ArticleJournal of inflammation research2024
Integrated Bioinformatics Exploration and Preliminary Clinical Verification for the Identification of Crucial Biomarkers in Severe Cases of COVID-19.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 9 citations in OpenAlex.
- Association of ANXA3 methylation with clinical outcomes of glucocorticoid therapy in patients with hepatitis B virus-related acute-on-chronic liver failure.Scientific reports · 2026Article
- Integrated miR-omics and proteomics reveal the regulatory role of miR in protein networks associated with COVID-19 disease progression.Frontiers in immunology · 2026Article
- Analysis of the Specific Expression Profile of Immune Cells in Infants and Young Children Infected with RSV and Construction of a Disease Prediction Model.Tropical medicine and infectious disease · 2025Article
- Article
- Low-dose pro-resolving mediators temporally reset the resolution response to microbial inflammation.Molecular medicine (Cambridge, Mass.) · 2024Article
- Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19.Heliyon · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Coronavirus disease 2019 (COVID-19) is a respiratory infectious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of this study is to identify reliable and accurate biomarkers for the early stratification of disease severity, a crucial aspect that is currently lacking for the impending phases of the next COVID-19 pandemic. Methods: In this study, we identified important module and hub genes related to clinical severe COVID-19 using differentially expressed genes (DEGs) screening combing weighted gene co-expression network analysis (WGCNA) in dataset GSE213313. We further screened and confirmed these hub genes in another two new independent datasets (GSE172114 and GSE157103). In order to evaluate these key genes' stability and robustness for diagnosing or predicting the progression of illness, we used RT-PCR validation of selected genes in blood samples obtained from hospitalized COVID-19 patients. Results: A total of 968 and 52 DEGs were identified between COVID-19 patients and normal people, critical and non-critical patients, respectively. Then, using WGCNA, 10 modules were constructed. Among them, the blue module positively associated with clinic disease severity of COVID-19. From overlapped section between DEGs and blue module, 12 intersected common differential genes were obtained. Subsequently, these hub genes were validated in another two new independent datasets as well and 9 genes that overlapped showed a highly correlation with disease severity. Finally, the mRNA expression levels of these hub genes were tested in blood samples from COVID-19 patients. In severe cases, there was increased expression of Conclusion: Using comprehensive bioinformatical analysis and the validation of clinical samples, we identified four major candidate genes,
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.