Murga, Iñigo, Aranburu, Larraitz, Gargiulo, Pascual A et al. · Frontiers in psychiatry · 2021 · DOI
This study examined 84 ME/CFS patients and 22 healthy controls using questionnaires to measure fatigue, pain, sleep quality, heart rate problems, thinking difficulties, mood, and other symptoms. Researchers used statistical clustering to group patients into five distinct subtypes based on their symptom patterns. The findings suggest that ME/CFS is not one-size-fits-all—some patients have high anxiety and depression without fibromyalgia, while others have fibromyalgia combined with heart rate regulation problems, hormone imbalances, or immune issues.
ME/CFS is clinically heterogeneous, and identifying objective phenotypes may enable personalized treatment approaches and help clarify why patients respond differently to interventions. This phenotyping approach also provides a framework for understanding Long-COVID fatigue, potentially benefiting the growing population of post-infection patients. Demonstrating measurable, distinct symptom profiles validates the biological complexity of ME/CFS and supports the need for subtype-specific research.
This study does not establish causation—it identifies associations between symptoms, not mechanisms. The cross-sectional design captures patients at one time point, so it cannot determine whether phenotypes are stable over time or if they represent disease stages. The relatively small cohort (n=84) limits generalizability, and the findings require replication in larger, diverse populations before clinical application.
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
Murga, Iñigo, Aranburu, Larraitz, Gargiulo, Pascual A, Gómez Esteban, Juan Carlos, & Lafuente, José-Vicente (2021). Clinical Heterogeneity in ME/CFS. A Way to Understand Long-COVID19 Fatigue.. Frontiers in psychiatry. https://doi.org/10.3389/fpsyt.2021.735784
BibTeX
@article{mecfsatlas-murga-2021-clinical-heterogeneity,
author = {Murga, Iñigo and Aranburu, Larraitz and Gargiulo, Pascual A and Gómez Esteban, Juan Carlos and Lafuente, José-Vicente},
title = {Clinical Heterogeneity in ME/CFS. A Way to Understand Long-COVID19 Fatigue.},
journal = {Frontiers in psychiatry},
year = {2021},
doi = {10.3389/fpsyt.2021.735784},
note = {PubMed: 34707521},
url = {https://www.mecfsatlas.com/evidence/murga-2021-clinical-heterogeneity},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-28. https://www.mecfsatlas.com/evidence/murga-2021-clinical-heterogeneity
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