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

[Andy]

Apologies if this has been answered already: is there any hope of looking for genetic clues in early onset cases of the DecodeME data? Was age-of-onset data collected? (The thinking being that early-onset cases might have a stronger genetic predisposition, or something else distinct going on.)

Age of onset wasn't specifically collected, but date of birth and length of illness was. This isn't something that the remaining DecodeME team would be able to look at but if a researcher wanted to apply for the necessary data access then the process can be found here.

 

[Jonathan Edwards]

Apologies if this has been answered already: is there any hope of looking for genetic clues in early onset cases of the DecodeME data? Was age-of-onset data collected? (The thinking being that early-onset cases might have a stronger genetic predisposition, or something else distinct going on.)

I have discussed this with Chris. His problem is that the more post-hoc analyses of the DecodeME dataset that are done, the less statistical validity you have.

On the other hand, I would personally like to see someone do the necessary math (that is all you need) on data accessed from DecodeME and jut see what turns up. I think researchers are entitled to play around with the data as much as they like if that leads to some sharply focused questions for a further study of another cohort. If you have much more focused questions then the massive p value corrections needed for GWAS, and the consequent need for huge samples, do not arise.

 

[Jonathan Edwards]

I guess that there is another potential way to argue around the statistical Catch22 that comes with more analyses. You might be able to argue that if the 8 DNA segments identified are robust genetic markers then they ought to show up at least as strongly for very early onset cases, if not more strongly. The analysis could be seen as quality control!

 

[jnmaciuch]

I guess that there is another potential way to argue around the statistical Catch22 that comes with more analyses. You might be able to argue that if the 8 DNA segments identified are robust genetic markers then they ought to show up at least as strongly for very early onset cases, if not more strongly. The analysis could be seen as quality control!

I just attended a lecture on this exact question in child vs. adult onset asthma. Different sets of genes were predictive in either case. There was some small amount of overlap and I believe that the risk loci from one cohort did have some association in the other cohort when collapsed into an overall score, but it was definitely a much weaker signal. Risk loci from GWAS generally tend to be heavily context specific

[Edit: pretty sure this is the paper that some of the discussed data came from:

Integration of functional genomics and statistical fine-mapping systematically characterizes adult-onset and childhood-onset asthma genetic associations - Genome Medicine

Background Genome-wide association studies (GWAS) have identified hundreds of loci underlying adult-onset asthma (AOA) and childhood-onset asthma (COA). However, the causal variants, regulatory elements, and effector genes at these loci are largely unknown. Methods We performed heritability...

link.springer.com

And a press release with summary:

Research fine tunes tools used to search for genetic causes of asthma

New study from UChicago combines genetic data and new computational tools to identify likely genetic variants that cause childhood- and adult-onset asthma.

biologicalsciences.uchicago.edu

]

 

[Jonathan Edwards]

I just attended a lecture on this exact question in child vs. adult onset asthma.

I think there are reasons for thinking that chldhood onset asthma may have a very different origin from adult onset. It is a long time since I heard anything about it but that was my impression. For ME/CFS we tend to assume the same mechanism I guess, even if there seem to be two age peaks.

But it adds another burning question maybe - would the 8 regions replicate at all in people with onset under 13? I am not sure why there isn't more interest in doing the analyses but I respect Chris's position that he cannot hope to publish analyses that are just scattershot.

 

[jnmaciuch]

I think there are reasons for thinking that chldhood onset asthma may have a very different origin from adult onset. It is a long time since I heard anything about it but that was my impression. For ME/CFS we tend to assume the same mechanism I guess, even if there seem to be two age peaks.

it’s also pretty well established that risk loci often don’t translate well between different ethnicities even in diseases with similar dynamics and presentation across groups. Risk loci from a study should always be interpreted as “variants associated with X in group Y”

Ultimately it’s not a safe assumption that these specific loci will hold in any other group that differs by a key demographic, though findings from multiple GWAS will likely paint similar biological stories at a broad level

 

[SNT Gatchaman]

I think there are reasons for thinking that chldhood onset asthma may have a very different origin from adult onset.

Childhood asthma may relate to maternal programming of fetal mast cells.

Fetal mast cells mediate postnatal allergic responses dependent on maternal IgE (2020, Science)

Spoiler: Abstract

Mast cells (MCs) are central effector cells in allergic reactions that are often mediated by immunoglobulin E (IgE). Allergies commonly start at an early age, and both MCs and IgE are detectable in fetuses. However, the origin of fetal IgE and whether fetal MCs can degranulate in response to IgE-dependent activation are presently unknown. Here, we show that human and mouse fetal MCs phenotypically mature through pregnancy and can be sensitized by maternal IgE. IgE crossed the placenta, dependent on the fetal neonatal Fc receptor (FcRN), and sensitized fetal MCs for allergen-specific degranulation. Both passive and active prenatal sensitization conferred allergen sensitivity, resulting in postnatal skin and airway inflammation after the first allergen encounter. We report a role for MCs within the developing fetus and demonstrate that fetal MCs may contribute to antigen-specific vertical transmission of allergic disease.

Mast cell ontogeny: From fetal development to life-long health and disease (2023, Immunological Reviews)

Spoiler: Abstract

Mast cells (MCs) are evolutionarily ancient innate immune cells with important roles in protective immunity against bacteria, parasites, and venomous animals. They can be found in most organs of the body, where they also contribute to normal tissue functioning, for example by engaging in crosstalk with nerves. Despite this, they are most widely known for their detrimental roles in allergy, anaphylaxis, and atopic disease. Just like macrophages, mast cells were conventionally thought to originate from the bone marrow. However, they are already present in fetal tissues before the onset of bone marrow hematopoiesis, questioning this dogma.

In recent years, our view of myeloid cell ontogeny has been revised. We now know that the first mast cells originate from progenitors made in the extra-embryonic yolk sac, and later get supplemented with mast cells produced from subsequent waves of hematopoiesis. In most connective tissues, sizeable populations of fetal-derived mast cells persist into adulthood, where they self-maintain largely independently from the bone marrow. These developmental origins are highly reminiscent of macrophages, which are known to have critical functions in development. Mast cells too may thus support healthy development. Their fetal origins and longevity also make mast cells susceptible to genetic and environmental perturbations, which may render them pathological.

Here, we review our current understanding of mast cell biology from a developmental perspective. We first summarize how mast cell populations are established from distinct hematopoietic progenitor waves, and how they are subsequently maintained throughout life. We then discuss what functions mast cells may normally have at early life stages, and how they may be co-opted to cause, worsen, or increase susceptibility to disease.

Maternal stress triggers early-life eczema through fetal mast cell programming (2025, Nature)

Spoiler: Abstract

Prenatal stress (PS) is a repeated exposure to aversive situations during pregnancy, including high emotional strain, which is suspected to affect homeostatic systems in infants. Paediatric eczema develops quickly after birth at flexural sites subjected to continuous mechanical constraints1,2. Although epidemiological studies have suggested an association between PS and a higher risk of eczema in children3,4,5,6, no causative biological link has yet been identified.

Here we show that eczema at birth originates from molecular dysregulations of neuroimmune circuits in utero, triggered by fluctuations in the maternal hypothalamic–pituitary–adrenal axis.

We found that offspring of stressed pregnant dams have dysregulated mast cells and skin-projecting neurons and quickly develop eczema in response to harmless mechanical friction. We demonstrated that PS transiently modulates amniotic fluid corticosterone concentrations, which directly alters the activation program of skin mast cells expressing the glucocorticoid receptor Nr3c1 and the adjacent sensory neurons conveying mechanosensation. Therapeutic normalization of maternal corticosterone concentrations or genetic depletion of Mcpt5+ mast cells during stressed gestation prevents fetal immune dysregulation and protects against eczema development after birth.

Our findings support a new model in which early-onset paediatric eczema originates from dysregulations in the fetal immune system, caused by fluctuations in maternal glucocorticoids induced by stress.

 

[ScoutB]

I just attended a lecture on this exact question in child vs. adult onset asthma. Different sets of genes were predictive in either case.

Interesting. I've heard of this in a number of diseases now. Did the lecture have any thoughts on if this kind of thing applies broadly?

@jnmaciuch do you have a sense of how much work would be involved in a thing like this? I guess the main stumbling block is that we need someone at a university who's allowed to handle the DecodeME data?

But it adds another burning question maybe - would the 8 regions replicate at all in people with onset under 13? I am not sure why there isn't more interest in doing the analyses but I respect Chris's position that he cannot hope to publish analyses that are just scattershot.

Right yea, this seems like a top question. We're always wondering if ME/CFS has subtypes, and the two peaks of onset seem like a strong candidates for at least different genetic subtypes. (I say, as a totally uninformed person.)

 

[MelbME]

I have discussed this with Chris. His problem is that the more post-hoc analyses of the DecodeME dataset that are done, the less statistical validity you have.

On the other hand, I would personally like to see someone do the necessary math (that is all you need) on data accessed from DecodeME and jut see what turns up. I think researchers are entitled to play around with the data as much as they like if that leads to some sharply focused questions for a further study of another cohort. If you have much more focused questions then the massive p value corrections needed for GWAS, and the consequent need for huge samples, do not arise.

This is more a concern I have about the use of LLMs for analysing data. It's becoming more and more common. If you give AI your data to analyse how can you know how many different ways it looked at the answer before getting it back to you. Some groups at Stanford (not ME research) have been letting AI work on data for 24 hours. I asked how many iterative analyses did it perform before spitting out data, they had no idea why that would be relevant.