31 Marker Panel - ME/CFS and Long COVID

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This comprehensive panel evaluates 31 biomarkers across interconnected biological systems implicated in ME/CFS and Long COVID pathophysiology. The markers span energy metabolism, mitochondrial dynamics, vascular regulation, blood-brain barrier integrity, innate immunity, renin-angiotensin system function, growth factor signalling, oxidative stress, and hypoxia pathways, providing insight into the complex physiological disruptions underlying these chronic conditions.

Join batches 2 and 3
£1,125 

See below for more information.
Information about Joining
Batches will commence once sufficient participants have joined (progress updates will be shared publicly).
Expected turnaround time after all samples collected: Results estimated within 1-3 months of batch initiation.

Included in cost:
  • Support organising blood collection and international delivery of samples to UK lab
  • Analysis of 31 biomarkers in your blood sample
  • Generation of results and personalised report
  • Secure access to your results via our database
  • Ongoing research to deepen insights and refine your results over time
  • Integration of advanced Machine Learning (ML) techniques for data analysis and interpretation
  • Coordination with your personal physician to provide insights tailored to your individual case
  • Opportunity to be considered for future clinical trials and research projects by joining our extensively characterised patient database

Multi-system analysis of ME/CFS and Long COVID mechanisms
This panel measures activity across multiple biological systems implicated in ME/CFS and Long COVID pathophysiology:
  • Renin-Angiotensin-Aldosterone System (RAAS): Ang-(1-7), ACE2, ANG I, ANG II, ACE
  • Vascular and viral regulation: ARG1, ROCK1, ROCK2
  • TGFβ Signaling Pathway: TGFβ1, TGFβ2, TGFβ3, Activin B, Follistatin, GDF-15
  • Hypoxia: Hif-1α
  • Mitochondria function and energy production: DRP1, PINK-1, SIRT1
  • Innate Immune Response: IFNα, IFNβ, IFNγ, IFNL1, PGE2, Nagalase
  • Autophagy: ATG13Blood Brain Barrier (BBB) integrity: NEFL, S100B
  • Neurotransmitter: SerotoninNitric Oxide & Oxidative Stress: BH2, BH4
  • Exercise Intolerance: TWEAK
Find more information and research on these biomarkers here.

Relating disease profiles to molecular mechanisms
Our research combines detailed patient questionnaires with molecular data to identify mechanisms driving different symptom patterns in ME/CFS and Long COVID.
We will apply Machine Learning (ML) to identify underlying mechanisms that associate with certain symptom clusters or disease profiles.

Classifying individual disease patterns.
ME/CFS and Long COVID manifest differently across individuals. Understanding each person's specific disease profile is a critical step currently missing from how we treat these chronic conditions.
We will analyse treatment responses vs patient classification and molecular signatures, allowing clinicians to better understand their patients.

Advancing research towards biomarkers and treatments
By combining detailed patient classification with molecular data, we aim to identify clear subgroups (e.g. POTS, NeuroCOVID, Muscle Weakness). This will enable better research design for both disease classification and future treatments.
We will provide subgroup classification data to partner clinical trials to improve patient recruitment and identification of responder subgroups, supporting increased Long COVID trial success rates.
Our data will also be used to identify new therapeutic targets for drug repurposing and development.