Meier–Gorlin syndrome: Growth and secondary sexual development of a microcephalic primordial dwarfism disorder
Bibliographic record
Abstract
Meier-Gorlin syndrome (MGS) is a rare autosomal recessive disorder characterized by primordial dwarfism, microtia, and patellar aplasia/hypoplasia. Recently, mutations in the ORC1, ORC4, ORC6, CDT1, and CDC6 genes, encoding components of the pre-replication complex, have been identified. This complex is essential for DNA replication and therefore mutations are expected to impair cell proliferation and consequently could globally reduce growth. However, detailed growth characteristics of MGS patients have not been reported, and so this is addressed here through study of 45 MGS patients, the largest cohort worldwide. Here, we report that growth velocity (length) is impaired in MGS during pregnancy and first year of life, but, thereafter, height increases in paralleled normal reference centiles, resulting in a mean adult height of -4.5 standard deviations (SD). Height is dependent on ethnic background and underlying molecular cause, with ORC1 and ORC4 mutations causing more severe short stature and microcephaly. Growth hormone therapy (n = 9) was generally ineffective, though in two patients with significantly reduced IGF1 levels, growth was substantially improved by GH treatment, with 2SD and 3.8 SD improvement in height. Growth parameters for monitoring growth in future MGS patients are provided and as well we highlight that growth is disproportionately affected in certain structures, with growth related minor genital abnormalities (42%) and mammary hypoplasia (100%) frequently present, in addition to established effects on ears and patellar growth.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".