Chris Ponting Research Group

Research in a Nutshell 

Our research uses cutting-edge analytical approaches in genetics, genomics, transcriptomics, and cell biology to determine the causal mechanisms of myalgic encephalomyelitis (ME, sometimes known as chronic fatigue syndrome [CFS]). We work closely with colleagues, Sjoerd Beentjes and Ava Khamseh, and host Audrey Ryback’s ME/CFS research programme.

In previous research, we estimated the lifetime prevalence of ME/CFS to be approximately 400,000 UK individuals. We also identified 116 molecular traits that differ significantly between cases and controls, for females and separately for males. 

The DecodeME project is a £3.2m NIHR and MRC-funded strategic grant run as a coproduction with people with lived experience of ME/CFS. With 18,000 DNA participants, this is the world’s largest genetic study into ME/CFS. An initial genome-wide association analysis (using matched UK Biobank individuals as controls) identified 8 genetic signals. The preprint describing these results has been highlighted by UK and international media. 

PhD students also work in the group on ME/CFS genetics funded by Action for ME or by ME Research UK. We support Action for ME’s vision to establish the UK’s first Genetics Centre of Excellence, a virtual network of ME researchers who, with the ME community, will build on the genetic insights gained through DecodeME and other studies.

Please get in touch (chris.ponting@ed.ac.uk) if you would like to undertake a personal Fellowship, postdoctoral post or studentship with us.

1. Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome. DecodeME collaboration. https://www.research.ed.ac.uk/en/publications/initial-findings-from-the-decodeme-genome-wide-association-study-
2. Unequal access to diagnosis of myalgic encephalomyelitis in England. Samms, G.L. & Ponting, C.P. (2025) BMC Public Health 1417. https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-025-22603-9
3. Replicated blood-based biomarkers for myalgic encephalomyelitis not explicable by inactivity Beentjes et al. (2025) EMBO Mol Med 17: 1868 https://www.embopress.org/doi/full/10.1038/s44321-025-00258-8
4. High order expression dependencies finely resolve cryptic states and subtypes in single cell data. Jansma et al. (2025) Mol Syst Biol. 21: 173. https://www.embopress.org/doi/full/10.1038/s44320-024-00074-1
5. Typing myalgic encephalomyelitis by infection at onset: A DecodeME study. Bretherick et al. (2023) NIHR Open Res. 3: 20. https://openresearch.nihr.ac.uk/articles/3-20/v4 

Full publication list can be found on Research Explorer: Chris Ponting — University of Edinburgh Research Explorer

• Dr Ava Khamseh & Dr Sjoerd Beentjes, University of Edinburgh
• Action for ME: ME/CFS Genetics Centre of Excellence, DecodeME
• Dr Audrey Ryback, University of Edinburgh

• MRC
• NIHR
• ME Research UK