Determinants of antibody levels and protection against omicron BQ.1/XBB breakthrough infection
Bibliographic record
Abstract
The ongoing evolution of SARS-CoV-2, particularly through the emergence of new variants, continues to challenge our understanding of immune protection. While antibody levels correlate with protection against earlier variants such as Alpha and Delta, their relationship with Omicron sub-variants remains unclear. To investigate the role of antibody levels and neutralizing activity in preventing breakthrough infections, we analyzed longitudinal SARS-CoV-2 humoral responses and neutralizing activity against the ancestral virus and major emerging variants in a well-characterized cohort of healthcare workers in Spain (N = 405). We find that antibody levels and neutralization titers are key indicators of protection against SARS-CoV-2, including the more evasive BQ.1 and XBB Omicron variants. Higher IgG and IgA levels are associated with protection over three 6-month follow-up periods sequentially dominated by BA.1, BA.2, BA.5, BQ.1, and XBB Omicron sub-variants, although the strength of the association between antibody levels and protection declines over time. Our findings demonstrate that binding antibody levels and neutralizing responses are valid correlates of protection against more evasive BQ.1 and XBB Omicron variants, although the strength of this association diminishes over time. Additionally, our results underscore the importance of continuous monitoring and updating vaccination strategies to maintain effective protection against emerging SARS-CoV-2 variants. The SARS-CoV-2 virus continues to change, creating new variants that can sometimes avoid the body’s immune defenses. Antibodies are proteins the body makes to recognize and help remove viruses and other foreign substances. We studied whether the amount and quality of antibodies in a person’s blood could predict how likely they are to avoid infection, especially when exposed to newer Omicron sub-variants like BQ.1 and XBB. We followed 405 Spanish healthcare workers, drawing blood every six months, as the dominant variant of SARS-CoV-2 shifted from BA.1 to BA.2, BA.5, BQ.1 and XBB. Higher antibody levels were associated with lower risk of infection, but the strength of this association weakened over time. Our results show regular antibody monitoring can signal when booster or updated vaccines are required to prevent infection by new virus variants, enabling health agencies to optimize vaccination schedules. Pérez et al. evaluate whether antibody levels and neutralization titers correlate with protection against SARS-CoV-2, including Omicron sub-variants BQ.1 and XBB, in a cohort of Spanish healthcare workers. They find an association that wanes over time, highlighting the need for updated vaccination strategies.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".