A Molecular network approach reveals shared cellular and molecular signatures between chronic fatigue syndrome and other fatiguing illnesses
| Autor: | Miriam Merad, Alexander W. Charney, Scott R. Tyler, Shreya Chandrasekar, Eric E. Schadt, Bojan Losic, Wenhui Wang, Irene Font Peradejordi, Carmen Argmann, Christian D. Becker, Roman Kosoy, Gabriel E. Hoffman, Noam D. Beckmann, Edgar Gonzalez-Kozlova, Zeynep H. Gümüş, Phillip H. Comella, Jingjing Qi, Jun Zhu, Andrew Kasarskis, Manishkumar Patel, Mayte Suárez-Fariñas, Seunghee Kim-Schulze |
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| Rok vydání: | 2021 |
| Předmět: |
musculoskeletal diseases
Coronavirus disease 2019 (COVID-19) business.industry Cell type specific virus diseases Master regulator Context (language use) Disease medicine.disease Article nervous system diseases Molecular network Immunology Etiology Chronic fatigue syndrome medicine business human activities |
| Zdroj: | medRxiv |
| Popis: | IntroThe molecular mechanisms of chronic fatigue syndrome (CFS, or Myalgic encephalomyelitis), a disease defined by extreme, long-term fatigue, remain largely uncharacterized, and presently no molecular diagnostic test and no specific treatments exist to diagnose and treat CFS patients. While CFS has historically had an estimated prevalence of 0.1-0.5% [1], concerns of a “long hauler” version of Coronavirus disease 2019 (COVID-19) that symptomatically overlaps CFS to a significant degree(Supplemental Table-1)and appears to occur in 10% of COVID-19 patients[2], has raised concerns of a larger spike in CFS [3]. Here, we established molecular signatures of CFS and a corresponding network-based disease context from RNA-sequencing data generated on whole blood and FACs sorted specific peripheral blood mononuclear cells (PBMCs) isolated from CFS cases and non-CFS controls. The immune cell type specific molecular signatures of CFS we identified, overlapped molecular signatures from other fatiguing illnesses, demonstrating a common molecular etiology. Further, after constructing a probabilistic causal model of the CFS gene expression data, we identified master regulator genes modulating network states associated with CFS, suggesting potential therapeutic targets for CFS. |
| Databáze: | OpenAIRE |
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