ArticleFrontiers in neurology2023
Identification of key genes as potential diagnostic and therapeutic targets for comorbidity of myasthenia gravis and COVID-19.
Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Surgical management of pineal region tumors in Italy: a SINch (SINch®) National Survey with systematic review.Neurosurgical review · 2026Pooled it
- MicroRNAs as Diagnostic Biomarkers of Myasthenia Gravis: A Systematic Review and Meta-Analysis.Cellular and molecular neurobiology · 2025Pooled it
- Mapping global research landscape and trends in magnetic resonance imaging applications for primary trigeminal neuralgia: a bibliometric analysis.Neurosurgical review · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Myasthenia gravis (MG) is a chronic autoimmune neuromuscular disorder. Coronavirus disease 2019 (COVID-19) has a significant impact on the health and quality of life of MG patients and may even trigger the onset of MG in some cases. With the worldwide development of the COVID-19 vaccination, several new-onset MG cases and exacerbations following the COVID-19 vaccines have been acknowledged. The potential link between myasthenia gravis (MG) and COVID-19 has prompted the need for further investigation into the underlying molecular mechanism. Methods and results: The differential expression analysis identified six differentially expressed genes (DEGs) shared by myasthenia gravis (MG) and COVID-19, namely SAMD9, PLEK, GZMB, JUNB, NR4A1, and NR1D1. The relationship between the six common genes and immune cells was investigated in the COVID-19 dataset. The predictive value of the shared genes was assessed and a nomogram was constructed using machine learning algorithms. The regulatory miRNAs, transcription factors and small molecular drugs were predicted, and the molecular docking was carried out by AutoDock. Discussion: We have identified six common DEGs of MG and COVID-19 and explored their immunological effects and regulatory mechanisms. The result may provide new insights for further mechanism research.
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