ArticleJournal of multidisciplinary healthcare2022
The m7G Modification Level and Immune Infiltration Characteristics in Patients with COVID-19.
Article in Journal of multidisciplinary healthcare, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Coronavirus NSP14 drives internal m7G modification to rewire host splicing and promote viral replication.Nucleic acids research · 2026Article
- Integrated analysis of bulk RNA and single-cell RNA sequencing data reveals potential biomarkers and immune infiltrates associated with N7-methylguanosine in osteoarthritis.International journal of surgery (London, England) · 2026Article
- Deciphering N7-methylguanosine-driven immune dysregulation in unexplained recurrent spontaneous abortion based on transcriptome data and experimental validation.European journal of medical research · 2025Article
- RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease.Scientific reports · 2025Article
- m7G gene expression and disease risk model construction in patients with herpes zoster.Scientific reports · 2025Article
- Article
- Role of the epitranscriptome in viral infections: beneficial or detrimental?Memorias do Instituto Oswaldo Cruz · 2025Review
- Emerging influence of RNA post-transcriptional modifications in the synovial homeostasis of rheumatoid arthritis.Frontiers in immunology · 2024Review
- Identification and prediction of m7G-related Alzheimer's disease subtypes: insights from immune infiltration and machine learning models.Frontiers in aging neuroscience · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: The 7-methylguanosine (m7G)-related genes were used to identify the clinical severity and prognosis of patients with coronavirus disease 2019 (COVID-19) and to identify possible therapeutic targets. Patients and Methods: The GSE157103 dataset provides the transcriptional spectrum and clinical information required to analyze the expression of m7G-related genes and the disease subtypes. R language was applied for immune infiltration analysis, functional enrichment analysis, and nomogram model construction. Results: Most m7G-related genes were up-regulated in COVID-19 and were closely related to immune cell infiltration. Disease subtypes were grouped using a clustering algorithm. It was found that the m7G-cluster B was associated with higher immune infiltration, lower mechanical ventilation, lower intensive care unit (ICU) status, higher ventilator-free days, and lower m7G scores. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that differentially expressed genes (DEGs) between m7G-cluster A and B were enriched in viral infection and immune-related aspects, including COVID-19 infection; Th17, Th1, and Th2 cell differentiation, and human T-cell leukemia virus 1 infection. Finally, through machine learning, six disease characteristic genes, NUDT4B, IFIT5, LARP1, EIF4E, LSM1, and NUDT4, were screened and used to develop a nomogram model to estimate disease risk. Conclusion: The expression of most m7G genes was higher in COVID-19 patients compared with that in non-COVID-19 patients. The m7G-cluster B showed higher immune infiltration and milder symptoms. The predictive nomogram based on the six m7G genes can be used to accurately assess risk.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.