Dimeric immunoglobulin A as a novel diagnostic marker of measles infection
Bibliographic record
Abstract
ABSTRACT Despite tremendous measles incidence reduction through universal vaccination, elimination efforts rely on improved surveillance. The detection of anti-measles immunoglobulin M (IgM) by enzyme-linked immunosorbent assay is the standard laboratory diagnostic method. However, true infection is rare, and seroconversion following measles, mumps, and rubella vaccination also generates IgM, which results in low positive predictive values of assays in elimination settings, thus necessitating confirmatory testing. Improved diagnostic tests for measles infection are a World Health Organization research priority. We investigated whether dimeric immunoglobulin A (dIgA), the predominant antibody produced in mucosal immunity, may be a marker of recent or acute measles infection. We examined a serological panel of confirmed measles infection (anti-measles IgM positives, n = 50) and non-measles infection with rubella ( n = 36), roseola ( n = 40), chikungunya/dengue/zika ( n = 41), parvovirus ( n = 35), and other fever-rash illnesses of unknown cause ( n = 37). Sera were examined on microimmune anti-measles IgM, Euroimmun anti-measles virus lysate (VL), and nucleoprotein (NP) IgM kits. Assays were then modified to detect dIgA using an in-house protocol based on a recombinant chimeric secretory component protein and an anti-secretory component monoclonal antibody. We observed significantly higher levels of anti-measles VL dIgA in measles samples than in non-measles controls ( P < 0.001), and there was a low correlation with IgM (R 2 : 0.01, P value: 0.487). Unlike IgM, dIgA reactive to measles NP was not detected in most samples. The comparable diagnostic potential of anti-measles dIgA (area under the curve, AUC: 0.920–0.945) to anti-measles IgM (AUC: 0.986–0.995) suggests that dIgA may be a new blood-based marker of acute measles, independent of IgM, which merits further investigation and optimization. IMPORTANCE The world is facing a measles resurgence, and improved diagnostic tests for measles infection are an urgent World Health Organization research priority. Detection of measles-specific immunoglobulin M (IgM) as a standard diagnostic test has low positive predictive value in elimination settings, and there is a need for new biomarkers of measles infection to enable enhanced surveillance and response to outbreaks. We demonstrate the detection of measles-specific dimeric immunoglobulin A (dIgA) in patients with confirmed measles infections using a new indirect enzyme-linked immunosorbent assay protocol that selects for the dIgA fraction from total IgA in the blood. The magnitude of measles-specific dIgA responses showed a low correlation with IgM responses, and our results highlight the potential of dIgA for further development as an alternative and/or complementary biomarker to IgM for serological diagnosis of measles infection.
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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) | 0.000 | 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 | 0.001 |
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".