Adult Height, 22q11.2 Deletion Extent, and Short Stature in 22q11.2 Deletion Syndrome
Bibliographic record
Abstract
The 22q11.2 deletion syndrome (22q11.2DS) manifests as a wide range of medical conditions across a number of systems. Pediatric growth deficiency with some catch-up growth is reported, but there are few studies of final adult height. We aimed to investigate how final adult height in 22q11.2DS compared with general population norms, and to examine predictors of short stature in in a cohort of 397 adults with 22q11.2DS (aged 17.6–76.3 years) with confirmed typical 22q11.2 microdeletion (overlapping the LCR22A to LCR22B region). We defined short stature as <3rd percentile using population norms. For the subset (n = 314, 79.1%) with 22q11.2 deletion extent, we used a binomial logistic regression model to predict short stature in 22q11.2DS, accounting for effects of sex, age, ancestry, major congenital heart disease (CHD), moderate-to-severe intellectual disability (ID), and 22q11.2 deletion extent. Adult height in 22q11.2DS showed a normal distribution but with a shift to the left, compared with population norms. Those with short stature represented 22.7% of the 22q11.2DS sample, 7.6-fold greater than population expectations (p < 0.0001). In the regression model, moderate-to-severe ID, major CHD, and the common LCR22A-LCR22D (A-D) deletion were significant independent risk factors for short stature while accounting for other factors (model p = 0.0004). The results suggest that the 22q11.2 microdeletion has a significant effect on final adult height distribution, and on short stature with effects appearing to arise from reduced gene dosage involving both the proximal and distal sub-regions of the A-D region. Future studies involving larger sample sizes with proximal nested 22q11.2 deletions, longitudinal lifetime data, parental heights, and genotype data will be valuable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".