Taylor, Krystyna, Pearson, Matthew, Das, Sayoni et al. · Journal of translational medicine · 2023 · DOI
Researchers studied the genetic differences between people with long COVID to understand why some develop severe symptoms while others mainly experience extreme fatigue. They found that certain genetic variations, especially in genes related to brain function and metabolism, may influence how the disease develops. Importantly, they discovered that some of the same genetic patterns appear in both long COVID and ME/CFS patients, suggesting these conditions may share similar underlying biological mechanisms.
This study provides critical evidence that ME/CFS and long COVID may share common genetic foundations, validating the biological plausibility of their phenotypic similarities and suggesting that therapeutic discoveries in one condition could benefit patients with the other. The identification of druggable targets offers concrete avenues for developing treatments for both conditions, which currently lack approved therapies.
This study does not establish causation—the identified genetic variants are associated with disease but do not prove they cause long COVID or ME/CFS. The findings are observational and mechanistic; they do not demonstrate that proposed drugs (like TLR4 antagonists) will actually be effective in treating patients. Additionally, results from a single cohort require independent validation 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
Taylor, Krystyna, Pearson, Matthew, Das, Sayoni, Sardell, Jason, Chocian, Karolina, & Gardner, Steve (2023). Genetic risk factors for severe and fatigue dominant long COVID and commonalities with ME/CFS identified by combinatorial analysis.. Journal of translational medicine. https://doi.org/10.1186/s12967-023-04588-4
BibTeX
@article{mecfsatlas-taylor-2023-genetic-risk,
author = {Taylor, Krystyna and Pearson, Matthew and Das, Sayoni and Sardell, Jason and Chocian, Karolina and Gardner, Steve},
title = {Genetic risk factors for severe and fatigue dominant long COVID and commonalities with ME/CFS identified by combinatorial analysis.},
journal = {Journal of translational medicine},
year = {2023},
doi = {10.1186/s12967-023-04588-4},
note = {PubMed: 37915075},
url = {https://www.mecfsatlas.com/evidence/taylor-2023-genetic-risk},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-28. https://www.mecfsatlas.com/evidence/taylor-2023-genetic-risk
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