Interleukin-6 Is a Potential Biomarker for Severe Pandemic H1N1 Influenza A Infection
Bibliographic record
Abstract
Pandemic H1N1 influenza A (H1N1pdm) is currently a dominant circulating influenza strain worldwide. Severe cases of H1N1pdm infection are characterized by prolonged activation of the immune response, yet the specific role of inflammatory mediators in disease is poorly understood. The inflammatory cytokine IL-6 has been implicated in both seasonal and severe pandemic H1N1 influenza A (H1N1pdm) infection. Here, we investigated the role of IL-6 in severe H1N1pdm infection. We found IL-6 to be an important feature of the host response in both humans and mice infected with H1N1pdm. Elevated levels of IL-6 were associated with severe disease in patients hospitalized with H1N1pdm infection. Notably, serum IL-6 levels associated strongly with the requirement of critical care admission and were predictive of fatal outcome. In C57BL/6J, BALB/cJ, and B6129SF2/J mice, infection with A/Mexico/4108/2009 (H1N1pdm) consistently triggered severe disease and increased IL-6 levels in both lung and serum. Furthermore, in our lethal C57BL/6J mouse model of H1N1pdm infection, global gene expression analysis indicated a pronounced IL-6 associated inflammatory response. Subsequently, we examined disease and outcome in IL-6 deficient mice infected with H1N1pdm. No significant differences in survival, weight loss, viral load, or pathology were observed between IL-6 deficient and wild-type mice following infection. Taken together, our findings suggest IL-6 may be a potential disease severity biomarker, but may not be a suitable therapeutic target in cases of severe H1N1pdm infection due to our mouse data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".