Morris, Matthew C, Cooney, Katherine E, Sedghamiz, Hooman et al. · Clinical therapeutics · 2019 · DOI
This study used computer modeling to understand how hormones and immune system chemicals become unbalanced in ME/CFS. Researchers measured 17 immune markers in women with ME/CFS before, during, and after exercise, then created detailed mathematical models to predict what other hormones and chemicals might also be out of balance. The models suggested that two existing drugs (rintatolimod and rituximab) might help different subgroups of patients, depending on their specific hormone and immune profiles.
This study provides a mechanistic framework suggesting that ME/CFS involves dysregulated cross-talk between hormonal and immune systems, which could explain why single-target therapies often fail and why patients are heterogeneous. Identifying patient subtypes based on specific endocrine-immune signatures may enable precision medicine approaches and help predict which treatments might benefit which patients.
This computational modeling study does not prove that the predicted endocrine abnormalities actually occur in patients, nor does it establish causal mechanisms. The model predictions require experimental validation through direct measurement of the unmeasured hormones and prospective clinical trials; the inferred patient subtypes and treatment responses remain theoretical until tested in controlled studies.
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
The first block is for the primary paper and is the citation you should use in research work. The atlas-snapshot line only applies if you are specifically referring to this atlas’s reading of the paper on the date shown.
Primary citation
Morris, Matthew C, Cooney, Katherine E, Sedghamiz, Hooman, Abreu, Maria, Collado, Fanny, Balbin, Elizabeth G, et al. (2019). Leveraging Prior Knowledge of Endocrine Immune Regulation in the Therapeutically Relevant Phenotyping of Women With Chronic Fatigue Syndrome.. Clinical therapeutics. https://doi.org/10.1016/j.clinthera.2019.03.002
BibTeX
@article{mecfsatlas-morris-2019-leveraging-prior,
author = {Morris, Matthew C and Cooney, Katherine E and Sedghamiz, Hooman and Abreu, Maria and Collado, Fanny and Balbin, Elizabeth G and Craddock, Travis J A and Klimas, Nancy G and Broderick, Gordon and Fletcher, Mary Ann},
title = {Leveraging Prior Knowledge of Endocrine Immune Regulation in the Therapeutically Relevant Phenotyping of Women With Chronic Fatigue Syndrome.},
journal = {Clinical therapeutics},
year = {2019},
doi = {10.1016/j.clinthera.2019.03.002},
note = {PubMed: 30929860},
url = {https://www.mecfsatlas.com/evidence/morris-2019-leveraging-prior},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-30. https://www.mecfsatlas.com/evidence/morris-2019-leveraging-prior
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