Hypertriglyceridemia in young adults with a 22q11.2 microdeletion
Bibliographic record
Abstract
Objective: Mild to moderate hypertriglyceridemia is a condition often associated with obesity and diabetes, with as yet incomplete knowledge of underlying genetic architecture. The 22q11.2 microdeletion is associated with multimorbidity, including increased risk of obesity and diabetes. In this study, we sought to investigate whether the 22q11.2 microdeletion was associated with mild to moderate hypertriglyceridemia (1.7-10 mmol/L). Design: This was a cohort study comparing 6793 population-based adults and 267 with a 22q11.2 microdeletion aged 17-69 years, excluding those with diabetes or on statins. Methods: We used binomial logistic regression modeling to identify predictors of hypertriglyceridemia, accounting for the 22q11.2 microdeletion, male sex, BMI, ethnicity, age, and antipsychotic medications. Results: The 22q11.2 microdeletion was a significant independent predictor of mild to moderate hypertriglyceridemia (odds ratio (OR): 2.35, 95% CI: 1.70-3.26). All other factors examined were also significant predictors (OR: 1.23-2.10), except for antipsychotic medication use. Within the 22q11.2 microdeletion subgroup, only male sex (OR: 3.10, 95% CI: 1.77-5.44) and BMI (OR: 1.63, 95% CI: 1.14-1.98) were significant predictors of hypertriglyceridemia, evident at mean age 31.2 years. Conclusions: The 22q11.2 microdeletion is associated with hypertriglyceridemia even when accounting for other known risk factors for elevated triglycerides. This effect is seen in young adulthood (76.6% were <40 years), in the absence of diabetes, and irrespective of antipsychotics, suggesting that the 22q11.2 microdeletion may represent an unrecognized genetic risk factor for hypertriglyceridemia, providing novel opportunities for animal and cellular models. Early dyslipidemia screening and management strategies would appear prudent for individuals with 22q11.2 microdeletions.
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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 | 0.001 |
| 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".