Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

With the help of @forestglip, I've finally managed to run linkage disequilibrium score regression (LDSC) on the DecodeME results. The original package is written in the outdated Python 2 which caused all sorts of errors. So I've used the Python package GWASlab which provides a wrapper function to run the code.
LDSC in gwaslab - GWASLab

As reference for LD structure we used the European LD scores from 1000 Genomes which can be downloaded here:

The output looks like this:
h2_obsh2_seLambda_gcMean_chi2InterceptIntercept_seRatioRatio_seCatagories
0.040580380.002916921.099476051.141692790.914159330.00766967Ratio < 0NANA

The LDSC paper from 2015 suggests that for binary traits (having ME/CFS or not) h^2 is on the observed scale.
... This relationship holds for meta-analyses, and also for ascertained studies of binary phenotypes, in which case h2 is on the observed scale.
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies - PubMed

So to transform it to the liability scale as reported in the DecodeME paper we have to use this formula.
1756628336877.png
Heritability 201: Types of heritability and how we estimate it — Neale lab

Where K is the population prevalence and P is the prevalence of the trait in your GWAS. In R this becomes:
observed_to_liability <- function(h2_obs, K, P) {
# h2_obs: observed-scale heritability
# K: population prevalence
# P: proportion of cases in GWAS sample

# Calculate threshold corresponding to prevalence
t <- qnorm(1 - K)

# Height of standard normal distribution at that threshold
z <- dnorm(t)

conversion_factor <- (K * (1 - K))^2 / (P * (1 - P) * z^2)

h2_liability <- h2_obs * conversion_factor

return(h2_liability)
}
h2_liab <- observed_to_liability(h2_obs = 0.0405, K = 0.0065, P = 15579/(259909+15579))

In The DecodeME paper they report a h^2 of 0.095. The ME/CFS prevalence that would convert our observed h^2 of 0.0405 to this number would be 0.65%. In other words, it seems like the DecodeME paper assumed a prevalence of 0.65% in calculating the heritability.

Also tried to calculate the LDSC using only SNP that had a MAF > 0.05 and using LD data from the UK biobank but the results were similar (h^2 = 0.0402 and 0.0405 respectively on the observed scale ). If you upload the DecodeME data to BigaGWAS it also gives the same result of h^2 = 0.0405.
 
Last edited:
The intercept of LDSC is often used as a measure of stratification effects or confounding bias. It should be close to 1. If it is substantially higher, it would suggest that population differences between group are inflating the p-values. The good news is that this isn't the case in DecodeME!

The LDSC intercept, however was 0.914, which is substantially smaller than 1. I'm not sure what this means. Perhaps it's because only half of measured SNPs could be used for imputation so that the LD in the sample was underestimated? Or perhaps it indicates that the principal components took away more than just population differences but also some real effects of the illness?

Would be interested in hearing if these figures are correct and if so what the the low intercept might mean @Chris Ponting
 
Some weirder findings are:
  • Never eats dairy products
I remembered that some people with irritable bowel syndrome avoid dairy. So I think the genetic correlation to not eating dairy is related to the genetic correlation to IBS and/or 43% of the DecodeME cohort having IBS.

Prevalence and Presentation of Lactose Intolerance and Effects on Dairy Product Intake in Healthy Subjects and Patients With Irritable Bowel Syndrome, Clinical Gastroenterology and Hepatology, 2013
Methods
Sixty patients diagnosed with D-IBS at the Sir Run Run Shaw Hospital, Hangzhou, China and 60 controls were given hydrogen breath tests to detect malabsorption and intolerance after administration of 10, 20, and 40 g lactose in random order 7–14 days apart; participants and researchers were blinded to the dose. We assessed associations between the results and self-reported lactose intolerance (LI).

Results
Malabsorption of 40 g lactose was observed in 93% of controls and 92% of patients with D-IBS.

Fewer controls than patients with D-IBS were intolerant to 10 g lactose (3% vs 18%; odds ratio [OR], 6.51; 95% confidence interval [CI], 1.38–30.8; P = .008), 20 g lactose (22% vs 47%; OR, 3.16; 95% CI, 1.43–7.02; P = .004), and 40 g lactose (68% vs 85%; OR, 2.63; 95% CI, 1.08–6.42; P = .03). H2 excretion was associated with symptom score (P = .001).

Patients with D-IBS self-reported LI more frequently than controls (63% vs 22%; OR, 6.25; 95% CI, 2.78–14.0; P < .001) and ate fewer dairy products (P = .040).

However, self-reported LI did not correlate with results from hydrogen breath tests.

Diet in subjects with irritable bowel syndrome: A cross-sectional study in the general population, BMC Gastroenterology, 2012
Methods
The cross-sectional, population-based study was conducted in Norway in 2001. Out of 11078 invited subjects, 4621 completed a survey about abdominal complaints and intake of common food items. IBS and IBS subgroups were classified according to Rome II criteria.

Results
IBS was diagnosed in 388 subjects (8.4%) and, of these, 26.5% had constipation-predominant IBS (C-IBS), 44.8% alternating IBS (A-IBS), and 28.6% diarrhoea-predominant IBS (D-IBS).

Low intake of dairy products (portions/day) (Odds Ratio 0.85 [CI 0.78 to 0.93], p = 0.001) and high intake of water (100 ml/day) (1.08 [1.02 to 1.15], p = 0.002), tea (1.05 [1.01 to 1.10], p = 0.019) and carbonated beverages (1.07 [1.01 to 1.14], p = 0.023) were associated with IBS.

A lower intake of dairy products and a higher intake of alcohol and carbonated beverages were associated with D-IBS and a higher intake of water and tea was associated with A-IBS. [...]
 
I remembered that some people with irritable bowel syndrome avoid dairy. So I think the genetic correlation to not eating dairy is related to the genetic correlation to IBS and/or 43% of the DecodeME cohort having IBS.

Prevalence and Presentation of Lactose Intolerance and Effects on Dairy Product Intake in Healthy Subjects and Patients With Irritable Bowel Syndrome, Clinical Gastroenterology and Hepatology, 2013


Diet in subjects with irritable bowel syndrome: A cross-sectional study in the general population, BMC Gastroenterology, 2012
Yeah. The first thing that happened when I came to a doctor with my weird stomach symptoms (which a year and a half later were diagnosed as ME/CFS).

Was I was told to try not eating dairy.
 
Honestly 99% of the overlapping list calculated by Me/cfs science could IMO be attributed to misdiagnosis or clinical constructs which are vague and overlap.
In the DecodeME sample, they did quite some efforts with the questionnaires + self-reported clinical diagnosis to ensure patients had ME/CFS. So I don't think its likely that misdiagnosis would affect the results so much to create spurious relationships of this magnitude.

Another option is that the categories about depression or anxiety include patients with ME/CFS who were misdiagnosed or had this as a comorbidity. But as you say these clinical constructs are so vague and broad that I think ME/CFS patients would only form a very small subgroup. So that wouldn't explain the correlation either.
 
Last edited:
In the DecodeME sample, they did quite some efforts with the questionnaires + self-reported clinical diagnosis to ensure patients had ME/CFS. So I don't think its likely that misdiagnosis would affect the results so much to create spurious relationships of this magnitude.

Another option is that the categories about depression or anxiety include patients with ME/CFS who were misdiagnosed or had this as a comorbidity. But as you say these clinical constructs are so vague and broad that I think ME/CFS patients would only form a very small subgroup. So that wouldn't explain the correlation either.
Yes. That’s what I meant by misdiagnosis. Not necessarily the decode sample. But the anxiety/depression/ibs samples. Since they seemed pretty loose.
 
Back
Top Bottom