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

They have previously described this cohort in another paper:
Other clinical procedures, tests, cohort descriptions, and results have been reported previously, including comparisons with a healthy control group [29] and the calculation of symptom severity via Weighted Standing Time (WST) [30]. For these exome analyses, only the ME/CFS cohort was investigated, with 77 of the 80 participants initially recruited providing consent for this study, as well as meeting all inclusion criteria and availability requirements.
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[29] Lidbury, B.A.; Kita, B.; Richardson, A.M.; Lewis, D.P.; Privitera, E.; Hayward, S.; de Kretser, D.; Hedger, M. Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity. Diagnostics 2019, 9, 79. [Google Scholar] [CrossRef] [S4ME]

[30] Richardson, A.M.; Lewis, D.P.; Kita, B.; Ludlow, H.; Groome, N.P.; Hedger, M.P.; de Kretser, D.M.; Lidbury, B.A. Weighting of orthostatic intolerance time measurements with standing difficulty score stratifies ME/CFS symptom severity and analyte detection. J. Transl. Med. 2018, 16, 97. [Google Scholar] [CrossRef] [S4ME]

Ref 29 has 80 participants so that matches with this study, but ref 30 has 45 participants, so I think that's a different cohort.

Edit: It says again here that ref 30 is the same cohort, so maybe it was a subset of this current study's cohort:
This ME/CFS cohort has been described previously and compared to a non-ME/CFS (healthy) control group in relation to pathology markers and serum activin B, with symptom severity assessed via Weighted Standing Time (WST) [29,30].
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wigglethemouse said:
I wish they included a count of n/77 for cases with the variant so we could get a better feel for the data. I couldn't find where they pulled the MAF numbers from for comparing against (sorry, can only scan and Ctrl-F search papers nowadays).
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Supplementary table S1 seems to have some sort of extra data but I'm not sure what it is listing.

When analysing GWAS you need to be aware of miscalls for the platform you are using. I'm aware of some studies finding very high frequency vs low MAF or vice versa in cases and it turned out to be known mis-calls of the technology used, or getting the MAF very wrong. The most famous in ME/CFS is the Perez et al 23andMe ME/CFS paper that didn't clean the dataset beforehand. That is why I am dubious of such low p values.
RE: Re-analysis of Genetic Risks for Chronic Fatigue Syndrome From 23andMe Data Finds Few Remain

I have much more faith in DecodeME because patients and controls use the same sequencing technology and process.
 
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GWAS Analysis: As mentioned in the introduction, given the low prevalence of ME we used 323 individuals belonging to Caucasian communities recruited and genotyped by the 1000 Genome Project (1 K Genomes) as controls [40]: Utah residents (CEPH) with Northern and Western European Ancestry (CEU, n = 32), Finnish individuals in Finland (FIN, n = 93), British individuals in England and Scotland (GBR, n = 86), an Iberian population in Spain (IBS, n = 14), and individuals from Tuscany in Italy (TSI, n = 98). The potential bias was minimal given the rareness of the ME phenotype.
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Considering their control group is just individuals from the general population and they didn't attempt to limit to those without ME/CFS, why would they limit it to 323 individuals? Couldn't they have used a few hundred thousand individuals from a database like the UK BioBank to increase statistical power?
 
This is also the same cohort as their previous paper that found Complex V insufficiency. (That paper says 51 participants though, so not exactly the same.)
The significance of ALDH18A1, in addition to its role in metabolic perturbations, draws attention to mitochondrial function in ME/CFS patients. While future functional studies on the myriad neurodevelopment genes are needed to confirm their significance, mitochondrial function studies have been conducted on the same patient cohort as presented here [84]. Notable for ME/CFS dysfunction were Complex V insufficiency combined with TORC-1 increases in comparison to healthy (non-ME) control participants. Whether ALDH18A1 is directly involved in this ME/CFS mitochondrial function profile will require further investigation.
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[84] Missailidis, D.; Annesley, S.J.; Allan, C.Y.; Sanislav, O.; Lidbury, B.A.; Lewis, D.P.; Fisher, P.R. An Isolated Complex V Inefficiency and Dysregulated Mitochondrial Function in Immortalized Lymphocytes from ME/CFS Patients. Int. J. Mol. Sci. 2020, 21, 1074. [Google Scholar] [CrossRef] [S4ME]
 
SNT Gatchaman said:
Just looking at the first one, NBPF1 also has high expression outside the nervous system, including in bone marrow, lymph nodes and skeletal muscle.
https://www.genecards.org/cgi-bin/carddisp.pl?gene=NBPF1#expression
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It always baffles me that studies will talk about only association with the brain when that gene is expressed (even at higher levels) in so many other tissues. I think it's because neuroscience has simply done quite a thorough job of functionally categorizing relevant genes in their neurological context, and that effort has not been matched in other fields. This can often give a skewed an impression that the brain must be involved when really it could be a whole host of tissues. There doesn't seem to be any functional data in this paper to confirm that it is the neurological actions of those genes that are relevant.

I'll also echo other concerns about the appropriateness of using a small-cohort genomic analysis method here.
 
I take a slightly different view. Some of us on this thread (at least three) co-authored a paper nearly ten years ago (OK it may all have been my fault) suggesting that there was some real biology deep behind MECFS and that it was likely either in CNS or immune cells or both. So genes expressed in CNS fit a story, even if they are expressed elsewhere.
 
wigglethemouse said:
When analysing GWAS you need to be aware of miscalls for the platform you are using. I'm aware of some studies finding very high frequency vs low MAF or vice versa in cases and it turned out to be known mis-calls of the technology used, or getting the MAF very wrong. The most famous in ME/CFS is the Perez et al 23andMe ME/CFS paper that didn't clean the dataset beforehand. That is why I am dubious of such low p values.
RE: Re-analysis of Genetic Risks for Chronic Fatigue Syndrome From 23andMe Data Finds Few Remain
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Thanks for linking that interesting paper @wigglethemouse. I missed it when it came out - here's the forum thread link.
 
Jonathan Edwards said:
I take a slightly different view. Some of us on this thread (at least three) co-authored a paper nearly ten years ago (OK it may all have been my fault) suggesting that there was some real biology deep behind MECFS and that it was likely either in CNS or immune cells or both. So genes expressed in CNS fit a story, even if they are expressed elsewhere.
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The CNS may well be involved somehow in ME/CFS, I’m commenting on a tendency in papers across fields to implicate neurological involvement solely on the basis of genes that happen to be extensively characterized in the CNS but are also expressed elsewhere.

It’s one of my biggest pet peeves with CX3CR1 or GFAP CRE mouse models—people show a significant finding and claim it must be due to microglia or astrocytes when there are a ton of other places where those genes are expressed. Happens in genomics studies all the time as well.
 
This paper looks to have serious quality issues. 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.

NBPF1, rs3897177, SNV:1-16909052-C-T (GRCh37) Warning : Genomes failed random forest filter
Link

NBPF10, rs10910794, SNV:1-145303971-A-G (GRCh37) Warning: Genomes have inbreed coeff. < -0.3
Link

NBPF10, rs1553120233, SNV:1-145355624-C-T (GRCh37) Warning : No matching variants found. rs1553120233
Link
Search based on location 1-145355624-C-T = rs112674709
Warning: This variant is covered in fewer than 50% of individuals in gnomAD v2.1.1 genomes. This may indicate a low-quality site.
Link

I'm not going to check any more.
 
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