Rapid Near Point-of-Care Assay for <i>HLA-B*57:01</i> Genotype Associated with Severe Hypersensitivity Reaction to Abacavir
Bibliographic record
Abstract
The nucleoside reverse transcriptase inhibitor abacavir ( ABC ) is used commonly to treat young children with HIV infection and is a component of the fixed-dose-combination Triumeq ® . ABC can trigger a severe hypersensitivity reaction in people who are homozygous or heterozygous for HLA-B*57:01 . Testing for HLA-B*57:01 before ABC initiation is standard-of-care in high-resource settings, but current tests are costly or difficult to access in resource-limited settings. To address these gaps, we developed an inexpensive simple-to-use rapid assay to detect HLA-B*57:01 . We designed and optimized a multiplexed polymerase chain reaction (PCR) to amplify HLA-B*57 subtypes and the human beta-globin gene; employed probes and ligation to specifically tag the HLA-B*57:01 allele with biotin. Tagged-ligated products were detected by immunocapture in an enzyme-linked immunosorbent assay plate or lateral flow strip. Cell lines with known HLA genotypes were used to optimize the assay. The optimized assay was then compared with genotypes of clinical specimens ( n = 60) determined by sequencing, with specimens enriched for individuals with HLA-B*57:01 . The optimized assay utilizes 40-min 35-cycle multiplex PCR for B*57 and beta-globin; 20-min ligation reaction; and 15-min detection. Evaluation of the HLA-B*57:01 oligonucleotide ligation assay using clinical specimens had a sensitivity of 100% ( n = 27/27 typed as B*57:01 ) and specificity of 100% ( n = 33/33 typed as non- B*57:01 ) by visual interpretation of lateral flow strips. The cost is US$5.96/specimen. This rapid and economical assay accurately detects HLA-B*57:01 in clinical specimens. Use of this assay could expand access to HLA-B*57:01 genotyping and facilitate safe same-day initiation of ABC -based treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".