Metagenomic Analysis of Blood Virome in Ischemic Stroke Reveals an Increase in Herpesvirus Transcripts and Host Immune Activation
Bibliographic record
Abstract
BACKGROUND: Viral infections may influence stroke pathophysiology. Several infections have been linked to increased risk of stroke, however our understanding of these viral interactions with immune and host tissue is limited. We performed a transcriptomic analysis of the blood virome following ischemic stroke to study these interactions. METHODS: Viruses were measured by RNA sequencing of blood from 37 patients with ischemic stroke and 32 matched controls. RNA reads are aligned against a human reference genome, as well as a comprehensive database of human virus genomes. Host gene expression following stroke is examined in relation to the presence of viral transcripts. RESULTS: Viral RNAs were detected in the blood samples of both ischemic stroke and control groups. Viral reads with a prevalence > 3% and raw counts > 2 were from a total of 6 viral families. This included several human herpesviruses (HHVs), adenoviruses, and papillomaviruses, as well as human pegivirus, respiratory syncytial virus, and human endogenous retrovirus K (HERV-K). Combined, counts from HHVs were higher in stroke compared to control by a fold change of 2.13. Coinfection with multiple HHVs was more common in stroke, with a 1.23 fold increase in the number of detected herpesviruses. Reads from two viral genes were increased in stroke, UL95 from cytomegalovirus (CMV), and EBNA2 from Epstein-Barr virus (EBV). Genes associated with stroke, including APOE, C3, PDGF, and CXCL2 were differentially expressed in stroke samples which contained high counts of one or both of UL95 and EBNA2. CONCLUSION: Viral RNAs from multiple families can be detected within the human blood virome. HHV transcripts were the most abundant of viral RNAs detected. Among stroke patients, HHV transcripts were more prevalent, with higher counts, and indicated a higher rate of coinfection with multiple HHV species. Expression of the EBV gene EBNA2 and the CMV gene UL95 may relate to changes in immune gene expression following stroke. Further evaluation is needed to determine the effects that the human virome have on stroke risk, immune response to stroke, and long-term outcome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".