Thrombotic risk after acute COVID-19 has been reported to extend beyond the phase of clinical illness, including in nonhospitalized patients. This observation raises the possibility that thrombo-inflammatory biology can persist during recovery. Distinguishing infection-associated blood gene-expression changes from normal inter-individual variability and time-related transcriptional drift requires longitudinal sampling with pre-infection baselines.
This study aimed to define coordinated, time-resolved whole-blood transcriptomic programs during SARS-CoV-2 convalescence using within-person comparisons before and after infection, with COVID-19‑naïve controls sampled across matched timepoints for comparison.
Adults were enrolled with longitudinal specimen collection at three defined timepoints: before SARS-CoV-2 infection (T0), approximately 3 months after infection (T1), and approximately 6 months after infection (T2). A group of COVID-19‑naïve control participants was sampled at matched intervals to capture time-dependent gene-expression changes not related to SARS-CoV-2 exposure.
Control participants’ COVID-19‑naïve status was confirmed using a multiplex anti-nucleocapsid IgG assay that spanned multiple variant antigens, ensuring that comparisons prioritized infection-associated signals rather than previously undetected infections.
Whole-blood RNA was collected in PAXgene tubes and subjected to RNA sequencing. Differential expression analysis used DESeq2 with models that included both time point and participant to leverage within-person longitudinal comparisons.
To focus on transcriptional changes attributable to SARS-CoV-2 infection, the investigators first identified genes whose expression changed over time in the COVID-19‑naïve control group; those control-associated genes were excluded from subsequent comparisons between COVID-19 timepoints.
Pathway-level assessment used pre-ranked Gene Set Enrichment Analysis (GSEA) with gene sets from MSigDB. Resulting pathway-level enrichments were clustered using aPEAR to define coordinated programs of transcriptional activity.
After excluding genes that varied over time in controls, comparisons of convalescent samples to pre-infection baselines revealed marked transcriptional remodeling associated with SARS-CoV-2 infection. Specifically, T1 (≈3 months) versus T0 showed 782 differentially expressed genes, and T2 (≈6 months) versus T0 showed 655 differentially expressed genes, using a p < 0.05 threshold.
These gene-level changes translated into persistent pathway-level alterations, indicating that convalescence is accompanied by coordinated shifts in blood transcriptomic programs rather than isolated, transient gene changes.
Pathway analyses demonstrated enrichment of both interferon-α and interferon-γ signatures at T1 and at T2. The authors identified a core set of interferon-associated genes that remained elevated across the convalescent period, detectable up to 6 months after acute infection.
The persistence of interferon-related transcriptional programs in whole blood indicates continued engagement of host immune-defense pathways well beyond resolution of acute illness. The study emphasizes that these signatures were observed after controlling for temporal changes seen in uninfected controls, strengthening the association with SARS-CoV-2 exposure.
Sustained activation of interferon-linked immune programs provides a mechanistic basis for prolonged post-infectious immune activation. Because interferon signaling intersects with pathways involved in inflammation and coagulation, the authors propose that these durable blood signatures may contribute to extended thromboinflammatory risk after COVID-19.
This model is consistent with clinical reports of increased thrombotic events and altered platelet and coagulation biology in the months following SARS-CoV-2 infection, though the study itself reports transcriptomic associations rather than direct clinical outcomes.
The abstract reports study design, sampling intervals, assay platforms, analytic approach, gene counts, and pathway findings. Details that were not reported in the abstract and therefore cannot be inferred here include specific participant numbers, demographic breakdowns, clinical severity of acute infections, exact gene lists or effect sizes, statistical adjustment methods beyond the DESeq2 model specification, and any direct clinical correlations between transcriptomic signatures and thrombotic events. The abstract also does not report longitudinal protein-level or functional assays to corroborate transcriptomic findings.
Using longitudinal within-person comparisons with pre-infection baselines and matched COVID-19‑naïve controls, the study found durable whole-blood transcriptional remodeling after SARS-CoV-2 infection. Enrichment of interferon-α and interferon-γ programs persisted at ~3 and ~6 months post-infection, with a core interferon-associated gene set remaining elevated across convalescence. These sustained immune-defense signatures support a model of prolonged post-infectious immune activation that may underlie extended thromboinflammatory risk observed after COVID-19.
Keywords provided in the source include COVID‑19, Interferons, RNA‑Seq, and Transcriptome.