3-phenylpropionate (hydrocinnamate)
3-ureidopropionate
3,4-dihydroxybutyrate
4-acetamidobutanoate
4-acetaminophen sulfate
4-guanidinobutanoate
4-hydroxybutyrate (GHB)
4-hydroxyphenylpyruvate
4-methyl-2-oxopentanoate
4-methylbenzenesulfonate
4-methylcatechol sulfate
5-acetylamino-6-amino-3-methyluracil
5-hydroxyindoleacetate
5-methylcytidine
5-methyltetrahydrofolate (5MeTHF)
5-methylthioadenosine (MTA)
5-methylthioribose**
5-methyluridine (ribothymidine)
5-oxoproline
5,6-dihydrothymine
5,6-dihydrouracil
5,6-dihydrouridine
6-oxopiperidine-2-carboxylate
7-alpha-hydroxy-3-oxo-4-cholestenoate (7-Hoca)
7-methylguanine
acesulfame
acetoacetate
acetylcarnitine (C2)
acisoga
aconitate [cis or trans]
adenine
adenosine 3',5'-cyclic monophosphate (cAMP)
adipoylcarnitine (C6-DC)
alanine
allantoin
alpha-hydroxyisocaproate
alpha-hydroxyisovalerate
alpha-ketobutyrate
alpha-ketoglutaramate*
alpha-ketoglutarate
alpha-tocopherol
androstenediol (3beta,17beta) disulfate (1)
anthranilate
arabinose
arabitol/xylitol
arabonate/xylonate
argininate*
arginine
argininosuccinate
ascorbate (Vitamin C)
ascorbic acid 3-sulfate*
asparagine
aspartate
benzoate
beta-alanine
beta-citrylglutamate
beta-hydroxyisovalerate
beta-hydroxyisovaleroylcarnitine
betaine
betonicine
bilirubin (Z,Z)
butyrate/isobutyrate (4:0)
C-glycosyltryptophan
carboxyethyl-GABA
carnitine
catechol sulfate
chenodeoxycholate
chiro-inositol
cholate
cholesterol
choline
choline phosphate
cis-3,4-methyleneheptanoate
citraconate/glutaconate
citrate
citrulline
cortisol
cortisone
creatine
creatine phosphate
creatinine
cyclo(leu-pro)
cystathionine
cysteine
cysteinylglycine disulfide*
cytidine
deoxycarnitine
deoxycholate
diacetylspermidine*
dimethyl sulfone
dimethylarginine (SDMA + ADMA)
dimethylglycine
dimethylmalonic acid
dopamine 3-O-sulfate
equol glucuronide
ergothioneine
erythritol
erythronate*
ethyl beta-glucopyranoside
fructose
fructosyllysine
gabapentin
galactonate
gamma-glutamyl-2-aminobutyrate
gamma-glutamyl-alpha-lysine
gamma-glutamyl-epsilon-lysine
gamma-glutamylcitrulline*
gamma-glutamylglutamine
gamma-glutamylhistidine
gamma-glutamylisoleucine*
gamma-glutamylleucine
gamma-glutamylmethionine
gamma-glutamylphenylalanine
gamma-glutamylthreonine
gamma-glutamyltyrosine
gamma-glutamylvaline
gluconate
glucose
glucuronate
glutamate
glutamate, gamma-methyl ester
glutamine
glutamine_degradant*
glutarylcarnitine (C5-DC)
glycerate
glycerol
glycerol 3-phosphate
glycerophosphoinositol*
glycine
guaiacol sulfate
guanosine
gulonate*
heme
hippurate
histidine
homoarginine
homovanillate (HVA)
hydroxy-N6,N6,N6-trimethyllysine*
hydroxyasparagine**
hydroxybupropion
hypoxanthine
imidazole lactate
indoleacetate
indolelactate
inosine
isobutyrylcarnitine (C4)
isocitrate
isoleucine
isovalerate (i5:0)
isovalerylcarnitine (C5)
kynurenate
kynurenine
lactate
leucine
lidocaine
lysine
lyxonate
malate
maleate
malonate
malonylcarnitine
mannitol/sorbitol
mannonate*
mannose
methionine
methionine sulfone
methionine sulfoxide
methyl glucopyranoside (alpha + beta)
myo-inositol
N-acetyl-2-aminoadipate
N-acetyl-aspartyl-glutamate (NAAG)
N-acetyl-beta-alanine
N-acetyl-isoputreanine
N-acetylalanine
N-acetylarginine
N-acetylasparagine
N-acetylaspartate (NAA)
N-acetylcarnosine
N-acetylglucosamine/N-acetylgalactosamine
N-acetylglucosaminylasparagine
N-acetylglutamate
N-acetylglutamine
N-acetylglycine
N-acetylhistidine
N-acetylisoleucine
N-acetylmethionine
N-acetylneuraminate
N-acetylphenylalanine
N-acetylputrescine
N-acetylserine
N-acetyltaurine
N-acetylthreonine
N-acetylvaline
N-delta-acetylornithine
N-ethylglycinexylidide
N-formylmethionine
N-methylproline
N,N-dimethyl-pro-pro
N,N,N-trimethyl-5-aminovalerate
N,N,N-trimethyl-alanylproline betaine (TMAP)
N1-Methyl-2-pyridone-5-carboxamide
N1-methyladenosine
N1-methylinosine
N2-acetyl,N6-methyllysine
N2-methylguanosine
N2,N2-dimethylguanosine
N6-acetyllysine
N6-carbamoylthreonyladenosine
N6-methyladenosine
N6-methyllysine
N6-succinyladenosine
N6,N6-dimethyllysine
N6,N6,N6-trimethyllysine
nicotinamide riboside
O-sulfo-L-tyrosine
octanoylcarnitine (C8)
ornithine
orotate
orotidine
oxalate (ethanedioate)
p-cresol sulfate
palmitoyl dihydrosphingomyelin (d18:0/16:0)*
palmitoyl sphingomyelin (d18:1/16:0)
pantothenate
paraxanthine
pentose acid*
phenylacetate
phenylacetylglutamine
phenylalanine
phenyllactate (PLA)
phosphate
phosphoethanolamine
picolinate
pipecolate
piperine
pregabalin
pro-hydroxy-pro
proline
propionylcarnitine (C3)
pseudouridine
pyridoxal
pyridoxate
pyruvate
quinate
ranitidine
ribonate
ribose
S-1-pyrroline-5-carboxylate
S-allylcysteine
S-methylcysteine
S-methylcysteine sulfoxide
saccharopine
salicylate
serine
spermidine
sphingomyelin (d18:1/14:0, d16:1/16:0)*
sphingomyelin (d18:1/18:1, d18:2/18:0)
sphingomyelin (d18:1/20:1, d18:2/20:0)*
sphingomyelin (d18:1/22:1, d18:2/22:0, d16:1/24:1)*
sphingomyelin (d18:1/24:1, d18:2/24:0)*
sphingomyelin (d18:2/16:0, d18:1/16:1)*
sphingomyelin (d18:2/24:1, d18:1/24:2)*
stachydrine
stearoyl sphingomyelin (d18:1/18:0)
succinate
succinylcarnitine (C4-DC)
succinylglutamine
sucrose
sulfate*
tartronate (hydroxymalonate)
taurine
tetradecadienoate (14:2)*
threonate
threonine
thymol sulfate
tiglylcarnitine (C5:1-DC)
topiramate
trigonelline (N'-methylnicotinate)
trimethylamine N-oxide
tryptophan
tryptophan betaine
tyrosine
uracil
urate
urea
uridine
valine
X-10457
X-11299
X-11381
X-11478
X-11612
X-11787
X-11795
X-12007
X-12015
X-12026
X-12100
X-12101
X-12104
X-12127
X-12411
X-12680
X-12689
X-12844
X-12906
X-13431
X-13684
X-13728
X-15674
X-16580
X-18887
X-19438
X-21286
X-21733
X-22143
X-22162
X-23583
X-23587
X-23593
X-23639
X-23644
X-23666
X-23739
X-24027
X-24228
X-24295
X-24337
X-24408
X-24422
X-24728
X-24736
X-25109
X-25217
X-25271
X-25790
X-25936
X-25983
X-26008
xanthine
xanthosine

 

[forestglip]

I was curious about energy expenditure after looking at my own food tracking over the past six months, which shows I ate an average of 2,950 calories per day, yet have gained at most, maybe five pounds, if any. There's a chance the recorded intake is a bit higher than reality, as I was eating beef from the farmer's market often, and I probably guessed too high for the fat content. But at most it'd be about 150 calories too high per day.

So I'm wondering if my body is burning tons of energy for some reason, even though I'm mostly sedentary. Average 2,800 steps per day over the past month. I think a typical energy expenditure for someone my size and age and activity is around 2,250, according to a calculator on Mayo Clinic's website. 2850 for "very active" which is quite far from my activity level.

Looking at the data from the study, it doesn't look like that's a universal thing, if my own recorded calorie count is even accurate for me. The average intake seems to be similar for both groups. There are some outliers both high and low, but their body weights are also pretty high and low, respectively, compared to most of the other participants.

Definition of the metric: "total energy expenditure in kcals/day from the full whole room indirect calorimeter measurement on the Baseline chamber night". So that was before the CPET.

Looks like it's maybe trending up in the three days after the CPET:


Largest difference seems to be during sleep on the third day after CPET:


The study says no differences found, although a p-value of 0.07 for that last sleep measurement.

Despite altered cardiorespiratory function, there were no clinically meaningful differences in dietary energy intake (Supplementary Data S11) or total body energy use, sleeping energy use, or respiratory quotient between the groups before or after CPET testing (Supplementary Fig. S9A–D; Supplementary Data S12).

S12:


Fig S9A-D:

Figure S9: Total body energy expenditure, sleeping energy expenditure, and respiratory quotient measurements at baseline and 48 hours after cardiopulmonary exercise testing (CPET) A-B. Correlation of fat free mass on the x axis with (A) total body energy expenditure and (B) sleeping energy expenditure on the y axis for HV (blue; n = 10 independent participants) and PI-ME/CFS (red; n = 14 independent participants). Squares represent males and circles represent females. Solid data points are baseline measurements, open data points are measurements 48 hours after CPET. No statistically significant differences in total or sleeping energy expenditure was noted between the groups. C-D. Respiratory quotient measurements taken (C) daily and (D) sleeping at baseline and 48 hours after CPET for HV (blue; n = 9 independent participants) and PI-ME/CFS (red; n = 10 independent participants). E-G. Serial mitochondrial flux assay measurements of peripheral blood mononuclear cells immediate before (baseline), 24, 48, and 72 hours after CPET for HV (blue; n = 9 independent participants) and PI-ME/CFS (red; n = 8 independent participants). No differences were observed in (E) basal, (F) maximum respiration, and (G) non-mitochondrial oxygen consumption between the groups. Source data are provided as a Source Data file.

I might try to see what the data looks like if the energy expenditure is normalized to body weight.