Rare mutations in the beta-globin gene and their clinical phenotypes
Bibliographic record
Abstract
Objectives: Beta-thalassemia is one of the most common inherited genetic disorders and the repertoire of mutations in the beta-globin gene is ever-expanding. Sequencing for beta-globin gene mutations, is done, where phenotype-high-performance liquid chromatography discrepancies exist or where amplification refractory mutation system – polymerase chain reaction (ARMS-PCR) cannot identify common mutations, and often leads to the discovery of rare and novel mutations. Materials and Methods: This is a retrospective data analysis of 160 patients of beta-thalassemia and other hemoglobinopathies where some patients were found to have unexplained clinical features. Comprehensive genetic diagnosis was done on these patients by ARMS-PCR, gap-polymerase chain reaction, and sequencing. Results: Out of the total, 124 cases were homozygous/compound heterozygous for beta-thalassemia; 26 cases had heterozygous beta mutations with coexistent alpha-triplications and four patients (with unique clinical features) were found to harbor five rare mutations. The mutations detected were hemoglobin (Hb) Monroe (co-occurring with beta nt-42 mutation), beta-globin mutation −90(C>T), Hb Randwick, and Hb-M-Saskatoon (a variant hemoglobin causing methemoglobinemia and cyanosis). The spectrum of common mutations detected, in our study, was similar to that published in the literature. The unique clinical features of the patients were conclusively explained by the sequencing results. Conclusion: This study emphasizes the role of sequencing in the genetic diagnosis of beta-thalassemia. As next-generation sequencing increasingly finds use in routine diagnostics, newer clinically significant mutations will continue to be added to the large palette of mutations in beta-thalassemia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".