Serum sBCMA in primary and secondary antibody deficiency
Bibliographic record
Abstract
B-cell maturation antigen (BCMA) is a B cell surface receptor that regulates B cell activation, proliferation and survival. BCMA can be cleaved from the cell surface, producing soluble BCMA (sBCMA), which has been studied as a disease biomarker in systemic lupus erythematosus, multiple sclerosis and multiple myeloma. Reduced sBCMA concentrations have been associated with the severity of different primary antibody deficiencies. We explored the relationship between sBCMA concentrations, humoral immune responses to SARS-CoV-2 vaccination and disease complications in 107 individuals with primary (PAD) and secondary antibody deficiency (SAD) enrolled in the COVID-19 in Antibody Deficiency (COV-AD) study. Serum sBCMA concentrations were significantly reduced in PAD compared to healthy controls and asymptomatic selective IgA deficiency. Individuals with X- linked agammaglobulinemia and common variable immunodeficiency (CVID) demonstrated the lowest serum concentrations of sBCMA. sBCMA concentrations in SAD were highly variable. Amongst individuals with CVID, peripheral blood CD19 count, but not sBCMA concentrations discriminated SARS-CoV-2 vaccine responders. sBCMA was significantly lower in individuals with CVID and bronchiectasis and outperformed serum IgA and IgM concentrations in discriminating this subgroup. sBCMA was not associated with any other complication of CVID. Our data highlights the potential of sBCMA as biomarker to support the assessment of antibody deficiency. In PAD, sBCMA may contribute to the risk stratification of disease severity and identify those at risk of bronchiectasis. In SAD, it may identify subgroups that would benefit from intensive monitoring and therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".