Pain Registries and Databases as Biomarker Data Sources

Pain is among the most prevalent symptoms in ME/CFS (80–94% of patients) yet remains one of the least studied areas for biomarker development. Several registries and databases now collect systematic pain data that could support biomarker discovery and pain phenotype stratification.

1 Multi-site Clinical Assessment of ME/CFS (MCAM)

The MCAM study, coordinated by the CDC, enrolled 595 ME/CFS patients and 328 healthy controls from 7 specialty clinics across the United States (2012–2020) Instruments include the Brief Pain Inventory (BPI), PROMIS Pain Scales, CDC Symptom Inventory, SF-36 (bodily pain subscale), and full body maps. The MCAM dataset is the richest existing source of systematically collected ME/CFS pain data using validated instruments: 76.1% of ME/CFS participants had at least one Chronic Overlapping Pain Condition, compared to 17.4% of controls.

2 You + ME Registry

The Solve ME/CFS Initiative’s You + ME Registry is a patient-powered research platform with over 4,200 participants (3,033 ME/CFS, 833 long COVID, 473 controls as of 2021), growing at approximately 72 new registrants per week The mobile app captures longitudinal symptom tracking on a 0–4 severity scale, including pain. The registry is designed to harmonize with other ME/CFS data collection efforts and enables researchers to access de-identified data for analysis.

3 UK ME/CFS Biobank

The UK ME/CFS Biobank at UCL/Royal Free Hospital holds over 600 donors (ME/CFS, MS, and healthy controls) with more than 30,000 blood aliquots linked to clinical phenotyping data, including pain measures As Europe’s first ME/CFS-specific biobank, it provides the infrastructure for correlating pain phenotypes with biological specimens.

4 UK Biobank

The UK Biobank contains population-level data from which researchers have defined high-quality ME/CFS cohorts. Linked pain questionnaire data and health records enable large-scale epidemiological analysis of pain patterns in ME/CFS at a scale impossible with dedicated research cohorts.