Distinct circulating autoantibodies are associated with COVID-19 hospitalization and SARS-CoV-2 neutralization activity
Bibliographic record
Abstract
SARS-CoV-2 infection disrupts the host's immune system, altering autoimmune responses. This study investigated host autoreactivities in SARS-CoV-2 infections, their association with severe COVID-19, and the neutralizing antibody response. Circulating autoantibodies were detected in convalescent serum samples from unvaccinated SARS-CoV-2-infected patients. Clustering, correlation analysis, principal component analysis, and neural network modeling were used to explore the relationship between autoantibodies, hospitalization, and SARS-CoV-2 neutralization. The presence of one autoantibody correlated with the detection of multiple others. Anti-IFNα antibodies were associated with elevated levels of anti-ENAs (extractable-nuclear antigen) but not with clinical outcome. COVID-19 hospitalization was significantly associated with the collective expression of autoantibodies targeting three ENAs: SSA/Ro52, Jo-1, and RNP. In contrast, autoantibodies targeting RNP/Sm, PCNA, Scl-70, and PL-12 were strongly associated with SARS-CoV-2 neutralization. In summary, this study has identified self-antigens targeted in hospitalized COVID-19 patients and highlights a novel association between the autoantibody response and the antiviral humoral response.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".