Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.10.25.465798

COVID 19 breakthrough infection risk: a simple physical model describing the dependence on antibody concentration

Williams, D.
View original source ↗Export metadata ↓

Abstract

The increase of COVID-19 breakthrough infection risk with time since vaccination has a clear relationship to the decrease of antibody concentration with time. The empirically-observed dependence on blood IgG anti-receptor binding domain antibody concentration of SARS-CoV-2 vaccine efficacy against infection has a rational explanation in the statistics of binding of antibody to spike proteins on the virus surface, leading to blocking of binding to the receptor: namely that the probability of infection is the probability that a critical number of the spike proteins protruding from the virus are unblocked. The model is consistent with the observed antibody concentrations required to induce immunity and with the observed dependence of vaccine efficacy on antibody concentration and thus is a useful tool in the development of models to relate, for an individual person, risk of infection given measured antibody concentration. It can be used to relate population breakthrough infection risk to the distribution across the population of antibody concentration, and its variation with time.

Source connections

Explore related subjects

immunologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Williams, D.. 2021-10-26. COVID 19 breakthrough infection risk: a simple physical model describing the dependence on antibody concentration. https://doi.org/10.1101/2021.10.25.465798

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Common viral infections seed regionally distinct resident memory T cells in the human CNS

T cells persist in the central nervous system (CNS) and can drive both protection and neurological disease. How these cells are organized in humans and what they recognize is largely unknown. Here, we profiled CD8 T cells across anatomically distinct CNS regions, obtained through on-site autopsies and temporal lobe resection surgeries, using single-cell RNA sequencing, paired T cell receptor sequencing, and DNA-barcoded tetramers. Resident memory T cells (TRM) specific for Epstein-Barr virus, cytomegalovirus, influenza A, and SARS-CoV-2 were identified across CNS compartments. Anatomical location was the strongest correlate of TRM cell state, with leptomeningeal cells adopting a cytokine-poised TRM program, whereas brain TRM cells were transcriptionally restrained. Cells of the same clonotype spanned tissues yet adopted local transcriptional states. Viral specificity added another layer of TRM heterogeneity with GZMK/GZMA-expressing EBV-specific populations and interferon-stimulated gene signatures in SARS-CoV-2 and Influenza A-specific cells. The human CNS thus harbors regionally distinct CD8+ TRM shaped by common viral exposures.

immunology↗
bioRxiv2026

A regulatory T cell signature provides a shared molecular basis for the therapeutic window of opportunity in rheumatic disease

Rheumatic diseases, including rheumatoid arthritis (RA), spondyloarthritis (SpA) and osteoarthritis (OA), show distinct phenotypes yet respond to overlapping therapies, implicating shared immune mechanisms. In the Transimmunom cohort, we profiled peripheral blood from 240 individuals (47 healthy, 44 OA, 91 RA, 58 SpA) across deep immunophenotyping, immunoproteomics and Treg-Teff transcriptomics. Single-layer analyses revealed broader Treg than Teff remodeling, along with a shared pattern of reduced activated Tregs and expanded Helios+ Tregs across all diseases, alongside a decrease in functional Treg subpopulations, including CTLA4+ and CD45RA- Tregs. In RA specifically, LAG3+ Tregs were also expanded. Combining omics layers outperformed single-layer approaches for disease classification. Among individual layers, Treg transcriptomes were most discriminative, and integration uncovered disease-specific programs. Unsupervised clustering identified a cross-disease cluster independent of activity, treatment and age, mapping to early disease (<= years) and dominated by a Treg dysfunction-associated program. These results provide a biological rationale for the therapeutic "window of opportunity" concept and duration-stratified Treg-directed trials.

immunology↗
bioRxiv2026

Inhibitory Fc Receptor sets a time limit on macrophage response to IgG

Antibodies engage both activating Fc Receptors and the inhibitory receptor Fc{gamma}RIIB. Why macrophages need a dedicated inhibitory receptor rather than simply tuning activating receptor signaling is unclear. Using DNA-based chimeric receptors and in silico modeling, we independently controlled activating and inhibitory Fc Receptors. We found that Fc{gamma}RIIB imposed a time limit on macrophage phagocytosis and ERK signaling. The time limit is due to activating Fc Receptors converting PI(4,5)P2 to PI(3,4,5)P3, which is subsequently converted to PI(3,4)P2 by Fc{gamma}RIIB. This leads to a pulse of active signaling, which is sufficient for phagocytosis of small bacteria-sized targets but not phagocytosis of large targets and TNF secretion. Unlike engaging Fc{gamma}RIIB, reducing activating Fc Receptor signaling decreased initiation of phagocytosis, the speed of PI(3,4,5)P3 generation, and the amplitude of ERK signaling. Our results demonstrate that Fc{gamma}RIIB controls the duration of IgG signaling, while the activating Fc Receptors control sensitivity.

immunology↗