Neurodevelopment Genes Encoding Olduvai Domains Link Myalgic Encephalomyelitis to Neuropsychiatric Disorders, 2025, Lidbury et al

[forestglip]

I took the first three variants in Table 1 (Top ranked genes) and all three have known quality issues noted on the Broad Institute gnomAD browser/database.

At least all the variants for the genes that replicated in the other cohort show "Pass".

Spoiler: Links to variants on gnomAD

PTPRD
https://gnomad.broadinstitute.org/variant/9-8436361-A-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-8318231-A-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-8409888-C-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-8845429-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-8897215-C-T?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-8901739-A-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-9270379-G-T?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-9829690-G-C?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-9904274-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/9-10254793-T-G?dataset=gnomad_r2_1

CSMD3
https://gnomad.broadinstitute.org/variant/8-113650725-C-T?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/8-113617156-T-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/8-114359441-G-T?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/8-114399612-A-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/8-114406336-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/8-114418955-T-C?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/8-114436474-T-G?dataset=gnomad_r2_1

RAPGEF5
https://gnomad.broadinstitute.org/variant/7-22184167-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/7-22278040-A-T?dataset=gnomad_r2_1

DCC
https://gnomad.broadinstitute.org/variant/18-50924132-T-C?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50369520-G-C?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50567129-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50597529-T-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50618359-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50622857-T-G?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50622885-C-T?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50623189-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/18-50668321-C-A?dataset=gnomad_r2_1

ALDH18A1
https://gnomad.broadinstitute.org/variant/10-97367511-C-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/10-97392993-T-C?dataset=gnomad_r2_1

GALNT16
https://gnomad.broadinstitute.org/variant/14-69809143-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/14-69734498-C-G?dataset=gnomad_r2_1

UNC79
https://gnomad.broadinstitute.org/variant/14-94120712-C-T?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/14-93902973-A-G?dataset=gnomad_r2_1

NCOA3
https://gnomad.broadinstitute.org/variant/20-46270379-G-A?dataset=gnomad_r2_1
https://gnomad.broadinstitute.org/variant/20-46215501-G-A?dataset=gnomad_r2_1

 

[wigglethemouse]

At least all the variants for the genes that replicated in the other cohort show "Pass".

That's a relief. I checked PTPRD in the UK Biobank data and nothing jumped out at me. Is it easy for you to do the other gene variants you list?

Spoiler: UK Biobank CFS data for PTPRD gene variants listed by paper

Table of data for the 10 variants on PTPRD
http://geneatlas.roslin.ed.ac.uk/se...573+rs1746813+rs16930522+rs2498611+rs996924

And this is the plot centered on PTPRD (scroll down to see plot)

http://geneatlas.roslin.ed.ac.uk/region/?traits=615&esymbol=PTPRD+&gextrawind=50&maxregion=10664&minregion=8263&chrom=9&representation=plot

 

[forestglip]

That's a relief. I checked PTPRD in the UK Biobank data and nothing jumped out at me. Is it easy for you to do the other gene variants you list?

Spoiler: UK Biobank CFS data for PTPRD gene variants listed by paper

Table of data for the 10 variants on PTPRD
http://geneatlas.roslin.ed.ac.uk/se...573+rs1746813+rs16930522+rs2498611+rs996924

And this is the plot centered on PTPRD (scroll down to see plot)

http://geneatlas.roslin.ed.ac.uk/region/?traits=615&esymbol=PTPRD+&gextrawind=50&maxregion=10664&minregion=8263&chrom=9&representation=plot

Sure. I wasn't sure if it'd be better to do all variants at once or per gene. Here is all except PTPRD together, but let me know if you want to see them split by gene: Link

Plots:
PTPRD
CSMD3
RAPGEF5
DCC
ALDH18A1
GALNT16
UNC79
NCOA3

Edit: I'll just paste all the variants here for easy copying if necessary:

Spoiler: Variants

PTPRD
rs7854171
rs996924
rs3847293
rs2570961
rs7866753
rs10815990
rs12341573
rs1746813
rs16930522
rs2498611

CSMD3
rs7833307
rs4876478
rs17608734
rs4311682
rs4354335
rs7002354
rs2942852

RAPGEF5
rs1859806
rs11766861

DCC
rs11082992
rs1560521
rs11874663
rs4995148
rs7233997
rs9957443
rs16956110
rs16956114
rs9956477

ALDH18A1
rs11188397
rs3750700

GALNT16
rs1296214
rs1890939

UNC79
rs55882426
rs28385502

NCOA3
rs623953
rs6066395

 

[Hutan]

Thank you both.

Here's the chart @forestglip posted for RAPGEF5:



I'm interested to try to understand what we are looking at here. Tell me if I am understanding things wrong.

You have taken a gene that this study has identified as useful in differentiating people with ME/CFS. You used the UK Biobank database to assess the prevalence of the SNPs making up that gene in the people in the database labelled with CFS versus the whole population in the database.

So, is the x axis the position of the SNPs on the gene? And each dot is an individual SNP. So, at any particular position, there might be several variants present in the UK Biobank population.

And the y axis (-log10 (pv)) is the p value, so a measure of whether the two samples are likely to be genuinely different in the prevalence of that particular SNP. A -log10(pv) of 4 is 0.0001 (i.e. 10^-4). So, there does look like something interesting going on around that 22,400 kb position. (?) What sort of p values would you want to see in order to get a bit excited?

And SNPs are labelled with rs numbers.

 

[forestglip]

So, is the x axis the position of the SNPs on the gene? And each dot is an individual SNP. So, at any particular position, there might be several variants present in the UK Biobank population.

Yeah, the gene is most of the width of the plot, and the x-axis is the position of the SNP on the gene/chromosome. If I look at GeneCards for the location of RAPGEF5 using the GRCh37 assembly which Gene Atlas is using, it says it is located at chr7:22,157,854-22,396,773. The plot goes from 22,100,000 to 22,450,000.

I'm not sure about the interestingness of the cluster of SNPs or a good p-value cutoff.

I don't know too much about this subject, and am not sure what to look for on these pages.

 

[butter.]

Ask clinicians who've seen thousands of people with ME/CFS—they'll almost uniformly tell you that individuals with ADHD, autism spectrum traits, and hypermobility syndromes (whatever label you use) are notably overrepresented. Both, ADHD and hypermobility are also overrepresented in ASD.

All of these conditions seem to exist on spectrums and are very likely polygenic, with environmental stress (note that infections during pregnancy have always been a leading theory in ASD) playing a significant role in how they manifest.

The idea that ASD might predispose individuals to other neurological diseases—even if it's not yet being systematically studied—makes a lot of sense. (If you've seen the severe dysautonomias in severe and very severe ME/CFS, there’s no doubt this is a neurological disease.)

Take Parkinson’s, for example: recent studies suggest it's more common in people with ASD. And when you think about what we know about ASD—particularly on a biomolecular level but also from a sensory processing and nervous system regulation perspective—it’s not surprising that other neurological conditions might 'follow'.

Apart from all that, ME/CFS also shares many very obvious symptomatic overlaps with ASD that you don't find in many other neurologic conditions.

I'm on the spectrum myself, as are others in my family. And while "spectrum" is a useful concept, in practice it often gets diluted. It’s become trendy to be “on the spectrum,” but labeling people who are merely a bit socially awkward as autistic isn’t clinically useful, imo. Like ME/CFS, ASD would benefit enormously from better stratification—clearer subtypes defined by biological markers, and more precise definitions.

All in all, it would make a lot of sense to find shared genetic vulnerabilities in ASD and ME/CFS. I can't read the paper itself and it is probably way above me anyways, I am merely speaking from a clinical and first person experience perspective.

 

[Sean]

And worth noting that while education and income don’t necessarily correlate with “smartness”. They tend to correlate with the imperfect methods we use to approximate “smartness”.

Could be measuring the ability and/or willingness to mimic or conform to normative models of 'smartness'.

 

[Yann04]

Could be measuring the ability and/or willingness to mimic or conform to normative models of 'smartness'.

Yup.
Could just be that “smartness” is defined by “successful” people who see themselves as smart so it ends up measuring more class correlates than actual “smartness”.

 

[Sean]

Frank Zappa's take on it was: Without deviation from the norm there is no progress.

 

[wigglethemouse]

I'm interested to try to understand what we are looking at here.

On top of what @forestglip explained about the plot you need to manually check variants that are higher in the plot that you are interested in to see if the MAF is too low. Low MAF values are not filtered out by the plot that would be filtered in a research study analysis.

If you look at the results in table form you can sort the table by pv and then check the MAF.

 

[Snow Leopard]

And worth noting that while education and income don’t necessarily correlate with “smartness”. They tend to correlate with the imperfect methods we use to approximate “smartness”.

Especially as most PwME's SES income/status tends to plummet after becoming ill.

 

[wigglethemouse]

Edit: I'll just paste all the variants here for easy copying if necessary:

Thank you. The best p-value on the UK Biobank for these variants for CFS is 0.1 which is nothing close to the p-values reported in the paper of this thread.
Link

 

[forestglip]

Replication of these results was attempted via a GWAS on raw data from a US cohort, which confirmed shared significant associations with variation identified in the PTPRD, CSMD3, RAPGEF5, DCC, ALDH18A1, GALNT16, UNC79, and NCOA3 genes.

One of the genes that was significant in both cohorts, DCC, was also significant in depressive symptoms not associated with recent stress:

S4ME Thread: Disentangling nature and nurture: Exploring the genetic background of depressive symptoms in the absence of recent stress exposure using a GWAS approach, 2025, Erdelyi-Hamza et al

We included nearly 200,000 subjects reporting no stressful life events in the past two years with data on current depressive symptom severity.

64 SNPs with suggestive significance were identified, one SNP (rs60939828 p = 5.92 × 10−11), located in DCC survived Bonferroni correction. DCC (p = 4.16 × 10−10) was also among three genes significant in gene-level associations.

DCC on GeneCards:

This gene encodes a netrin 1 receptor. The transmembrane protein is a member of the immunoglobulin superfamily of cell adhesion molecules, and mediates axon guidance of neuronal growth cones towards sources of netrin 1 ligand. The cytoplasmic tail interacts with the tyrosine kinases Src and focal adhesion kinase (FAK, also known as PTK2) to mediate axon attraction. The protein partially localizes to lipid rafts, and induces apoptosis in the absence of ligand. The protein functions as a tumor suppressor, and is frequently mutated or downregulated in colorectal cancer and esophageal carcinoma.