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pmid:41595454

circRNA Signatures Distinguishing COVID-19 Outcomes and Acute Respiratory Distress Syndrome: A Longitudinal, Two-Timepoint, Precision-Weighted Analysis of a Public RNA-Seq Cohort.

Alawi Habara

Genes · 2025 doi:10.3390/genes17010034

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
circRNA Signatures Distinguishing COVID-19 Outcomes and Acute Respiratory Distress Syndrome: A Longitudinal, Two-Timepoint, Precision-Weighted Analysis of a Public RNA-Seq Cohort.
doi
10.3390/genes17010034
pmid
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Alawi Habara
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Genes
year
2025
abstract
BACKGROUND: Although 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. METHOD: Public 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); |log2FC| ≥ 1 was used as a guide for interpretation. Early and Late effects were combined using a two-timepoint, precision-weighted approach to prioritize time-consistent signals. RESULTS: A 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. CONCLUSION: This 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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From each timepoint, the log2 fold change and its standard error were obtained. To emphasize effects that were stable across time, the two timepoint estimates were combined via fixed-effects, inverse-variance (precision-weighted) summarization, yielding a single effect estimate and a p-value for each circRNA.
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From each timepoint, the log2 fold change and its standard error were obtained. To emphasize effects that were stable across time, the two timepoint estimates were combined via fixed-effects, inverse-variance (precision-weighted) summarization, yielding a single effect estimate and a p-value for each circRNA.
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The combined two-timepoint precision-weighted analysis identified nine significant and four suggestive circRNA candidates distinguishing COVID-19 non-survivors from survivors.
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A 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.
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