The hairless gene in androgenetic alopecia: results of a systematic mutation screening and a family-based association approach
Bibliographic record
Abstract
BACKGROUND: Genetic disposition and androgen dependence are important characteristics of the common patterned loss of scalp hair known as androgenetic alopecia (AGA). The genetic factors contributing to AGA are currently unknown. The human hairless gene (HR) has recently been cloned and mutations have been reported in families with autosomal recessive universal congenital alopecia and papular atrichia. The main feature of these disorders is persistent complete absence of hair at or shortly after birth. This suggests that HR is essential and specific for the development of hair. OBJECTIVES: To test the hypothesis that HR may be involved in AGA. METHODS: We systematically screened HR for genetic variability by means of single-strand conformation analysis (SSCA) in 46 unrelated men with AGA. To test for an involvement of HR in the development of AGA, seven common variants were genotyped in 61 families with 93 affected offspring. The results were analysed with the transmission/disequilibrium test (TDT). RESULTS: SSCA showed 15 single nucleotide substitutions: eight missense mutations, four silent mutations and three mutations in exon-flanking intronic sequences. TDT results showed a marginally significant association between AGA and variants 3379-29G/T (P = 0.024) and 2611-68C/T (P = 0.047). These results, however, did not remain significant after applying the conservative Bonferroni correction for multiple testing. CONCLUSIONS: Our results do not provide evidence for a strong involvement of HR in the development of AGA, although a minor role cannot be fully excluded.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".