Human genetic and immunological determinants of SARS-CoV-2 infection and multisystem inflammatory syndrome in children
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces pneumonia and acute respiratory failure in coronavirus disease 2019 (COVID-19) patients with inborn errors of immunity to type I interferon (IFN-I). The impact of SARS-CoV-2 infection varies widely, ranging from mild respiratory symptoms to life-threatening illness and organ failure, with a higher incidence in men than in women. Approximately 3-5% of critical COVID-19 patients under 60 and a smaller percentage of elderly patients exhibit genetic defects in IFN-I production, including X-chromosome-linked TLR7 and autosomal TLR3 deficiencies. Around 15-20% of cases over 70 years old, and a smaller percentage of younger patients, present with preexisting autoantibodies neutralizing type I interferons. Additionally, innate errors affecting the control of the response to type I interferon have been associated with pediatric multisystem inflammatory syndrome (MIS-C). Several studies have described rare errors of immunity, such as XIAP deficiency, CYBB, SOCS1, OAS1/2, and RNASEL, as underlying factors in MIS-C susceptibility. However, further investigations in expanded patient cohorts are needed to validate these findings and pave the way for new genetic approaches to MIS-C. This review aims to present recent evidence from the scientific literature on genetic and immunological abnormalities predisposing individuals to critical SARS-CoV-2 infection through IFN-I. We will also discuss multisystem inflammatory syndrome in children (MIS-C). Understanding the immunological mechanisms and pathogenesis of severe COVID-19 may inform personalized patient care and population protection strategies against future serious viral infections.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".