Heterozygous Missense Pathogenic Variants Within the Second Spectrin Repeat of SPTBN2 Lead to Infantile-Onset Cerebellar Ataxia
Bibliographic record
Abstract
The term spinocerebellar ataxia encompasses a heterogeneous group of neurodegenerative disorders due to pathogenic variants in more than 100 genes, underlying 2 major groups of ataxia: autosomal dominant cerebellar ataxias (ADCA, also known as spinocerebellar ataxias [SCAs]) due to heterozygous variants or polyglutamine triplet expansions leading to adult-onset ataxia, and autosomal recessive spinocerebellar ataxias (ARCAs, also known as SCARs) due to biallelic variants, usually resulting in more severe and earlier-onset cerebellar ataxia. Certain ataxia genes, including SPTBN2 which encodes β-III spectrin, are responsible for both SCA and SCAR, depending on whether the pathogenic variant occurs in a monoallelic or biallelic state, respectively. Accordingly, 2 major phenotypes have been linked to SPTBN2: pathogenic heterozygous in-frame deletions and missense variants result in an adult-onset, slowly progressive ADCA (SCA5) through a dominant negative effect, whereas biallelic loss-of-function variants cause SCAR14, an allelic disorder characterized by infantile-onset cerebellar ataxia and cognitive impairment. Of note, 2 heterozygous missense variants (c.1438C>T, p.R480 W; c.1309C>G, p.R437G), both lying in the second spectrin repeat of SPTBN2, have been linked to infantile-onset cerebellar ataxia, similar to SCAR14. Here, we report a novel de novo heterozygous pathogenic missense variant (c.1310G>A) in SPTBN2 in a child with infantile-onset cerebellar ataxia and mild cognitive impairment. This variant affects the same R437 residue of the second spectrin repeat but results in a different amino acid change (p.R437Q). We review previously reported cases and discuss possible pathomechanisms responsible for the early-onset cerebellar phenotype due to disease-causing variants in the second spectrin repeat.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".