ArticleGenes2025
circRNA Signatures Distinguishing COVID-19 Outcomes and Acute Respiratory Distress Syndrome: A Longitudinal, Two-Timepoint, Precision-Weighted Analysis of a Public RNA-Seq Cohort.
Article in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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
1 citing paper in PubMed.
- The regulatory mechanisms and translational applications of non-coding RNA in SARS-CoV-2 infection-related cardiovascular pathology.Frontiers in cardiovascular medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
backgroundAlthough circular RNAs are increasingly implicated in host responses, their longitudinal behaviors to predict outcomes in severe COVID-19 remain unclear. The purpose of this study is to distinguish the circRNA signature associated with COVID-19 outcome.
methodPublic total RNA-seq data from GEO (GSE273149) were used to assess circRNA differences among COVID-19 non-survivors, COVID-19 survivors, and patients with acute respiratory distress syndrome (ARDS) serving as severity-matched disease controls at two timepoints: Early (Day 3) and Late (Days 7 to 10). Differential expression was assessed after quality filtering, with the results reported as significant (FDR < 0.05) or suggestive (0.05-0.10); |log
resultsA distinction between non-survivors and survivors was observed, with nine significant and four suggestive candidates identified in the combined analysis; in addition, some candidates indicated a difference between survivors and ARDS controls. Early and Late effects primarily occurred in the same direction, and several circRNAs that were borderline at one timepoint became significant when the two timepoints were combined.
conclusionThis time-resolved, precision-weighted analysis of public RNA-seq data reveals stable circRNA differences between key clinical groups (patients with severe COVID-19 and those with ARDS), improving detection and interpretability relative to single-timepoint tests and yielding a concise set of candidates suitable for mechanistic follow-up and potential biomarker development.
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