ArticleJournal of cardiovascular development and disease2022
Developing a Novel Immune-Related Seven-Gene Signature and Immune Infiltration Pattern in Patients with COVID-19 and Cardiovascular Disease.
Article in Journal of cardiovascular development and disease, 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, 5 citations in OpenAlex.
- Involvement of formyl peptide receptor 2 in canine coronavirus infection: in vitro and in Silico approaches.Virology journal · 2025Article
- Landscape of molecular crosstalk between SARS-CoV-2 infection and cardiovascular diseases: emphasis on mitochondrial dysfunction and immune-inflammation.Journal of translational medicine · 2023Article
- Integrated bioinformatics analysis identifies shared immune changes between ischemic stroke and COVID 19.Frontiers in immunology · 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 at 1 institution in 1 country.
Funding
Abstract
backgroundpatients with pre-existence of cardiovascular disease (CVD) are vulnerable to coronavirus disease 2019 (COVID-19), and COVID-19 will cause long-term burden of CVD. However, the common pathogenic mechanisms are not fully elucidated. More detailed knowledge of linking biological molecules and the role of immune signature would allow more valuable and specific clinical management.
methodsthe gene expression profiles of CVD and COVID-19 were retrieved from the GEO database. Common differentially expressed genes (DEGs) were screened with the Limma R package and the WGCNA algorithm, and then functional enrichment analysis, protein-protein interaction network, hub genes, and small therapeutic molecules analyses were performed. The hub immune-related genes (HIRGs) were intersected, and their associations with immune cells, expressional correlation, evaluated performance, and potential signal pathways were further investigated.
resultsIn total, 57 common DEGs were identified as a shared transcriptional signature between CVD and COVID-19, and 12 hub genes were screened using five topological algorithms. There are common altered immune responses in the response of these two diseases, and seven HIRGs, including C5AR1, MMP9, CYBB, FPR2, CSF1R, TLR2, and TLR4, were identified, with positive correlation to altered macrophages and neutrophils. Nine small molecular agents (SMAs) were detected as promising therapeutic drugs. These seven HIRGs mainly participated in the inflammatory immune response through activation of Il2 stat5 signaling and Tnfa signaling via nfκb pathways, and ROC curves confirmed their good discriminatory capacity in the two diseases.
conclusionsthis study established the co-expression network and identified a new immune-related seven-gene signature as therapeutic targets, which may provide new insights into pathogenic mechanisms and novel clinical management strategies.
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.