Identification of a large intronic transposal insertion in SLC17A5 causing sialic acid storage disease
Bibliographic record
Abstract
BACKGROUND: Sialic acid storage diseases are neurodegenerative disorders characterized by accumulation of sialic acid in the lysosome. These disorders are caused by mutations in SLC17A5, the gene encoding sialin, a sialic acid transporter located in the lysosomal membrane. The most common form of sialic acid storage disease is the slowly progressive Salla disease, presenting with hypotonia, ataxia, epilepsy, nystagmus and findings of cerebral and cerebellar atrophy. Hypomyelination and corpus callosum hypoplasia are typical as well. We report a 16 year-old boy with an atypically mild clinical phenotype of sialic acid storage disease characterized by psychomotor retardation and a mixture of spasticity and rigidity but no ataxia, and only weak features of hypomyelination and thinning of corpus callosum on MRI of the brain. RESULTS: The thiobarbituric acid method showed elevated levels of free sialic acid in urine and fibroblasts, indicating sialic acid storage disease. Initial Sanger sequencing of SLC17A5 coding regions did not show any pathogenic variants, although exon 9 could not be sequenced. Whole exome sequencing followed by RNA and genomic DNA analysis identified a homozygous 6040 bp insertion in intron 9 of SLC17A5 corresponding to a long interspersed element-1 retrotransposon (KF425758.1). This insertion adds two splice sites, both resulting in a frameshift which in turn creates a premature stop codon 4 bp into intron 9. CONCLUSIONS: This study describes a novel pathogenic variant in SLC17A5, namely an intronic transposal insertion, in a patient with mild biochemical and clinical phenotypes. The presence of a small fraction of normal transcript may explain the mild phenotype. This case illustrates the importance of including lysosomal sialic acid storage disease in the differential diagnosis of developmental delay with postnatal onset and hypomyelination, as well as intronic regions in the genetic investigation of inborn errors of metabolism.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".