A homozygous stop codon in <i>HORMAD2</i> in a patient with recurrent digynic triploid miscarriage
Bibliographic record
Abstract
BACKGROUND: Recurrent miscarriage (RM) affects 1% to 5% of couples trying to conceive. Despite extensive clinical and laboratory testing, half of the RM cases remain unexplained. We report the genetic analysis of a couple with eight miscarriages and the search for their potential genetic etiology. METHODS: Short tandem repeat (STR) markers, single nucleotide polymorphic (SNP) microarray, and human DNA methylation microarray were used to analyze the genotypes of two miscarriages. Exomes sequencing was performed on DNA from the two partners and identified variants were validated by Sanger sequencing. RESULTS: STR marker genotyping demonstrated that the two available miscarriages are triploid digynic and resulted from the failure of Meiosis II. SNP microarray analysis revealed an additional Meiosis I abnormality that is the segregation of the two maternal homologous chromosomes in one triploid miscarriage. Whole-exome sequencing on DNA from the two partners identified candidate variants only in the female partner in two genes with roles in female reproduction, a missense in EIF4ENIF1 (OMIM 607445) and a stop gain in HORMAD2 (OMIM 618842). EIF4ENIF1 is a eukaryotic translation initiation factor 4E nuclear import factor required for the oocyte germinal vesicle breakdown, and HORMAD2 is part of the synaptonemal complex that was hypothesized to act as a checkpoint mechanism to eliminate oocytes with asynapsis during meiotic prophase I in mice. CONCLUSION: While both genes may contribute to the phenotype, the Meiosis I abnormalities in the conceptions favor the causal role of HORMAD2 in the etiology of RM in this couple. This report illustrates the importance of comprehensively analyzing the products of conception to guide the search for the genetic causation of RM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".