E2 ModeratePreliminaryPEM ?Registry-ResourcePeer-reviewedMachine draft
The Facilitation of Clinical and Therapeutic Discoveries in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Related Diseases: Protocol for the You + ME Registry Research Platform.
Ramiller, Allison, Mudie, Kathleen, Seibert, Elle et al. · JMIR research protocols · 2022 · DOI
Quick Summary
Researchers created a registry called 'You + ME' to collect health information from thousands of people with ME/CFS, long COVID, and healthy volunteers over time. By gathering this large amount of data in one place, researchers hope to better understand why people get sick differently and develop new treatments. As of September 2021, over 4,200 people had joined, with most participants finding the registry helpful and likely to recommend it to others.
Why It Matters
ME/CFS lacks validated diagnostics and treatments partly because the disease is heterogeneous—meaning it manifests differently across patients. By collecting standardized data from thousands of participants, the You + ME Registry creates a resource that could help identify disease subtypes, discover biomarkers, and accelerate development of personalized treatments, similar to how big data approaches have advanced cancer and MS research.
Observed Findings
- Over 4,200 geographically diverse participants enrolled as of September 30, 2021.
- 69.9% of participants had ME/CFS, 19.2% had post-COVID-19 illness, and 10.9% were healthy controls.
- The registry achieved a 'great' net promoter score, indicating high participant satisfaction and willingness to recommend participation.
- Average enrollment rate of approximately 72 new participants per week.
Inferred Conclusions
- The You + ME Registry successfully established a large, diverse participant cohort with strong engagement and satisfaction metrics.
- Integrating symptom-tracking apps with biorepository capabilities creates a comprehensive resource for identifying disease heterogeneity and developing personalized therapies.
- Collaborative, harmonized data collection across multiple groups may accelerate discovery of ME/CFS causes and mechanisms.
Remaining Questions
- What disease subtypes or phenotypes emerge from analysis of the longitudinal health data?
- Which biomarkers or biological mechanisms distinguish ME/CFS from long COVID and healthy controls?
- Will data from this registry identify modifiable factors or lead to testable therapeutic targets?
What This Study Does Not Prove
This protocol paper describes the registry's design and enrollment metrics but does not present clinical findings, biomarkers, disease subtypes, or evidence that any particular treatment is effective. The high enrollment and satisfaction rates do not prove that the data collected will reveal new causes of ME/CFS or lead to new therapies—only that the infrastructure is functioning and ready for analysis.
Tags
Symptom:Post-Exertional MalaiseCognitive DysfunctionUnrefreshing SleepFatigue
Phenotype:Long COVID Overlap
Method Flag:PEM Not DefinedExploratory OnlyMixed Cohort
Metadata
- DOI
- 10.2196/36798
- PMID
- 35816681
- Review status
- Machine draft
- Evidence level
- Single-study or moderate support from human research
- Last updated
- 8 April 2026