Protocol: DecodeME: community recruitment for a large genetics study of ME/CFS, 2022, Devereux-Cooke et al

Andy

Andy

Senior Member (Voting rights)
Abstract

Background

Myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) is a common, long-term condition characterised by post-exertional malaise, often with fatigue that is not significantly relieved by rest. ME/CFS has no confirmed diagnostic test or effective treatment and we lack knowledge of its causes. Identification of genes and cellular processes whose disruption adds to ME/CFS risk is a necessary first step towards development of effective therapy.

Methods
Here we describe DecodeME, an ongoing study co-produced by people with lived experience of ME/CFS and scientists. Together we designed the study and obtained funding and are now recruiting up to 25,000 people in the UK with a clinical diagnosis of ME/CFS. Those eligible for the study are at least 16 years old, pass international study criteria, and lack any alternative diagnoses that can result in chronic fatigue. These will include 5,000 people whose ME/CFS diagnosis was a consequence of SARS-CoV-2 infection. Questionnaires are completed online or on paper. Participants’ saliva DNA samples are acquired by post, which improves participation by more severely-affected individuals. Digital marketing and social media approaches resulted in 29,000 people with ME/CFS in the UK pre-registering their interest in participating. We will perform a genome-wide association study, comparing participants’ genotypes with those from UK Biobank as controls. This should generate hypotheses regarding the genes, mechanisms and cell types contributing to ME/CFS disease aetiology.

Discussion
The DecodeME study has been reviewed and given a favourable opinion by the North West – Liverpool Central Research Ethics Committee (21/NW/0169). Relevant documents will be available online (www.decodeme.org.uk). Genetic data will be disseminated as associated variants and genomic intervals, and as summary statistics. Results will be reported on the DecodeME website and via open access publications.

Open access, https://bmcneurol.biomedcentral.com/articles/10.1186/s12883-022-02763-6
 
Congratulations, @Andy and the rest of the team. I haven't read every word of this yet, but what I have read is a model of clarity and openness.

Oh how I wish all ME research were so well conducted. Whether this study comes up with useful answers or not, I think it demonstrates just how valuable a true collaboration between scientists and expert patients and carers can be. On that basis alone, I think it's a triumph.
 
Simon M said:
Devereux-Cooke et al., 2022 :)
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Well, I had to abuse my power to achieve some sort of personal benefit out of the study.... ;)

[For clarity for everybody else, the above is a joke - I had no expectation that I would end up where I did in the list of authors. What I do think is fantastic though is that all patients and carers who were happy to be named are included as authors.]
 
Congrats to everyone who made this happen.

To me DecodeME is so much more than a big genetic study. It's about bringing ME/CFS research to the next level. There are also so many interesting side-projects and ideas. Just to quote a few things from the protocol:

"Recruitment of a further 5,000 ME/CFS diagnosed cases whose symptoms arose following SARS-CoV-2 infection was agreed by funders in 2021. Comparison of the two sub-cohorts will permit investigation of whether they share genetic risk factors. Cases whose initial ME/CFS symptoms arose following SARS-CoV-2 infection will not have been hospitalised as a result of SARS-CoV-2 infection and not informed of heart or lung damage as a result of COVID-19."

"Cases and/or controls will be analysed for closerelatedness [23] and genetic ancestry, and 1,000 UK Biobank control image fles will be analysed alongside those from cases to minimise spurious associations arising from the separate genotyping of cases and controls."

"Any associated SNPs discovered will be investigated for independent replication using separately recruited cohorts such as 23andMe [26] and Genes for Good [16], which each include a question on CFS diagnosis. Te 5 k post COVID ME/CFS cases would be analysed separately using GWAS and then by comparison of top associations from pre- or post-COVID cases’ GWAS."

"In 2023–24, an EHR pilot project of the expected~10% of DecodeME participants living in Scotland will be undertaken. We will organise and summarise the resulting EHR morbidity data (SMR01) and any other relevant available datasets to inform future EHR linkage analyses across the entire cohort. Te frequency of ME/CFS ICD-10 codes in this DecodeME sub-cohort will be analysed and compared with EHR data on matched population controls, such as from Generation Scotland [27] or UK Biobank"

"Only approximately half of a participant’s DNA sample will be used for genotyping of common DNA variants. Te other half will be stored by the NIHR Biosample Centre for future whole genome sequencing (WGS) when funding allows. "

"DecodeME’s three principal objectives are to: [...] 3) Curate an open (managed) resource of genotype and phenotype data for these 25 k people with ME/CFS, consented to be invited to take part in future epidemiological, genetic, biomolecular and clinical trial and other clinical studies. [...] To accelerate ME/CFS research, for participants who have given their informed consent, the DecodeME genotype and phenotype data will be available, via controlled access, to all bona fde researchers whose studies have ethics approval."​
 
One point of criticism would be that the protocol doesn't fully explain that patients in DecodeME will not receive a clinical examination to see if they meet ME/CFS criteria as is usually the case in ME/CFS studies.

Prevalences studies have previously indicated that a large percentage of patients that meet ME/CFS-like criteria on questionnaires, do not meet ME/CFS criteria after clinical examination. Big caveat though: this previous research was done with the Fukuda criteria which focuses on fatigue rather than PEM and it used less specific questionnaires. So the Decode ME approach may be significantly better at selecting ME/CFS patients.

It would still be interesting to see the concordance, for example by subjecting a subgroup of DecodeME participants to a clinical examination and see how many would then still meet ME/CFS criteria afterwards.
 
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ME/CFS Skeptic said:
Prevalences studies have previously indicated that a large percentage of patients that meet ME/CFS-like criteria on questionnaires, do not meet ME/CFS criteria after clinical examination. Big caveat though: this previous research was done with the Fukuda criteria which focuses on fatigue rather than PEM and it used less specific questionnaires. So the Decode ME approach may be significantly better at selecting ME/CFS patients.
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Thanks for all your comments and analysis.

Compared with prevalence studies, DecodeME requires PEM, as you say, and also requires all participants to have a diagnosis of ME or CFS from a healthcare professional. Clinically diagnosing each case ourselves would have been ideal but would also have made the study unaffordable. And it would have excluded the severely affected who, regardless of the importance of inclusivity, might prove to provide the most valuable data.

ME/CFS Skeptic said:
It would still be interesting to see the concordance, for example by subjecting a subgroup of DecodeME participants to a clinical examination and see how many would then still meet ME/CFS criteria afterwards.
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It would, and we explored exactly this in the early days, but the cost and logistics made it unworkable. I believe this could still be done as a separate study at a later date.
 
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