Investigating TSHR gene variants in consanguineous families: novel insights into variable expression in familial congenital hypothyroidism
Bibliographic record
Abstract
Background A defective thyroid-stimulating hormone receptor (TSHR) gene is one of the main known genetic factors leading to congenital hypothyroidism (CH). However, the relationship between TSHR genotypes and phenotype and the underlying reason for the broad spectrum of phenotypes in the patients carrying TSHR gene defects have not yet been clearly established. This study aimed to investigate the genetics of patients with CH to identify TSHR defects and to explore the specific extrathyroidal defects and other phenotypic features in these patients to establish a genotype-phenotype correlation. Methods Consanguineous families with primary CH and a history of non-autoimmune acquired hypothyroidism were included in this study. The causative variants in the TSHR gene were identified using exome sequencing. Multiple in silico analysis tools were employed to interpret the variants. Results Five TSHR variants including two novel variants were identified in patients with thyroid dysgenesis from five families. Some patients presented inter- and intra-familial variable expression and different ages of onset. The data suggest the possibility that the clinical phenotype of patients with CH caused by TSHR variants can be influenced by the coexistence of other gene defects. Conclusions This study investigated the variants of the TSHR gene contributing to CH for the first time in Iran. Our study on multiplex consanguineous families could help provide further evidence for the elucidation of the oligogenic inheritance in CH, possibly leading to variable expressivity in patients with CH. These data could have implications for genetic diagnosis and counseling to identify deleterious variants for possible diagnostics, clinical management, and preventive aims.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".