Role of DYSF Genetic Variant in Limb Girdle Muscular Dystrophy: A Case Report
Bibliographic record
Abstract
Introduction: Muscular dystrophy is a hereditary degenerative muscle disease which progressively reduces the strength of the muscles that control movement. In this study, we tried to investigate genetic variants in muscular dystrophy using sequencing of whole exons. Case Presentation: A family with two affected patients with muscular dystrophy was referred for genetic counseling followed by exome sequencing testing on the proband. After filling out informed consent, blood samples were obtained from each available family member. Candidate genetic variant was confirmed using Sanger sequencing. Conclusions: Exome data analysis revealed a variant of c.2864 + 1G > A in the proband, which altered the exon-intron 26 splice site within the DYSF gene. Genetic changes in this gene are known to be associated with muscular disorders, such as limb-girdle muscular dystrophy and other dysferlinopathies. Assessment of this genetic variant in the patient's sister also showed homozygous variant. Since the patient's sister was married to her cousin, the same variant was tested in her husband, which was normal homozygous. NGS-based techniques, including whole-exome sequencing, can identify the molecular genetic basis of the disease in families with limb-girdle muscular dystrophy. The results can be helpful in identifying potential carriers in the family and in prenatal diagnosis to the families involved.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".