What the research found

Researchers measured 48 different immune signalling molecules (cytokines) in blood samples from over 200 women—roughly half with PMOS and half without—using a multiplexed laboratory technique. They found that 14 cytokines were consistently elevated in the PMOS group compared to healthy controls, with IL-16 showing the strongest association overall.

When they looked specifically at the two main PMOS phenotypes, different cytokine patterns emerged. Phenotype A showed a distinctive signature centred on IL-16, CTACK, and IP-10, while phenotype B was characterised by IL-18, M-CSF, and HGF. The data also suggested these cytokines don't act in isolation: in women with PMOS, several pairs of cytokines were tightly correlated, implying they're regulated together as part of a coordinated inflammatory process rather than random dysregulation.

Why it matters for you

PMOS drives chronic inflammation, and MyKine users increasingly track inflammatory biomarkers—CRP, ESR, or specific cytokines—as part of optimising metabolic health and recovery. This work suggests that the inflammatory landscape in PMOS isn't uniform. If you have PMOS and track cytokines, knowing whether your profile resembles phenotype A or B could eventually help predict which metabolic or immune interventions (dietary, supplement, hormonal, or training-based) might be most effective for your variant.

The identification of phenotype-specific cytokine signatures also hints at why one-size-fits-all PMOS protocols often disappoint. Two people with the same diagnosis might have fundamentally different immune drivers, which would logically demand different approaches to training intensity, recovery modulation, supplement strategy, or TRT timing.

Right now, this is a cataloguing study—not yet actionable clinical guidance—but it reinforces the value of detailed biomarker stratification before designing your protocol.

Caveats

• Cross-sectional design: Shows association, not causation or mechanism. These cytokines may be consequences rather than drivers of PMOS.
• No validation cohort mentioned: Results haven't been tested in a separate population yet.
• Phenotype definitions unclear in abstract: The criteria distinguishing A from B phenotypes aren't specified, limiting ability to self-assess.
• Clinical utility unknown: Having a cytokine signature doesn't yet tell you what to do differently.
• Single timepoint: No information on whether these profiles are stable or fluctuate across menstrual cycles.