An overview of L-2-hydroxyglutarate dehydrogenase gene (L2HGDH) variants: a genotype-phenotype study
Bibliographic record
Abstract
L-2-Hydroxyglutaric aciduria (L2HGA) is a rare, neurometabolic disorder with an autosomal recessive mode of inheritance. Affected individuals only have neurological manifestations, including psychomotor retardation, cerebellar ataxia, and more variably macrocephaly, or epilepsy. The diagnosis of L2HGA can be made based on magnetic resonance imaging (MRI), biochemical analysis, and mutational analysis of L2HGDH. About 200 patients with elevated concentrations of 2-hydroxyglutarate (2HG) in the urine were referred for chiral determination of 2HG and L2HGDH mutational analysis. All patients with increased L2HG (n=106; 83 families) were included. Clinical information on 61 patients was obtained via questionnaires. In 82 families the mutations were detected by direct sequence analysis and/or multiplex ligation dependent probe amplification (MLPA), including one case where MLPA was essential to detect the second allele. In another case RT-PCR followed by deep intronic sequencing was needed to detect the mutation. Thirty-five novel mutations as well as 35 reported mutations and 14 nondisease-related variants are reviewed and included in a novel Leiden Open source Variation Database (LOVD) for L2HGDH variants (http://www.LOVD.nl/L2HGDH). Every user can access the database and submit variants/patients. Furthermore, we report on the phenotype, including neurological manifestations and urinary levels of L2HG, and we evaluate the phenotype-genotype relationship.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".