ArticleInformatics in medicine unlocked2022
Identification of differentially expressed genes and their major pathways among the patient with COVID-19, cystic fibrosis, and chronic kidney disease.
Article in Informatics in medicine unlocked, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.Bioinformatics (Oxford, England) · 2026Article
- DENetwork unveils non-differentially expressed genes with functional relevance across conditions through information flow perturbation.Nucleic acids research · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The SARS-CoV-2 virus causes Coronavirus disease, an infectious disease. The majority of people who are infected with this virus will have mild to moderate respiratory symptoms. Multiple studies have proved that there is a substantial pathophysiological link between COVID-19 disease and patients having comorbidities such as cystic fibrosis and chronic kidney disease. In this study, we attempted to identify differentially expressed genes as well as genes that intersected among them in order to comprehend their compatibility. Gene expression profiling indicated that 849 genes were mutually exclusive and functional analysis was done within the context of gene ontology and key pathways involvement. Three genes (PRPF31, FOXN2, and RIOK3) were commonly upregulated in the analysed datasets of three disease categories. These genes could be potential biomarkers for patients with COVID-19 and cystic fibrosis, and COVID-19 and chronic kidney disease. Further extensive analyses have been performed to describe how these genes are regulated by various transcription factors and microRNAs. Then, our analyses revealed six hub genes (PRPF31, FOXN2, RIOK3, UBC, HNF4A, and ELAVL). As they were involved in the interaction between COVID-19 and the patient with CF and CKD, they could help researchers identify potential therapeutic molecules. Some drugs have been predicted based on the upregulated genes, which may have a significant impact on reducing the burden of these diseases in the future.
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.