Maternal and neonatal immune response to SARS-CoV-2, IgG transplacental transfer and cytokine profile
Bibliographic record
Abstract
SARS-CoV-2 infected pregnant women are at increased risk of severe COVID-19 than non-pregnant women and have a higher risk of adverse pregnancy outcomes like intrauterine/fetal distress and preterm birth. However, little is known about the impact of SARS-CoV-2 infection on maternal and neonatal immunological profiles. In this study, we investigated the inflammatory and humoral responses to SARS-CoV-2 in maternal and cord blood paired samples. Thirty-six pregnant women were recruited at delivery at Hospital Sant Joan de Déu, Barcelona, Spain, between April-August 2020, before having COVID-19 available vaccines. Maternal and pregnancy variables, as well as perinatal outcomes, were recorded in questionnaires. Nasopharyngeal swabs and maternal and cord blood samples were collected for SARS-CoV-2 detection by rRT-PCR and serology, respectively. We measured IgM, IgG and IgA levels to 6 SARS-CoV-2 antigens (spike [S], S1, S2, receptor-binding domain [RBD], nucleocapsid [N] full-length and C-terminus), IgG to N from 4 human coronaviruses (OC43, HKU1, 229E and NL63), and the concentrations of 30 cytokines, chemokines and growth factors by Luminex. Mothers were classified as infected or non-infected based on the rRT-PCR and serology results. Sixty-four % of pregnant women were infected with SARS-CoV-2 (positive by rRT-PCR during the third trimester and/or serology just after delivery). None of the newborns tested positive for rRT-PCR. SARS-CoV-2 infected mothers had increased levels of virus-specific antibodies and several cytokines. Those with symptoms had higher cytokine levels. IFN-α was increased in cord blood from infected mothers, and in cord blood of symptomatic mothers, EGF, FGF, IL-17 and IL-15 were increased, whereas RANTES was decreased. Maternal IgG and cytokine levels showed positive correlations with their counterparts in cord blood. rRT-PCR positive mothers showed lower transfer of SARS-CoV-2-specific IgGs, with a stronger effect when infection was closer to delivery. SARS-CoV-2 infected mothers carrying a male fetus had higher antibody levels and higher EGF, IL-15 and IL-7 concentrations. Our results show that SARS-CoV-2 infection during the third trimester of pregnancy induces a robust antibody and cytokine response at delivery and causes a significant reduction of the SARS-CoV-2-specific IgGs transplacental transfer, with a stronger negative effect when the infection is closer to delivery.
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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) | 0.000 | 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) | 0.001 | 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".