Digenic Inheritance Mode in Congenital Hypothyroidism Due to Thyroid Dysgenesis: HYPOTYGEN Translational Cohort Study
Bibliographic record
Abstract
CONTEXT: Congenital hypothyroidism (CH) is the most common neonatal endocrine disorder and is chiefly caused by thyroid dysgenesis (CHTD). The inheritance mode of the disease remains complex. OBJECTIVE: Gain insight into the inheritance mode of CHTD. METHODS: Prospective multicenter nationwide translational study in France including 514 patients with CH diagnosed through systematic newborn screening (HYPOTYGEN cohort). We focused on CHTD cases and studied their clinical and molecular phenotypes. Targeted next-generation sequencing using a 78-gene panel, including genes involved in thyroid development, function, transport, metabolism and action of thyroid hormones. Statistical analysis, familial segregation, and in vitro functional studies focusing on cell migration have been performed. RESULTS: We analyzed the clinical phenotypes of 458 patients with CH. Cardiac and renal malformations were present in 7.7% (14/182) and 3.9% (7/178) of patients, respectively. Genetic analysis was performed on 292 patients of the cohort, based on criteria for ethnicity and availability of DNA samples for index cases and their parents. A disease-causing mutation in 1 of the 10 known genes for CHTD was identified in 20/292 (6.8%) patients. We found a digenic mode of inheritance in 16 (5.5%) patients, each carrying a variant in a thyroid development gene and a variant in the H2O2 generation complex gene DUOX2/DUOXA2. Familial segregation analysis and in vitro functional studies supported this model. CONCLUSION: This work expands our understanding of the molecular causes of CHTD by demonstrating that digenic inheritance can be implicated, with deleterious variants in thyroid development and DUOX2/DUOXA2 genes. The complexity of this model implies a revision of the genetic landscape of CHTD and specific clinical care of patients during long-term follow-up.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".