Comparative genomics of aldehyde dehydrogenase 5a1 (succinate semialdehyde dehydrogenase) and accumulation of gamma-hydroxybutyrate associated with its deficiency
Bibliographic record
Abstract
Succinic semialdehyde dehydrogenase (SSADH; aldehyde dehydrogenase 5A1 [ALDH5A1]; locus 6p22) occupies a central position in central nervous system (CNS) neurotransmitter metabolism as one of two enzymes necessary for gamma-aminobutyric acid (GABA) recycling from the synaptic cleft. Its importance is highlighted by the neurometabolic disease associated with its inherited deficiency in humans, as well as the severe epileptic phenotype observed in Aldh5a1(-/-) knockout mice. Expanding evidence now suggests, however, that even subtle decreases in human SSADH activity, associated with rare and common single nucleotide polymorphisms, may produce subclinical pathological effects. SSADH, in conjunction with aldo-keto reductase 7A2 (AKR7A2), represent two neural enzymes responsible for further catabolism of succinic semialdehyde, producing either succinate (SSADH) or gamma-hydroxybutyrate (GHB; AKR7A2). A GABA analogue, GHB is a short-chain fatty alcohol with unusual properties in the CNS and a long pharmacological history. Moreover, SSADH occupies a further role in the CNS as the enzyme responsible for further metabolism of the lipid peroxidation aldehyde 4-hydroxy-2-nonenal (4-HNE), an intermediate known to induce oxidant stress. Accordingly, subtle decreases in SSADH activity may have the capacity to lead to regional accumulation of neurotoxic intermediates (GHB, 4-HNE). Polymorphisms in SSADH gene structure may also associate with quantitative traits, including intelligence quotient and life expectancy. Further population-based studies of human SSADH activity promise to reveal additional properties of its function and additional roles in CNS tissue.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".