Allelic Diversity, De Novo CAG Expansions and Intergenerational Instability at the HTT Locus in a Sample from India
Bibliographic record
Abstract
ABSTRACT Background: Huntington’s disease (HD) is an inherited, neurodegenerative disorder caused by the expansion of an unstable CAG repeat sequence in the Huntingtin (HTT) gene. The prevalence of HD, allelic diversity, rate of novel expansions and the clinical correlates vary across populations. Objective: We analyzed the diversity of alleles and their clinical correlates and examined the inheritance patterns and the pattern of instability of CAG repeats in a few families. Methods: Clinical history and pedigree structure were collected from records or through interviews between 2016 and 2019. Genetic testing at the HD locus was done on clinical suspicion, or relatedness, after counseling. Descriptive statistics and correlation analysis were used. Results: Expanded repeats were detected in 239 individuals, including 232 who were symptomatic and 7 presymptomatic relatives. The number of CAG repeats (mean = 45.6) and age at onset (mean = 39.2 years) showed a strong inverse correlation ( r = -0.67). We found atypical alleles such as 8 intermediate alleles (IA), 12 reduced penetrance alleles and 14 large (>60) expansion alleles corresponding to juvenile HD. Three individuals carried biallelic expansions. Paternal inheritance was more common, and the mean increase in repeats in the available parent-child pairs was 14. Thirty-seven individuals had no family history of HD, with de novo expansion confirmed in three cases. Conclusions: Novel mutations at the HTT locus may not be rare in India. A lack of family history should not exclude appropriate testing. The prevalence of IA and incidence of de novo expansions suggest that there may be a reservoir of alleles prone to expansion.
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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 | 0.001 | 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".