Biallelic <i>CACNA2D2</i> variants in epileptic encephalopathy and cerebellar atrophy
Bibliographic record
Abstract
OBJECTIVE: To characterize the molecular and clinical phenotypic basis of developmental and epileptic encephalopathies caused by rare biallelic variants in CACNA2D2. METHODS: Two affected individuals from a family with clinical features of early onset epileptic encephalopathy were recruited for exome sequencing at the Centers for Mendelian Genomics to identify their molecular diagnosis. GeneMatcher facilitated identification of a second family with a shared candidate disease gene identified through clinical gene panel-based testing. RESULTS: Rare biallelic CACNA2D2 variants have been previously reported in three families with developmental and epileptic encephalopathy, and one family with congenital ataxia. We identified three individuals in two unrelated families with novel homozygous rare variants in CACNA2D2 with clinical features of developmental and epileptic encephalopathy and cerebellar atrophy. Family 1 includes two affected siblings with a likely damaging homozygous rare missense variant c.1778G>C; p.(Arg593Pro) in CACNA2D2. Family 2 includes a proband with a homozygous rare nonsense variant c.485_486del; p.(Tyr162Ter) in CACNA2D2. We compared clinical and molecular findings from all nine individuals reported to date and note that cerebellar atrophy is shared among all. INTERPRETATION: Our study supports the candidacy of CACNA2D2 as a disease gene associated with a phenotypic spectrum of neurological disease that include features of developmental and epileptic encephalopathy, ataxia, and cerebellar atrophy. Age at presentation may affect apparent penetrance of neurogenetic trait manifestations and of a particular clinical neurological endophenotype, for example, seizures or ataxia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".