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

Nightsong

Nightsong

Senior Member (Voting Rights)
Abstract:
Background/Objectives: The aetiology of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a chronic and severe debilitating disease with a complex phenotype, remains elusive. Associations with infectious diseases and autoimmune and neuropsychiatric disorders have been observed, without the identification of mechanisms. Previous studies suggest that genetic predisposition plays a role, but results are difficult to replicate, with Genome-Wide Association Studies of ME/CFS being challenging due to the relative rareness and heterogeneity of the disorder.

Methods: We studied a well-defined Australian patient cohort diagnosed via the International Consensus Criteria, recruited by a specialist ME/CFS clinic. The whole-exome sequences of 77 patients were contrasted against genome variation in the 1000 Genome Project’s genome-matched population.

Results: Significant associations with ME/CFS were harboured in genes that belong to the Neuroblastoma Breakpoint Family encoding Olduvai (DUF1220) domains, namely NBPF1 (rs3897177, p-value = 3.15 × 10−8), NBPF10 (rs1553120233, p-value = 9.262 × 10−13), and NBPF16 (rs200632836, p-value = 1.04 × 10−6). Other significantly associated variants were detected in the ATR, RSPH10B,ADGRE5-CD97, and NTRK2 genes, among others. 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.

Conclusions: These genes are involved in cortical neurogenesis, brain evolution, and neuroblastoma, and have been implicated by several studies in schizophrenia and autism. The sharing of these associations by the two cohorts supports their validity and grants the necessity of future studies to evaluate the implications for ME/CFS aetiology.

https://www.mdpi.com/2075-4418/15/12/1542
 
The discussion section where they try to explain what the relevance of these genes are is quite a stretch, due to lack of primary research. (same goes with the link to neuropsychiatric disorders / autism, we simply don't know enough to say this)

I want to believe the NBPF and GO:0050773 association as a means of peripheral nerve sensitisation, but there isn't enough evidence.
 
Snow Leopard said:
The discussion section where they try to explain what the relevance of these genes are is quite a stretch, due to lack of primary research. (same goes with the link to neuropsychiatric disorders / autism, we simply don't know enough to say this)
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Yes, I agree. The NBPF genes weren't replicated in the Nevada cohort. I think the attention should go to the genes that they say were found in both cohorts.

I think it's possible to make up all sorts of speculative stories. For example, variations in the NBPF genes have been associated with cognitive ability and IQ, as well as cognitive defects and cognitive differences. It's possible that some of the people who put themselves forward for inclusion in the Australian cohort highly value research and science, and have higher cognitive abilities than average.
 
Simon M said:
With only 77 cases, the WES looks underpowered to me.
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This paper comments on this:

The team’s genomics expert (M.A.-B.)specialises in the genetics of complex diseases (e.g., Alzheimer’s Disease) and has led thedevelopment of methods that allow the performance of GWAS on small patient sample sizes (pooling/bootstrap methods) [21].
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Reference 21 is:
Pooling/bootstrap-based GWAS (pbGWAS) identifies new loci modifying the age of onset in PSEN1 p.Glu280Ala Alzheimer's disease - PubMed

Abstract​

The literature on GWAS (genome-wide association studies) data suggests that very large sample sizes (for example, 50,000 cases and 50,000 controls) may be required to detect significant associations of genomic regions for complex disorders such as Alzheimer's disease (AD). Because of the challenges of obtaining such large cohorts, we describe here a novel sequential strategy that combines pooling of DNA and bootstrapping (pbGWAS) in order to significantly increase the statistical power and exponentially reduce expenses. We applied this method to a very homogeneous sample of patients belonging to a unique and clinically well-characterized multigenerational pedigree with one of the most severe forms of early onset AD, carrying the PSEN1 p.Glu280Ala mutation (often referred to as E280A mutation), which originated as a consequence of a founder effect. In this cohort, we identified novel loci genome-wide significantly associated as modifiers of the age of onset of AD (CD44, rs187116, P=1.29 × 10⁻¹²; NPHP1, rs10173717, P=1.74 × 10⁻¹²; CADPS2, rs3757536, P=1.54 × 10⁻¹⁰; GREM2, rs12129547, P=1.69 × 10⁻¹³, among others) as well as other loci known to be associated with AD. Regions identified by pbGWAS were confirmed by subsequent individual genotyping. The pbGWAS methodology and the genes it targeted could provide important insights in determining the genetic causes of AD and other complex conditions.

(haven't read it myself)
 
Nevada replication
We conducted a replication study of our positive Australian associations on the GWAS raw data genotyped in an ME/CFS cohort recruited from Nevada in the United States [22]. Several associations shared by both cohorts were successfully identified, namely (1) a cluster harboured in the genomic region encoding protein tyrosine phosphatase receptor type D (PTPRD) (Australian cohort, p-value = 2.21 × 10−6; Schlauch et al. cohort, p-value = 1.14 × 10−6); (2) a cluster of six markers harboured in the CUB and Sushi multiple domains 3 (CSMD3); (3) other variants anchored in the coding regions of the RAPGEF5, CSMD3, DCC, ALDH18A1, GALNT16, UNC79, NCOA3 genes. We found novel and functional variants harboured in the coding regions of some of these genes, suggesting that these mutations might underlie the common association highlighted inside of these genome regions.
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PTPRD
The PTPRD gene encodes a member of the protein tyrosine phosphatase (PTP) family, signalling molecules associated with cellular processes including cell growth, differentiation, the mitotic cycle, and oncogenic transformation. Members of the PTP family also promote neurite growth and regulate neurons’ axon guidance. PTPRD is one of the most frequently inactivated genes across human cancers, including glioblastoma multiforme (GBM) [74]. It is well known that pre-synaptic PTPRD promotes the differentiation of glutamatergic synapses, and several studies link PTPRD genetic variation to psychiatric phenotypes such as schizophrenia, bipolar disorder and mood instability [75], obsessive–compulsive disorder [76,77], and weight gain with antipsychotic medication [78]. Variants harboured in PTRPD have also been associated with susceptibility to the de-development of neurofibrillary tangles [79].
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That gene is covering an awful lot of ground - even just the first two things mentioned 'cell growth and differentiation' cover an enormous number of possible things that might be going wrong in a wide range of places.

And again, there might be a problem caused by the variants, but it might be reflecting the cohorts putting themselves forward for research being special, and perhaps high-functioning, in some way. Take that last sentences 'Variants harboured in PTRPD have also been associated with susceptibility to the de-development of neurofibrillary tangles'. 'De-development' is actually a good thing I think - pharmaceutical companies are trying to find out how to de-develop neurofibrillary tangles in Alzheimers.

I'm not sure, but 'variants harboured' makes it sound as though the authors may have identified these variants in their cohort.
 
Hutan said:
I think it's possible to make up all sorts of speculative stories. For example, variations in the NBPF genes have been associated with cognitive ability and IQ, as well as cognitive defects and cognitive differences.
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As with autism being found to have genetic links both with intellectual disability and with higher ability. it probably says more about who gets diagnosed.
 
ME/CFS Skeptic said:
We applied this method to a very homogeneous sample of patients belonging to a unique and clinically well-characterized multigenerational pedigree with one of the most severe forms of early onset AD, carrying the PSEN1 p.Glu280Ala mutation (often referred to as E280A mutation), which originated as a consequence of a founder effect.
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That's quite a special case, basically a family.
 
ME/CFS Skeptic said:
This paper comments on this:


Reference 21 is:
Pooling/bootstrap-based GWAS (pbGWAS) identifies new loci modifying the age of onset in PSEN1 p.Glu280Ala Alzheimer's disease - PubMed

Abstract​

The literature on GWAS (genome-wide association studies) data suggests that very large sample sizes (for example, 50,000 cases and 50,000 controls) may be required to detect significant associations of genomic regions for complex disorders such as Alzheimer's disease (AD). Because of the challenges of obtaining such large cohorts, we describe here a novel sequential strategy that combines pooling of DNA and bootstrapping (pbGWAS) in order to significantly increase the statistical power and exponentially reduce expenses. We applied this method to a very homogeneous sample of patients belonging to a unique and clinically well-characterized multigenerational pedigree with one of the most severe forms of early onset AD, carrying the PSEN1 p.Glu280Ala mutation (often referred to as E280A mutation), which originated as a consequence of a founder effect. In this cohort, we identified novel loci genome-wide significantly associated as modifiers of the age of onset of AD (CD44, rs187116, P=1.29 × 10⁻¹²; NPHP1, rs10173717, P=1.74 × 10⁻¹²; CADPS2, rs3757536, P=1.54 × 10⁻¹⁰; GREM2, rs12129547, P=1.69 × 10⁻¹³, among others) as well as other loci known to be associated with AD. Regions identified by pbGWAS were confirmed by subsequent individual genotyping. The pbGWAS methodology and the genes it targeted could provide important insights in determining the genetic causes of AD and other complex conditions.

(haven't read it myself)
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Abstract:
>We applied this method to a very homogeneous sample of patients belonging to a unique and clinically well-characterized multigenerational pedigree with one of the most severe forms of early onset AD, carrying the PSEN1 p.Glu280Ala mutation (often referred to as E280A mutation), which originated as a consequence of a founder effect. <

As they say, that's a unique cohort with a very strong genetic effect. I don't think it's appropriate to extrapolate that method to this study.

Added
I should've read @Hutan 's comment first! Exactly what she said
 
Eleanor said:
As with autism being found to have genetic links both with intellectual disability and with higher ability. it probably says more about who gets diagnosed.
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Yup. The autism criteria being a sort of socio-normative category that encompasses a very wide range of very different experiences is something that has always confused me from a medical research sense. Like researching people who broadly “behave different to neurotypicals” doesn’t sound like a very homogenous group…

I guess this is definitely the case for Fukuda type criteria and to a lesser extend also CCC, IOM, ICC type.
 
Just linking this Norwegian study that looked at how education and income correlates with risk of diagnosis:
IMG_0201.png
Kalliope

Thread 'Socioeconomic determinants of ME/CFS in Norway: a registry study, Hilland and Anthun, 2023'

Now published - link here
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Preprint
Research Square
Socioeconomic determinants of myalgic encephalomyelitis/chronic fatigue syndrome in Norway: a registry study

Abstract

Background: Previous research has shown that socioeconomic status (SES) is a strong predictor of chronic disease. However, to the best of our knowledge, there has been no studies of how SES affects the risk of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) that has not been based upon self-reporting or retrospectively screening of symptoms. As far as we know, this is therefore the...
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Utsikt said:
Just linking this Norwegian study that looked at how education and income correlates with risk of diagnosis:
View attachment 26644
Kalliope

Thread 'Socioeconomic determinants of ME/CFS in Norway: a registry study, Hilland and Anthun, 2023'

Now published - link here
*******
Preprint
Research Square
Socioeconomic determinants of myalgic encephalomyelitis/chronic fatigue syndrome in Norway: a registry study

Abstract

Background: Previous research has shown that socioeconomic status (SES) is a strong predictor of chronic disease. However, to the best of our knowledge, there has been no studies of how SES affects the risk of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) that has not been based upon self-reporting or retrospectively screening of symptoms. As far as we know, this is therefore the...
  • Like
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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”.
 
Snow Leopard said:
That is an excellent point and a key confounder for small convenience samples like this compared to large GWAS studies.
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I agree that cohort selection is important but my impression is that these are probably all patients from one clinic with one physician. That has certain strengths. If anything I think patients recruited for self-referral to big GWAS projects might be even more likely to be skewed on intellect or personality. And if that skew is systematic it becomes MORE of a problem with large cohorts. I think systematic skewing may have been a significant issue for the Leeds Biobank cohort genetics and proteomic findings. Although interestingly , no clear gene links came out of it, possibly because of dilution.
 
I can't make any sense of the data in table 1. How on earth do they get such low p-values for very common gene variants. Doesn't make sense to my simple understanding.

I spot checked a few NBPF* variants in section A of table 1 and the internet genetic databases shows quite a lot of MAF variation between different cohorts. And those databases sometimes show the reference allele having a lower frequency than the alternate allele.

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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