Genetic analysis of autoimmune regulator haplotypes in alopecia areata
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alopecia areata is an immune-mediated disorder, occurring with the highest observed frequency in the rare recessive autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) syndrome caused by mutations of the autoimmune regulator (AIRE) gene on chromosome 21q22.3. We have previously detected association between alopecia areata and a single nucleotide polymorphism (SNP) in the AIRE gene in patients without APECED, and we now report the findings of an extended examination of the association of alopecia areata with haplotype analysis including six SNPs in the AIRE gene: C-103T, C4144G, T5238C, G6528A, T7215C and T11787C. In Caucasian groups of 295 patients and 363 controls, we found strong association between the AIRE 7215C allele and AA [P = 3.8 x 10(-8), OR (95% CI): 2.69 (1.8-4.0)]. The previously reported association between AA and the AIRE 4144G allele was no longer significant on correction for multiple testing. The AIRE haplotypes CCTGCT and CGTGCC showed a highly significant association with AA [P = 6.05 x 10(-6), 9.47 (2.91-30.8) and P = 0.001, 3.51 (1.55-7.95), respectively]. To select the haplotypes most informative for analysis, we tagged the polymorphisms using SNPTag software. Employing AIRE C-103T, G6528A, T7215C and T11787C as tag SNPs, two haplotypes were associated with AA; AIRE CGCT and AIRE CGCC [P = 3.84 x 10(-7), 11.40 (3.53-36.9) and P = 3.94 x 10(-4), 2.13 (1.39-3.24) respectively]. The AIRE risk haplotypes identified in this study potentially account for a major component of the genetic risk of developing alopecia areata.
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.
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 | 0.001 |
| 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) | 0.000 | 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 it