Faculty Opinions recommendation of Association of maternal killer-cell immunoglobulin-like receptors and parental HLA-C genotypes with recurrent miscarriage.
Bibliographic record
Abstract
BACKGROUND: The natural killer (NK) cells at the site of placentation express killer-cell immunoglobulin-like receptors (KIR) that can bind to human leukocyte antigen (HLA)-C molecules on trophoblast cells. Both these gene systems are polymorphic and an association of particular maternal KIR/fetal HLA-C genotypes has been shown in pre-eclampsia. Pre-eclampsia and recurrent miscarriage (RM) share the pathogenesis of defective placentation and therefore we have now genotyped couples with RM.METHODS AND RESULTS: DNA was obtained from the male (n = 67) and female (n = 95) partners of couples with three or more spontaneous miscarriages and genotyped for HLA-C groups and 11 KIR genes using the PCR-sequence-specific primer method (SSP). The frequency of the HLA-C2 group was increased in both parents (reaching significance only in the male partners, P = 0.018) compared with a parous control population. The KIR gene frequencies of the male partners were similar to controls, but the women had a high frequency of KIR AA haplotypes that lack activating KIR. In particular, the activating KIR for HLA-C2 groups (KIR2DS1) was significantly lower in these women (P = 0.00035, odds ratio 2.63, confidence interval 1.54-4.49).CONCLUSIONS: This is the first report to identify a genetic male factor that confers risk in RM. These findings support the idea that successful placentation depends on the correct balance of NK cell inhibition and activation in response to trophoblast. PMID: 18263639 Funding information This work was supported by: Wellcome Trust, United Kingdom Intramural NIH HHS, United States British Heart Foundation, United Kingdom NCI NIH HHS, United States Grant ID: N01-CO-12400
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.344 | 0.153 |
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".