Two novel mutations in the KHDC3L gene in Asian patients with recurrent hydatidiform mole
Bibliographic record
Abstract
Recurrent hydatidiform mole (RHM) is defined by the occurrence of repeated molar pregnancies in affected women. Two genes, NLRP7 and KHDC3L, play a causal role in RHM and are responsible for 48–80% and 5% of cases, respectively. Here, we report the results of screening these two genes for mutations in one Iranian and one Indian patient with RHM. No mutations in NLRP7 were identified in the two patients. KHDC3L sequencing identified two novel protein-truncating mutations in a homozygous state, a 4-bp deletion, c.17_20delGGTT (p.Arg6Leufs*7), in the Iranian patient and a splice mutation, c.349+1G>A, that affects the invariant donor site at the junction of exon 2 and intron 2 in the Indian patient. To date, only four mutations in KHDC3L have been reported. The identification of two additional mutations provides further evidence for the important role of KHDC3L in the pathophysiology of RHM and increases the diversity of mutations described in Asian populations. Two new mutations have been identified in a gene associated with recurrent hydatidiform moles (RHMs). A RHM is a form of non-viable pregnancy in which the placenta develops into a mass of cysts. This condition occurs in higher frequencies in the Middle and Far East. Majid Fardaei of Shiraz University of Medical Science in Iran and colleagues screened Iranian and Indian women for mutations in two genes, NLRP7 and KHDC3L. These genes have been implicated as having a role in 48—80% and 5% of RHMs, respectively. In two patients, no mutations were found in NLRP7, but two new mutations were identified in KHDC3L that were not found in controls or two large gene databases. The findings confirm a causal role for KHDC3L in RHMs, which should be screened for when mutations are not detected in NLRP7.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".