Lv, Yongbiao, Zhang, Tian, Cai, Junxiang et al. · Frontiers in immunology · 2022 · DOI
Researchers compared the genes involved in Long COVID (lasting symptoms after COVID-19 infection) and ME/CFS to see if they share common biological causes. They found 9 genes that appear in both conditions and identified five key proteins that may be driving the shared symptoms. The study suggests these conditions may have overlapping mechanisms, pointing toward potential new treatments worth testing in future research.
This study provides evidence that Long COVID and ME/CFS may share underlying biological mechanisms, which could explain why many COVID-19 patients develop ME/CFS-like symptoms. Identifying common molecular pathways offers a foundation for developing treatments that could benefit both conditions, and the predicted drug candidates provide specific leads for experimental testing.
This computational study does not prove that the identified genes actually cause Long COVID or ME/CFS—it identifies statistical associations and predicts pathways based on existing data. The predicted drug candidates have not been tested in laboratory or clinical settings, so efficacy remains entirely theoretical. The findings do not establish whether Long COVID and ME/CFS are identical conditions or merely share some overlapping features.
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
Lv, Yongbiao, Zhang, Tian, Cai, Junxiang, Huang, Chushuan, Zhan, Shaofeng, & Liu, Jianbo (2022). Bioinformatics and systems biology approach to identify the pathogenetic link of Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.. Frontiers in immunology. https://doi.org/10.3389/fimmu.2022.952987
BibTeX
@article{mecfsatlas-lv-2022-bioinformatics-systems,
author = {Lv, Yongbiao and Zhang, Tian and Cai, Junxiang and Huang, Chushuan and Zhan, Shaofeng and Liu, Jianbo},
title = {Bioinformatics and systems biology approach to identify the pathogenetic link of Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.},
journal = {Frontiers in immunology},
year = {2022},
doi = {10.3389/fimmu.2022.952987},
note = {PubMed: 36189286},
url = {https://www.mecfsatlas.com/evidence/lv-2022-bioinformatics-systems},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-30. https://www.mecfsatlas.com/evidence/lv-2022-bioinformatics-systems
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